Name: determination of the friction coefficients of icy pavements under different amounts of snowfall
Uploaded: 2023-01-06T12:40:00.000+00:00
Duration: 12 min 21 s
Description: Watch this Scientific Journal Video about Determination of the Friction Coefficients of Icy Pavements Under Different Amounts of Snowfall at JoVE.com

The authors would like to acknowledge the Scientific Research Program Funded by the Shaanxi Provincial Education Department (Program No. 21JK0908).

1. Preparation of the equipment
<ol>
	<li>BPT
	<ol>
		<li>Ensure that the BPT (Figure 1) is within its service life and that the surface is clean and undamaged. 
		NOTE: The components of the BPT are the base, leveling spiral, leveling bubble, pointer, pendulum, lifting spiral, fastening spiral, handle, and dial.</li>
	</ol>
	</li>
	<li>Asphalt slabs
	<ol>
		<li>Ensure that the asphalt mixture sample size used for the experiment is 30 cm x 30 cm x 5 cm.</li>
	</ol>
	</li>
	<li>Freezing equipment
	<ol>
		<li>Ensure that the freezing equipment used can freely regulate the temperature between -20 &#176;C and 0 &#176;C.</li>
	</ol>
	</li>
	<li>Prepare other equipment used in the experiment: a tripod, a measuring cylinder, a rubber sheet, a pavement thermometer, a sliding length ruler, and a brush. 
	NOTE: The size of the rubber sheet used in the experiment was 6.35 mm x 25.4 mm x 76.2 mm, and it should meet the quality requirements given in Table 124.
	<ol>
		<li>Ensure that the rubber sheet does not have any of the following defects: 1) oil stains; 2) widthways edge wear greater than 3.2 mm; or 3) lengthways wear greater than 1.6 mm.</li>
		<li>Before using a new rubber sheet, ensure that the rubber sheet is measured 10 times using a BPT on a dry surface before using it for official testing.</li>
	</ol>
	</li>
</ol>
2. Calculation and analysis of the snowfall
NOTE: Table 2 provides the snowfall class classification. Considering extreme cases, the equipment requires 24 h of snowfall to conduct the study.
<ol>
	<li>To ensure the ease of the experiment, carry out the corresponding calculation and analysis using the upper limit for each level of snowfall. 
	&#8203;NOTE: The different levels of the snowfall depth and the corresponding water volume of the samples after calculation are provided in Table 3. The experiment did not consider the influence of extraordinary snowstorms, and the categories of very light snow to large blizzards were numbered from 1 to 6.</li>
</ol>
3. Equipment calibration
<ol>
	<li>Leveling and zero adjustment
	<ol>
		<li>Place the BPT in a suitable position. 
		NOTE: A suitable position means that the ground is flat and free of potholes.</li>
		<li>Rotate the leveling spiral on the base of the BPT to ensure that the leveling bubble remains in the middle position.</li>
		<li>Loosen the fastening spiral, rotate the lifting spiral to make the pendulum lift and swing freely, and then tighten the fastening spiral.</li>
		<li>Place the pendulum arm on the right cantilever of the pendulum table, keeping the arm in the horizontal position while rotating the pointer to the right side flush with the arm.</li>
		<li>Press the release button to let the pendulum arm swing freely. When the pendulum crosses the lowest point to reach the highest point, hold it by hand. 
		NOTE: If it is accurate, the pointer should indicate zero at this time.</li>
		<li>If the pointer does not show the zero point, loosen or tighten the zeroing nut, and repeat step 3.1.4 and step 3.1.5 until the pointer indicates the zero point.</li>
	</ol>
	</li>
	<li>Calibration of the sliding length
	<ol>
		<li>Place the asphalt slab directly under the pendulum while loosening the fastening spiral so that the lowest edge of the rubber sheet touches the surface of the asphalt slab.</li>
		<li>Prepare the sliding length ruler, and bring it close to the rubber sheet.</li>
		<li>Lift the carrying handle so that the left scale mark of the sliding length ruler is flush with the lowest edge of the rubber sheet.</li>
		<li>Lift the carrying handle, and move the pendulum to the right so that the lowest edge of the rubber sheet just touches the surface of the asphalt slab.</li>
		<li>Observe whether the sliding length ruler is leveled with the edge of the rubber sheet. If it is, the sliding length meets the requirement of 126 mm. Otherwise, continue the following operations.</li>
		<li>Turn the lifting spiral to adjust the height of the pendulum, and repeat steps 3.2.3-3.2.5 to adjust the sliding length so that it meets the requirements.</li>
		<li>When fine-tuning is needed, twist the leveling spiral on the base. 
		&#8203;NOTE: The leveling bubble needs to remain in the center during the adjustment.</li>
	</ol>
	</li>
</ol>
4. Friction coefficient determination
<ol>
	<li>Select seven asphalt slab pieces, clean them with a brush, and dry them naturally at room temperature.</li>
	<li>Number the asphalt slabs in the order of 1-7.</li>
	<li>Place the asphalt slabs into molds, and simultaneously cool and freeze them with a water layer. 
	NOTE: In this experiment, the seven samples were placed into the freezer at a controlled temperature of -10 &#176;C for 24 h. The different samples with the corresponding water volumes are shown in Figure 2.
	<ol>
		<li>Sample 1: To simulate very light snow, pour 9 cm3 of water onto the asphalt sample. Fill the asphalt slab surface void with water, and level the raised part. The ice layer is not expected to completely cover the sample surface asphalt particles. Therefore, some particles will be exposed, and this phenomenon is known as patchy ice.</li>
		<li>Sample 2: To simulate light snow, pour 216 cm3 of water onto the asphalt sample using a measuring cylinder. The expected icing thickness is 2.17 mm. In this case, the water layer completely covers the surface of the sample. It should be completely frozen after icing.</li>
		<li>Sample 3: To simulate medium snow, pour 441 cm3 of water onto the asphalt sample using a measuring cylinder. The expected ice thickness is 5.4 mm.</li>
		<li>Sample 4: To simulate heavy snow, pour 891 cm3 of water onto the asphalt sample using a measuring cylinder. The expected ice thickness is 11 mm.</li>
		<li>Sample 5: To simulate a blizzard, pour 1,791 cm3 of water onto the asphalt sample using a measuring cylinder. The expected ice thickness is 22.1 mm.</li>
		<li>Sample 6: To simulate a large blizzard, pour 2,691 cm3 of water onto the asphalt sample using a measuring cylinder. The expected ice thickness is 33.2 mm.</li>
		<li>Sample 7: Directly place the sample into the freezer for cooling without adding water as a dry frozen sample for comparison.</li>
	</ol>
	</li>
	<li>After freezing, remove the samples from the freezer; in turn, remove the molds, and place them onto the BPT centers, which were previously leveled and zeroed.</li>
	<li>Use the pavement thermometer to measure the surface temperature of the sample and record it.</li>
	<li>Perform sliding length calibration to ensure a sliding distance of 126 mm.</li>
	<li>Press the pendulum arm release switch. When the pendulum arm crosses the lowest point and swings to the highest one, hold it by hand, and read and record the result.</li>
	<li>Restore both the pendulum arm and the pointer to the zero and horizontal positions, respectively. 
	NOTE: The sliding length should be recalibrated each time a new sample is tested.</li>
	<li>Repeat the steps a total of 10 times, and measure seven samples in sequence. 
	&#8203;NOTE: Each sample has 10 measurement readouts, and both the minimum and the maximum value differences should be less than 3.</li>
</ol>
5. Data analysis
<ol>
	<li>Record the data in Figure 3 in a table, and average the measurement results to obtain the final result (Table 4).</li>
	<li>Temperature correction for pendulum values
	<ol>
		<li>Input the temperature value measurements into the following equation to obtain the temperature-compensated BPN value: 
		<img alt="Equation 1" src="/files/ftp_upload/63769/63769eq01.jpg" style="margin: auto;" /> 
		NOTE: The temperature unit used in the original equation is the Kelvin, while the experimental temperatures are all in centigrade, so a temperature conversion has to be carried out. The two temperature units are converted as follows: 
		T (K)&#160;= 273.15 + T (oC)</li>
		<li>Subtract the compensated BPN value from the average BPN value in Table 4 to obtain the final temperature-compensated BPN value.</li>
		<li>Plot the final BPN values in Table 4 as a bar graph for more intuitive results (Figure 4).</li>
	</ol>
	</li>
</ol>

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The authors have nothing to disclose.

The present paper examines the procedure for testing the friction coefficient of icy pavement using a BPT. Several points need to be comprehensively analyzed and are discussed in detail here. First, in terms of the preparation of the asphalt mixture samples, one should try to use road petroleum asphalt to prepare the samples, but this is not a requirement. The preparation of the asphalt mixture samples should be performed in strict accordance with the ASTM (D6926-20) experimental protocols, as this affects the accuracy o...

Pavement friction is defined as the grip between the vehicle tires and the underlying road surface1. The index most commonly associated with pavement friction in road design is the pavement friction coefficient. Friction is one of the most important factors in road design and is second only to durability. There is a strong and clear correlation between pavement friction performance and accident risk2. For example, there is a significant negative correlation between road accident rates and pavement skid resistance3,4,5. Several factors may contribute to a decrease in pavement friction, and one of the most direct and influential of these factors is snowfall6. Specifically, snowfall causes ice to form on the pavement, thereby resulting in a significant reduction in the road friction coefficient7,8. A study focusing on the factors that influence traffic accident rates in southern Finland noted that accident rates commonly peak on days with heavy snowfall and that more than 10 cm of snow can lead to a doubling of the accident rate9. Similar results have been found in studies performed both in Sweden and Canada10,11. Therefore, studying the friction properties of snow-frozen pavements is crucial for improving road safety.
Determining the friction coefficient of icy pavements is a complex process because the friction coefficient may vary under different snowfall levels and pavement ice thicknesses. Furthermore, varying temperatures and tire characteristics may also affect the friction coefficient. In the past, numerous experiments have been conducted to study the friction characteristics of tires on ice12. However, due to the differences in individual environments and tire characteristics, consistent results cannot be obtained and used as a basis for theoretical studies. Therefore, many researchers have attempted to develop theoretical models to analyze the friction of tires on ice. Hayhoe and Sahpley13 suggested the concept of wet friction heat exchange at the interface between tires and ice, while Peng et al.14 proposed an advanced data model to predict friction based on the above concept. In addition, Klapproth presented an innovative mathematical model for describing the friction of rough rubber on smooth ice15. However, the above models have been shown to have significant errors, mainly due to their inability to accurately and efficiently characterize the friction properties of tires on ice16.
To reduce the errors of theoretical models, a large amount of experimental data is needed. The Finnish Meteorological Agency developed a friction model for predicting icy pavement friction, and the formula for that model was primarily based on data obtained from road weather stations and through statistical analysis17. Furthermore, Ivanovi&#263; et al. gathered a significant amount of experimental data by analyzing the friction characteristics of tires on ice and calculated the friction coefficient of ice by regression analysis18. Gao et al. also proposed a novel prediction model of tire-rubber-ice traction by combining the Levenberg-Marquardt (LM) optimization algorithm with a neural network to obtain the formula for the friction coefficient on ice19. All the above models have been either validated or applied in practice and are, thus, considered feasible.
In addition to theoretical methods, many practical methods have been developed for measuring the friction coefficient of pavements in snowy and frozen areas. Due to the particularities of the weather, these methods have been widely used in Nordic countries such as Sweden, Norway, and Finland20. In Sweden, the following three main types of friction measuring devices are used: the BV11, SFT, and BV14. The BV14, a dual friction tester developed specifically for winter maintenance assessments, is directly connected to the measuring vehicle and measures the dry friction on both wheel paths simultaneously20. In Finland, the friction measuring vehicle (TIE 475) is used for winter road maintenance assessments, while in Norway, the ROAR friction measuring device (without water) is a commonly used piece of equipment2. Most of the winter friction measurements carried out in Sweden, Norway, and Finland have been performed using ordinary passenger cars with ABS and instruments measuring deceleration under braking2,20. The advantage of this method is that it is simple and relatively inexpensive, and the main disadvantage is that the accuracy of the method is very low.
The studies described above provide methods for predicting and detecting friction coefficients on ice. However, a uniform method and a specific value to guide road designers have still not been provided. Moreover, for winter roads, the friction coefficient between the tires and ice may vary with respect to different ice thicknesses, and different disposal measures should also be implemented21. Therefore, this paper aims to determine the friction coefficient of icy roads under different amounts of snowfall.
Internationally, the British portable tester (BPT) and the Swedish Road and Transport Research Institute portable friction tester (VTI PFT) are currently the most commonly used instruments for measuring the friction coefficient22,23. The PFT is a portable friction tester developed by VTI, and it allows the operator to take measurements in an upright position and save the data on the computer22. The PFT can measure most contoured road markings, but the number of instruments currently available is still very small2. The BPT is a pendulum friction coefficient tester that was developed by the British Road Research Laboratory (RRL, now TRL). The instrument is a dynamic pendulum impact-type tester used to measure the energy loss in cases when a rubber slider edge is propelled over a test surface. The results are reported as British Pendulum Numbers (BPNs) to emphasize that they are specific to this tester and not directly equivalent to those from other devices24. The instrument has been shown to be useful for the determination of friction coefficients in the experimental pavement field23. This experiment uses the BPT for the determination of friction coefficients.
The present study describes the experimental procedure for measuring the friction coefficient of icy pavements corresponding to different snowfall amounts indoors. The problems to be noted in the experiments, such as experimental calibration, experimental implementation, and the methods of data analysis, are explained in detail. The present experimental procedures can be summarized by the following five steps: 1) the preparation of the equipment, 2) the calculation and analysis of the snowfall, 3) equipment calibration, 4) friction coefficient determination, and 5) data analysis.

<table><tbody><tr><td>Brush</td><td>Shenzhen Huarui Brush Industry Co., LTD</td><td>L-31</td><td></td></tr><tr><td>Freezing equipment</td><td>Haier Group</td><td>BC/BD-251HD</td><td></td></tr><tr><td>Measuring cylinder</td><td>Zhaoqing High-tech Zone Qianghong Plastic Mould Co., LTD</td><td>lb1</td><td></td></tr><tr><td>Pavement thermometer&amp;nbsp;</td><td>Fluke Electronic Insrtument Company</td><td>F62MAX</td><td></td></tr><tr><td>Pendulum Friction Cofficient Meter</td><td>Muyang County Highway Instrument Co., LTD</td><td>/</td><td></td></tr><tr><td>Rubber sheet</td><td>Jiangsu Muyang Xinchen Highway Instrument Co., LTD</td><td>785120123500</td><td></td></tr><tr><td>Sliding length ruler&amp;nbsp;</td><td>Jiangsu Muyang Xinchen Highway Instrument Co., LTD</td><td>785120123500</td><td></td></tr><tr><td>Tripod</td><td>Hangzhou Ruiqi Trading Co., LTD</td><td>TRGC1169</td><td></td></tr></tbody></table>

determination of the friction coefficients of icy pavements under different amounts of snowfall

Ice on road surfaces can lead to a significant decrease in the friction coefficient, thus endangering driving safety. However, there are still no studies that provide exact friction coefficient values for pavements covered in ice, which is detrimental to both road design and the selection of winter road maintenance measures. Therefore, this article presents an experimental method to determine the friction coefficient of icy road surfaces in the winter. A British portable tester (BPT), also known as a pendulum friction coefficient meter, was employed for the experiment. The experiment was divided into the following five steps: the preparation of the equipment, the calculation and analysis of the snowfall, equipment calibration, friction coefficient determination, and data analysis. The accuracy of the final experiment is directly affected by the equipment accuracy, which is described in detail. Moreover, this article suggests a method for calculating the ice thickness for corresponding amounts of snowfall. The results illustrate that even patchy ice formed by very light snowfall may lead to a significant decrease in the friction coefficient of the pavement, thus endangering driving safety. Additionally, the friction coefficient is at its peak when the ice thickness reaches 5 mm, meaning protection measures should be taken to avoid the formation of such ice.

Sample 7 in Table 4 is the dry sample control group, while the remaining samples 1-6 correspond to ice thicknesses ranging from very light snow to a large blizzard.
When comparing sample 7 and the other six groups, ice formation was observed to significantly reduce the friction coefficient of the pavement. Furthermore, the pavement friction coefficient decreased with increasing ice thickness, and the ice thickness tended to stabilize at 5 mm, which corresponds to medium snow. ...

Watch this Scientific Journal Video about Determination of the Friction Coefficients of Icy Pavements Under Different Amounts of Snowfall at JoVE.com

Determination of the Friction Coefficients of Icy Pavements Under Different Amounts of Snowfall

Here, we present a method for determining the friction coefficient of pavements with different ice thicknesses indoors. The complete procedure includes the preparation of the equipment, the calculation and analysis of the snowfall, equipment calibration, friction coefficient determination, and data analysis.

Ice on road surfaces can lead to a significant decrease in the friction coefficient, thus endangering driving safety. However, there are still no studies ...

determination-friction-coefficients-icy-pavements-under-different

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Education

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Mechanical Engineering

Engineering

Unit 1

Friction

SCIENTISTS IN ACTION

2.8K Views.  Chang’an University. Here, we present a method for determining the friction coefficient of pavements with different ice thicknesses indoors. The complete procedure includes the preparation of the equipment, the calculation and analysis of the snowfall, equipment calibration, friction coefficient determination, and data analysis.

Video: Determination of the Friction Coefficients of Icy Pavements Under Different Amounts of Snowfall

Determining the Ice-binding Planes of Antifreeze Proteins by Fluorescence-based Ice Plane Affinity

Antifreeze proteins (AFPs) are expressed in a variety of cold-hardy organisms to prevent or slow internal ice growth. AFPs bind to specific planes of ice through their ice-binding surfaces. Fluorescence-based ice plane affinity (FIPA) analysis is a modified technique used to determine the ice planes to which the AFPs bind. FIPA is based on the original ice-etching method for determining AFP-bound ice-planes. It produces clearer images in a shortened experimental time. In FIPA analysis, AFPs are fluorescently labeled with a chimeric tag or a covalent dye then slowly incorporated into a macroscopic single ice crystal, which has been preformed into a hemisphere and oriented to determine the a- and c-axes. The AFP-bound ice hemisphere is imaged under UV light to visualize AFP-bound planes using filters to block out nonspecific light. Fluorescent labeling of the AFPs allows real-time monitoring of AFP adsorption into ice. The labels have been found not to influence the planes to which AFPs bind. FIPA analysis also introduces the option to bind more than one differently tagged AFP on the same single ice crystal to help differentiate their binding planes. These applications of FIPA are helping to advance our understanding of how AFPs bind to ice to halt its growth and why many AFP-producing organisms express multiple AFP isoforms.

Antifreeze proteins (AFPs) bind to specific planes of ice to prevent or slow ice growth. Fluorescence-based ice plane affinity (FIPA) analysis is a modification of the original ice-etching method for determination of AFP-bound ice planes. AFPs are fluorescently labeled, incorporated into macroscopic single ice crystals, and visualized under UV light.

Antifreeze proteins (AFPs) are expressed in a variety of cold-hardy organisms to prevent or slow internal ice growth. AFPs bind to specific planes of ice ...

Chemistry

Knowledge Based Cloud FE Simulation of Sheet Metal Forming Processes

The use of Finite Element (FE) simulation software to adequately predict the outcome of sheet metal forming processes is crucial to enhancing the efficiency and lowering the development time of such processes, whilst reducing costs involved in trial-and-error prototyping. Recent focus on the substitution of steel components with aluminum alloy alternatives in the automotive and aerospace sectors has increased the need to simulate the forming behavior of such alloys for ever more complex component geometries. However these alloys, and in particular their high strength variants, exhibit limited formability at room temperature, and high temperature manufacturing technologies have been developed to form them. Consequently, advanced constitutive models are required to reflect the associated temperature and strain rate effects. Simulating such behavior is computationally very expensive using conventional FE simulation techniques.
This paper presents a novel Knowledge Based Cloud FE (KBC-FE) simulation technique that combines advanced material and friction models with conventional FE simulations in an efficient manner thus enhancing the capability of commercial simulation software packages. The application of these methods is demonstrated through two example case studies, namely: the prediction of a material's forming limit under hot stamping conditions, and the tool life prediction under multi-cycle loading conditions.

The following paper presents a novel FE simulation technique (KBC-FE), which reduces computational cost by performing simulations on a cloud computing environment, through the application of individual modules. Moreover, it establishes a seamless collaborative network between world leading scientists, enabling the integration of cutting edge knowledge modules into FE simulations.

The use of Finite Element (FE) simulation software to adequately predict the outcome of sheet metal forming processes is crucial to enhancing the ...

Preparation and High-temperature Anti-adhesion Behavior of a Slippery Surface on Stainless Steel

Anti-adhesion surfaces with high-temperature resistance have a wide application potential in electrosurgical instruments, engines, and pipelines. A typical anti-wetting superhydrophobic surface easily fails when exposed to a high-temperature liquid. Recently, Nepenthes-inspired slippery surfaces demonstrated a new way to solve the adhesion problem. A lubricant layer on the slippery surface can act as a barrier between the repelled materials and the surface structure. However, the slippery surfaces in previous studies rarely showed high-temperature resistance. Here, we describe a protocol for the preparation of slippery surfaces with high-temperature resistance. A photolithography-assisted method was used to fabricate pillar structures on stainless steel. By functionalizing the surface with saline, a slippery surface was prepared by adding silicone oil. The prepared slippery surface maintained the anti-wetting property for water, even when the surface was heated to 300 &#176;C. Also, the slippery surface exhibited great anti-adhesion effects on soft tissues at high temperatures. This type of slippery surface on stainless steel has applications in medical devices, mechanical equipment, etc.

Slippery surfaces provide a new way to solve the adhesion problem. This protocol describes how to fabricate slippery surfaces at high temperatures. The results demonstrate that the slippery surfaces showed anti-wetting for liquids and a remarkable anti-adhesion effect on soft tissues at high temperatures.

Anti-adhesion surfaces with high-temperature resistance have a wide application potential in electrosurgical instruments, engines, and pipelines. A ...

Simulating Impacts of Ice Storms on Forest Ecosystems

Ice storms can have profound and lasting effects on the structure and function of forest ecosystems in regions that experience freezing conditions. Current models suggest that the frequency and intensity of ice storms could increase over the coming decades in response to changes in climate, heightening interest in understanding their impacts. Because of the stochastic nature of ice storms and difficulties in predicting when and where they will occur, most past investigations of the ecological effects of ice storms have been based on case studies following major storms. Since intense ice storms are exceedingly rare events it is impractical to study them by waiting for their natural occurrence. Here we present a novel alternative experimental approach, involving the simulation of glaze ice events on forest plots under field conditions. With this method, water is pumped from a stream or lake and sprayed above the forest canopy when air temperatures are below freezing. The water rains down and freezes upon contact with cold surfaces. As the ice accumulates on trees, the boles and branches bend and break; damage that can be quantified through comparisons with untreated reference stands. The experimental approach described is advantageous because it enables control over the timing and amount of ice applied. Creating ice storms of different frequency and intensity makes it possible to identify critical ecological thresholds necessary for predicting and preparing for ice storm impacts.

Ice storms are important weather events that are challenging to study because of difficulties in predicting their occurrence. Here, we describe a novel method for simulating ice storms that involves spraying water over a forest canopy during sub-freezing conditions.

Ice storms can have profound and lasting effects on the structure and function of forest ecosystems in regions that experience freezing conditions. ...

Environment

Fabrication of Superhydrophobic Metal Surfaces for Anti-Icing Applications

Several ways to produce superhydrophobic metal surfaces are presented in this work. Aluminum was chosen as the metal substrate due to its wide use in industry. The wettability of the produced surface was analyzed by bouncing drop experiments and the topography was analyzed by confocal microscopy. In addition, we show various methodologies to measure its durability and anti-icing properties. Superhydrophobic surfaces hold a special texture that must be preserved to keep their water-repellency. To fabricate durable surfaces, we followed two strategies to incorporate a resistant texture. The first strategy is a direct incorporation of roughness to the metal substrate by acid etching. After this surface texturization, the surface energy was decreased by silanization or fluoropolymer deposition. The second strategy is the growth of a ceria layer (after surface texturization) that should enhance the surface hardness and corrosion resistance. The surface energy was decreased with a stearic acid film.
The durability of the superhydrophobic surfaces was examined by a particle impact test, mechanical wear by lateral abrasion, and UV-ozone resistance. The anti-icing properties were explored by studying the ability to repeal subcooled water, freezing delay, and ice adhesion.

We illustrate several methodologies to produce superhydrophobic metal surfaces and to explore their durability and anti-icing properties.

Several ways to produce superhydrophobic metal surfaces are presented in this work. Aluminum was chosen as the metal substrate due to its wide use in ...

Determining and Controlling External Power Output During Regular Handrim Wheelchair Propulsion

The use of a manual wheelchair is critical to 1% of the world&#39;s population. Human powered wheeled mobility research has considerably matured, which has led to improved research techniques becoming available over the last decades. To increase the understanding of wheeled mobility performance, monitoring, training, skill acquisition, and optimization of the wheelchair-user interface in rehabilitation, daily life, and sports, further standardization of measurement set-ups and analyses is required. A crucial stepping-stone is the accurate measurement and standardization of external power output (measured in Watts), which is pivotal for the interpretation and comparison of experiments aiming to improve rehabilitation practice, activities of daily living, and adaptive sports. The different methodologies and advantages of accurate power output determination during overground, treadmill, and ergometer-based testing are presented and discussed in detail. Overground propulsion provides the most externally valid mode for testing, but standardization can be troublesome. Treadmill propulsion is mechanically similar to overground propulsion, but turning and accelerating is not possible. An ergometer is the most constrained and standardization is relatively easy. The goal is to stimulate good practice and standardization to facilitate the further development of theory and its application among research facilities and applied clinical and sports sciences around the world.

Accurate and standardized assessment of external power output is crucial in the evaluation of physiological, biomechanical, and perceived stress, strain, and capacity in manual wheelchair propulsion. The current article presents various methods to determine and control power output during wheelchair propulsion studies in the laboratory and beyond.

The use of a manual wheelchair is critical to 1% of the world&#39;s population. Human powered wheeled mobility research has considerably matured, which ...

Medicine

Source: Nicholas Timmons,&#160;Asantha Cooray, PhD, Department of Physics &#38; Astronomy, School of Physical Sciences, University of California, Irvine, CA

The goal of this experiment is to examine the physical nature of the two types of friction (i.e., static and kinetic). The procedure will include measuring the coefficients of friction for objects sliding horizontally as well as down an inclined plane.
Friction is not completely understood, but it is experimentally determined to be proportional to the normal force exerted on an object. If a microscope zooms in on two surfaces that are in contact, it would reveal that their surfaces are very rough on a small scale. This prevents the surfaces from easily sliding past one another. Combining the effect of rough surfaces with the electric forces between the atoms in the materials may account for the frictional force.
There are two types of friction. Static friction is present when an object is not moving and some force is required to get that object in motion. Kinetic friction is present when an object is already moving but slows down due to the friction between the sliding surfaces.

Friction: Static and Kinetic

Source: Nicholas Timmons,&#160;Asantha Cooray, PhD, Department of Physics &#38; Astronomy, School of Physical Sciences, University of California, Irvine, ...

JoVE Science Education

Physics

Physics I

Characteristics of Dry Friction

Dry friction occurs when two solid surfaces slide against each other without any lubrication or fluid present. It causes resistance when pushing objects along a surface, like a gardener pushing a wheelbarrow. The force applied to move the cart causes dry friction between the wheel and the ground.
Before the wheelbarrow starts moving, the static frictional force acts tangentially to the contact surface, opposing the force that is about to induce the motion. This frictional force prevents the wheelbarrow from slipping and helps to maintain stability. It is important to note that the static frictional force is only present when there is no relative motion between the two surfaces.
When the wheelbarrow is about to slip, the maximum static frictional force at the interface is directly proportional to the normal force. This relationship is defined by the coefficient of static friction, which depends on the types of materials in contact and the roughness of their surfaces.
Interestingly, the static frictional force is independent of the contact area when the normal pressure is within a specific range that avoids deformation or damage to the contacting surfaces. This means that even if the contact area between the wheel and the ground changes, the static frictional force remains constant as long as the normal pressure stays within this particular range.
Once the wheelbarrow starts slipping and movement occurs, the developed kinetic frictional force comes into play. This force is also proportional to the normal force but is generally lower than the maximum static frictional force. The difference between the two forces can be attributed to the fact that surfaces in relative motion have less time to interlock and create resistance.
However, if the wheelbarrow moves at a very low velocity over the surface, the kinetic frictional force becomes approximately equal to the maximum static frictional force. This is because the slow movement allows for more interaction between the surfaces, leading to increased resistance.
The coefficient of kinetic friction primarily depends on the material&#39;s surface properties and the surrounding environment. Factors such as temperature, humidity, and surface contamination can significantly impact the kinetic frictional force.
By examining the factors that influence the coefficients of static and kinetic friction, one can better understand the relationship between the materials in contact, the roughness of their surfaces, and the surrounding environment. This understanding enables individuals to make informed decisions when designing and selecting materials for specific applications, ultimately enhancing the performance and functionality of various systems and devices.

Dry friction occurs when two solid surfaces slide against each other without any lubrication or fluid present. It causes resistance when pushing objects ...

KEY TERMS AND CONCEPTS

Frictional Force

When a body is in motion, it encounters resistance because the body interacts with its surroundings. This resistance is known as friction, a common yet complex force whose behavior is still not completely understood. Friction opposes relative motion between systems in contact, but also allows us to move. Friction arises in part due to the roughness of surfaces in contact. For one object to move along a surface, it must rise to where the peaks of the surface can skip along the bottom of the object. Thus, a force is required that just sets the object in motion. Much of the friction experienced is due to the attractive forces between molecules of the two objects, so even perfectly smooth surfaces are not frictionless. In fact, perfectly smooth, clean surfaces of similar materials tend to adhere, forming a bond called a &#8220;cold weld&#8221;. Frictional forces, such as <img alt="Equation1" src="/files/ftp_upload/12569/12569eq1.png" />, always oppose the motion or attempted motion between objects in contact.&#160;
This text is adapted from <a href="https://openstax.org/books/university-physics-volume-1/pages/6-2-friction">Openstax, University Physics Volume 1, Section 6.2: Friction.</a>

When a body is in motion, it encounters resistance because the body interacts with its surroundings. This resistance is known as friction, a common yet ...

Application of Newton's Laws of Motion

Static and Kinetic Frictional Force

One of the simpler characteristics of sliding friction is that it is parallel to the contact surfaces between systems, and is always in a direction that opposes the motion or attempted motion of the systems relative to each other. If two systems are in contact and moving relative to one another, then the friction between them is called kinetic friction. For example, kinetic friction slows a hockey puck sliding on ice.
However, if two systems are in contact and are stationary relative to one another, then the friction between them is called static friction. The static friction is usually greater than the kinetic friction between two objects. For example, if a person is trying to slide a heavy crate across a concrete floor, they may be pushing very hard but the crate does not move at all. This means that the static friction responds to what we do; it increases to be equal to the push and acts in the opposite direction. If the person pushes hard enough, and the crate starts to move, this is the moment when static friction gives way to kinetic friction. Once in motion, it is easier to keep an object in motion than to get the motion started, indicating that the kinetic frictional force is less than the static frictional force.
This text is adapted from <a href="https://openstax.org/books/university-physics-volume-1/pages/6-2-friction">Openstax, University Physics Volume 1, Section 6.2: Friction.</a>

One of the simpler characteristics of sliding friction is that it is parallel to the contact surfaces between systems, and is always in a direction that ...