Proceedings of the 11th International Conference on Fluid Flow, Heat and Mass Transfer (FFHMT 2024)
Chestnut Conference Centre - University of Toronto, Toronto, Canada – June 16-18, 2024
Paper No. 107
DOI: 10.11159/ffhmt24.107

Experimental Study of Heat Transfer Mechanisms and Energy
Consumption in a Heated Truck Weigh Station during WinterMohammadreza Tohidi1, Jean Rouleau1, Louis Gosselin1
1

Department of Mechanical Engineering, Université Laval,
Quebec City, Quebec, Canada
Mohammadreza.Tohidi.1@ulaval.ca
Jean.Rouleau.1@ulaval.ca
Louis.Gosselin@gmc.ulaval.ca

Abstract – This study presents the findings of an extensive experimental campaign conducted at a weigh station located in Quebec City
(Canada) during the winter 2023-2024. The primary objective was to understand the thermal dynamics and energy consumption profileof the weigh station when the unit heaters beneath the weighing platforms were activated. Our investigation revealed that non-uniform
temperature distributions within the pit, where the scales and associated equipment are located, resulted from the inactive state of one of
the unit heaters during the initial 36 days of the experimental campaign and additionally due to their arrangement. Furthermore, distinct
energy consumption profiles were observed during operational periods when all seven-unit heaters were in use compared to periods with
only six unit heaters operating. The utilization of all unit heaters improved the control of the heating system, which is based on two
thermocouple temperature readings, leading to a range of energy consumption more adapted to outdoor temperature fluctuations. Overall,increasing the heating capacity of the weighing station by 10 kW raised the average pit temperature. This allowed the pit temperature tostay within the adequate working temperature for the weighing equipment within the pit while reducing the average energy consumptionof the weighing station. In addition, this study presents a dataset for validating steady-state Computational Fluid Dynamics (CFD) models
of weighing stations, contributing to future optimization of design and operational strategies.
Keywords: Heat transfer monitoring; Energy consumption; Temperature distribution; CFD validation

1. Introduction
The trucking sector plays a crucial role in the transportation supply chain. Trucks account for over 28% of goods
transportation in Canada [1]. However, overloaded trucks pose significant safety risks and cause damage to the roads.
Regulations governing truck loading are consequently necessary and enforced through weigh stations nationwide. It has beenshown that weigh stations help reduce the percentage of heavy vehicles with excess loading and stabilizes truck equivalency
factors for pavement design [2]. Currently, there are 32 operational weighing stations in the province of Québec, managed
by the Société de l’assurance automobile du Québec (SAAQ) [3]. When an operation is carried out, trucks in the station’s
vicinity are rerouted toward the station and are required to move onto a platform to be weighed. In regions with cold climates
like Québec, snow and ice accumulation on weighing platform surfaces and freezing of the sensing equipment can distortreadings. Heating systems are employed to melt the snow accumulated on the platforms of the weighing station and maintainequipment at an acceptable temperature. Air unit heaters, placed beneath weighing platforms, are commonly used for thispurpose, but they often result in high energy consumption and non-uniform temperature distribution. Whereas current
research on weigh stations is focused on topics such as weigh-in-motion systems [4-5] and improving accuracy [6], thechallenge of reducing their energy consumption in cold climates is still largely unexplored in open literature. Utilizing avalidated Computational Fluid Dynamics (CFD) model of weighing stations, supported by experimental data, facilitates theprecise identification of sources of energy inefficiencies and the design of better stations. However, the size, complexity, andthe fact that stations are subjected to changing outdoor conditions, make in situ experimental studies quite challenging. To
the authors’ knowledge, there is currently no available experimental thermal datasets on operating weigh stations in open
literature, nor energy consumption profiles available. This limits our understanding of the system’s performance, complicatesmodel validation, and, in the end, prevents the design of better systems. In this paper, we present the results of a

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comprehensive experimental campaign that was conducted in a weighing station in the winter 2023-2024. This study offers
an overview of the experimental procedure and presents essential datasets that aid in understanding the thermal behavior andenergy consumption of the system. Additionally, it supports the validation of the weighing station’s CFD model by providing
one of many validation cases.

2. Description of weighing stations
The studied weighing station comprises a series of six platforms of varying lengths (from 4 to 5 m long) over which
trucks pass, positioned above a pit measuring 26.1 m in length, 3.7 m in width, and 1.7 m in height. Fig. 1 offers a visualpresentation of the weighing station, where the pit houses the scales and associated equipment, such as the air unit heaters.
The platforms, constructed from steel, have a thin asphalt layer on top of them, while the pit itself is made from concrete andinsulated by a 0.1-m-thick rigid insulation layer on all sides. Seven unit heaters with different heating powers are positioned
within the pit. These unit heaters are equipped with internal fans and adjustable diffusers. Notably, except for the unit heaters
situated in platforms 1 and 2, all other unit heaters share the same orientation, with the flow directed towards the northernwall of the pit. Fig. 2 illustrates the flow direction from the heater’s outlet. The unit heaters operate using a rule-driven
algorithm; if the temperature in the pit exceeds 3°C, the heating system stops, and it is turned on when the temperature drops
below 3°C within the pit. The control pit temperature is determined by averaging readings from the two thermocouples
located at both ends of the pit. At the beginning of this experimental campaign, the unit heater situated under the platform 6(in yellow in Fig. 2) was out of service. That heater became operational on January 26, 2024. It is worth mentioning that
there are 0.02-m-wide junctions throughout the weighing station, both between consecutive platforms and between theplatforms and the upper surface of the pit, as visible in Fig. 1b. Air exchanges between the pit and the ambient environment
can occur through these gaps. In this paper, we analyzed data from December 21, 2023, to March 5, 2024, covering 36 days
when the platform 6 heater was unavailable and 40 days when it was operational.

Figure 1. Photos of the weighing station (a) Seen inside the pit (b) Seen from above

Figure 2. Floor plan of the pit
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3. Methodology
Figure 3 illustrates the sequential steps of the experimental campaign, beginning with the initial design phase,
progressing through data processing and the presentation of essential datasets. Due to the length of the weighing station (26.1m) and the non-symmetric distribution of unit heaters within the pit, the temperature sensors used for this measurement
campaign had to be strategically placed in the pit. The positions of the 87 temperature sensors are indicated in Fig. 2. As
shown in the figure, 29 vertical stands are used (visible in Fig. 1a and labeled “S” in Fig. 2) to monitor the temperature atthree different heights: LOW (0.40 m above the floor), MID (0.80 m), and TOP (1.2 m) levels. The temperature sensors are
NTC thermistors with a resistance tolerance of ±3%, operating within a temperature range from -55°C to 125°C. Dataregistration occurs every 60 seconds, a frequency chosen due to its effectiveness in minimizing noise levels for the 8-channel
data acquisition system used in this experimental study. The initial data collection started on December 21, 2023. At the timeof writing this paper, data registration is still ongoing. It is worth mentioning that alongside the data registration process,ambient data were simultaneously collected from a nearby weather station. The registration process was briefly paused on
January 9, 2024, February 12, 2024, and March 5, 2024, to apply some modifications to the monitoring setup and it was
promptly restarted to ensure continuous acquisition of data.

Figure 3. Measurement campaign chart
The first step of the data treatment stage of this data analysis involved identifying malfunctioning sensors. Consideringthat sensors are exposed to harsh outdoor conditions, it was expected that some of them could be disconnected or shorted.
After a careful analysis of the results, we found that 5 sensors were not functioning properly, and they were excluded fromthe analysis. At the next step, the recorded data were modified from a 1-minute frequency to a chosen frequency bycomputing the average values to facilitate the present analysis. After profiling the sensors using the average values, thesubsequent stage involved post-processing the data for analyzing the temperature evolution in the pit and the energy
consumption of the weighing station when the heating systems start operating. For tracking temperature evolution, a 30minute frequency was employed. However, for a more detailed understanding of the heating system's status (whether it is
ON or OFF), a 2-minute frequency was used in this study. The analysis of energy consumption at the weighing station during
the winter 2023-2024 was facilitated by discerning the status of the heaters and the duration of their operation.

4. Results
4.1. Analysis
4.1.1. Temperature evolution in the pit
Figure 4 illustrates the 30-minute averaged temperature values reported by sensors positioned at the LOW, MID, andTOP levels of six selected stands along the pit centerline, spanning from December 21, 2023, to March 5, 2024. Additionally,
it depicts the daily averaged outdoor temperature recorded by the nearby weather station and the 3°C threshold to control pit
temperature. By analyzing the temperature profile of sensors affixed to S27, positioned beneath platform 6 and precisely infront of the unit heater, we can observe the operation of the unit heater beneath this platform since January 26, 2024. Prior
to this date, the unit heater was not operating, and the S27 sensors mostly mirrored the outdoor temperature pattern. Before
January 26, 2024, except for December 25, 26, and 27—during which the weighing station was closed, and no operations
were conducted—the rest of the unit heaters were operational, and they functioned continuously. The uninterrupted operation

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(a)

(b)

(c)

Figure 4. Sensors profiles at the (a) LOW, (b) MID, and (c) TOP levelsof the unit heaters was due to the low temperature readings reported by the thermocouple positioned on the northernwall of the pit, directly facing the unit heater at the last platform, which was out of service for that period. This prolonged
operation of the unit heaters resulted in a nearly steady-state temperature profile of the sensors, which was only affected by
the change in outdoor temperature due to heat losses through the gaps. The steady-state temperature profiles will be further
discussed in Section 4.2.
The studied weighing station can be segmented into two distinct sections: the first section, encompassing platforms 1 to
3, and the second section, comprising platforms 4 to 6. Upon examining Fig. 4, it becomes evident that before January 26,
2024, significant differences existed in temperature readings, with reported values decreasing as one move from S3 to S27
for sensors positioned at all three levels. This variation can be attributed to the non-operational status of the unit heater
situated beneath platform 6. After solving the technical issue and ensuring the functionality of all unit heaters, the temperature
difference persisted, but to a lesser extent, and sensors situated at the center of platforms 1, 2, and 3 consistently recorded
higher temperatures. This disparity can be ascribed to the total heating power of 35 kW provided by unit heaters in the firstsection (platforms 1 to 3), in contrast to the 25 kW supplied by those in second section (platforms 4 to 6). Furthermore, oneof the unit heaters under the second platform and the unit heater under the first platform push air toward the pit south wall,
contributing to this non-uniform temperature profile within the pit.
Upon further investigation into the evolution of the temperature profile within the pit, it becomes apparent that, despite
the average outdoor temperature remaining consistently similar during periods with and without the operation of the unit
heater beneath platform 6, with only a 1.43°C difference, there were notable disparities in the maximum and minimum
average temperature values within the pit for these two specific intervals. Fig. 5 illustrates the daily volume averagetemperature within the pit, alongside the daily average outdoor temperature registered by the nearby weather station.
Preceding and following January 26, 2024, the maximum average temperature values were 22.88°C and 31.50°C,
respectively. Similarly, the minimum average temperature values before and after January 26, 2024, were 5.69°C and 9.06°C,
respectively. These findings underscore variations in temperature dynamics within the pit, which contribute to enhancing themelting rate of accumulated snow on the platforms and maintaining equipment at a higher temperature.
4.1.2. Energy Consumption
Given that the weighing station was constrained by having one unit heater not functioning for the initial 36 days of thisexperimental campaign, comparing the energy consumption profile of the weighing station during these two periods would
result in a better understanding of the weighing station’s energy performance. Fig. 6a illustrates the energy consumption of
the weighing station versus the average outdoor temperature, while Fig. 6b represents the energy consumption of theweighing station versus the average pit temperature. To enhance data representation, temperature values are averaged for

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every 6-hour interval, and the reported energy consumption corresponds to the amount of energy consumed during theseintervals.

Figure 5. Daily volume average temperature inside the pit(a)(b)
Figure 6. Energy consumption during 6-h periods versus (a) average outdoor temperature, and (b) average pit temperature
Figure 6.a illustrates that when the weighing station was limited to 6 operational unit heaters, their operation remained
continuous for most days across a wide range of outdoor temperatures, from -20°C to nearly 0°C. This continuous operationof the unit heaters resulted in the energy consumption profile of the system before January 26, 2024, resembling a step
function. During these periods, the heating system showed less dynamic behavior in response to the outdoor temperature

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changes. When the outdoor temperature dropped below -3°C, the unit heaters were unable to maintain their operation status
relatively, and their full heating capacity was reported for each 6-hour interval. Since January 26, 2024, with all seven-unit
heaters operational, the heating system has been capable of adjusting its operation based on readings obtained fromthermocouples. This adjustment has resulted in a more diverse range of energy consumption in response to varying outdoor
temperatures, effectively preventing excessive energy consumption. With the unit heaters now automatically adapting theiroperational status, the average outdoor temperature threshold for unit heaters to operate continuously has shifted toapproximately -12°C, which is about 9 degrees lower than when one unit heater was out of service.
Additionally, Fig. 6.b illustrates that at identical energy consumption levels, the average temperature within the pit was higher
when seven unit heaters were operational compared to periods when six unit heaters were in operation. For instance, themaximum average pit temperature reported for the days prior to January 26, 2024, was 24.85°C. However, this temperature
value was achieved with a significantly lower energy consumption level during the subsequent 40 days when all heaters werein operation. As depicted in the figure, for the operational periods following January 26, 2024, the average pit temperature
exhibited greater sensitivity to the energy consumption variation, resulting in preventing the unit heaters from operating
uninterrupted as much as possible.
Figure 7 illustrates the daily energy consumption of the studied weighing station over the 76 days of the experimental
campaign. As depicted in the figure, the average energy consumption for the initial 36 days, with 6-unit heaters, was 1049.5
kWh/day. However, this number decreased to 972.48 kWh/day for the subsequent 40 days. It is worth mentioning that thedifference in the average outdoor temperature between both periods was negligible, allowing a direct comparison of energy
consumption without considering the outdoor temperature effect. Increasing the number of operational unit heaters by one
unit enhanced the heating capacity of the weighing station by 10 kW; however, the energy consumption was reduced despite
this increase, attributable to the unit heaters operating for shorter periods of time and their operation being better controlled
by the thermocouples' temperature readings.

Figure 7. Daily energy consumption of weighing station during
the 76 days of experimental campaign
4.2. Extraction of data for CFD Validation
In addition to being used for developing a better understanding of the heat transfer and energy consumption patterns of
the weighing stations, the measurements were also used to validate a CFD model that was developed in parallel (not describedhere). This subsection explains how data were extracted from the dataset for that purpose and presents an example of theresulting temperature profiles used for validation.
Given that the first version of the weighing station's CFD model that we developed runs in steady state to limit thecomputational time, extracting information suitable for model validation requires identifying instances when the system107-6

achieved thermal stability while the ambient conditions remained relatively constant. When thermally constant conditions
within and outside the pit are present, the measurements at the different sensor locations during that time interval can becompared with the results of the CFD model. The continuous experimental campaigns enabled the identification of several
instances during which nearly steady-state conditions were reached, but only one is presented here for the sake of concision.
It has been previously discussed that before January 26, 2024, the unit heater situated in front of the thermocouple
attached to the northern end of the pit was not operational. This technical issue resulted in the continuous operation of theremaining unit heaters. Consequently, this created several thermally steady-state intervals within the pit, coinciding withrelatively constant ambient conditions. In essence, most validation cases correspond to those moments preceding January
26, 2024. The case selected for this paper was arbitrarily chosen from that specific interval. The duration of the validationcase is defined by the period during which the ambient conditions remained relatively constant.
For instance, on January 11, 2024, the outdoor temperature remained nearly constant at -8°C from 6 PM to 8 PM. During
this time, there was negligible snow precipitation with a total accumulation of 0.0005 m. The average wind velocity was 0.04
m/s, and the average humidity, 89%. By analyzing the sensor profiles during this two-hour interval, it was found thatmaximum standard deviation for temperature values was 0.67°C for the TOP level, 0.70°C for the MID level, and 0.58°C
for the LOW level sensors. In other words, the temperature profile was nearly constant during that two-hour interval.

Figure 8. Steady-state temperature profile the (a) LOW, (b) MID, and (c) TOP levels (January 11, 2024, 6 PM to 8PM)
Figure 8 reports the measured temperature values within the pit. Note that due to sensor malfunction, there is no value
reported for sensors 24 and 25 from the LOW level, sensor number 8 from the TOP level, and sensors 18 and 25 from theMID level. Fig. 8 is one of several datasets that could be used as a validation case for weighing station's steady-state CFD
models. The validity of the converged CFD solution can be evaluated by directly comparing temperature values at thelocations of the stands at three different heights.

5. Conclusion
In this study, we presented the results of a comprehensive experimental campaign that was conducted in a weighing
station during the winter 2023-2024. Our findings reveal several crucial insights into the operation of weighing stations incold climates like in Canada. First, we observed that the non-operational status of one of unit heaters and the arrangement ofunit heaters within the pit resulted in a non-uniform temperature distribution within the pit.
Additionally, we observed disparities in energy consumption profiles between periods when all unit heaters wereoperational and when one was out of service. Having all seven unit heaters available resulted in enhanced automatic
adjustment of their operation based on thermocouple temperature readings. This led to a wider range of energy consumption
level in response to outdoor temperature variations and a higher sensitivity of the average pit indoor temperature to energy
consumption changes. This improvement ultimately resulted in a lower average energy consumption during the period when
the heating capacity of the weighing station was increased by 10 kW.
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Moreover, our study provides valuable data for validating CFD models of weighing stations, enhancing ourunderstanding of heat transfer dynamics, and aiding in the design of more efficient systems. By comparing experimental datawith the results of the steady-state CFD model, we can refine modeling techniques and improve predictive capabilities for
optimizing weighing station designs.
Different avenues for future research can be explored. We aim to utilize the validation case presented in this study toevaluate the validity of the weighing station's CFD model. Upon validating the model, our objective is to identify energy
inefficiencies and determine the optimal configuration and control that can reduce the energy, consumption while keeping
adequate temperature profiles within weighing stations in winter.

6. Acknowledgement
This work was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) and by the
Société de l’assurance automobile du Québec (SAAQ) through Alliance grant ALLRP 571280 - 21. The authors would also
like to thank André Chamberland, technician at the Department of Mechanical Engineering, Université Laval, for his great
help during the measurement campaign.

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equivalency factors for pavement design, Journal of Transportation Engineering Part B – Pavements 149 (3) Article
number: 04023015 (10.1061/JPEODX.PVENG-1123)[3] https://saaq.gouv.qc.ca/controle-routier-quebec/controle-route/presence-territoire (as of March 29, 2024).
[4] A. Konior, T. Konior, K. Brzozowski, A. Maczynski, A. Rygula, New functionalities of the weigh-in-motion system:
iWIM solution, Transport Problems 18 (2023) 161-170 (10.20858/tp.2023.18.2.14).
[5] P. Aguero, R.E. Christenson, S. Lobo-Aguilar, Utilizing Krigin metamodeling to provide practical and effective bridge
weigh-in-motion, Journal of Bridge Engineering 28 (2023) Article number: 04022138 (10.1061/JBENF2.BEENG5760).
[6] S. Stawska, J. Chmielewski, M. Bacharz, K. Bacharz, A. Nowak, Comparative accuracy analysis of truck weightmeasurement techniques, Applied Sciences – Basel 11 (2021) Article number 745 (10.3390/app11020745).

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