Complementary metal-oxide semiconductor (CMOS) image sensors is comprised of photodiodes with and mixed-signal circuits ahving capability to amplify small photocurrents into digital signals. The CMOS image sensor is one of the best cricuitry for multiple photography related applications, i.e digital video cameras, photo scanners, Xerox machine, printing and various others. CMOS are nowadays utilized because of its multiple usage and it’s simple fabrications technique even with constain of sensivity in comparison with CCD.
Three types of the topology of CMOS colour sensors are discussed, namely the transimpedance amplifier (TIA), light to frequency converter, and light integrating.
In general, four types of procedures are available
Standard CMOS,
Analog-mixed-signal CMOS,
Digital CMOS, and
CMOS image sensor processes.
The most obvious difference between this process and the other processes is the availability of photo devices, such as a pinned photodiode. The advantages of smaller dimension technology are smaller pixel, high spatial resolution, and lower power consumption. A technology lower than 100 nm requires modification to the fabrication process (not following the digital road map) and pixel architecture.
Fundamental parameters such as leakage current (will affect the sensitivity to the light) and operation voltage (will affect dynamic range, i.e., the saturation, a pinned photodiode is most likely not going to work at a low voltage are very important when a process is selected for CIS development. Because of these limitations, a new circuit technique is introduced:
1. An old circuit, such as a standard pixel circuit cannot be used when using 0.1 micron and lower. This is due to the topology which requires high voltage; because the maximum supply voltage is now lower.
2. Calibration circuit and cancellation circuit are normally employed to reduce noises.
In order to increase the resolution into multi-megapixel and hundreds of frame rate, lower dimension technology is normally chosen. Evidently, it has been reported that 0.13 micron and 0.18 micron are good enough to achieve good imaging performance.
These modifications of the CMOS process have started at 0.25 micron and below to improve their imaging characteristics. As process scaling is going to be much lower than 0.25 micron and below, several fundamental parameters are degraded, namely, photo responsivity and dark current. Therefore, the modifications are focused on mitigating these parameter degradations. System requirements (such as supply voltage and temperature) are also one of the criteria in selecting a suitable process.
The price of tool and development costs will also determine the process selection.
Photo Detetor Devices
The typical photo detector devices are photodiode and phototransistor. Typical photodiode devices are N+/Psub, P+/N_well, N_well/Psub, and P+/N_well/Psub (back-to-back diode) [9]. Phototransistor devices are P+/n_well/Psub (vertical transistor), P+/N_well/P+ (lateral transistor), and N_well/gate (tied phototransistor).
These standard photo devices still require a micro lens and colour filter array. The quantum efficiency of photodiodes in a standard CMOS is usually below 0.3.
The devices which are normally developed for the modified CMOS process are a photogate, pinned photodiode, and amorphous silicon diode. These devices will improve the sensitivity of the CIS. A pinned photodiode, which has a low dark current, offers good imaging characteristics for the CIS.
The photodevices exhibit the parasitic capacitance, which should be considered during the design process. An example of the parasitic capacitance of N_well/Psub is:
Cphoto = (capacitance per area) × photodevice area.
Design Methodology of CMOS Image Sensors:
The typical design flow of the CMOS image sensor is shown below.
Typical design flow of the CMOS image sensor
A wave propagation simulation can be done for optics simulation. Commercially available technology computer-aided design tools, such as from Synopsys and Silvaco, can be used to simulate the process or technology of the photodevices. There is a work, (mixed-mode simulation) that combines the technology computer-aided design and pixel-level simulation.
There are many electronic design automation tools available for pixel electrical simulation, these electronic design automation tools are similar to any integrated circuit (IC) design tool, such as spectre, SPICE, Verilog-A, and Verilog. These tools may be time consuming sometimes if the number of pixels is large.
Indeed, if large pixels together with the deep submicron process are required, more capital has to be provided (cost of tools are more expensive for very deep submicron, especially below 90 nm). Even though the CMOS foundry provides the models for supported design tools, sometimes designers still have to model the sub-block on their own to suit the CIS specification. This can speed up the pixel electrical simulation time, however, this will degrade the accuracy. For system simulation, VHDL-AMS, System-C, or MATLAB can be used to predict the overall function and performance.
CMOS Image Sensor Architecture:
Pixel Level ADC – A digital pixel sensor (DPS) offers a wide dynamic range. The DPS converts the analog values to a digital signa within the pixel range. The processing can also be done at the pixel level.
Chip Level ADC –Chip-level ADC or sometimes matrix-level ADC is depicted in Figure below.
Matrix-level ADC
The ADC for this topology has to be very fast, this topology would also consume a very high current. The ADC type suitable for the CIS topology is pipelined ADC. However, successive approximation register (SAR) and flash type ADC have also been reported in the CIS design. The balance of necessary overall power intake and speed of operation is therefore essential.
Digital Pixel Sensor – The DPS concept is similar to the solution used in the CMOS neuron-stimulus chip. The DPS in number is found useful for on-chip compression. The photodiode is used to discharge the input capacitance of the comparator and photodiode itself. It will be discharged proportionally to the light intensity. When this reaches the threshold, the comparator’s O/P will be triggered.
Low Power Technique in CMOS Image Sensor:
Biasing method: The subthreshold region or weak inversion biasing is one of the approaches to achieve low current consumption. This technique can be applied to an operational transconductance amplifier (OTA) or an amplifier for an ADC. Triode region biasing can also be used to further reduce power consumption.
Circuit technique: The regenerative latch can be used to reduce the digital power consumption. Reducing/scaling the capacitors in the pipeline stages (for ADC) can also reduce the power consumption.
Advanced power management technique: Another type of biasing or circuit technique, a “smart” approach, such as harvesting solar energy can also be employed to reduce the power consumption. We can also selectively ON only the required readout circuit. Pixels can also be periodically activated to reduce the power consumption further.
Low Noise Techniques in CMOS Image Sensor:
At pixel level: The thermal noise can be reduced by correlated double sampling and oversampling. The flicker noise is reduced by using a large device, periodically biasing the transistor, and proper PMOS substrate voltage biasing.
Column level: The off-chip calibration can be used to reduce fixed pattern noise. The calibration is done to select suitable capacitor weights in the SAR ADC.
ADC level: The kT/C noise is reduced by selecting a suitable value for Cf and Cs of the S/H circuit and buffer.
Photodiode level: The high conversion gain helps to reduce referred-to input noise.
In this VBScript Tutorial, we are going to learn about the most important and frequently used VBScript Date Functions and VBScript Time Functions, including vbscript Cdate, vbscript DateAdd, vbscript date, vbscript time, vbscript FormatDateTime function, etc. All the vbscript date functions and vbscript time functions are explained with examples.
VBScript Tutorial #6:VBScript Date Functions
While working with dates in vbscript, we can use in-build vbscript date functions to perform important date-related operations such as capture system date, date conversion, extract different parts of a date, calculation, formatting, etc. This article(VBScript Date Functions) contains all the important built-in VBScript date functions, which are mostly used in programs.
VBScript Date Functions – Summary:
vbscript Cdate – Convert a valid date and time expression into datatype as the date.
All the important vbscript date functions are explained in this section with a proper example.
vbscript Cdate:
vbscript cdate function used to convert a string expression of a date into date format and returns the converted date value. While updating any date type field such as database field with the date data type, we need to convert the string into date format. Otherwise, an error will be thrown.
Syntax:Cdate(date)
Parameter Description:
date – It denotes any valid date and time expression in string format.
Example:
In the below example, any valid date expression will be converted into date format using vbscript Cdate function.
strDate = "10-Feb-2021"
dtDate = Cdate(strDate)
‘After the date conversion the variable dtDate will hold the value with date format (#10-Feb-2021#).
vbscript Date:
The vbscript date function returns the present system date.
Syntax: Date
Example:
In the below example, we will store the current system date in a variable and display in the message box.
sysDate = Date
msgbox " Current system date is " & sysDate
' OutPut (Msgbox):
' Current system date is 04-Jan-2020
vbscript DateAdd:
vbscript dateadd function returns the calculated date value after adding with specific interval time.
Syntax: DateAdd(interval,number,date)
Parameter Description:
number – It represents any number we want to add. It can be positive(future date) or negative(past date) value.
date – It represents any valid date.
interval – It’s a mandatory parameter which denotes the interval of time. The different interval options are –
· yyyy – Represents the quarter interval.
· q – Represents the quarter interval.
· m – Represents the month interval.
· y – Represents the the day of a year interval.
· d – Represents the day interval.
· w – Represents the weekday interval.
· ww – Represents the week of the year interval.
· h – Represents the hour.
· n – Represents the minute.
· s – Represents the second.
Example:
In the below example, we will calculate the future date after adding two months with the system date using vbscript dateadd function.
sDate = "04-Jan-2021"
newDate = Cdate(sDate)
newDate = DateAdd("m",+2,sDate)
msgbox "Future date after adding 2 months with " & sDate & " is " & newDate
vbscript date functions – vbscript DateAdd
vbscript DateDiff:
vbscript datediff function returns the number of an interval between two dates.
interval – It’s a mandatory parameter which denotes the interval of time. The different interval options are –
· yyyy – Represents the quarter interval.
· q – Represents the quarter interval.
· m – Represents the month interval.
· y – Represents the the day of a year interval.
· d – Represents the day interval.
· w – Represents the weekday interval.
· ww – Represents the week of the year interval.
· h – Represents the hour.
· n – Represents the minute.
· s – Represents the second.
date – It represents any valid date expression.
firstdayofweek – It’s an optional field which denotes the day of the week. The available values are –
0 = vbUseSystemDayOfWeek (API Setting for National Language Support)
1 = vbSunday (Sunday – default)
2 = vbMonday (Monday)
3 = vbTuesday (Tuesday)
4 = vbWednesday (Wednesday)
5 = vbThursday (Thursday)
6 = vbFriday (Friday)
7 = vbSaturday (Saturday)
firstweekofyear – It’s also an optional field which denotes the first week of the year. The available values are –
0 = vbUseSystem (API Setting for National Language Support)
1 = vbFirstJan1 (Start with the week when January 1 occurs – default)
2 = vbFirstFourDays (It represent the start week where minimum 4 days are fall in the new year)
3 = vbFirstFullWeek (It represent the week which completely falls in new year)
Example:
Below example evaluates the month part of a given date using vbscript datepart function.
date=Cdate("04-Jan-2021")
monthPart = DatePart("d", date)
msgbox "The month part - " & monthPart
' OutPut (Msgbox):
' The month part - 1
vbscript IsDate:
vbscript isdate function returns the boolean value as true or false if any string expressing can be converted into date format. Vbscript isdate function is used to test a date expression.
Syntax: Isdate(date)
Parameter Description:
date – It denotes any date expression to be verified.
Example:
In the below example, any given test expression is checked for the valid date expression.
date = "04-Jan-2021"
boolResult = IsDate(date)
msgbox "Is Valid date ? Ans: " & monthPart
' OutPut (Msgbox):
' Is Valid date ? Ans: true
vbscript Day:
vbscript day function extracts the number(1-31) that represents the day from a valid date expression.
Syntax: Day(date)
Parameter Description:
date – It’s a valid date expression.
Example:
In the below example, the day part will be extracted from a given date using vbscript day function.
date = Cdate("04-Jan-2021")
num = Day(date)
msgbox "The day part is - " & num
' OutPut (Msgbox):
' The day part is - 4
vbscript Month:
vbscript month function extracts the number(1-12) that represents the month from a valid date expression.
Syntax: Month(date)
Parameter Description:
date – It’s a valid date expression.
Example:
In the below example, month will be extracted from a given date using vbscript month function.
date = Cdate("04-Jan-2021")
num = Month(date)
msgbox "The month part is - " & num
' OutPut (Msgbox):
' The month part is - 1
vbscript Year:
vbscript year function extracts the four digit number that represents the year from a valid date expression.
Syntax: Year(date)
Parameter Description:
date – It’s a valid date expression.
Example:
In the below example, the year will be extracted from a given date using vbscript year function.
date = Cdate("04-Jan-2021")
num = year(date)
msgbox "The year part is - " & num
' OutPut (Msgbox):
' The year part is - 2021
vbscript MonthName:
vbscript monthname function returns the name of a specific month code(1-12).
Syntax: MonthName(month[,abbreviate])
Parameter Description:
month – It’s representing the code(1-12) for any specific month.
abbreviate – It’s not an mandatory parameter. It represents to check about the name of the month is abbreviated or not. The default value is false.
Example:
month_name = MonthName(12)
msgbox "The month name is - " & month_name
' OutPut (Msgbox):
' The month name is - December
vbscript Weekday:
vbscript weekday function returns the number between 1 and 7 that denotes the day of the particular week.
Syntax: WeekDay(date[,firstdayofweek])
Parameter Description:
date – It’s a valid date expression.
firstdayofweek – It’s an optional field which denotes the start day of the week. The available values are –
0 = vbUseSystemDayOfWeek (API Setting for National Language Support)
1 = vbSunday (Sunday – default)
2 = vbMonday (Monday)
3 = vbTuesday (Tuesday)
4 = vbWednesday (Wednesday)
5 = vbThursday (Thursday)
6 = vbFriday (Friday)
7 = vbSaturday (Saturday)
Example:
In the below example, the day representing the week, will be extracted from a given date using vbscript weekday function.
date = Cdate("06-Jan-2021")
num = Weekday(date,1)
msgbox "The week day is - " & num
' OutPut (Msgbox):
' The week day is - 4
vbscript WeekDayName:
vbscript weekdayname function returns the name of a specific day of a week(1-7).
weekday – It’s representing the day code(1-7) for any week.
abbreviate – It’s not an mandatory parameter. It represents to check about the name of the day is abbreviated or not. The default value is false.
firstdayofweek – It’s an optional field which denotes the start day of the week. The available values are –
0 = vbUseSystemDayOfWeek (API Setting for National Language Support)
1 = vbSunday (Sunday – default)
2 = vbMonday (Monday)
3 = vbTuesday (Tuesday)
4 = vbWednesday (Wednesday)
5 = vbThursday (Thursday)
6 = vbFriday (Friday)
7 = vbSaturday (Saturday)
Example:
day_name = WeekdayName(2)
msgbox "The name of the week day - " & day_name
' OutPut (Msgbox):
' The name of the week day - Monday
VBScript Tutorial #7: VBScript Time Functions
While working with time in vbscript, we can use in-build vbscript time functions to perform important time-related operations such as capture system time, extract different parts of any time, calculation, time formatting, etc. This article(VBScript Time Functions) contains all the important built-in VBScript time functions, which are mostly used in programs.
Important VBScript Time Functions – Summary:
vbscript Hour– Extract the hour of the day as a number(0-23) from date/time expression.
vbscript Minute – Extract the minute of the hour as a number(0-59) from date/time expression.
vbscript Second– Extract the second of the minutes as a number(0-59) from a date/time expression.
We will explain all the essential vbscript time functions in this section with a proper example.
vbscript Hour:
vbscript hour function extracts the hour of the day as a number between 0 to 23 from time expression.
Syntax: Hour(time)
Parameter Description:
time – It’s a mandatory parameter that represents a valid time expression.
Example:
In the below example, an hour of the day will be extracted from a valid time expression using vbscript hour function.
numHour = Hour("14:40:35")
msgbox "The hour for the day is - " & numHour
' OutPut (Msgbox):
' The hour for the day is - 14
vbscript Minute:
vbscript minute function extracts the minute of the hour as a number between 0 to 59 from time expression.
Syntax: Minute(time)
Parameter Description:
time – It’s a mandatory parameter that represents a valid time expression.
Example:
In the below example, the minute of the hour will be extracted from a valid time expression using vbscript minute function.
numMin = Minute("14:40:35")
msgbox "The minute for the hour is - " & numMin
' OutPut (Msgbox):
' The minute for the hour is - 40
vbscript Second:
vbscript second function extracts the second of the minute as a number between 0 to 59 from time expression.
Syntax: Second(time)
Parameter Description:
time – It’s a mandatory parameter that represents a valid time expression.
Example:
In the below example, the second of the minute will be extracted from a valid time expression using vbscript second function.
numSec = Second("14:40:35")
msgbox "The second for the minute is - " & numSec
' OutPut (Msgbox):
' The second for the minute is - 35
vbscript Time:
vbscript time function returns the current system time.
Syntax: Time
Example:
In the below example, we will store the current system time in a variable and display in a message box.
sysTime = Time
msgbox " Current system time is " & sysTime
' OutPut (Msgbox):
' Current system time is 14:40:35
vbscript time functions – vbscript Time
vbscript Now:
vbscript now function returns the current system date with timestamp.
Syntax: Now
Example:
In the below example, we will store the current system date and time in a variable and display in a message box.
sysTimeStamp = Now
msgbox "Current system date with time is " & sysTimeStamp
' OutPut (Msgbox):
' Current system date with time is 07-Jan-2021 14:40:35
vbscript Timer:
vbscript timer function returns the count of seconds from 12:00 AM.
Syntax: Timer
Example:
secondCounter = Timer
msgbox "Number of seconds since 12:00 AM " & secondCounter
' OutPut (Msgbox):
' Number of seconds since 12:00 AM 1067.002
vbscript TimeSerial:
vbscript timeserial method fetch the exact time for a mentioned hour, minute and second.
Syntax: TimeSerial(hour, minute, second)
Parameter Description:
hour – It’s a mandatory numeric parameter, denotes hours.
minute – It’s a mandatory numeric parameter, denotes minutes.
second – It’s a mandatory numeric parameter, denotes seconds.
Example:
In the below example, vbscript timeserial function returns the time for the given hours, minutes and seconds.
time = TimeSerial(15,2,20)
msgbox "Specified time is " & time
' OutPut (Msgbox):
' Specified time is 03:02:20 PM
vbscript FormatDateTime:
vbscript formatdatetime function formats and returns a valid and time expression.
Syntax: FormatDateTime(dateExp, format)
Parameter Description:
dateExp– This is a mandatory parameter. It represents a valid date-time expression.
format – It’s an optional arameter that specifies the date and time format. The available return date and time formats are –
0 = vbGeneralDate – This is the default format value (date format: mm/dd/yyyy and time if specified: hh:mm:ss PM/AM).
1 = vbLongDate (date: weekday, monthname, year)
2 = vbShortDate (date: mm/dd/yyyy)
3 = vbLongTime (time: hh:mm:ss PM/AM)
4 = vbShortTime (Return time: hh:mm)
Example:
In the below example, vbscript timeserial function returns the time for the given hours, minutes and seconds.
d=CDate("06-Jan-2021 13:45")
msgbox "Specified formated date time is " & FormatDateTime(d,1)
' OutPut (Msgbox):
' Specified formated date time is Wednesday, Jan 06, 2021
vbscript time functions – vbscript FormatDateTime
Conclusion:
Through this VBScript Date and Time Functions article, we have learned about the learn about the most important and frequently used VBScript Date Functions and VBScript Time functions, including vbscript Cdate, vbscript DateAdd, vbscript FormatDateTime function, etc. We hope this tutorial has helped a lot to brush up on your basics of VB Scripting. If you want to learn more about VBScript, please click here.
Scanning probe microscopy (SPM) is a powerful technique in nanometrology, which records sample topography and other physical or chemical surface properties using the forces between a sharp probe and the sample as the feedback source. SPM has an exceptional position in nanometrology due to its simple metrological traceability and minimum sample preparation needs. However, achieving high spatial resolution is demanding, and instruments are prone to systematic errors and imaging artifacts.
Understanding the Principles of Scanning Probe Microscopy
Scanning probe microscopy (SPM) is a family of techniques that utilize a sharp probe to scan the surface of a sample and measure various surface properties, such as topography, electrical, magnetic, and chemical characteristics. The fundamental principle of SPM is the interaction between the probe and the sample surface, which is detected and used as the feedback signal to generate an image.
The main components of an SPM system include:
Probe: A sharp tip, typically made of materials like silicon, silicon nitride, or metal, which interacts with the sample surface.
Piezoelectric Scanner: A device that precisely controls the position of the probe relative to the sample surface, enabling the scanning motion.
Feedback System: A control system that maintains a constant interaction between the probe and the sample surface, such as a constant force or tunneling current.
Detection System: A system that measures the interaction between the probe and the sample, such as deflection of a cantilever or tunneling current.
Data Acquisition and Processing: A system that converts the detected signals into an image or other data representation.
The different SPM techniques, such as Atomic Force Microscopy (AFM), Scanning Tunneling Microscopy (STM), Magnetic Force Microscopy (MFM), and Kelvin Probe Force Microscopy (KPFM), vary in the specific type of probe-sample interaction they utilize and the information they provide about the sample.
Measurement Uncertainty in Scanning Probe Microscopy
Measurement uncertainty in SPM consists of various sources, including:
Measurements of Known Reference Samples: Calibrating the SPM system using well-characterized reference samples is crucial for accurate measurements. Factors like the quality and traceability of the reference samples can contribute to measurement uncertainty.
Environmental Influences: Factors such as thermal drift, mechanical vibrations, and electrical noise can introduce systematic errors and affect the stability of the SPM system.
Data Processing Impacts: The data processing steps, such as image filtering, background subtraction, and feature extraction, can also introduce uncertainties in the final measurement results.
To analyze and mitigate measurement uncertainty in SPM, researchers often employ modeling and simulation techniques, such as:
Whole Device Level Modeling: Incorporating all instrumentation errors into a large Monte Carlo (MC) model for uncertainty propagation at the whole SPM system level.
Finer Level Modeling: Using ideal, synthesized data to analyze systematic errors related to the measurement principle or typical data processing paths in specific SPM techniques.
The Role of Synthetic Data in Scanning Probe Microscopy
Synthetic data are of increasing importance in nanometrology, with applications in:
Developing Data Processing Methods: Synthetic data can be used to test and validate new data processing algorithms and techniques for SPM, ensuring their robustness and accuracy.
Analyzing Uncertainties: Synthetic data can be used to model the imaging process and data evaluation steps, allowing for a detailed analysis of measurement uncertainties and the identification of systematic errors.
Estimating Measurement Artifacts: Synthetic data can be used to simulate various measurement scenarios, including the presence of known artifacts, to understand their impact on the final measurement results.
Synthetic data can be generated using mathematical models or simulations that accurately represent the physical and chemical processes involved in SPM techniques, such as:
Atomic Force Microscopy (AFM): Simulating the interaction between the AFM tip and the sample surface, including van der Waals forces, capillary forces, and electrostatic interactions.
Scanning Tunneling Microscopy (STM): Modeling the quantum mechanical tunneling process between the STM tip and the sample surface.
Magnetic Force Microscopy (MFM): Simulating the magnetic interactions between the MFM tip and the sample’s magnetic domains.
By using synthetic data, researchers can develop and validate data processing methods, analyze measurement uncertainties, and estimate the impact of various systematic errors and imaging artifacts on the final measurement results.
Comprehensive Software Solutions for Scanning Probe Microscopy
MountainsSPIP® is a dedicated imaging and analysis software for SPM techniques, offering a wide range of tools and functionalities:
Surface Topography Analysis: Detecting and analyzing particles, pores, grains, islands, and other structured surfaces on 3D images.
Spectroscopic Data Correlation: Visualizing, processing, analyzing, and correlating spectroscopic data, such as IR, Raman, TERS, EDS/EDX, and XRF.
Measurement Uncertainty Quantification: Providing tools for estimating and analyzing measurement uncertainties in SPM data.
Synthetic Data Generation: Generating synthetic data to test data processing algorithms and analyze systematic errors.
Advanced Visualization and Reporting: Offering comprehensive visualization and reporting capabilities for SPM data and analysis results.
MountainsSPIP® supports a wide range of SPM techniques, including AFM, STM, MFM, SNOM, CSAFM, and KPFM, making it a versatile and powerful tool for nanometrology and materials characterization.
Conclusion
Scanning probe microscopy is a powerful and versatile technique in nanometrology, with a strong focus on quantifiable data and measurement uncertainty analysis. Synthetic data play a crucial role in understanding and mitigating systematic errors and imaging artifacts, while comprehensive software solutions like MountainsSPIP® provide advanced tools for imaging, analysis, and metrology in SPM techniques. By understanding the principles, measurement uncertainties, and the role of synthetic data, science students can effectively leverage the capabilities of scanning probe microscopy for their research and applications.
When force transmits from one body to another, forces parallel to the surface are experienced by the body, such kind of forces produce shear stress.
It is vital to know about the shear stresses acting on the material while designing the product. Shear failure is the most common failure which occurs due to inappropriate consideration of shear forces.
Shear Stress Definition
When the applied force is parallel/tangential to the surface area of application, then the stress produced is known as shear stress.
Here application of force is tangential to the surface of application.
A component of the stress tensor in the direction parallel to the area of application.
Shear stress also occurs in axial loading, bending, etc.
Shear Stress Formula
Shear Stress= Force imposed parallel to the area/ Area of cross-section
What is Shear Stress Units ?
Unit of shear stress is N/m2 or Pa.
In industries, the unit used to measure shear stress is N/mm2 or MPa (Mega Pascal)
Shear Stress Symbol | Shear Stress tau
The symbol used to represent shear stress is τ (Tau). It is also represented by T.
Shear Stress Diagram
Shear Stress Diagram
Shear Stress Notation
Symbol τ is used to represent shear stress.
To show the applied force and direction of the application area, subscripts are used with the symbol τ as τij.
Where i represent the direction of the surface plane on which it is being applied (perpendicular to the surface), and j represents the applied force’s direction.
Thus, τij= Shear stress acting on the i-surface in j-direction.
τji= Shear stress acting on the j-surface in i-direction.
We can write it as:
Shear Stress Direction
In 2 Dimensions:
Shear Stress Direction
In the vector form, shear stress is the ratio of a parallel component of force applied to the unit normal vector of area.
τ= F‖ / A
In 3 Dimensions:
In naming xy, which is in the subscript form (subscript convention), index x represents the direction of a vector perpendicular to the application area, and y represents the direction of applied force.
In the following figure, it is represented for all three axes.
Shear Stress Direction
Any of the shear stress can be represented as follow:
Shear Stress Sign Convention
When the shear stress is applied on a surface along the principal axis, the adjacent perpendicular axis experiences the equal amount of shear stress in the opposite direction known as complementary shear stress as shown in the figure:
Complimentary Shear Stress
Shear stress is positive if the shear force applied along the x-axis is in the right direction or clockwise.
Similarly, Shear stress is positive if the shear force applied along the y-axis is in an upward direction or it is counterclockwise.
Shear stress is negative if the shear force applied along the x-axis is in the left direction or in counterclockwise.
Similarly, Shear stress is negative if the shear force applied along the y-axis is in a downward direction or it is clockwise.
Half arrowheads are used to represent shear stress.
Shear Stress Sign Convention
Shear Strain
When the shear stress is applied on a surface, deformation is produced in the material. So, the ratio of deformation to the original length perpendicular to the member’s axes is known as shear strain. It is denoted by γ.
It is also defined as the tangent of the strain angle ө.
Shear Strain= del l/ h = tangent(Ө)
Shear Strain
Shear Stress and Shear Strain
It is noted that shear strain is dependent on shear stress. The relation is expressed as
Modulus of Rigidity | Shear Stress Modulus | Shear Modulus of Rigidity
The proportionality constant G is known as Modulus of Rigidity or Shear Stress Modulus or Shear Modulus of Rigidity.
Thus,
Modulus of Rigidity = Shear Stress/ Shear Strain
In most of the metals, G is about 0.4 times of Young’s Modulus of Elasticity.
For isotropic materials, Modulus of Rigidity and Modulus of Elasticity is related to each other according to
Shear strength is the maximum value of shear stress that can resist failure due to shear stress.
It is a significant parameter while designing and manufacturing machines.
Example: While designing bolts and rivets, it is indispensable to know about the material’s shear strength.
Shear Stress vs Normal Stress
Shear Stress
Normal Stress
1.
Force applied is parallel to the surface on which it is being applied
Force applied is perpendicular to the surface on which it is being applied.
2.
Force vector and area vector are perpendicular to each other
Force vector and area vector are parallel to each other.
Shear Stress from Torque | Shear Stress Due to Torsion
Torque is a rotational form of force which makes the object to rotate around an axis. When this torque is applied on a deformable body, it generates shear stress in that body, making that body twist around an axis, known as torsion.
This type of stress is significant in shafts. The stresses or deformations induced in the shaft due to this torsion are shear kinds of stresses.
The shear strain produced in the following shaft of radius r is represented as follows:
γ= rdө/dz
Shear Stress due to Torque
Thus, the shear stress produced is represented by
Shear Stress Fluid
Shear stress produced in any material is due to relative movement of planes on each other.
When it comes to fluid, shear stress is produced in the fluids due to relative movement of fluid layers on one another. It is the viscosity which causes shear stress in the fluid.
Due to shear stress, fluid cannot be held in one place.
Thus, the shear stress produced in the fluid is equal to the
Where μ= Dynamic Viscosity
u= Flow Velocity
y= Height above the boundary
This equation is also known as Newton’s Law of Viscosity.
Shear rate is the rate at which one layer of fluid passes on another adjacent layer of fluid; this can find out by both using geometry and speed of the flow.
The viscosity of fluid mainly depends upon the shear rate of the fluid.
This parameter is very important while designing fluid products like syrups, sunscreen cream, body lotion, etc.
Shear Stress vs Shear Rate
The shear rate is defined as the rate of change of velocity of layers of fluid on one another. For all Newtonian fluids, the viscosity remains constant when there is a change in shear rate, and the shear stress is directly proportional to the shear rate.
Following is a graphical representation of shear stress vs shear for a different type of fluid:
Shear Stress vs Shear Rate for Newtonian Fluids
Shear Stress in Beams
If a cantilever beam of diameter d is twisted on its free end, if torsion of magnitude T is applied on its free end, then the shear stress produced in the beam.
Bolts are mainly used to fix two different assembly bodies like joints, two different metal sheets, two different pipes of an assembly etc.
The bolt experiences shear load or shear force due to the presence of two different loadings acting in the different directions this causes one plane of the bolt to slip on another plane of the bolt.
; This causes shear failure in joints like cotter joint, knuckle joint, etc. so, while selecting material for different mechanisms, it is essential to know its shear stress.
Double shear stress is calculated in bolts.
Shear Stress in Bolts
Shear Stress Steel
Steel is one of the most applicable metals in all types of industries. From constructions to machines, steel is used everywhere. Therefore the maximum shear stress value of steel is a significant parameter while designing.
It is determined using the ultimate tensile strength of the steel. Von Misses factor is used to determine maximum shear stress. It states that maximum shear stress is 0.577 times of the ultimate tensile strength.
In many cases, it is considered as 0.5 times of ultimate tensile strength of the steel.
Ans.: When the applied force is parallel to the surface/area of application, then the stress produced is known as shear stress. Shear stress is a component of the stress tensor in the direction parallel to the area of application.
What is complementary shear stress?
Ans.: When the shear stress is applied on a surface along the principal axis the adjacent perpendicular axis experiences the equal amount of shear stress in the opposite direction known as complementary shear stress
What are the sign conventions for shear stress? | How to decide sign of shear stress?
Ans.: Shear stress is positive if the shear force applied along the x-axis is in the right direction or clockwise.
Similarly, Shear stress is positive if the shear force applied along the y-axis is in an upward direction or it is counterclockwise.
Shear stress is negative if the shear force applied along the x-axis is in the left direction or in counterclockwise.
Similarly, Shear stress is negative if the shear force applied along the y-axis is in a downward direction or it is clockwise.
What is the sign for shear stress?
Symbol τ is used to represent shear stress. To specify the directions of applied force and direction of the application area, subscripts are used with the symbol τ as τij.
What are examples of shear?
When a piece of paper is cut with the scissor.
A bolt and nut tightly fixed with plates.
Rubbing palm on each other
Any friction leads to the production of shear.
What’s an example of shear stress?
Painting walls using colour.
Chewing food under the teeth.
In cotter and knuckle joints, cotter and knuckle experiences shear stress.
How do you solve shear stress?
Shear Stress= Force imposed parallel to the area/ Area of cross Section
What causes shear stress?
When force transmits from one body to another, forces parallel to the surface are experienced by the body, such kind of forces produce shear stress.
What is the difference between shear stress and shear force?
Shear force is the force applied parallel or tangential to the plane’s surface, whereas shear stress is the shear force experienced by the plane’s surface per unit area.
What is the difference between shear stress and shear rate?
When the applied force is parallel to the surface area of application, then the stress produced is known as shear stress whereas the shear rate is the rate at which one layer of fluid passes on another adjacent layer of fluid.
What is a positive shear force?
Shear stress is positive if the shear force applied along the x-axis is in the right direction or clockwise. Similarly, Shear stress is positive if the shear force applied along the y-axis is in an upward direction or it is counterclockwise.
Positive and Negative Shear Stress
What is average shear stress?
Actual shear stress is never uniform; it is different for the different unit cross-sectional area. So, to calculate this shear stress, the considered shear stress is the average shear stress.
Average shear stress is always lesser than maximum shear stress for the given area of cross-section.
What is Shear Strain?
When the shear stress is applied on a surface, deformation is produced in the material. So, the ratio of deformation to the original length perpendicular to the member’s axes is known as shear strain. It is denoted by γ.
Shear Strain
Is shear strain in radian?
No. shear strain is the tangent value of del l and h, which is a unitless quantity.
Objective Questions:
A block of a material with a shear modulus of rigidity G = 90 KPa is bonded to two rigid horizontal plates. The lower plate is fixed, while the upper plate is subjected to a horizontal force P. knowing that the upper plate moves through 0.04 cm under the force’s action if the height of the block is 2cm, determine the average shearing strain in the material.
0.04 rad
0.02 rad
0.01 rad
0.08 rad
Solution: Option 2. Is the answer.
A block of a material with a shear modulus of rigidity G = 90 KPa is bonded to two rigid horizontal plates. The lower plate is fixed, while the upper plate is subjected to a horizontal force P. knowing that the upper plate moves through 0.04 cm under the force’s action if the height of the block is 2cm, find the force P exerted on the upper plate.
180
360
720
90
Solution: Option 1. is the answer.
Find the value of shear stresses developed in the pin A for the bell crank mechanism shown in the figure? Find the safe diameter of the pin if the allowable shear stresses for the pin material is180 MPa.
3mm
4mm
4.5mm
5mm
Solution: Answer is option 4.
Stresses developed in pin are shear stress and bearing stress.
Force at B= 5*0.1/0.15= 3.33KN
Considering double shear at A
The safe diameter of pin is more significant than 4.6mm.
Which of the following basic assumption is not considered while deriving torsion equation for a circular member?
The material must be homogenous and isotropic.
A plane perpendicular to the axis remains plane also after the torque application.
Shear strain varies linearly from the central axis in a circular member when subjected to a torque.
The material does not obey Hooke’s law
Solution: Option 4.
CONCLUSION
In this article all the concepts related to shear stress are discussed in detail. It is very important to know about shear stress while designing any product.
To learn more on mechanical engineering click here!
Robotics and Autonomous Systems (RAS) have become increasingly prevalent in various industries, offering numerous benefits such as cost savings, performance improvements, and enhanced health and safety. To measure the value of RAS projects, it is essential to define clear objectives, expectations, and quantitative benchmarks in advance, aligning the project’s scope and ensuring the delivery of results and return on investment.
Measuring the Value of RAS Projects
Metrics for RAS Projects
In the context of RAS, the following metrics can be used to measure the value of projects:
Efficiency: Metrics such as task completion time, energy consumption, and resource utilization can be used to assess the efficiency of RAS systems.
Cost: Metrics like initial investment, operational costs, and maintenance expenses can help evaluate the cost-effectiveness of RAS implementations.
Quality: Metrics such as accuracy, precision, and defect rates can be used to measure the quality of outputs produced by RAS systems.
Scalability: Metrics like the ability to handle increased workloads, adaptability to changing requirements, and ease of integration can assess the scalability of RAS systems.
Adaptability: Metrics like the ability to handle unexpected situations, respond to dynamic environments, and learn from experience can evaluate the adaptability of RAS systems.
These metrics should be tailored to the specific pain points or opportunities that clients want to address, ensuring the delivery of results and return on investment.
Case Study: Industrial Robots
The implementation of industrial robots, which are automatically controlled, reprogrammable, multipurpose machines capable of welding, painting, and packaging, has shown a fourfold increase in the U.S. between 1993 and 2007. This growth can be attributed to the improved efficiency, cost-effectiveness, and quality of industrial processes enabled by these RAS systems.
Machine Learning in RAS
Machine learning techniques, particularly deep learning, have demonstrated efficacy in supporting RAS requirements and applications. These techniques can be used for:
Training and Learning: Machine learning algorithms can be trained on large, complex datasets to enable RAS systems to learn and adapt to various scenarios.
Analysis and Modeling: Machine learning can be used to analyze and model structured and unstructured data, supporting RAS applications in areas like planning, navigation, and robot manipulation.
Computer Vision: Deep learning-based computer vision techniques can be employed for tasks such as object detection, recognition, and segmentation, which are crucial for RAS systems operating in complex environments.
These machine learning techniques have been commonly deployed in various industries, including the inspection and monitoring of mechanical systems and civil infrastructure.
Human Factors in RAS
When it comes to human-robot interaction, several measurable dimensions have been identified to quantify the human factors in RAS:
Tactility: Metrics like perceived pleasantness when touching a robot can be used to assess the tactile experience.
Physical Comfort: Metrics such as human posture, muscular effort, and joint torque overloading can be used to evaluate the physical comfort of human-robot interaction.
Mechanical Transparency: Metrics like peri-personal space, comfortable handover, and legibility can be used to assess the transparency of the robot’s mechanical operations.
Robot Perception: Metrics like physical safety, predictability of the robot’s motion, and naturalness and smoothness of the motion can be used to evaluate the perception of the robot’s behavior.
Perceived Intuition: Metrics such as the sense of being in control, responsiveness to physical instruction, and feeling of resistive force can be used to assess the perceived intuitiveness of the robot’s interactions.
Conveying Emotions: Metrics like attitudes, impressions, opinions, preferences, favorability, and likeability can be used to evaluate the robot’s ability to convey emotions.
Receiving Emotions: Metrics like willingness for another interaction, behavior perception, politeness, anthropomorphism, animacy, and vitality can be used to assess the human’s emotional response to the robot.
Emotional State: Metrics such as perceived naturalness, agency, perceived intelligence, competence, perceived safety, emotional security, harmlessness, toughness, familiarity, friendship, friendliness, warmth, psychological comfort, helpfulness, reliable alliance, acceptance, ease of use, and perceived performance can be used to evaluate the human’s emotional state during the interaction.
These dimensions can provide valuable insights for researchers and practitioners in the field of RAS, helping to design and develop systems that are more intuitive, comfortable, and engaging for human users.
Conclusion
In summary, the value of RAS projects can be measured using various metrics, such as efficiency, cost, quality, scalability, and adaptability, focusing on specific pain points or opportunities that clients want to address. Machine learning techniques, particularly deep learning, have demonstrated efficacy in supporting RAS requirements and applications. Human factors in RAS can be quantified through several measurable dimensions, providing valuable insights for researchers and practitioners in the field.
Macaulay Michael O., Shafiee Mahmood, Machine learning techniques for robotic and autonomous inspection of mechanical systems and civil infrastructure, 2022-04-29, https://link.springer.com/article/10.1007/s43684-022-00025-3
Hillebrand et al., Human Factors Considerations for Quantifiable Human States in Physical Human-Robot Interaction, 2023-03-15, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10490212/
Daron Acemoglu and Pascual Restrepo, A new study measures the actual impact of robots on jobs. It’s significant, 2020-07-29, https://mitsloan.mit.edu/ideas-made-to-matter/a-new-study-measures-actual-impact-robots-jobs-its-significant
Stereo microscopes, also known as dissection microscopes or stereomicroscopes, are a specialized type of microscope that provide a three-dimensional view of a sample. These instruments are widely used in various fields, including biology, materials science, and electronics, for observing and analyzing relatively large and opaque specimens. With their unique optical design and versatile features, stereo microscopes offer a wealth of capabilities that make them an indispensable tool for scientific exploration and research.
Understanding the Optical Design of Stereo Microscopes
The key feature that distinguishes stereo microscopes from other types of microscopes is their use of two separate optical paths, each with its own objective lens and eyepiece. This binocular arrangement allows the user to perceive depth and three-dimensional structure, providing a more natural and intuitive viewing experience compared to traditional compound microscopes.
The optical design of a stereo microscope typically consists of the following components:
Objective Lenses: Stereo microscopes employ two objective lenses, one for each optical path. These lenses can have a wide range of magnification powers, typically ranging from 1x to 40x. The choice of objective lenses determines the overall magnification and resolution of the microscope.
Eyepieces: The two eyepieces, one for each eye, allow the user to view the sample in a three-dimensional manner. The eyepieces can have varying magnification levels, often ranging from 1x to 10x, which can be combined with the objective lenses to achieve the desired overall magnification.
Zoom Mechanism: Many stereo microscopes feature a zoom mechanism that allows the user to continuously adjust the magnification without changing the objective lenses. This provides a seamless transition between different magnification levels, enabling the user to explore the sample in greater detail.
Illumination System: Stereo microscopes often incorporate built-in illumination systems, such as LED or halogen lights, to provide optimal lighting for the sample. The illumination can be adjusted to enhance contrast and reveal fine details.
Working Distance: One of the key advantages of stereo microscopes is their large working distance, which can range from a few inches to several inches. This allows the user to manipulate the sample directly under the microscope, making it particularly useful for tasks such as dissection, assembly, and repair.
Magnification and Resolution Considerations
The magnification and resolution of a stereo microscope are crucial factors to consider when selecting the appropriate instrument for your specific application. The overall magnification is determined by the combination of the objective lens and the eyepiece magnification.
For example, if a stereo microscope has a 4x objective lens and a 10x eyepiece, the overall magnification would be 40x (4x × 10x). It’s important to note that increasing the magnification does not necessarily result in higher resolution, as the resolving power of the microscope is primarily determined by the numerical aperture (NA) of the objective lens.
The numerical aperture is a dimensionless quantity that represents the light-gathering ability of the lens. A higher numerical aperture generally corresponds to a higher resolving power, allowing the microscope to distinguish smaller details. Typical numerical apertures for stereo microscope objectives range from 0.1 to 0.3.
To achieve the desired magnification and resolution, it’s essential to carefully select the appropriate combination of objective lenses and eyepieces based on your specific needs and the characteristics of the sample you’re observing.
Quantitative and Qualitative Measurements with Stereo Microscopes
In addition to their primary role in observation, stereo microscopes can also be used for quantitative and qualitative measurements. These measurements can provide valuable insights into the physical properties and characteristics of the sample.
Some common measurements that can be performed with stereo microscopes include:
Dimensional Measurements: Stereo microscopes can be used to measure the length, width, height, and perimeter of a sample. This information can be crucial in applications such as materials science, engineering, and quality control.
Area Measurements: The two-dimensional area of a sample can be determined using the measurement capabilities of a stereo microscope. This is particularly useful in fields like biology, where the size and distribution of cells or tissues need to be quantified.
Fluorescence Intensity Measurements: Stereo microscopes can be equipped with fluorescence imaging capabilities, allowing for the quantification of fluorescence intensity within a sample. This is valuable in applications such as cell biology and molecular biology.
In Situ Hybridization: Stereo microscopes can be used to visualize and analyze the spatial distribution of specific DNA or RNA sequences within a sample, a technique known as in situ hybridization. This is an important tool in genetics and developmental biology.
To ensure accurate and reliable measurements, it’s essential to follow best practices for image acquisition and analysis. This includes using lossless file formats, adjusting exposure time to avoid saturation or lack of dynamic range, and correcting for any illumination or background variations.
Practical Applications of Stereo Microscopes
Stereo microscopes find a wide range of applications across various scientific and industrial fields. Some of the key areas where these versatile instruments are commonly used include:
Biology and Life Sciences: Stereo microscopes are indispensable tools in fields such as zoology, botany, and microbiology, where they are used for the observation and analysis of larger biological specimens, such as insects, plant structures, and tissue samples.
Materials Science and Engineering: Stereo microscopes are valuable in materials science and engineering applications, where they are used to examine the surface topography, defects, and microstructural features of materials, including metals, ceramics, and polymers.
Electronics and Microelectronics: In the electronics and microelectronics industries, stereo microscopes are used for the inspection, assembly, and repair of small electronic components, printed circuit boards, and other delicate devices.
Forensics and Crime Scene Investigation: Stereo microscopes play a crucial role in forensic investigations, where they are used to examine and document evidence, such as fibers, hair, and small fragments, at the crime scene or in the laboratory.
Jewelry and Gemology: Stereo microscopes are indispensable tools in the jewelry and gemology industries, where they are used to inspect, grade, and identify precious stones, as well as to examine the craftsmanship and details of jewelry pieces.
Archaeology and Paleontology: Stereo microscopes are employed in the fields of archaeology and paleontology to study and document small artifacts, fossils, and other delicate historical and paleontological specimens.
Quality Control and Inspection: In various manufacturing and production settings, stereo microscopes are used for quality control and inspection purposes, ensuring the quality and consistency of products, components, and materials.
The versatility and capabilities of stereo microscopes make them an essential tool for a wide range of scientific and industrial applications, enabling researchers, engineers, and professionals to explore the world in greater detail and make informed decisions based on their observations and measurements.
Emerging Trends and Future Developments in Stereo Microscopy
The field of stereo microscopy is continuously evolving, with ongoing advancements in technology and the introduction of innovative features. Some of the emerging trends and future developments in this field include:
Digital Imaging and Image Analysis: The integration of digital imaging capabilities, such as high-resolution cameras and advanced image processing software, is transforming the way stereo microscopes are used. These advancements enable more precise quantitative analysis, automated measurements, and the creation of detailed digital records of samples.
Increased Magnification and Resolution: Researchers and manufacturers are continuously working to develop stereo microscopes with higher magnification and improved resolving power, allowing for the observation and analysis of smaller features and structures.
Specialized Accessories and Attachments: The stereo microscope market is seeing the introduction of specialized accessories and attachments, such as fluorescence imaging modules, polarization filters, and 3D imaging capabilities, expanding the versatility and applications of these instruments.
Automation and Robotics: The integration of automation and robotic systems with stereo microscopes is enabling more efficient and precise sample handling, positioning, and analysis, particularly in high-throughput applications.
Miniaturization and Portability: The development of compact and portable stereo microscopes is making these instruments more accessible and suitable for field work, on-site inspections, and remote locations where traditional laboratory equipment may not be feasible.
Augmented and Virtual Reality: Emerging technologies, such as augmented reality (AR) and virtual reality (VR), are being explored to enhance the user experience and provide new ways of interacting with and visualizing samples under a stereo microscope.
Artificial Intelligence and Machine Learning: The integration of artificial intelligence (AI) and machine learning algorithms is enabling more advanced image analysis, automated feature recognition, and intelligent decision-making capabilities within stereo microscopy systems.
As the field of stereo microscopy continues to evolve, these emerging trends and future developments are poised to revolutionize the way scientists, engineers, and professionals observe, analyze, and interact with the microscopic world, opening up new avenues for discovery and innovation.
Conclusion
Stereo microscopes are versatile and powerful instruments that play a crucial role in a wide range of scientific and industrial applications. With their unique optical design, these microscopes provide a three-dimensional view of samples, enabling users to observe and analyze larger, opaque, and complex specimens in greater detail.
By understanding the technical specifications, measurement capabilities, and practical applications of stereo microscopes, researchers, engineers, and professionals can leverage these instruments to unlock new insights, improve quality control, and drive advancements in their respective fields.
As the field of stereo microscopy continues to evolve, the integration of digital imaging, automation, and emerging technologies promises to further enhance the capabilities and accessibility of these versatile instruments, paving the way for even more groundbreaking discoveries and innovations in the years to come.
Few mathematical problems related to Yagi-Uda antenna
Introduction
To define a Yagi-Uda antenna, we should know the proper definition of the antenna. According to IEEE standard definitions of antennas, “An antenna is a means for radiating or receiving radio waves”.
A yagi-uda antenna is basically an array of rectilinear dipoles with a feed element and other parasitic elements. It can be described as an end-fire array which means the array is set of internally connected antennas and the total unit functions as a single antenna.
Yagi Uda antenna is a very realistic antenna for the high-frequency domain as it operates in the high-frequency field to an ultra-high frequency domain.
Professor S. Uda and professor H. Yagi of Tohoku Imperial University, Japan, first described this type of antenna’s operation. The antenna is often interrupted as ‘Yagi Antenna’.
Use of yagi uda antenna || Applications of yagi uda antenna
Yagi antenna is one of the widely used antennae. It has been used as TV antennas at uncountable homes due to its high directivity. Many readers would recognize it just seeing the picture. It has application in amateur radios, in fields of RADARs, in satellites and RFID applications.
A modern High Frequency yagi-Uda antenna, used for television,
As earlier said, a typical Yagi Uda antenna, is an array of small antennas and it has one element for energy feed and others are parasitic.
The most used feed element of a yagi uda antenna is a folded dipole. The radiator is specially constructed for operation of an end-fire array. Parasitic elements at the forward beam act as directors and the pieces at the rear beam act as reflectors. This completes the antenna.
The thin rods are aligned on a crossbar with their centres. There is one driven element, several parasitic elements, a reflector, and one or more directors. As the name suggests, the parasitic elements are not physically connected with the transceiver and work as passive radiators. They radiate radio waves which further affects the radiation pattern. The distance between the two rods depends on the wavelength of the signal. Typically, the distance changes from one-tenth to one-fourth of the wavelength.
The directors’ size is generally shorter than the driven element, which is also more concise than the reflector.
The gain of a yagi uda antenna depends upon the number of parasitic elements present. Increase in the number of parasitic elements increases the overall gain of the antenna. That is why there are numerous directors in a yagi-uda antenna. As the reflector has a negligible effect on the antenna gain, there is only one reflector in the antenna.
Yagi uda antenna construction
We will discuss the construction of a few parts of the yagi uda antenna. The stakes are – Driven element, Director, & the Reflector.
Director: It is the shortest element of the yagi uda antenna. This part is directed towards the receiving source. The length of the detectors depends upon the distance between the details and the wavelength of the signals. The gain of a yagi uda antenna has a relation with the length of the antenna. The antenna length also increases by increasing the number of directors.
Driven element: It is the element which has the feed point for energy. The transmitter is connected with this element through the feed point. The feed point typically lies at the centre of the component. The length of the part is half of the wavelength.
Reflectors: It is a single unit and constructed at the end of the antenna array just after the driven element. It has the highest length among the parasitic elements. The spacing of reflector depends on the wavelength, beamwidth and gain of the yagi uda antenna. The resonant frequency of reflector is generally lower.
Let us draw some attention towards the operation and working of a yagi uda antenna. Assume a typical yagi uda antenna with a reflector, with a driven element and a single director.
As discussed earlier, the driving element’s length is half of the dipole, and it is connected with electrical energy directly. It supplies power throughout the antenna as it has the feed point, and all other parasitic elements are internally associated with this element.
Now, assume the parasitic elements (both the reflectors and directors) as a general dipole element of a measurable diameter and fed at the middle via a short circuit. Transmission line theory says that a short circuit is enabled to reflect power at 180 degrees.
Thus, the operation can be designed as the mixing up of a power receiver dipole element that receives the power and sends to the matched load and a power transmitter dipole element that transmits the power to the array of the antenna.
Now, at an instant, if the received and sent power are in 180 degrees out of phase with each other, then the result will be zero voltage. That signifies the short circuit of the diode at the feed point. That is why the radiated power is in 180 degrees phase out with the incident waves.
The parasitic elements in the antenna are shorter than ½λ. The reflector is longer than ½λ, and it generally lags the phase of open-circuit voltage. The incoming signal generates the voltage. The director is also shorter than ½λ. It lags the voltage that of current.
Yagi Uda antenna design
Unlike the horn antenna, there are no hard and fast rules to design a yagi-uda antenna. There are some critical physical parameters which resist doing so. Some of the parameters are as follow –
‘Length of element and distance between them.’
The measurement of the rods or the diameter of the rods.
Some critical parameters like – Gain and input resistance.
Though, there are some methods for analysis and calculation to find out the desired results. For an n-element yagi uda antenna, there are 2n-1 numbers of parameters to consider.
The analysis for current distribution is done by solving the ‘Hallen’s integral equation’. The assumption of a classical standing wave and condition of other conductors are also taken into account. The analysis method is complicated and requires accurate results though some vital approximations are necessary to complete it.
The designed antennas go through trial-and-error methods to modify further. Sometimes, the antenna starts with a design and ends up with another after certain modifications in the process. Nowadays, computer simulation helps designers/ engineers to check the result.
Yagi Uda antenna radiation pattern
Radiation Pattern is the angular dependence of the strength of the radio waves from any electromagnetic source. The below image shows the radiation pattern of a yagi uda antenna.
Advantages yagi uda Antenna || Disadvantages of yagi uda antenna
Yagi uda antenna has both its advantages and disadvantages. But there is no doubt that this antenna has made some drastic changes in the field of commercial antennas. It has the highest ever popularity as TV antennas because of its large bandwidth. Let us discuss some of its advantages.
Advantages of yagi uda antenna
Yagi uda antenna has a decent gain of 7dB, which is sufficient for its applications.
Yagi uda antenna array is direction type of antenna.
This type of antennas is suitable for applications in high frequency to the ultra-high frequency range.
These antennas have adjustable from to ack ratio.
Let us discuss some drawbacks of yagi uda antenna.
Disadvantages of yagi uda antenna
Though the applications of yagi uda antennas are suitable for the antenna’s gain, the gain is not very high compared to any other types of antenna.
The designing has a requirement of a large number of elements.
Any damage to the parasitic elements leads to the dysfunctionality of the whole antenna.
The size is quite large, that is why nowadays the antennas are not used by peoples.
Few mathematical problems related to Yagi Uda Antenna
1. Design a yagi uda antenna with the following specifications.Directivity: Relative to ½λ dipole and situated at the same level. Magnitude: 9.2 dB.f0= 50.1 MHz. The desired diameter of the parasitic rods: 2.54 cm.The desired diameter of the metal supporting boom: 5.1 cm.Find out the spacings between elements, lengths and length of the entire array.
Solution:
The operating frequency is given as 50.1 MHz. The wavelength comes as λ = 5.988m.
The desired diameter of the parasitic rods is given as d = 2.54 cm.
Therefore, d /λ = 2.54/598.8
Or, d /λ = 4.24 x 10-3
The desired diameter of the metal supporting boom is given as D = 5.1cm.
Therefore, D /λ = 5.1 / 598.8
Or, D /λ = 8.52 x 10-3
We need to use a chart that gives us ‘optimized uncompressed lengths of parasitic elements of a yagi-uda antenna’. Using this chart, we can understand that the desired antenna array would have a total of five elements (one driven element, one reflector and three directors).
The second column of the chart gives us the optimum uncompressed length for the value of d/λ = 0.0085.
l1 = 0.482λ
l3 = 0.428λ
l4 = 0.424λ
l5 = 0.428λ
The overall antenna length will be L = (0.6 + 0.2) λ = 0.8λ. The spacing or the distance between the directors parasitic will be 0.2λ and the spacing of the reflector will be same that is 0.2λ.
When a deformable material is stretched in a particular direction, its length increases in that direction, and thickness reduces in the lateral one. Similarly, the material is compressed in a specific direction and, its length decreases in that direction, and thickness increases in the lateral one. Poisson’s ratio is a parameter that relates these deformations, which is useful in material selection and application.
Poisson’s Ratio Definition | Poisson’s Ratio Equation
When we apply tensile stress on the material, there is elongation in the direction of applied force and shrinkage in the transverse/lateral movement. Thus the strain gets produced in both directions. The ratio of strain produced in the transverse direction to the strain produced in the direction of tensile stress application is known as Poisson’s ratio.
Its symbol is ʋ or μ.
The ratio obtained has a negative sign, as the ratio obtained is always negative.
Thus,
Poisson’s Ratio= Transverse Strain/ axial Strain
ʋ= -(εx/εy)
Figure : Lateral Strain
Similarly, if compressive stress is applied to the material, there is shrinkage in the direction of applied force and thickening in the transverse/ lateral direction. Thus, the strain gets produced in both directions. The ratio of strain produced in the transverse direction to the strain produced in the direction of compressive stress application is also known as Poisson’s ratio.
Generally, it ranges from 0 to 0.5 for engineering materials. Its value increases under tensile stress and decreases under compressive stress.
The value of Poisson’s ratio for steel ranges from 0.25 to 0.33.
The average value of Poisson’s ratio for steel 0.28.
It depends on the steel type used.
Following is the list of Poisson’s ratio for different steels
Steel Type
Poisson’s Ratio
High Carbon Steel
0.295
Mild Steel
0.303
Cast Steel
0.265
Cold Rolled Steel
0.287
Stainless Steel 18-8
0.305( 0.30-0.31)
Poisson’s Ratio of Aluminum
The value of Poisson’s ratio for aluminum ranges from 0.33 to 0.34.
The average value of Poisson’s ratio for aluminum is 0.33 and for aluminum alloy 0.32.
It depends on the type of aluminum or aluminum alloy used.
Following is the list of Poisson’s ratio for different aluminum
Aluminum Type
Poisson’s Ratio
Aluminum Bronze
0.30
Rolled Aluminum
0.337/0.339
Rolled Pure Aluminum
0.327
Poisson’s Ratio of Concrete
The value of Poisson’s ratio for concrete ranges from 0.15 to 0.25.
Its general value is taken as 0.2.
It depends on the type of concrete (wet, dry, saturated) and loading conditions.
Its value for high strength concrete is 0.1, and for low strength concrete, it is o.2.
Poisson’s Ratio of Copper
The value of Poisson’s ratio ranges from 0.34 to 0.35.
Its general value is taken as 0.355.
It depends on the type of copper or copper alloy used.
Following is the list of Poisson’s ratio for different copper
Copper Type
Poisson’s Ratio
Normal Brass
0.34
Brass, 70-30
0.331
Brass, cast
0.357
Bronze
0.34
Poisson’s Ratio of Rubber
The value of Poisson’s ratio for rubber is from 0.48 to 0.50.
For most of the rubbers, it is equal to 0.5.
Its value for natural rubber is 0.5.
It has the highest value of Poisson’s Ratio.
Poisson’s Ratio of Plastic
The Poisson’s ratio of plastics generally increases with time, strain, and temperature and decreases with strain rate.
Following is the list of Poisson’s ratio for different plastics
Plastic Type
Poisson’s Ratio
PAMS
0.32
PPMS
0.34
PS
0.35
PVC
0.40
Poisson’s Ratio and Young’s Modulus
The materials for which elastic behavior does not vary with the crystallographic direction are known as elastically isotropic materials. Using Poisson’s ratio of the material, we can obtain a relation between Modulus of Rigidity and Modulus of Elasticity for isotropic materials as follows.
Y= 2*G*(1+ʋ)
Where, Y= Modulus of Elasticity
G= Modulus of Rigidity
ʋ= Poisson’s Ratio
Questions and Answers
What is meant by Poisson’s ratio?
When we apply tensile stress on the material, there is elongation in the direction of applied force and shrinkage in the transverse/lateral direction. Thus the strain gets produced in both directions. The ratio of strain produced in the transverse direction to the strain produced in the direction of tensile stress application is known as Poisson’s ratio.
Figure : Lateral Strain
What does a Poisson ratio of 0.5 mean?
Poisson’s ratio of precisely 0.5 means the material is perfectly incompressible isotropic material deformed elastically at small strains.
How is Poisson’s ratio calculated?
Poisson’s Ratio= Transverse Strain/ axial Strain
ʋ=-εx/εy
Figure : Lateral Strain
What is the Poisson’s ratio for steel?
The value of Poisson’s ratio for steel ranges between 0.25 to 0.33.
The average value of Poisson’s ratio for steel 0.28.
What is Poisson’s ratio for aluminum?
The value of Poisson’s ratio for aluminum ranges between 0.33 to 0.34.
The average value of Poisson’s ratio for aluminum is 0.33 and for aluminum alloy 0.32.
What is Poisson’s ratio for concrete?
The value of Poisson’s ratio for concrete ranges between 0.15 to 0.25.
Its general value is taken as 0.2.
It depends on the type of concrete (wet, dry, saturated) and loading conditions.
Its value for high strength concrete is 0.1, and for low strength concrete, it is 0.2.
What is the relation between Poisson’s Ratio and Young’s Modulus of Elasticity?
Y= 2*G*(1+ʋ)
Where, Y= Modulus of Elasticity
G= Modulus of Rigidity
ʋ= Poisson’s Ratio
Which parameters affect the Poisson’s Ratio of Polymers?
The Poisson’s ratio of polymeric materials like plastic generally increases with time, strain, and temperature and decreases with strain rate.
What if Poisson’s ratio is zero?
If the Poisson’s ratio is zero, the material is not deformable; hence, it is a rigid body.
Which material has the highest Poisson’s ratio?
Rubber has the highest Poisson’s Ratio, almost equal to 0.5.
Why is Poisson’s ratio always positive?
Poisson’s ratio is the negative of the ratio of lateral strain to axial strain. The ratio of lateral strain to axial strain is always negative because elongation causes contraction in diameter, which ultimately makes the ratio negative .similarly, compression causes elongation in diameter, which makes the ratio negative.
Is Poisson’s ratio constant?
For the stresses in the elastic range, Poisson’s ratio is almost constant.
Does Poisson’s ratio dependent on temperature?
Yes. With the increasing temperature, Poisson’s ratio decreases.
ObjectiveQuestions
Tensile stress is applied along the longitudinal axis of a cylindrical brass rod with a diameter of 10mm. Determine the magnitude of the strain produced in the transverse direction where the load is required to produce a 2.5 *10-3 change in diameter if the deformation is entirely elastic. Poisson’s ratio of brass is 0.34.
3.5*10-3
5.5*10-3
7.35*10-3
1.0*10-3
Solution: Answer is option 3.
A wire of length 2 m is loaded, and an elongation of 2mm is produced. If the wire’s diameter is 5 mm, find the change in the diameter of the wire when elongated. Poisson’s ratio of the wire is 0.35
Lateral Strain= Change in diameter/ Original Diameter=0.35*10-3
Change in Diameter=0.35*10-3*5*10-3
= 1.75*10-6
=1.75*10-7
Thus, the Change in diameter is 1.75*10-7mm.
A wire of steel having a cross-sectional area of 2 mm2 is stretched by 20 N. Find the lateral strain produced in the wire. Young’s Modulus for steel is 2*1011N/m2, and Poisson’s ratio is 0.311.
In this articles, all the important concepts related to Poisson’s Ratio are discussed in detailed . Numerical and subjective type of questions are added for practice.
Nanofluids have emerged as a promising solution for enhancing heat transfer in various applications. By incorporating nanoparticles into conventional heat transfer fluids, nanofluids exhibit improved thermal properties that can significantly enhance heat transfer efficiency. In this section, we will explore the definition and composition of nanofluids, as well as their application in heat transfer enhancement.
Definition and Composition of Nanofluids
Nanofluids can be defined as suspensions of nanoscale particles in a base fluid, typically water or oil. These nanoparticles, which are usually metallic or non-metallic, are dispersed uniformly in the base fluid, creating a stable colloidal mixture. The size of the nanoparticles used in nanofluids typically ranges from 1 to 100 nanometers.
The composition of nanofluids plays a crucial role in determining their heat transfer properties. The choice of nanoparticles and base fluid depends on the specific application requirements. Metallic nanoparticles, such as copper, aluminum, and silver, are commonly used due to their high thermal conductivity. Non-metallic nanoparticles, such as carbon nanotubes and graphene, are also gaining attention for their unique properties.
To ensure the stability of nanofluids, various techniques are employed to prevent particle agglomeration. Surface modification of nanoparticles, such as coating them with surfactants or polymers, helps to maintain the stability and prevent sedimentation. Additionally, ultrasonication and magnetic stirring are used during the synthesis process to disperse the nanoparticles evenly in the base fluid.
Application of Nanofluids in Heat Transfer Enhancement
The use of nanofluids in heat transfer applications has gained significant interest due to their ability to enhance thermal conductivity and convective heat transfer. The incorporation of nanoparticles into the base fluid increases the effective thermal conductivity of the nanofluid, resulting in improved heat transfer rates.
Nanofluids find applications in various heat transfer systems, including heat exchangers, electronics cooling, and solar thermal systems. In heat exchangers, nanofluids can enhance the overall heat transfer coefficient, leading to improved system performance. The increased heat transfer efficiency of nanofluids allows for smaller heat exchanger designs, reducing space and cost requirements.
In electronics cooling, nanofluids offer a solution to dissipate heat generated by electronic devices more effectively. By using nanofluids as coolants, the heat transfer rate from the electronic components to the cooling system can be significantly improved, ensuring optimal device performance and reliability.
Furthermore, nanofluids have shown promise in solar thermal systems, where they can enhance the absorption and transfer of solar energy. The improved heat transfer properties of nanofluids enable more efficient conversion of solar radiation into usable heat, making them a potential solution for sustainable energy applications.
Heat Transfer Enhancement in Nanofluids
Overview of Heat Transfer Enhancement in Nanofluids
Nanofluids, a combination of base fluids and nanoparticles, have gained significant attention in recent years due to their ability to enhance heat transfer. These nanofluids exhibit improved thermal properties compared to traditional fluids, making them a promising solution for various heat transfer applications. In this section, we will explore the concept of heat transfer enhancement in nanofluids and delve into the underlying mechanisms that contribute to their superior performance.
Nanofluids are engineered by dispersing metallic or non-metallic nanoparticles, typically in the range of 1-100 nanometers, into a base fluid such as water, oil, or ethylene glycol. The addition of nanoparticles alters the thermal conductivity, viscosity, and convective heat transfer characteristics of the base fluid, leading to enhanced heat transfer rates.
One of the key factors that contribute to the improved heat transfer in nanofluids is the significantly higher thermal conductivity of nanoparticles compared to the base fluid. The presence of nanoparticles in the fluid creates a conductive network that facilitates the transfer of heat. This increased thermal conductivity allows for more efficient heat dissipation, resulting in enhanced heat transfer rates.
Importance of Thermal Conductivity in Nanofluids
Thermal conductivity plays a crucial role in determining the heat transfer performance of nanofluids. The ability of a material to conduct heat is quantified by its thermal conductivity coefficient. In the case of nanofluids, the thermal conductivity is significantly enhanced due to the presence of nanoparticles.
The high thermal conductivity of nanoparticles allows for better heat conduction within the nanofluid, enabling faster heat transfer. This property is particularly beneficial in applications where heat dissipation is critical, such as heat exchangers or electronic cooling systems. By utilizing nanofluids with enhanced thermal conductivity, the overall efficiency of these systems can be greatly improved.
Moreover, the increased thermal conductivity of nanofluids also leads to a higher heat transfer coefficient. The heat transfer coefficient represents the rate at which heat is transferred between a solid surface and a fluid. In the case of nanofluids, the higher thermal conductivity results in a larger heat transfer coefficient, indicating a more efficient heat transfer process.
In addition to thermal conductivity, the convective heat transfer characteristics of nanofluids are also influenced by the presence of nanoparticles. The nanoparticles alter the fluid dynamics within the nanofluid, promoting better heat transfer through convection. This enhanced convective heat transfer further contributes to the overall heat transfer enhancement in nanofluids.
Methods to Increase Heat Transfer
Heat transfer is a crucial process in various industrial applications, ranging from cooling electronic devices to optimizing the efficiency of power plants. Enhancing heat transfer is essential to improve the overall performance and effectiveness of these systems. In recent years, researchers have been exploring innovative methods to increase heat transfer, including the use of nanofluids. Nanofluids, which are a combination of nanoparticles and base fluids, have shown great potential in enhancing heat transfer due to their unique thermal properties. In this section, we will explore different ways to enhance heat transfer and delve into the fascinating world of nanofluid technology.
Before we delve into the ways to enhance heat transfer, let’s first understand the fundamental equation that governs heat transfer. The heat transfer equation, also known as Fourier’s law, describes the rate at which heat is transferred through a material. It states that the heat transfer rate is directly proportional to the temperature gradient and the thermal conductivity of the material, and inversely proportional to the thickness of the material. Mathematically, it can be represented as:
q = -k * A * (dT/dx)
Where:
– q is the heat transfer rate
– k is the thermal conductivity of the material
– A is the cross-sectional area through which heat is transferred
– dT/dx is the temperature gradient across the material
Understanding this equation is crucial as it forms the basis for exploring methods to enhance heat transfer.
Ways to Enhance Heat Transfer
Now that we have a basic understanding of the heat transfer equation, let’s explore some ways to enhance heat transfer. These methods can be broadly categorized into two main approaches: improving thermal conductivity and optimizing convective heat transfer.
Improving Thermal Conductivity
One way to enhance heat transfer is by improving the thermal conductivity of the working fluid. Thermal conductivity refers to the ability of a material to conduct heat. By incorporating high thermal conductivity nanomaterials, such as metallic or carbon-based nanoparticles, into the base fluid, the overall thermal conductivity of the nanofluid can be significantly enhanced. These nanoparticles, due to their small size and large surface area, facilitate efficient heat transfer by increasing the number of heat transfer pathways within the fluid.
Optimizing Convective Heat Transfer
Convective heat transfer, which occurs when a fluid flows over a solid surface, is another area where heat transfer enhancement can be achieved. By using nanofluids, researchers have observed improvements in convective heat transfer due to the unique properties of nanoparticles. The presence of nanoparticles in the fluid alters its flow behavior, leading to enhanced heat transfer. The nanoparticles act as disruptors, breaking up the thermal boundary layer near the solid surface and promoting better heat transfer between the fluid and the surface.
To optimize convective heat transfer, researchers have explored various parameters, such as nanoparticle concentration, particle size, and flow velocity. By carefully tuning these parameters, it is possible to achieve significant improvements in heat transfer performance. Additionally, the use of advanced heat exchangers and fluid dynamics techniques can further enhance convective heat transfer in nanofluids.
Comparison of Various Nanofluids
Overview of Nanofluid Thermal Conductivity Dependence on Metallic Particle Properties
Nanofluids, which are colloidal suspensions of nanoparticles in a base fluid, have gained significant attention in recent years due to their potential for enhancing heat transfer in various applications. Metallic nanoparticles, such as copper, silver, and aluminum, are commonly used in nanofluids due to their high thermal conductivity and stability.
The thermal conductivity of nanofluids is influenced by several factors, including the properties of the metallic nanoparticles. The size, shape, and concentration of the nanoparticles play a crucial role in determining the thermal conductivity enhancement of the nanofluid.
Size: The size of the nanoparticles affects the thermal conductivity enhancement of the nanofluid. Smaller nanoparticles have a larger surface area-to-volume ratio, which promotes better heat transfer. As the particle size decreases, the phonon scattering at the nanoparticle-fluid interface increases, leading to enhanced thermal conductivity.
Shape: The shape of the nanoparticles also impacts the thermal conductivity of the nanofluid. Nanoparticles with a higher aspect ratio, such as nanorods or nanowires, exhibit better thermal conductivity enhancement compared to spherical nanoparticles. The elongated shape provides a larger contact area, facilitating efficient heat transfer.
Concentration: The concentration of metallic nanoparticles in the nanofluid affects the thermal conductivity enhancement. As the nanoparticle concentration increases, the interparticle interactions and clustering can occur, leading to a decrease in thermal conductivity. However, at lower concentrations, the nanoparticles disperse more uniformly, resulting in enhanced thermal conductivity.
Comparison of Different Nanofluids for Heat Transfer Enhancement
Numerous studies have been conducted to compare the heat transfer enhancement capabilities of different nanofluids. These studies have focused on various factors, including the type of nanoparticles, base fluid, and experimental conditions. Let’s take a look at some of the key findings:
Metallic Nanoparticles: Nanofluids containing metallic nanoparticles, such as copper, silver, and aluminum, have shown significant heat transfer enhancement compared to pure base fluids. The high thermal conductivity of these metallic nanoparticles facilitates efficient heat transfer, making them suitable for applications in heat exchangers and cooling systems.
Carbon-Based Nanoparticles: Carbon-based nanoparticles, such as graphene and carbon nanotubes, have also demonstrated excellent heat transfer enhancement properties. These nanoparticles have high thermal conductivity and unique structural properties, enabling efficient heat dissipation. However, challenges related to dispersion and stability need to be addressed for practical applications.
Oxide Nanoparticles: Nanofluids containing oxide nanoparticles, such as alumina and titania, have been extensively studied for heat transfer enhancement. These nanoparticles offer good stability and have the potential to enhance convective heat transfer. However, their lower thermal conductivity compared to metallic nanoparticles limits their overall heat transfer enhancement capabilities.
Hybrid Nanofluids: Hybrid nanofluids, which combine different types of nanoparticles, have also been investigated for heat transfer enhancement. These nanofluids aim to leverage the unique properties of multiple nanoparticles to achieve enhanced heat transfer performance. However, further research is needed to optimize the nanoparticle combination and concentration for maximum heat transfer enhancement.
Applications of Nanofluids in Heat Transfer
Nanofluids, which are suspensions of nanoparticles in a base fluid, have gained significant attention in recent years due to their remarkable thermal properties. These unique fluids have found numerous applications in various heat transfer systems, ranging from electronic cooling to solar thermal devices. Let’s explore some of the key applications of nanofluids in heat transfer.
Use of Nanofluids in Electronic Cooling
Electronic devices generate a substantial amount of heat during operation, which can lead to performance degradation and even failure if not properly managed. Nanofluids offer a promising solution for efficient electronic cooling. Two commonly used techniques for electronic cooling are the vapor chamber and jet impingement methods.
Vapor Chamber
Vapor chambers are heat pipes that utilize the evaporation and condensation of a working fluid to transfer heat. By incorporating nanofluids as the working fluid, the heat transfer performance can be significantly enhanced. The high thermal conductivity of nanoparticles improves the overall heat transfer rate, allowing for more efficient cooling of electronic components.
Jet Impingement
Jet impingement cooling involves directing a high-velocity fluid jet onto the surface of a heated object. Nanofluids can be employed in this process to enhance convective heat transfer. The presence of nanoparticles in the fluid increases the heat transfer coefficient, resulting in improved cooling efficiency. This makes nanofluids an excellent choice for cooling high-power electronic devices.
Application of Nanofluids in Radiators for Engine Cooling
Efficient cooling is crucial for the proper functioning of internal combustion engines. Traditional coolants, such as water or ethylene glycol, can be enhanced by adding nanoparticles to form nanofluids. These nanofluids exhibit superior thermal conductivity compared to conventional coolants, leading to improved heat dissipation from the engine.
By utilizing nanofluids in radiators, the heat transfer rate can be significantly increased. This translates to better engine performance, reduced fuel consumption, and lower emissions. Moreover, nanofluids offer enhanced stability and reduced corrosion, making them an attractive option for engine cooling applications.
Utilization of Nanofluids in Solar Thermal Devices
Solar thermal devices, such as parabolic solar collectors, harness the energy from the sun to generate heat. Nanofluids can play a vital role in enhancing the efficiency of these devices. By incorporating nanoparticles into the heat transfer fluid, the thermal conductivity is improved, resulting in more effective heat absorption and transfer.
The use of nanofluids in solar thermal devices allows for higher operating temperatures and increased energy conversion efficiency. This, in turn, leads to improved performance and reduced costs in solar power generation. Nanofluids have the potential to revolutionize the field of solar energy by maximizing the utilization of available sunlight.
Nanofluid Application in Transformer Cooling
Transformers are essential components in electrical power systems, and efficient cooling is crucial to ensure their reliable operation. Nanofluids offer a promising solution for transformer cooling due to their excellent thermal properties. By using nanofluids as the cooling medium, the heat transfer rate can be significantly enhanced.
Nanofluids provide improved thermal conductivity and heat transfer coefficients compared to traditional cooling fluids. This allows for more efficient heat dissipation from the transformer, reducing the risk of overheating and extending its lifespan. The application of nanofluids in transformer cooling systems can lead to enhanced reliability and reduced maintenance costs.
Other Applications of Nanofluids in Cooling and Heat Transfer Systems
In addition to the aforementioned applications, nanofluids have found use in various other cooling and heat transfer systems. Some notable examples include:
Heat exchangers: Nanofluids can be employed in heat exchangers to enhance heat transfer efficiency and reduce energy consumption.
Fluid dynamics: Nanofluids have been studied extensively to understand their flow behavior and optimize their performance in different applications.
Nanotechnology: The field of nanotechnology has benefited greatly from the development of nanofluids, as they offer unique opportunities for heat transfer enhancement at the nanoscale.
Nanofluid synthesis: Researchers continue to explore new methods for synthesizing nanofluids with improved stability and enhanced thermal properties.
Nanofluid properties: The study of nanofluid properties, such as viscosity, density, and thermal conductivity, plays a crucial role in optimizing their performance in various heat transfer systems.
Feasibility and Future Scope of Nanofluids
Nanofluids, a suspension of nanoparticles in a base fluid, have gained significant attention in recent years due to their potential for enhancing heat transfer in various applications. In this section, we will explore the feasibility of nanofluids as thermal fluids, discuss their importance in increasing equipment efficiency, and highlight the future prospects and research opportunities in this exciting field.
Feasibility of Nanofluids as Thermal Fluids
Nanofluids offer several advantages over traditional heat transfer fluids. The addition of nanoparticles to the base fluid enhances its thermal conductivity, which is crucial for efficient heat transfer. The high surface area-to-volume ratio of nanoparticles allows for better heat dissipation, leading to improved thermal performance.
Moreover, nanofluids exhibit unique properties at the nanoscale, such as enhanced convective heat transfer and altered fluid dynamics. These properties make them suitable for a wide range of applications, including heat exchangers, cooling systems, and thermal management in electronic devices.
To ensure the feasibility of nanofluids, researchers have focused on studying their stability, flow characteristics, and thermal properties. Stability is a critical factor as nanoparticles tend to agglomerate, affecting the overall performance of the nanofluid. By employing suitable surfactants and dispersants, scientists have made significant progress in stabilizing nanofluids and preventing particle aggregation.
Importance of Nanofluids in Increasing Equipment Efficiency
The use of nanofluids can significantly enhance the efficiency of various equipment and systems. By improving heat transfer, nanofluids can reduce the energy consumption of heat exchangers, leading to cost savings and environmental benefits. The enhanced heat transfer coefficient and heat transfer rate of nanofluids ensure that heat is efficiently transferred between the solid surface and the fluid.
Additionally, the unique properties of nanofluids, such as their ability to alter fluid dynamics, enable the design of more compact and efficient heat exchangers. This, in turn, leads to space savings and increased performance in a wide range of applications, including automotive cooling systems, power plants, and electronic devices.
Future Prospects and Research Opportunities in Nanofluids
The field of nanofluids holds immense potential for future advancements and research opportunities. As nanotechnology continues to evolve, researchers are exploring novel nanomaterials and nanoparticles that can further enhance the thermal properties of nanofluids. By tailoring the size, shape, and composition of nanoparticles, scientists can optimize their heat transfer capabilities for specific applications.
Moreover, understanding the underlying heat transfer mechanisms in nanofluids is crucial for their successful implementation. Ongoing research aims to elucidate the fundamental mechanisms responsible for the enhanced heat transfer observed in nanofluids. This knowledge will enable the development of predictive models and simulations, facilitating the design and optimization of nanofluid-based systems.
Furthermore, the application of nanofluids extends beyond heat transfer enhancement. Researchers are exploring the use of nanofluids in areas such as energy storage, solar thermal systems, and biomedical applications. The versatility of nanofluids opens up new avenues for innovation and cross-disciplinary collaborations.
Frequently Asked Questions
1. How does nano heat transfer differ from traditional heat transfer?
Nano heat transfer refers to the study and application of heat transfer at the nanoscale, involving the transfer of heat between objects or systems at the nanometer level. Traditional heat transfer, on the other hand, deals with heat transfer at macroscopic scales. Nano heat transfer takes into account unique phenomena and properties that arise at the nanoscale, such as quantum effects and surface interactions.
2. What is heat transfer enhancement using nanofluids?
Heat transfer enhancement using nanofluids involves the incorporation of nanoparticles into conventional heat transfer fluids to improve their thermal properties. By adding nanoparticles, such as metal or oxide particles, to the base fluid, the thermal conductivity and convective heat transfer characteristics of the fluid can be enhanced, leading to improved heat transfer rates in various applications.
3. How can heat transfer be increased using nanofluids?
Heat transfer can be increased using nanofluids by exploiting the enhanced thermal conductivity and convective heat transfer properties of the nanoparticles suspended in the fluid. The nanoparticles facilitate better heat transfer by increasing the effective thermal conductivity of the fluid and promoting convective heat transfer through improved fluid dynamics. This results in higher heat transfer rates compared to conventional fluids.
4. What are the techniques for heat transfer enhancement using nanofluids?
There are several techniques for heat transfer enhancement using nanofluids, including altering the nanoparticle concentration, controlling the particle size and shape, optimizing the fluid flow conditions, and utilizing surface modifications to enhance the interaction between the nanoparticles and the fluid. These techniques aim to maximize the thermal properties and convective heat transfer characteristics of the nanofluid, leading to improved heat transfer rates.
5. How does nanotechnology contribute to heat transfer enhancement?
Nanotechnology plays a crucial role in heat transfer enhancement by enabling the synthesis and manipulation of nanomaterials and nanoparticles with unique thermal properties. Through nanotechnology, researchers can design and engineer nanofluids with enhanced thermal conductivity and convective heat transfer characteristics, thereby improving heat transfer rates in various applications, such as heat exchangers and thermal management systems.
6. What is the role of nanofluid flow in heat transfer enhancement?
Nanofluid flow plays a significant role in heat transfer enhancement as it affects the convective heat transfer characteristics of the fluid. By optimizing the flow conditions, such as flow rate, velocity, and turbulence, the interaction between the nanoparticles and the fluid can be maximized, leading to improved heat transfer rates. Proper understanding and control of nanofluid flow dynamics are essential for effective heat transfer enhancement.
7. How does nanofluid stability impact heat transfer enhancement?
Nanofluid stability is crucial for heat transfer enhancement as it ensures the uniform dispersion and suspension of nanoparticles in the base fluid. Stable nanofluids prevent particle agglomeration and sedimentation, which can hinder the convective heat transfer process. By maintaining nanofluid stability, the nanoparticles can effectively enhance the thermal conductivity and convective heat transfer properties of the fluid, leading to improved heat transfer rates.
8. What are the heat transfer mechanisms in nanofluids?
The heat transfer mechanisms in nanofluids involve three main processes: conduction, convection, and radiation. Conduction refers to the transfer of heat through direct particle-to-particle contact, while convection involves the transfer of heat through the movement of the nanofluid. Radiation, on the other hand, occurs when heat is transferred through electromagnetic waves. The combination of these mechanisms contributes to the overall heat transfer enhancement in nanofluids.
9. What are the applications of nanofluids in heat transfer?
Nanofluids find various applications in heat transfer, including heat exchangers, electronics cooling, solar thermal systems, and automotive cooling systems. The enhanced thermal properties and convective heat transfer characteristics of nanofluids make them suitable for improving heat transfer rates in these applications. Nanofluids offer potential benefits in terms of increased energy efficiency and improved thermal management.
10. How are nanofluids synthesized for heat transfer enhancement?
Nanofluids can be synthesized through various methods, including one-step and two-step processes. One-step synthesis involves directly dispersing nanoparticles into the base fluid, while two-step synthesis involves the separate synthesis of nanoparticles followed by their dispersion into the fluid. The choice of synthesis method depends on factors such as nanoparticle material, desired concentration, and stability requirements.
Elements of a horn antenna and Types of horn antenna
Horn antenna design
Directivity of horn antenna
Horn antenna radiation pattern
Horn antenna gain
Horn antenna beamwidth
Few mathematical problems related to Horn Antenna
Introduction
To define a horn antenna, we should know the proper definition of the antenna. According to IEEE standard definitions of antennas,
“An antenna is a means for radiating or receiving radio waves”.
Horn antenna is the most popular type of Aperture antenna. Aperture antennas are specially designed for microwave frequencies. These types of aperture antennas are widely used and most unadorned other than any kinds.
Though horn antenna usage was started back in the 1800s, the rapid application was created in the 1930s. These antennas had also undergone drastic modification during this time. Numerous thesis and research were done to describe the horn-antenna’s design, find out the radiation pattern of horn-antenna, and applications in different sectors. The applications in microwave and waveguide transmission domain made horns antenna famous. That is why horn- antennas are often interpreted as a microwave horn-antenna.
Horn-antennas have found impactful applications as feed elements for hefty radio astronomy, satellite tracking, communication dishes, and many other places. It is used as a feed for reflector and lenses and also used in phased arrays. These antennas are preferred over different types of aperture antennas, because of its fair and straightforward design, better gain, versatility, and overall performance.
Elements of a horn antenna
Horn antenna is a resonating pipe of various designs which can be shaped for making a larger opening. The overall performance of the antenna is affected by the direction, taper’s amount, directivity.
Types of horn antenna
Horn-antennas have different forms for operations. They are –
Pyramidal horn-antenna is the most used and popular types of the horn-antenna. It is known as a standard gain horn (that is why we choose pyramidal horn for describing). The pyramidal horn’s radiation pattern is the combination of E- and H- sectoral horn-antennas. Let us discuss the design of a pyramidal horn-antenna.
Design Procedure
The designer/ engineer should know the gain (G0). Also the measurements of ‘a’, ‘b’, of the quadrilateral waveguide (used as feed) should be known.
The designing aims to derive dimensions such as – a1, b1, ρe, ρh, Pe, Ph. The calculation should lead the designer to the optimum gain of the horn- antenna.
The selection of a1 and b1 should also be in a guided way so that they will help to find the optimum gain, and we can derive the design equations.
The efficiency of a horn- antenna including the apertures is about 50%. Now, we know that –
a1 ≈ √ (3λρ2)
b1 ≈ √ (2λρ1)
The directivity is given as – D0
D0 = Aem [ 4π / λ2]
Aem is the maximum effective area and has a relationship with the physical area (abbreviated as Ap).
Equation (2) is known as the horn- antenna design equation.
At first, we have to calculate the value of χ, which will gratify the value of gain. An iterative approach with a trial value is considered to find out the value χ.
χ (trail) = χ1 = G0 /2π√2π
Once the correct value is calculated, the value of ρeand ρhare calculated.
The a1 and b1 related to the designs are calculated after that.
a1 = √ (3λρ2) ≈ √ (3λρh) = (G0 /2π) * √ (3λ/2πχ)
b1 = √ (2λρ1) ≈ √ (2λρe) = √ (2λχ)
The values of pe and ph are calculated at last.
Directivity of Horn Antenna
Before we step into finding out the directivity of a horn-antenna, let us know the directivity of an antenna? An antenna’s directivity is defined as the ratio of radiation intensity of an antenna in a particular direction to the averaged radiation intensity over all the directions. Directivity is considered as a parameter for calculating the figure of merit of the antenna.
The following mathematical expression describes the directivity.
D = U / U0 = 4πU / Prad
When the direction is not given, the default direction is the direction of maximum radiation intensity.
Dmax = D0 = Umax / U0 = 4πUmax / Prad
Here, ‘D’ is the directivity, and it has no direction as it is a ratio. U is the radiation intensity. Umax is the maximum radiation intensity. U0 is the radiation intensity of the isotropic source. Prad is the total radiated power. Its unit is Watt (W).
As earlier said, the horn-antenna is of three types. All the classes have different directivity. Let us discuss all of them.
E-Plane Sectoral Horn
The following expression gives the directivity of the E-Plane horn-antenna.
Radiation Pattern is the angular dependence of the strength of the radio waves from any electromagnetic source. The below image shows the radiation pattern of a pyramidal horn-antenna.
Image depicting Horn antenna radiation pattern
Horn Antenna Gain
An antenna’s gain would refer to as the ratio of the intensity in a particular direction to the radiation intensity if the antenna were radiated isotopically. It is an essential parameter for measuring an antenna’s performance and has a close relationship with the antenna’s directivity. The gain of a horn- antenna lies around 25 dBi and the range is typically 10 – 20 dBi.
Horn antenna beamwidth
Antenna bandwidth is the angular distance between two matching points on the reverse side of the outline supreme. The horn-antenna beamwidth gets decreased if the frequency of the process gets increased.
The bandwidth of a practical horn-antenna stays in a range of 10:1 to 20:1.
Few mathematical problems related to Horn Antenna
1. Find the directivity of the E-plane sectoral horn-antenna. The details for the antenna are given below.a = 0.5λ, b = 0.25λ, b1 = 6λ, ρ1 = 6λ
So, the directivity of the given H-plane Sectoral Horn-Antenna is 6.84 dB.
3. Designing details of a pyramidal horn-antenna is given below.ρ2 = 6λ = ρ1 = 6λ; a = 0.5λ, b = 0.25λ; a1 = 6λ = b1 = 6λ;Check if a practical horn-antenna can be designed with those details. Also, find out the directivity of the pyramidal horn- antenna.
