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In this paper, we demonstrate three experimental approaches to improve the performance of lock-in thermography (LIT). The infrared imaging (IR) technique is extensively used for failure analysis (FA) in the semiconductor industry. However, with the conventional LIT, low-contrast topography images can be obtained at room temperature due to the poor emissivity gradient in the devices and the limitation on the performance of the infrared camera. The grayscale topographical contrast is improved significantly when the device under test is heated from room temperature to 90 °C. A compact printed circuit board heater is designed and customized for this application. Furthermore, the heater can also be used in the lock-in loop to get the enhanced topography images. These methods are implemented experimentally, and the results are validated using finite element simulation. The thermal enhancement approaches proposed in this paper are demonstrated at die level on a defective silicon interposer sample. The topographical contrast and the signal intensity of the hotspot obtained are enhanced when compared to the classical LIT performed at room temperature. To reduce the thermal budget of the heat-assisted method, dual LIT is developed where the two consecutive lock-in measurements are performed to obtain hotspot amplitude and topography image with good contrast. In addition, the topography image obtained from this technique is less susceptible to input noise levels. To increase the throughput of the FA process, quadrature lock-in thermography, a dual-purpose measurement technique is shown. A high-contrast topography image and the hotspot location are obtained from the same lock-in thermogram by performing trigonometric conditioning. The throughput from this approach is the same as the classical LIT technique. [ABSTRACT FROM AUTHOR]

Constraining the geometry and displacement of crustal‐scale normal faults has historically been challenging, owing to difficulties with geophysical imaging and inability to identify precise cut‐offs at depth. Using a modified workflow previously applied to contractional systems, flexural‐kinematic (Move) and thermal‐kinematic (Pecube) models are integrated with apatite (U‐Th)/He (AHe) and apatite fission track (AFT) data from Teton footwall transects to constrain total Teton fault displacement (Dmax). Models with slip onset at ∼10 Ma and flexure parameters that best match the observed Teton flexural profile require Dmax > 8 km to produce young (<10 Ma) AHe ages observed at low elevation footwall positions in the Tetons. For the same slip onset, models with Dmax of 11–13 km provide the best match to observed AHe data, but displacements ≥16 km are required to produce observed AFT ages (13.6–12.0 Ma) at low elevations. A more complex model with slow slip onset at ∼25 Ma followed by faster slip at ∼10 Ma yields a good match between modeled and observed AHe ages at a Dmax of 13–15 km. However, this model predicts low elevation AFT ages 6–8 Ma older than observed ages, even at Dmax values of 16–17 km. Based on this analysis and integration with previous studies, we propose a unified evolution wherein the Teton fault likely experienced 11–13 km of Miocene‐recent displacement, with AFT data likely indicating a pre‐to early Miocene cooling history. Importantly, this study highlights the utility of using integrated flexural‐ and thermal‐kinematic models to resolve displacement histories in extensional systems. Key Points: Integrating flexural‐ and thermal‐kinematic models with thermochronology data provides constraints on crustal‐scale normal fault evolutionResults show how effective elastic thickness, fault geometry, and detachment depth impact fault evolution and predicted age dataFor the contested displacement history of the Teton fault example, analyses indicate >11 km and potentially >16 km of normal displacement [ABSTRACT FROM AUTHOR]

Small topographic features below the resolution of existing orbital data sets may create "micro ultra‐cold traps" within the larger permanently shadowed regions that are present at the lunar poles. These ultra‐cold traps are protected from the major primary and secondary illumination sources, and thus would create surfaces that are much colder than lower‐resolution temperature maps would indicate. We examine this effect by creating a high resolution (1 m pix−1) terrain map based on upscaled data from the Lunar Orbiter Laser Altimeter. This map is illuminated by scattered sunlight and infrared emissions from sunlit terrain, which are then run through a thermal model to determine temperatures. We find that while most of the terrain experiences maximum temperatures around 50 K, there are a number of 1–30 m‐scale ultra‐cold traps with maximum temperatures as low as 20–30 K. By comparing our modeled ultra‐cold trapping area to volatile abundances measured by Lunar Crater Observation and Sensing Satellite (LCROSS), we reveal a diverse environment where the surficial abundances necessary to explain the LCROSS results are strongly dependent on precisely where the impact occurred. Plain Language Summary: Near the Moon's poles, there exist large regions of permanent shadow that are much colder than the surrounding terrain. Their consistently low temperatures allow molecules like water to accumulate within them, potentially creating deposits that play a key role in long‐term crewed exploration of the Moon. Within these permanently shadowed regions, there are likely smaller areas that are shielded from secondary illumination sources like scattered sunlight, making these areas even colder than the permanently shadowed terrain around them and allowing them to trap additional molecules like carbon dioxide, methane, and ammonia. We have modeled the temperatures of the lunar surface at the Lunar Crater Observation and Sensing Satellite (LCROSS) impact site at a resolution of 1 m px−1 to examine to what extent these small‐scale terrain features could explain the molecular abundances measured by LCROSS. By comparing our modeled temperatures to the LCROSS results, we find that the surface composition responsible for the LCROSS measurements depends on whether LCROSS impacted one or more of these small, extremely cold regions. Key Points: We model surface temperatures at the Lunar Crater Observation and Sensing Satellite (LCROSS) impact site at a resolution of 1 m px−1Small craters create ultra‐cold (<25 K) regions that enhance the surface's ability to cold‐trap non‐water volatilesComparisons with LCROSS volatile abundances reveal a diverse environment of potential surficial volatile compositions [ABSTRACT FROM AUTHOR]

Analytical thermal modeling is expected to be an efficient method for a rational heat dissipation strategy and quality assurance of products in oblique cutting processes. In contrast, conventional metal-cutting models are mainly limited to applications for lack of comprehensive analysis and unsustainable experimental validation. In this study, an improved analytical approach based on the velocity plane, including the cutting velocities, is proposed to determine the spatial distribution of heat source associated with the cutting edge inclination for addressing the geometrical complexity in the oblique cutting process. The model comprehensively considers the negative rake angle and the cutting edge inclination, nonuniform contact stress distribution at the tool–chip interface, and nonuniform partition of heat between the cutting tool and workpiece to predict the temperature distribution at the tool-chip/work interface in the oblique cutting process. To evaluate the model, a novel temperature measurement method, which can monitor the on-site temperature rise at the tool-chip/workpiece interface, was integrated at the multiple positions near the cutting edge. Experimental values measured by the sensor-integrated tool showed good consistency with the predicted value calculated using the analytical thermal model. Our proposed model is demonstrated to successfully predict the temperature distribution on the tool, which lays a foundation for optimizing the cutting parameters and guiding the tool design during the oblique cutting process. • Multiple sensors integrated in cutting tool for online monitoring temperature at the tool-chip/work interface. • Non-uniform heat partition fraction and contact stress at tool-chip interface was introduced in the presented model. • Predicted temperature field on the tool–chip interface was symmetric on the axis parallel to the chip flow direction. • Temperature in tool-work interface climbs faster but its maximum temperature is lower than that in tool-chip interface. [ABSTRACT FROM AUTHOR]

Cooling systems provide a safe thermal environment for the reliable operation of IT equipment in data centers (DCs) while generating significant energy consumption. Therefore, to achieve energy savings in cooling system control under dynamic thermal distribution in DCs, this paper proposes a multi-setpoint cooling control approach based on deep reinforcement learning (DRL). Firstly, a thermal model based on the XGBoost algorithm is constructed to precisely evaluate the thermal distribution in the rack room to guide real-time cooling control. Secondly, a multi-set point cooling control approach based on the deep Q-network algorithm (DQN-MSP) is designed to finely regulate the supply air temperature of each air conditioner by capturing the thermal fluctuations to ensure the dynamic balance of cooling supply and demand. Finally, we adopt the extended CloudSimPy simulation tool and the real workload trace of the PlanetLab system to evaluate the effectiveness and performance of the proposed approach. The simulation results show that the proposed control solution effectively reduces the cooling energy consumption by over 2.4% by raising the average air supply temperature of the air conditioner while satisfying the thermal constraints. [ABSTRACT FROM AUTHOR]

The paper presents the results of thermal modeling of a half-bridge monolithic integrated circuit (IC) with integrated drivers and enhanced mode power high electron mobility transistors, based on a GaN-on-SOI heterostructure. It had been established that the main heat sources in the IC were the half-bridge GaN HEMTs. The heat from the half-bridge GaN HEMTs propagates in the chip and leads to heating of the logic block and gate drivers. Heating of half-bridge GaN HEMTs leads to increased channel resistance and IC output current drop. Heating of the gate drivers reduces driving current, as a result, increases the switching time of the half-bridge GaN HEMTs. Heating of the logic block increases the rise and fall times of the generated control signals, which worsens the dynamic characteristics of the IC. A comparative analysis of heat propagation for IC dies based on GaN-on-SOI and GaN-on-Si heterostructures showed that GaN-on-SOI structure has a 40% greater junction-to-backside thermal resistivity compared to GaN-on-Si structure. In this case, the specific thermal resistance in the direction of heat propagation from the hotspot of the transistor to the backside of the die for the GaN-on-SOI structure is almost two orders of magnitude greater than in the direction of its propagation to the frontside of the chip. The results obtained were used for IC layout optimization. The rearrangement of GaN-on-SOI IC functional blocks, as well as to introduction of additional heat-spreading elements on the frontside of chip were carried out during the optimization. [ABSTRACT FROM AUTHOR]

Among solar energy technologies, differences exist in terms of costs, performance, and environmental sustainability. Flatplate solar collectors, solar towers, and parabolic dish systems offer high thermal efficiency and versatility, but they may be more costly and bulky compared to other collector models. This study focused on evaluating the efficiency of a cylindrical parabolic collector (CPC) for the production of domestic hot water in a high Andean region of Peru, using the F-Chart method. Its performance was estimated considering the energy demand for hot water in a single-family home with four occupants, in accordance with national regulations and international recommendations. Additionally, the collector area, water temperature, and incident solar radiation were determined based on meteorological data obtained using the PVsyst software. On the other hand, the F-Chart methodology was employed to find the dimensionless factors X and Y of the CPC collector, which allowed estimating the solar fraction factor and the monthly useful energy that can be provided by the designed CPC system. The results showed that, during months of maximum solar radiation, the CPC is capable of satisfying between 129% and 144% of the energy demand for hot water. This indicates that there is a surplus of usable solar energy in the collector during the summer, while in autumn and winter, the solar contribution balances and slightly exceeds the demand. CPC can significantly contribute to the development of high Andean areas by improving quality of life, reducing costs, and promoting environmental sustainability compared to other available technologies. [ABSTRACT FROM AUTHOR]

Reducing the usage of fossil fuels in today's applications is viewed as a feasible energy source, mainly by substituting Renewable Energy Sources (RESs). Many people utilize Renewable Energy Sources (RESs) for heating, particularly in Solar Water Heaters (SWH). Despite the accessibility and affordability of SWH technologies in Egypt, no comprehensive study has been conducted to explain the potential of Egyptian compounds to provide hot water for village home usage. For this reason, the first dynamical simulation of a solar heating system to supply Sanitary Hot Water (SHW) and the hot water needed to heat 756 villages in the Palm Hilis compound in New Cairo, Egypt, is attempted in this year-long project. The Metonym software, which is modeled in TSOLTM, is used to extract the climate data. In addition to using an auxiliary gas boiler, a one-year dynamic analysis that took into account all potential losses were carried out. Based on the results, the installed collector power of SWHS is 732 kW, and the solar energy contribution to DHW is 14.27 MWh. Solar energy powers 97% of the system. In terms of economics, COE and NPV are 0.00083 and 57072 $/kWh, respectively. In addition, the suggested system has a 4.4-year payback period and costs 0.223 dollars for 1 m3 of hot water. The suggested approach prevented 515075 kg of CO2 emissions annually, saving 4106080 dollars when the cost of CO2 emissions was taken into consideration. After the project's lifetime, the total profit is 10381$. Egypt and other nations with similar climates can benefit from the technological, economic, and environmental research presented in this paper. [ABSTRACT FROM AUTHOR]

Thermal energy storage (TES) is one of the key technologies for enabling a higher deployment of renewable energy. In this context, the present study analyzes the modeling strategies of one of the most common TES systems: stratified thermal storage tanks. These systems are essential to many solar thermal installations and heat pumps, among other clean energy technologies. Three different one-dimensional tank models are compared by their computing speed and resilience to long time steps. Two of the models analyzed are numerical, one being explicit and the other one implicit, and the other is analytical. The models are validated against data from experiments carried out considering small-scale stratified tanks, showing that their performance can be improved by using the Advanced Flowrate Distribution (AFD) method. The results show that the analytical model maintains its accuracy with longer time steps and is robust against divergence. Conversely, the numerical models show equivalent performance for short time steps, while the computation time is reduced. Although the AFD method shows promising results by achieving an improvement of 43% in terms of Dynamic Time Warping, its parameter optimization must be generalized for different tank designs, flow rates, and temperatures.

The energy impact of integrating phase change materials (PCMs) in buildings for thermal energy storage has been modeled by various whole-building simulation programs, demonstrating that PCM incorporation can reduce energy consumption, provide grid flexibility and resilience, and reduce CO2 emissions. The models assume that the PCMs are in perfect operating condition and underestimate the impact of actual phase change behavior (e.g., enthalpy curve shape) on thermal load shifting in practical deployment. In this paper, we bridge the gap between theory and practice when evaluating the energy impact of PCMs by using a model-driven approach to develop durable thermal energy storage materials with desired phase change properties. For ease of integration, we fabricate shape-stabilized PCMs (ss-PCMs) by encapsulating solid-liquid polyethylene glycol (PEG) consisting of different molecular weights within mesoporous magnesium oxide (MgO) matrices. Learning from the modeling results, we manipulate phase change properties such as peak melting temperature and temperature glide of PEG-MgO ss-PCMs during the synthesis process to achieve desired properties. As such, the energy density is maximized within the optimum operating temperature range, which is critical to boosting energy efficiency. Compared to a case with no PCM, a layer of PEG-MgO ss-PCM integrated into the wall provides a 50% reduction in the peak load and also exhibits a repeatable phase change behavior for up to 1000 thermal cycles without leakage, showing durability of this material. We also show that this lab-scale synthesis process is easy to be scaled up by 100 times for a demonstration of large-scale industrial production. The synthetic tunability of transition temperature of ss-PCMs also extends their applicability beyond buildings.

Appropriate thermal modeling is the first step in controlling thermal comfort and reducing energy consumption. In this article, the thermal modeling of an office room with a variable air volume (VAV) system is considered. Various thermal modeling methods are reviewed, and finally, the zonal method is selected. The main advantage of the selected method is its simple formulation but still accurate results. Furthermore, the output equations are in the state-space forms which are suitable for control applications. The thermal model is obtained by considering the airflow patterns in the office room. One of the key features of the obtained model is its applicability to winter as well as summer conditions. DesignBuilder software is also used to validate the thermal model. Results indicate the accuracy of the obtained thermal model in all weather conditions. [ABSTRACT FROM AUTHOR]

The primary power source for electric vehicles (EVs) is batteries. Due to the superior characteristics like higher energy density, power density, and life cycle of the lithium iron phosphate (LFP) battery is most frequently chosen among the various types of lithium‐ion batteries (LIBs). The main issues that users encounter are the time required to charge an EV battery and the safety of the EV battery during the charging period. The fast‐charging means, charging a battery with high currents which may lead to a rise in the temperature of a battery. The abrupt rise in battery temperature may cause changes in the internal chemical structures of the battery, reducing battery life even further. In this regard, an optimal charging profile design is of utmost importance in order to satisfy dual objectives simultaneously such as less charging time and improvement in life of the battery. To overcome the conflict between charging speed and rise in temperature an optimal multistage constant current (MSCC) based charging strategy has been investigated under different operating conditions. In addition, the proposed charging profiles have been studied using experimentation. [ABSTRACT FROM AUTHOR]

Predicting the operating temperature of lithium-ion battery during different cycles is important when it comes to the safety and efficiency of electric vehicles. In this regard, it is vital to adopt a suitable modeling approach to analyze the thermal performance of a battery. In this paper, the temperature of lithium-ion NMC pouch battery has been investigated. A new formulation of lumped model based on the thermal resistance network is proposed. Unlike previous models that treated the battery as a single entity, the proposed model introduces a more detailed analysis by incorporating thermal interactions between individual cells and tabs within a single cell scenario, while also considering interactions between cells and insulators or gaps, located between the cells, within the module case. This enhancement allows for the precise prediction of temperature variations across different cells implemented within the battery module. In order to evaluate the accuracy of the prediction, a three-dimensional finite element model was adopted as a reference. The study was performed first on a single cell, then on modules composed of several cells connected in series, during different operating conditions. A comprehensive comparison between both models was conducted. The analysis focused on two main aspects, the accuracy of temperature predictions and the computational time required. Notably, the developed lumped model showed a significant capability to estimate cell temperatures within the modules. The thermal results revealed close agreement with the values predicted by the finite element model, while needing significantly lower computational time. For instance, while the finite element model took almost 21 h to predict the battery temperature during consecutive charge/discharge cycles of a 10-cell module, the developed lumped model predicted the temperature within seconds, with a maximum difference of 0.42 °C. [ABSTRACT FROM AUTHOR]

The microphysical structure of the lunar regolith provides information on the geologic history of the Moon. We used remote sensing measurements of thermal emission and a thermophysical model to determine the microphysical properties of the lunar regolith. We expand upon previous investigations by developing a microphysical thermal model, which more directly simulates regolith properties, such as grain size and volume filling factor. The modeled temperatures are matched with surface temperatures measured by the Diviner Lunar Radiometer Experiment on board the Lunar Reconnaissance Orbiter. The maria and highlands are investigated separately and characterized in the model by a difference in albedo and grain density. We find similar regolith temperatures for both terrains, which can be well described by similar volume filling factor profiles and mean grain sizes obtained from returned Apollo samples. We also investigate a significantly lower thermal conductivity for highlands, which formally also gives a very good solution, but in a parameter range that is well outside the Apollo data. We then study the latitudinal dependence of regolith properties up to ±80° latitude. When assuming constant regolith properties, we find that a variation of the solar incidence‐dependent albedo can reduce the initially observed latitudinal gradient between model and Diviner measurements significantly. A better match between measurements and model can be achieved by a variation in intrinsic regolith properties with a decrease in bulk density with increasing latitude. We find that a variation in grain size alone cannot explain the Diviner measurements at higher latitudes. Plain Language Summary: The Moon is covered by a layer of fine grained material called regolith. To extract information about the regolith, such as grain size or stratification, we used data from the Diviner instrument on board the Lunar Reconnaissance Orbiter. Diviner measures the surface temperature of the regolith for each location on the Moon and all times during day and night. To derive regolith properties, we developed a model and varied its model parameters until the simulated surface temperatures matched the measured ones. We applied the model up to a latitude of 80° and find as the best solution a decrease in regolith packing density with increasing latitude. We also find that a variation of regolith grain size alone cannot explain the measurements. These predictions are valuable for planning future missions targeting higher latitudes and can be compared with future in situ measurements and returned samples. However, the fraction of sunlight that actually heats the regolith is quite unknown, especially at high latitudes. A variation of this fraction can explain the measured surface temperatures reasonably well even without a variation of the regolith properties with latitude. Key Points: We developed a microphysical thermal model accounting for regolith grain size and volume filling factorThe best match between model and Lunar Reconnaissance Orbiter/Diviner data was achieved with a decrease in bulk density between 30° and 80° latitudeWe also found a reasonable agreement between observed and modeled surface temperatures when varying the solar incidence dependent albedo [ABSTRACT FROM AUTHOR]

This study conducts an evaluation of an integrated power, heat, and cooling system reliant on geothermal energy. The process involves integrating both the Organic Rankine Cycle (ORC) and the Goswami cycle. The main objective of this investigation is to analyze the effects of different variables on the system's operation. Additionally, a comprehensive analysis is undertaken to examine how the presence of operational fluids in the ORC affects the overall efficiency of the system. Subsequently, an in-depth economic evaluation is conducted, taking into account the initial investment for system implementation, operational capital, and the levelized cost of goods. The calculation process involves determining the system's income, cash flow, and pay-back time, which heavily rely on the selling prices of the products. By utilizing a genetic algorithm in conjunction with an artificial intelligence algorithm, the system can be optimized to minimize pay-back time and levelized cost of energy, while simultaneously maximizing net production power. The results of this optimization process are then compared with the baseline state of the system to assess the effectiveness of the proposed enhancements. The multifaceted approach enables the evaluation of the system's performance across different conditions and facilitates the optimization of its parameters to improve efficiency and economic feasibility. The comparative optimization results demonstrated a 21 % reduction in payback time, a 14 % increase in net power, and a 12 % improvement in cooling when compared to the reference system state. The payback periods for different operating fluids ranged from 10 to 15 years. Isobutane demonstrated the shortest payback period of approximately 10 years, which was further optimized to 8.6 years. The system demonstrated a power output of 655.8 kW, a cooling output of 578.3 kW, and a heat output of 3042 kW.

This article evaluates the utilization of Polyethylene terephthalate (PET) and Polydimethylsiloxane (PDMS) polymeric coatings for passive radiative cooling of commercial photovoltaic (PV) modules. The methodology involves the design of film coatings and the analysis of their optical properties. A numerical model is developed to simulate the thermal behavior of the PV system. Parametric analysis explores the influence of atmospheric parameters, such as wind speed, solar radiation, and, relative humidity on passive radiative cooling of PV panels. Adoption of PDMS and PET coatings with 200 μm film thickness increases the transmissivity of glass in the solar band gap, maintains relatively higher thermal emissivity in the first and second atmospheric windows bands, and improves radiative cooling of PV panels. At low values of solar radiation, radiative cooling is shown to be capable of maintaining the cell temperature at values lower than the ambient temperature. A case study conducted to simulate nocturnal and daytime thermal behavior of PV modules shows the potential of radiative cooling integrated into PV modules under the specific hot and humid weather conditions of Jeddah, KSA. Temperature reductions of the PV panel by about 10 °C below the ambient temperature can be accomplished on summer nights using radiative cooling. Adoption of PDMS and PET coatings slightly improves the temperature reductions by up to 1.15 °C in the case of PET and 1.35 °C in the case of PDMS.

In this paper, a unique method for using thermoelectric generators (TEGs) to generate electricity is introduced, a technique that makes use of a cold oil tank and hot exhaust gases from generators. A set of TEGs and an integrated cold oil tank are connected to the diesel generator as part of the suggested design. A pertinent thermal modeling was designed and a thorough parametric study was carried out to show the validity of this innovative concept. The parametric study has demonstrated that when the generator power and the thickness to thermal conductivity ratio of each TEG in the system are increased, the temperature differential in each TEG module and the power produced by the assembly of TEGs both exhibit linear increases. The length of the TEG plate and the height of the exhaust gas duct cause an exponential increase in the temperature differential across each TEG module. The TEG assembly's power output increases linearly with TEG surface length and decreases exponentially with exhaust gas duct height. Using an exhaust gas duct height of 0.05 m, and a TEGs plate length of 1 m, the parametric study showed that power generation of up to 2778 W is feasible under the predetermined circumstances of a diesel generator with an output of 125 kW. When compared to a conventional setup, the new hybrid generator in this scenario may be able to increase power generation by up to 2.22 %.

Greenhouses are the most common agricultural structures for controlled environment agriculture, and it is not easy to control the indoor climate due to the complexity of the heat and mass transfer mechanisms. Therefore, numerical models help to simulate the greenhouse indoor environment under various design alternatives, obtain the heating and cooling rates, and determine the appropriate control strategy. In this study, a novel transient thermal model of a greenhouse is developed in MATLAB and implemented in TRNSYS software to simulate the thermal management procedure for the tomato growth process. A PV-aided HVAC system with a heat pump is integrated into the greenhouse to meet the heating/cooling load and maintain the temperature and relative humidity of the indoor ambient within the desired ranges. It is assumed that the greenhouse has three tomato growth seasons annually. The temperature and relative humidity of the indoor air and the heating and cooling rates of the HVAC system are determined, and the temperature and relative humidity variations are compared against a greenhouse without an HVAC unit. The simulations are conducted with TRNSYS for four climatically different cities: Izmir, Valencia, Casablanca, and Tunis. The results reveal that the electricity consumption of the heat pump-assisted HVAC system is highest in Izmir, with 742,230 kWh/year. Besides, the highest photovoltaic electricity production is determined in Tunis, with 417,960 kWh/year. The highest reduction in carbon emissions is determined in Casablanca, with 112,541.4 kg CO2 eq./year.

For the autonomous driving application, data movement has increased rapidly between a CMOS Image sensor (CIS) and the processor due to increase in image resolution. Advanced packaging techniques like 2.5D/3D integration have been proposed to reduce the data movement energy between memory and processor. In this work, we explore the use of such techniques to integrate a CIS and a backend accelerator on a silicon interposer. The data movement energy from CIS to the accelerator is thus reduced by $100\times $ compared to using the conventional MIPI links. We perform thermal simulations to study the impact of the thermal coupling of CIS and accelerator and ensure a peak temperature increase of less than $5~^{\circ }$ C. We also vary the distance between the CIS and the processor to study the trade-offs between energy savings and peak temperature. Next, we assume the 3D stacked CIS and accelerator to reduce the data movement further and obtain an energy efficiency of 45.81 TOPS/W. Now we observe a heat dissipation challenge with an increase in the peak temperature of more than $85~^{\circ }$ C. Hence, we scale down the operational frequency and study the trade-off between performance degradation and reduction in peak temperature, while maintaining the accurate multi-object tracking on the BDD100k dataset for autonomous driving.

This research introduces an approximation method for computing the temperature distribution in photodetectors operating in a steady state under optical excitation. The derived temperature profile is utilized to assess the impact of temperature variations on crucial performance metrics of photodetectors, encompassing quantum efficiency, bandwidth, and phase noise. Our methodology, grounded in simplified heat transport equations, yields significant insights into the intricate relationship between temperature and photodetector performance. Our findings reveal that assuming constant room temperature operation leads to an overestimate of the output current and quantum efficiency and an underestimate of bandwidth, by contrast, a model in which the temperature varies produces estimates that closely align with experimentally-measured values for quantum efficiency and bandwidth. The low thermal conductivity of InGaAs hampers heat dissipation, resulting in temperature accumulation. Varying the reverse bias voltage while keeping the output current constant by changing the input optical power leads to nonlinear variations in the bandwidth, phase noise, and quantum efficiency. These insights contribute to the understanding and optimization of thermal management in photodetectors under strong optical excitations.

Hyperthermia treatment consists of elevating the temperature of the tumor to increase the effectiveness of radiotherapy and chemotherapy. Hyperthermia treatment planning (HTP) is an important tool to optimize treatment quality using pre-treatment temperature predictions. The accuracy of these predictions depends on modeling uncertainties such as tissue properties and positioning. In this study, we evaluated if HTP accuracy improves when the patient is imaged inside the applicator at the start of treatment. Because perfusion is a major uncertainty source, the importance of accurate treatment position and anatomy was evaluated using different perfusion values. Volunteers were scanned using MR imaging without (“planning setup”) and with the MR-compatible hyperthermia device (“treatment setup”). Temperature-based quality indicators were used to assess the differences between the standard, apparent and the optimized hyperthermia dose. We conclude that pre-treatment imaging can improve HTP predictions accuracy but also, that tissue perfusion modelling is crucial if temperature-based optimization is applied.

IC engines in transportation sector are seen as a major cause of increasing air pollution. Electric Vehicles (EVs) are deemed as a green energy solution for pollution free future. The energy source of a modern-day EV is a Lithium ion battery pack. Temperature sensitivity is a major limitation for the lithium-ion battery performance and so the prevalent battery thermal management systems (BTMS) are reviewed in this study for practical implications. Firstly, the design considerations are analyzed to measure value of thermal safety and the international market potential is studied in this manuscript. Secondly, thermal stability analysis is drawn for thermal runaway situations, extreme weather conditions and aging phenomenon. The effect of sub-zero temperature, charging/discharging rates, failures caused by short circuiting, lack of temperature uniformity and mechanical deformation are also evaluated. In addition, the theoretical and experimental models of various battery thermal management strategies studied by different authors are compared for their effectiveness in hybrid and electric vehicles. The pinnacle of current review is to assess the upcoming challenges and substantial gaps in the approach of thermal management predicted by researchers and the latest practical methods used by EV manufacturers. Lastly, the optimization of BTMS is considered highly critical for the dominance of electric vehicles, by enhancement in lifespan and overall safety.

The present research work delves into the thermodynamic modeling and analysis of concentric tubular solar stills (CTSS) using a rigorous mathematical approach. The primary objective is to gain a comprehensive understanding of the system’s behavior by formulating and analyzing various crucial parameters. These parameters include the basin water temperature, inner and outer glass cover temperatures, heat transfer coefficients, heat loss coefficients, thermal efficiency, exergy efficiency, hourly yield, and cumulative yield. The study is specifically conducted under the environmental conditions of Nagpur city (21.1458° N, 79.0882° E), India, in the month of May 2022. By selecting this location, the present study ensures that their findings are contextually relevant and applicable to the local conditions. To facilitate the computation of results and generate informative visualizations, MATLAB code has been developed. This code allows for efficient analysis, processing, and presentation of the obtained data, enabling a comprehensive interpretation of the research findings. Results of the study indicate that hourly yield, considering only bottom losses, is 5.071 kg=m² and 3.012 kg=m² when water and air are used as cooling mediums, respectively. However, when all losses are taken into account, the hourly yield decreases to 4.575 kg=m² and 2.555 kg=m² for water and air as cooling mediums, respectively. The percentage error when water and air are used as the cooling medium by considering bottom losses is 1.05 and 3.06, while considering all losses, the error is 10.73 and 18.26. [ABSTRACT FROM AUTHOR]

Temperature is the primary factor affecting the growth and survival of aquatic species. At low temperatures, the metabolic rate decreases significantly. As a result, energy levels and growth rates in fish slow down which reduces the overall aquaculture production. Therefore, a novel thermal model of GiSPVT in terms of design and climatic parameters has been developed. An analytical expression for fishpond temperature and electrical energy has been derived and validated using the special case of the proposed GiSPVT for a particular day. The solar radiation passing through the non-packing area of the semi-transparent PV modules was used to heat the water to maintain the desired temperature. However, for experimental validation, the growth performance of Labeo rohita (26.15 ± 2.4 g) was cultured (90 days) with different conditions: T1bgl, T2agl (inside the greenhouse), T3bgl, T4agl (outside the greenhouse). Specific growth rate (SGR), average weight and weight gain of fishes were significantly higher (p < .05) in the T1bgl group as compared to other groups. Moreover, the SGR was observed 32.6%, 20.2%, and 14.0%, higher in the T4agl as compared to T2agl, T3bgl, and T4agl respectively. Significantly increased growth performance of T1bgl group during winter may be due to the combined effect of geothermal and solar energy integrated systems. [ABSTRACT FROM AUTHOR]

In birds, fine-scale selection of habitat, like roosting sites, plays an important role in energy conservation. Many diurnal birds roost in cavities or densely foliated coniferous trees, both of which may provide shelter from predators and precipitation, and reduce heat loss from convective and radiative forces. Thermal benefits of roost sites have not been widely studied in nocturnal birds, like owls, roosting during the day. The objective of this study was to assess possible thermal benefits of coniferous roosting sites for the small, nocturnal Northern Saw-whet Owl (Aegolius acadicus) at the southern extent of its nonbreeding distribution, where winters are often mild with warm days. I deployed operative temperature models (n = 40) for 21 d at 10 sites in Madison County, Arkansas. Sites were either a shortleaf pine (Pinus echinata) or eastern red cedar (Juniperus virginiana) roost tree, each paired with a deciduous tree. At each site, I synchronously deployed models in 4 microsites reflecting potential owl roosting sites that likely varied considerably in their thermal properties: conifer crown, conifer trunk, deciduous crown, deciduous trunk. My objectives were to (1) test for an effect of microsite on 4 composite operative temperature variables, and (2) test for an effect of microsite on mean wind speed. Results suggest conifer crown roost sites are cooler, more thermally buffered, and experience lower wind speed than deciduous crown and both trunk roost sites. Thus, the saw-whet owl likely benefits from overwintering in coniferous trees to avoid thermally stressful temperatures, particularly on warm winter days. En aves, la selección de escala fina del hábitat, como de los dormideros, juega un papel importante en la conservación de energía. Muchas aves diurnas anidan en cavidades o en árboles que son coníferas densamente foliadas, y ambas estrategias brindan refugio de depredadores y precipitación y reducen la pérdida de calor de fuerzas convectivas y radiativas. Los beneficios térmicos de los dormideros no han sido estudiados ampliamente en aves nocturnas, como las lechuzas, que duermen durante el día. El objetivo de este estudio fue evaluar los posibles beneficios térmicos de dormideros en coníferas para el pequeño tecolore Aegolius acadicus en la parte sureña de su distribución no reproductiva, donde los inviernos son leves y tienen días cálidos. Desplegué modelos de temperatura operativos (n = 40) por 21 días en 10 sitios en Madison County, Arkansas. Los dormideros se encontraban ya sea en pino de hoja corta (Pinus echinata) o el cedro de Virginia (Juniperus virginiana), cada uno junto a un árbol decíduo. En cada sitio, desplegué asincrónicamente modelos en 4 micrositios que reflejaban potenciales dormideros de los tecolotes que muy posiblemente variaban en sus propiedades térmicas: corona de la conífera, tronco de la conífera, corona decidua, tronco de la decidua. Mis objetivos fueron: (1) probar el efecto del micrositio en 4 variables de temperatura operatuva compuesta y (2) probar el efecto del micrositio en el promedio de la velocidad del viento. Los resultados sugieren que las coronas de las coníferas son más frescas, más aisladas térmicamente y experimentan menor velocidad del viento que las coronas de las decíduas y que ambos sitios del tronco. Entonces el tecolote Aegolius acadicus se beneficia posiblemente al hibernar en árboles de coníferas para evitar temperaturas termicamente estresantes, particularmente en días cálidos del invierno. Palabras clave: Aegolius acadicus, ecología térmica, lechuza, modelamiento térmico, selección de dormidero, tecolote Aegolius acadicus. [ABSTRACT FROM AUTHOR]

Middle infrared spectral results obtained in‐situ by the Hayabusa2 MARA instrument are generally in‐line with previous results and a new comparison with sample C0137 returned from asteroid (162173) Ryugu, being similar to an aqueously altered CI1 chondrite. The mid‐IR spectrum of the boulder on Ryugu measured by MARA is shallower around 9 μm compared to the laboratory spectrum of C0137. Here we show that discontinuous, fine dust deposits can partially explain the differences in the spectral data and remain in agreement with the temperature observations of the boulder by MARA if an opaque dust layer covers less than 3% of the field of view. Such a presence of dust covering a low porosity boulder was discounted by previous analysis of the mid‐infrared MARA data which did not consider a highly porous boulder as we do here. Plain Language Summary: The Japanese Hayabusa2 space mission returned samples from asteroid Ryugu. Here we compare the spectra of the sample observed in the middle infrared (5–25 μm) with in‐situ observations in the part of the electromagnetic spectrum. We find differences between the spectra that can be explained by the presence of fine particles on the surface of Ryugu. Earlier works found that little to no dust can be present on Ryugu and we revisit these studies an derive an upper limit on the amount of dust consistent with the infrared observations. We find that less than 3% of the observed surface can be covered in an opaque dust layer which is likely concentrated in cracks and pores. Our results are consistent with the results of other studies that the amount of dust that a surface of an asteroid can retain decreases with its size. Key Points: The Ryugu sample C0137's mid‐IR spectrum shows differences to in‐situ observations by MARAThe differences can be explained by the presence of dust on the boulders of RyuguThermal modeling reveals that dust covering less than 3% of the MARA field of view is consistent with the MARA data [ABSTRACT FROM AUTHOR]

In this study, we investigated the microstructural variation of Ti-6Al-4 V in inverted pyramid parts built using Laser Powder Bed Fusion (LPBF). Two parts were fabricated with and without ghost parts to study the effects of interlayer delay time on thermal history and microstructure. Finite Element Method (FEM) based process simulation was used to predict the thermal history and cooling rates during the LPBF process to understand the location-specific microstructure and mechanical properties variation. The thermal analysis findings revealed that the variations in the cooling rates and pre-deposition temperature were notably significant. Within the same part, the cooling rates exhibited significant variations, differing by up to three orders of magnitude in two scenarios: (1) within the same layer, influenced by the proximity to the edges, and (2) at different heights, attributable to the strongly varying cross-section. Comparing the two parts, the cooling rates of the part with ghost parts were approximately two orders of magnitude higher than in the part without the ghost parts. This significant difference can be attributed to the extended interlayer cooling time and lower pre-deposition temperature resulting from the presence of two ghost parts which introduced an effective delay time between laser scans. Experimental validation against microstructure images and hardness measurements showed similar trends with the predicted results. These findings provide valuable insights into controlling microstructure at specific locations during LPBF fabrication, which is essential for building complex geometries with controlled material properties.

Degradation of insulation paper is a key contributor to the failure of power transformers. Insulation degradation accelerates at elevated temperatures, which highlights the potential for better thermal management to prolong life. While several studies have analyzed the benefits of high thermal conductivity oil for reducing temperatures inside a transformer, this study is an initial assessment of the benefits of high thermal conductivity paper on transformer life. Blending particulates with cellulosic fibers offers a pathway for high thermal conductivity paper (with good dielectric properties), which can reduce internal temperatures. Presently, life extensions that can be achieved by the use of such thermally conducting papers were estimated, with the thermal conductivity of the paper being the key parameter under study. The analytical-numerical thermal model used in this study was validated against experimental measurements in a distribution transformer, adding confidence to the utility of the model. This model was then used to provide estimates of hot-spot temperature reduction resulting from the use of papers with higher thermal conductivity than baseline. Transformer life was predicted conventionally by tracking the degree of polymerization of paper over time, based on an Arrhenius model. Results indicate that increasing the thermal conductivity of paper from 0.2 W/mK (baseline) to 1 W/mK reduces the hot spot temperature by 10 °C. While degradation significantly depends on the moisture and oxygen content, the model shows that such a temperature reduction can increase life for all conditions, by as much as a factor of three.

Lithium-ion battery technology in the modern automotive industry utilizes highly temperature-sensitive batteries. Here, air cooling strategies will be the most applicable for the chosen example based on strategies for temperature control. Simulations have been utilized to evaluate the different thermal management strategies. A battery model was developed using the solutions offered by Computational Fluid Dynamics (CFD) simulation technology. It utilizes the heat produced by the discharge of the battery cells. Due to the simulation's limited computational capacity, the energy transfer model was implemented with a simplified but sufficiently complex physical mesh. Ten actual measurements were conducted in the laboratory to investigate the heating of the cell during the charging and discharging of 18650-type batteries. The results were applied to validate the simulation model. The simulation outcomes and thermal camera readings were compared. The cell-level numerical model was then extended to examine the temperature variation at the system level. The primary design objective is to achieve the highest energy density possible, which necessitates that the cells be constructed as closely as possible; however, increasing the distance between the cells can provide superior cooling from a thermal management perspective. The effect of varying the distance between individual cells on the system's heating was analyzed. Greater distance resulted in a more efficient heat transfer. It was also discovered that, in some instances, a small distance between cells produces inferior results compared to when constructed adjacently. A critical distance range has been established based on these simulations, which facilitates the placement of the cells.

A new concept of power generation from thermoelectric generators TEGs using the hot exhaust gas of boilers and a cold oil tank is proposed. The suggested concept consists of a flow of exhaust gas of boilers and cold oil in a tank separated by a plate comprising several TEGs in series. The oil tank at the bottom of the system constitutes the cold convection condition for the TEG plate and the upper hot exhaust gas flow constitutes the hot convection condition. Accordingly, a temperature gradient is created across the thickness of the TEGs, which play the role of a separation plate, and converted to an electrical power. To justify the feasibility of this new concept, a suitable thermal modeling is developed and the associated parametric analysis is carried out. The parametric analysis reveals that powers up to 622 W can be generated with a system having a space heating load of 200 kW, an exhaust gas duct height of 0.05 m, and a TEG plate length of 1 m. The temperature difference across each TEG module decreases exponentially when the TEGs plate length increases and decreases exponentially when the exhaust gas duct height increases.

On-orbit autonomous relative navigation performance strongly depends on both sensor suite and state reconstruction selection. Whenever that suite relies on image-based sensors working in the visible spectral band, the illumination conditions strongly affect the accuracy and robustness of the state reconstruction outputs. To cope with that limitation, we investigate the effectiveness of exploiting image sensors active in the IR spectral band, not limited by the lighting conditions. To run effective and comprehensive testing and validation campaigns on navigation algorithms, a large dataset of images is required, either available or easy to obtain in the visible band, not trivial and not accessible for the thermal band. The paper presents an open-source tool that exploits accurate finite volume thermal models of celestial objects and artificial satellites to create thermal images based on the camera dynamic. The thermal model relies on open CFD code (OpenFOAM), pushed to catch the finest details of the terrain or of the target geometries, and then the temperature field is processed to compute the view factors between the camera and each face of the mesh; thus, the radiative flux emitted by each face is extracted. Such data feed the rendering engine (Blender) that, together with the camera position and attitude, outputs the thermal image. The complete pipeline, fed by the orbiting target and the imaging sensor kinematic, outputs a proper synthetic thermal image dataset, exploitable either by a relative navigation block or any other scope of research. Furthermore, in the same framework, the article proposes two different thermal sensor models but any sensor model can be applied, providing full customization of the output. The tool performance is critically discussed and applied for two typical proximity scenarios, asteroid and artificial satellite; for both cases, the challenges and capabilities of the implemented tool for synthetic thermal images are highlighted. In the end, the tool is applied in a phase B mission design sponsored by ESA and in related research works; for such cases, the results are reported in the article.

The reliable and repeatable fabrication of complex geometries with predetermined homogeneous properties is still a major challenge in electron beam powder bed fusion (PBF-EB). Although previous research identified a variety of process parameter–property relationships, the underlying end-to-end approach, which directly relates process parameters to material properties, omits the underlying thermal conditions. Since the local properties are governed by the local thermal conditions of the melt pool, the end-to-end approach is insufficient to transfer predetermined properties to complex geometries and different processing conditions. This work utilizes high-throughput thermal simulation for the identification of fundamental relationships between process parameters, processing conditions, and the resulting melt pool geometry in the quasi-stationary state of line-based hatching strategies in PBF-EB. Through a comprehensive study of over 25,000 parameter combinations, including beam power, velocity, line offset, preheating temperature, and beam diameter, process parameter-melt pool relationships are established, processing boundaries are identified, and guidelines for the selection of process parameters to the achieve desired properties under different processing conditions are derived.

The long-term goal of this work is to predict and control the microstructure evolution in metal additive manufacturing processes. In pursuit of this goal, we developed and applied an approach which combines physics-based thermal modeling with machine learning to predict two important microstructure-related characteristics, namely, the meltpool depth and primary dendritic arm spacing in Nickel Alloy 718 parts made using the laser powder bed fusion (LPBF) process. Microstructure characteristics are critical determinants of functional physical properties, e.g., yield strength and fatigue life. Currently, the microstructure of LPBF parts is optimized through a cumbersome build-and-characterize empirical approach. Rapid and accurate models for predicting microstructure evolution are therefore valuable to reduce process development time and achieve consistent properties. However, owing to their computational complexity, existing physics-based models for predicting the microstructure evolution are limited to a few layers, and are challenging to scale to practical parts. This paper addresses the aforementioned research gap via a novel physics and data integrated modeling approach. The approach consists of two steps. First, a rapid, part-level computational thermal model was used to predict the temperature distribution and cooling rate in the entire part before it was printed. Second, the foregoing physics-based thermal history quantifiers were used as inputs to a simple machine learning model (support vector machine) trained to predict the meltpool depth and primary dendritic arm spacing based on empirical materials characterization data. As an example of its efficacy, when tested on a separate set of samples from a different build, the approach predicted the primary dendritic arm spacing with root mean squared error ≈ 110 nm. This work thus presents an avenue for future physics-based optimization and control of microstructure evolution in LPBF.

Axial-flux electrical machines are ideal candidates as in-wheel motors for electrical vehicles (EVs). Due to their characteristics of high power density and compact structure, thermal management is vital for them. Lowering the temperature of the stator windings can protect the insulation material from rapid degradation and reduce the extra copper losses by decreasing their electrical resistance. Contrary to the widely reported axial-flux permanent magnet synchronous machines, thermal modeling methods of axial-flux induction machines are rarely seen in previous literature. Hence, the present work aims at investigating their thermal response based on both the finite element method (FEM) and computational fluid dynamics (CFD) techniques. In addition, a test rig is built to validate the computed results of these two thermal models with the experimental measurement. The CFD conjugate heat transfer analysis is found to be more accurate than the FEM thermal analysis in predicting the temperature distribution of different components in the machine and the temperature rise of the airflow, with lower than 5 ∘C average errors deviating from the corresponding measured data at three rotation speeds. Additionally, the CFD simulation is able to capture the backflow occurring near the outlets of the casing that has been found during the experiments.

A greenhouse tunnel in Stellenbosch, South Africa was used for testing a generic sensing system for monitoring and control of climatic conditions in the tunnel. Three temperature and humidity sensors were used to record data throughout the day in 5 min intervals. Bambara Nuts, a climate change-resilient and nutritious crop, were grown in a separate study in the tunnel using an aeroponics system. These were chosen as it is regarded as the norm in autonomous greenhouse temperature control in the region. During data collection, the sensors were placed at the front, middle, and back of the tunnel. At the front, there was an industrial extraction fan, and at the back, there was an evaporative cooling wet wall. The fan and wet wall were controlled using the middle sensor data that was averaged every minute to determine if the fan and wet wall should be on or off. The hysteresis band used as a threshold was to turn the fan on when the middle temperature reached 30 °C and to turn it off it was 22 °C. This data collection method extended from 31 December 2022 to 13 June 2023, collecting 162 days of temperature and humidity data for that period.

Abstract Middle infrared spectral results obtained in‐situ by the Hayabusa2 MARA instrument are generally in‐line with previous results and a new comparison with sample C0137 returned from asteroid (162173) Ryugu, being similar to an aqueously altered CI1 chondrite. The mid‐IR spectrum of the boulder on Ryugu measured by MARA is shallower around 9 μm compared to the laboratory spectrum of C0137. Here we show that discontinuous, fine dust deposits can partially explain the differences in the spectral data and remain in agreement with the temperature observations of the boulder by MARA if an opaque dust layer covers less than 3% of the field of view. Such a presence of dust covering a low porosity boulder was discounted by previous analysis of the mid‐infrared MARA data which did not consider a highly porous boulder as we do here.

Analyzing and modeling the thermal behavior of mass concrete elements has been widely investigated by several researchers. Lately, many contemporary finite element packages have embedded modules for analyzing thermal behavior. Unfortunately, these packages are quite complex and require experts to be properly implemented. This paper proposes a simple and practical approach using the 3D-Finite Difference Model (3D-FDM) developed by MS-Excel to overcome the complexity of the other FE models. The model is utilized to predict the thermal behavior of actual bridge pile caps (3D model) rather than the previously developed 2D models in earlier research. The results of the analysis are compared with the concrete temperatures that were experimentally obtained from the site. Site data was collected using 18 thermocouple probes (K type) that were installed in two pile caps. These thermocouples were installed before concrete pouring to monitor the temperatures generated due to the exothermic reaction of the cement, which occurs during casting and the maturity period of concrete. The readings were registered every 3 hours for 7 days after concrete placement. This research provides a comparison between the recorded site data and the thermal analysis based on the proposed 3D-FDM. Results proved that concrete temperature time histories at different locations of the bridge pile caps could be properly predicted using the developed 3D-FDM. [ABSTRACT FROM AUTHOR]

In this research, a numerical investigation of the thermal behavior around a circular planar micro-coil with a variable width, deposited on a Kapton substrate has been presented using finite element method. The purpose of this study is to provide a thermal approach that takes into account the effect of air buoyancy which has not ever been used in this field. Moreover, the influence of this micro-coil inner width on its electrical and thermal behavior has been studied. The width of the micro-coil decreases from the value of wi to w (w ⩽ wi) with 100 ⩽ w ⩽ 600 µm. The three-dimensional simulation model focuses on the Maxwell's equations coupled to the momentum and heat equations. The air buoyancy is introduced along the vertical direction in the momentum equations when the micro-coil is considered as an internal heat source. In a first step, the effect of air buoyancy on the thermal profile has been visualized to highlight the changes that can occur in terms of temperature distribution. The results obtained have shown that the electromagnetic characteristics of this type of coils are improved according to the decrease of the width (w). However, the temperature increases significantly, which tends to accelerate the air motion and favors the convective heat flow. It should be noted, that the study of this kind of phenomena permits to identify the thermal operating zone of insulating materials, practically the Kapton and to prevent thermal damages that may occur. [ABSTRACT FROM AUTHOR]