Thermal Modeling Techniques Research Articles

Profiles of peripheral regulatory T cells forecasts the feasibility of steroid withdrawal after liver transplantation based on cellular thermal modeling

After liver transplantation, steroid therapy is often used to prevent rejection. However, long-term steroid use can lead to serious side effects, therefore, this study aimed to evaluate the feasibility of peripheral regulatory T cell profiles for steroid discontinuation after liver transplantation through cellular thermal modeling and real-time monitoring of intracellular thermodynamics. In this study, cellular thermal modeling techniques were used to simulate the thermodynamic characteristics of peripheral TREgs under different conditions. The dynamic changes of peripheral Treg in liver transplantation animal models were monitored by flow cytometry and molecular biology. Significant changes in peripheral Treg profiles were observed after initiation of steroid therapy, especially in the discontinuation group, and these changes were strongly associated with the restoration of immune homeostasis. Real-time monitoring of the thermodynamic data revealed that peripheral Treg activity showed a specific temperature dependence in the cellular thermal model. Cell thermal modeling combined with real-time monitoring of intracellular thermodynamics provides a new perspective for evaluating the feasibility of peripheral regulatory T cell profiles for steroid discontinuation after liver transplantation. Strengthening the dynamic monitoring of peripheral Treg spectrum provides an important basis for the formulation of personalized immunosuppression strategies, and improves the therapeutic effect and quality of life of liver transplant patients.

Thermal modeling and its role in management of bifurcation aneurysms and associated ischemic complications in the middle cerebral artery

Bifurcated aneurysm of cerebral artery is a common cerebrovascular disease, which can easily lead to serious ischemic complications. Traditional treatments face challenges of risk and effectiveness. Therefore, it is particularly important to explore new therapeutic strategies. In recent years, the application of thermal modeling techniques in medical biological systems has provided a new perspective for the analysis of hemodynamics and tissue thermal response. The purpose of this study was to investigate the role of heat model in the treatment of bifurcated cerebral artery aneurysms and their associated ischemic complications, and to evaluate its potential value in understanding disease mechanisms and optimizing treatment protocols. In this study, a three-dimensional thermal model was used to simulate the heat conduction and blood flow characteristics of the bifurcated parts of cerebral arteries. Combined with the clinical data of patients, the influence of the thermal model on the formation mechanism of aneurysms and the prognosis evaluation of ischemic complications were analyzed through numerical calculation and experimental verification. Compare the performance of different treatment methods in thermal models. The thermal model shows that the temperature distribution at the aneurysm site is closely related to the blood flow velocity, and the local temperature increase may promote thrombosis and lead to ischemic complications. The treatment regimen optimized by the thermal model showed significant improvement in the simulation, reducing the risk of complications and improving hemodynamic parameters. Heat model can reveal the dynamic relationship between blood flow and temperature in the study of cerebral artery bifurcation aneurysm, and provide theoretical support for clinical treatment.

Enhanced Thermal Modeling of Electric Vehicle Motors Using a Multihead Attention Mechanism

The rapid advancement of electric vehicles (EVs) accentuates the criticality of efficient thermal management systems for electric motors, which are pivotal for performance, reliability, and longevity. Traditional thermal modeling techniques often struggle with the dynamic and complex nature of EV operations, leading to inaccuracies in temperature prediction and management. This study introduces a novel thermal modeling approach that utilizes a multihead attention mechanism, aiming to significantly enhance the prediction accuracy of motor temperature under varying operational conditions. Through meticulous feature engineering and the deployment of advanced data handling techniques, we developed a model that adeptly navigates the intricacies of temperature fluctuations, thereby contributing to the optimization of EV performance and reliability. Our evaluation using a comprehensive dataset encompassing temperature data from 100 electric vehicles illustrates our model’s superior predictive performance, notably improving temperature prediction accuracy.

Understanding the burial history and the hydrocarbon potential of the late Paleozoic Claromecó foreland Basin (Southwestern Gondwana, Argentina) by combining organic geochemistry, organic petrology, and thermal modeling

The Claromecó foreland Basin (Carboniferous–Permian; southern Buenos Aires province, Argentina) is key to understanding the paleotectonic evolution of the southwestern Gondwana margin and is relevant to energy resource exploration. This study reconstructs the thermal and burial history of the Claromecó Basin by integrating geochemical data, organic petrology, and thermal modeling techniques. Cores samples of the Tunas Formation (Pillahuincó Group, Early Permian) were studied. A 1D thermal model was constructed, calibrated with vitrinite reflectance measurements (VRo %), and corroborated with fluid inclusion and apatite fission track data from previous studies. Rock-Eval pyrolysis results show TOC% values ranging from 0.13 to 60.35 wt%. The Hydrogen index (HI < 50 mg HC/g TOC) and Oxygen index (OI < 50 mg CO2/g TOC) indicate the dominance of Type III and Type IV kerogens, most likely resulting from the thermal maturation of an original Type III kerogen. Petrologic observations confirm the presence of macerals from the inertinite group, as well as minor amounts of vitrinite and liptinite. The Tmax displays a temperature range mostly from 460 to 610 °C. The VRo % values range from 1.5 to 2.0%. Geochemical data combined with VRo % measurements confirm a late catagenesis to metagenesis stage within the wet to dry gas window for coals and organic-rich strata.In order to constrain the thermal evolution of the basin infill, different scenarios were tested by varying the heat flow and the missing section thickness associated with the uplift and erosion of the basin (Permian–Cenozoic unconformity). The best calibration results were obtained with an erosion thickness of 3000 up to 4200 m and paleo heat flow peaks of either 60 or 80 mW/m2 during the Lower Permian–Lower Cretaceous. The Tunas Formation was deposited and buried during the Permian–Triassic (Gondwanides Orogeny phase), reaching a maximum temperature of 180 °C. The results obtained by combining geochemical analysis, organic petrology, and thermal modeling techniques indicate that the coal beds of the Tunas Formation could have a current potential as gas-prone source rocks. Despite that, the hydrocarbon generation capacity of coal levels is currently low due to the high percentage of residual (Type IV) kerogen. Further research could help clarify if the hydrocarbons potentially expelled by these source rocks have been lost due to migration or could be trapped somewhere in the basin.

Models, simulations, and applications of small satellite thermal analysis

Progress in satellite technology places higher expectations on the design period and reliability of thermal control systems, especially for small satellites with high intensification. Here, a thermal analysis is conducted throughout the satellite development process, with thermal modeling serving as the foundation for thermal analysis in the early and formal design and test verification stages. As a result, designers are required to appreciate, penetrate, and properly apply thermal models for the development of satellite thermal systems. Thus, in this article, we reviewed the research and development of thermal model techniques, as well as the preparation of crucial parameters and means of simplification for accurate and fast solutions. In addition, a summary of the relevant application and state-of-the-art technologies such as uncertainty and sensitivity analysis, intelligent optimization design, and parameter correlation, was dedicated to promoting the comprehensive development and innovation of thermal analysis of satellites.

VarSim: A fast process variation-aware thermal modeling methodology using Green’s functions

Despite temperature rise being a first-order design constraint, traditional thermal estimation techniques have severe limitations in modeling critical aspects affecting the temperature in modern-day chips. Existing thermal modeling techniques often ignore the effects of parameter variation, which can lead to significant errors. Such methods also ignore the dependence of conductivity on temperature and its variation. Leakage power is also incorporated inadequately by state-of-the-art techniques. Thermal modeling is a process that has to be repeated at least thousands of times in the design cycle, and hence speed is of utmost importance.To overcome these limitations, we propose VarSim, an ultrafast thermal simulator based on Green’s functions. Green’s functions have been shown to be faster than the traditional finite difference and finite element-based approaches but have rarely been employed in thermal modeling. Hence we propose a new Green’s function-based method to capture the effects of leakage power as well as process variation analytically. We provide a closed-form solution for the Green’s function considering the effects of variation on the process, temperature, and thermal conductivity. Additionally, we propose a novel way of dealing with the anisotropicity introduced by process variation by splitting the Green’s functions into shift-variant and shift-invariant components. Since our solutions are analytical expressions, we were able to obtain speedups that were several orders of magnitude more than state-of-the-art proposals with a mean absolute error limited to 4% for a wide range of test cases. Furthermore, our method accurately captures the steady-state as well as the transient variation in temperature.

The Energy-Saving Potential of Air-Side Economisers in Modular Data Centres: Analysis of Opportunities and Risks in Different Climates

This study examines the feasibility of utilising outside air for ‘free cooling’ in modular data centres through the implementation of an air-side economiser, as an alternative to traditional mechanical cooling systems. The objective is to offset the energy consumption associated with cooling by leveraging the natural cooling capacity of the ambient air. To investigate this potential, a 90-kW modular data centre is employed as the base case for model validation and analysis of energy reduction possibilities. The research employs dynamic thermal modelling techniques to assess the efficacy of the air-side economiser in four distinct climatic zones: Stockholm, Dubai, San Francisco, and Singapore, representing diverse worldwide climates. The model is meticulously calibrated and validated using power usage effectiveness (PUE) values obtained from the Open Compute Project. Simulation runs are conducted to evaluate the energy-reduction potential achievable with the air-side economiser compared to conventional mechanical air-conditioning systems. The results indicate significant energy reductions of up to 86% in moderate climates, while minimal reductions are observed in dry and hot climates. This comprehensive analysis offers valuable insights into the intricate relationship between modular data centres, their operational characteristics, and the viability of employing air-side economisers for free cooling and energy efficiency across different climatic conditions. The contribution of this publication to this field of science lies in its exploration of the practicality and energy-saving potential of air-side economisers in modular data centres. By utilising dynamic thermal modelling and empirical validation, this study provides evidence-based insights into the effectiveness of this cooling strategy, shedding light on its applicability in various climates. The findings contribute to the understanding of energy-efficient cooling solutions in data-centre design and operation, paving the way for more sustainable practices in the field.

Thermal Network Modeling and Thermal Stress Evaluation for a High-Power Linear Ultrasonic Motor

This article presents a high-efficient thermal analysis methodology and outlines a set of useful design guidelines for high-power linear ultrasonic motors. A thermal network modeling technique is introduced to rapidly calculate the temperature rise for a typical high-power linear ultrasonic motor with a V-shaped stator. First, a six-terminal equivalent circuit for Langevin piezoelectric transducer considering the prestress bolt loss and all three losses in piezoelectrics is proposed to calculate the stator loss. Then, the calculated losses along with the friction loss are used as inputs into the developed thermal network model to calculate the temperature rise of critical parts of the motor. Furthermore, an analytical mechanical model combined with the proposed thermal network is established to calculate the temporal–spatial distribution of the stator thermal stress for evaluating its fatigue under the heating-up process. Finally, some experimental measurements and finite-element simulations are conducted to validate the theoretical analyses.

An overview of thermal modelling techniques for permanent magnet machines

Permanent magnet (PM) machines have gained increasing attention from the industry because of their potential merits over conventional electrical machines. High-temperature level in electrical machines is a major factor that can adversely impact the performance and health conditions of these machines. These effects need to be minimized to make them competitive with currently operational machines in the industry. It can be done by performing a thorough thermal analysis of the prototype during the design process and proper online thermal monitoring of the machine during the operation stage. Thermal modelling is a powerful tool for achieving such goals in both cases. This paper aims to review the state-of-the-art of thermal modelling techniques and provide a detailed comparison of them in PM machines. The fundamental concepts of heat transfer and sources of heat in PM machines are first discussed. Then, different thermal modelling techniques, including thermal subdomain models (TSMs), lumped parameter thermal networks (LPTNs), finite element models (FEMs), computational fluid dynamics (CFD), reduced order models (ROMs), and hybrid thermal models (HTMs) are introduced and compared. Finally, the utilization of these models in the thermal design, control, and monitoring of PM machines is studied.

Determination of Core Losses Using an Inverse Modeling Technique

This paper presents an inverse thermal modeling technique to determine the core losses from the temperature rise inside the transformer core. For this purpose, initially, a customized printed circuit board (PCB) with thermal sensors is used to measure the temperature rise. Afterward, a 3D magneto-thermal forward model is developed to validate the temperature rise. The accuracy of the forward model is checked by comparing the simulated core losses and temperature rise of the transformer with experimental measurements for different supply conditions. The results show that the forward model can accurately estimate the core losses with a maximum relative error of less than 2.7&#x0025; and predict the temperature rise in the core with a maximum relative error of less than 6.2&#x0025;. Lastly, after ensuring the accuracy of the forward model, an inverse modeling technique is applied to the 3D thermal model to predict the core losses of the transformer directly from the measured temperature rise. The accuracy of the inverse model in estimating the core losses is checked by comparing the results with experimental measurements. The novel approach for the PCB design besides the inverse model shows that the technique can be applied to estimate the core losses directly from the measured temperature rise inside the core with a relative error of 2.7&#x0025; compared to experiments.

Dynamic rating assists cost-effective expansion of wind farms by utilizing the hidden capacity of transformers

Dynamic rating of power transmission devices is a technology that allows better equipment utilization through real-time monitoring of the weather conditions and the load. Dynamic rating of transformers is a fairly new technology if compared to the dynamic rating of power lines, and has a high potential for significantly improving component utilization while lowering investment costs on installing new transformers.The following work investigates how to utilize already operational transformers, which are used for wind farm connection, for expanding wind generation capacity. Also, this paper shows improvements that dynamic transformer rating can bring to both power grid operators and wind farm owners by exploring the economic benefits of expanding wind parks without investing in new power transformers. Connecting additional wind turbines at sites with high wind potential after the wind park is already in exploitation can assist in lowering electricity price and provide a possibility of less risky investment in the wind energy sector. This paper uses transformer thermal modelling and wind farm expansion techniques such as convolution method and product method to investigate to which extent existing wind farms can be expanded using already installed transformer units.Five transformer locations and nine units are studied for finding the potential of dynamic transformer rating for network expansion applications. The analysis shows that the optimal expansion of wind power from a generator perspective is around 30% to 50%, although, it can be limited further by network restrictions. A possibility to use a large component, such as power transformer, closer to its full potential can provide material and cost savings for building new devices and decrease investment costs on manufacturing, transportation and installation of new units. Dynamic rating of power transformers can also increase the socio-economic benefits of renewable energy by lowering electricity price from renewables and incentivize an increased share of green power in electricity markets.

Review of Cabin Thermal Management for Electrified Passenger Vehicles

The technical maturity and rapidly increasing market share of electrified vehicles have given more importance to the cabin thermal management. Efficient thermal management has a key role to maintain adequate electric operating range, protect components from aging and ensure passenger comfort. This research comprehensively reviews the cabin thermal management systems for electrified vehicles. Various vehicle cabin thermal modeling techniques and the key concepts for cabin thermal comfort have been discussed. Different technical and operational solutions of the cabin thermal management in hot and cold climate conditions are evaluated. The recent developments including heat pumps, thermal system control, passive thermal management, and cabin preconditioning to increase thermal management efficiency are analyzed. The results show that increasing amount of research is focusing on improving the thermal efficiency of the individual electrical components and the vehicle level systems. However, new solutions will be required for reducing the cabin thermal load under hot conditions and improving the heating system operational flexibility and efficiency in cold climates.

How to deal with missing overburden - Investigating exhumation of the fragment of the Mid-Polish Anticlinorium by a multi-proxy approach

Abstract Tectonic inversion and erosion conceal basin geological history. As simple stratigraphic reconstructions can be inaccurate, thermal modelling techniques are often applied. In this paper, we show the advantages of a multi-proxy approach for exhumation studies, which explores full range of all possible solutions. The part of the Mesozoic Central European Basin that was inverted into the Mid-Polish Anticlinorium in the Late Cretaceous is chosen as a case study. The analysis consists of three steps: First, a wide range of possible geological scenarios is constructed, accounting for two alternatives of the overburden sequence, southern and northern, that result from the impact of the Holy Cross Fault on Mesozoic deposition. The second stage comprises apatite fission track and vitrinite reflectance analyses carried out on a ~1500 m long vertical profile, inverse modelling of these data to obtain thermal histories, and 1D thermal modelling of burial-erosion using the PetroMod software. In the third step, results of modelling exercises are combined with probabilities of the overburden variants to define an ensemble of the most likely geological scenarios. By applying this workflow we conclude that exhumation of the Mid-Polish Anticlinorium began in the latest Turonian–early Campanian and that ~1.7–2.3 km of uppermost Triassic–Cretaceous rocks were removed. The heat flow was similar or slightly higher than the present-day value and during the Jurassic the study area was located on the northern side of the Holy Cross Fault, where deposition was faster. We also investigate the impact of elevated Late Palaeozoic heat flow on our samples and find that it was overprinted by high Late Cretaceous temperatures. All this is achieved by presenting the results as an ensemble of the most likely solutions within the wide modelling space.

Simulation thermal model of CNC machine tool operating with variable modes

The article presents the approach and the thermal modeling technique of CNC machine tools, implemented at the stage of operation. In the work, as a practical implementation of the fast modeling technology, a simulation method based on the Matlab Simulink application was used. In the work to build a thermal model of the machine tool, we used analytical solutions of the heat conduction equation. This method is applied to the machine tool operating in conditions of variable thermal processes due to varying cutting speeds. The conditions for the coordination of the thermal characteristics of the machine tool at their boundaries, corresponding to the changing spindle rotation speeds, determine the peculiarity of their construction. A feature of the implementation of the mathematical model is the use of experimental modal analysis. In this case, the modal parameters of the approximating functions are determined by solving the optimization problem. To coordinate the adjacent thermal characteristics at their borders, a special condition was adopted. Regardless of the number of temperature modes used in the model, the initial level of the first temperature mode for the next mode of operation of the machine tool was taken to be equal to the achieved level of the thermal characteristic of the machine tool at the last time interval of the current mode of operation.

Lumped Parameter Thermal Model for Axial flux Surface Mounted Permanent Magnet BLDC Machine

Axial flux surface mounted permanent magnet BLDC machines are of particular interest for power generation in typical and confined conditions. Due to their compactness & high power density, the ventilation and cooling inside axial flux permanent magnet BLDC machine have become increasingly important for further performance improvement. This paper describes a lumped parameter thermal model of Axial flux Surface Mounted Permanent Magnet BLDC Machine. The transient thermal characteristics and steady state temperature of the motor are estimated from a lumped parameter thermal model. The transient characteristic has been also simulated mathematically, developments of a lumped parameter, thermal modelling technique for axial flux permanent magnet generators. Lumped parameter thermal network is developed to predict the motor heat flow and nodal temperatures. The network is composed of 29 interconnected nodes, 63 thermal resistances and 29 capacitors representing the heat process within motor for steady state and transient analysis.

Thermal characterisation analysis and modelling techniques for CubeSat-sized spacecrafts

ABSTRACTRecently, universities and Small and Medium Enterprises (SMEs) have initiated the development of nanosatellites because of their low cost, small size and short development time. The challenging aspects for these satellites are their small surface area for heat dissipation due to their limited size. There is not enough space for mounting radiators for heat dissipation. As a result, thermal modelling becomes a very important element in designing a small satellite. The paper presents detailed and simplified generic thermal models for CubeSat panels and also for the complete satellite. The detailed model takes all thermal resistances associated with the respective layers into account, while in the simplified model, the layers with similar materials have been combined and are represented by a single thermal resistance. The proposed models are then applied to a CubeSat standard nanosatellite called AraMiS-C1, developed at Politecnico di Torino, Italy. Thermal resistance measured through both models is compared, and the results are similar. The absorbed power and the corresponding temperature differences between different points of the single panel and complete satellite are measured. In order to verify the theoretical results, thermal resistance of the AraMiS-C1 and its panels are measured through experimental set-ups. Theoretical and measured values are in close agreement.

High Current Testing and Simulation for Land Grid Array Sockets

Abstract Land grid array (LGA) sockets are commonly used for industry standard and custom microprocessors to meet the increased performance challenges for a variety of server applications. Along with the need for increased high speed signaling capabilities comes the challenge to support lower voltages and higher currents. Typical testing that is conducted by the LGA socket suppliers does not provide an accurate assessment of the maximum current capabilities in a real product application due to the test card design and construction limitations. Typical test card designs use daisy chain connections to wire multiple LGA socket contacts in series. The daisy chain wiring in the test card adds to the resistive heating and results in an inaccurate maximum current rating. Also, the test cards typically do not have a cross section construction that is representative of a real product application with multiple ground planes that provide improved thermal dissipation of the heat generated by the LGA socket interface. Hardware testing was conducted to better understand the performance limitations for a new product application. The test card was designed to use multiple voltage and ground planes in the circuit card cross section to provide a low impedance path for current flow and a low voltage drop through the LGA socket interface. In addition to the test card construction, the test hardware included a special test module with a shorted chip to provide a more accurate power distribution path through the socket and processor package. The test variables included different plating metallurgy options for the LGA socket and the processor module along with different configurations for the voltage supply and ground return contacts. Electrical and thermal modeling techniques were used to simulate the test hardware configuration with good correlation between the hardware and modeling results. Based on the positive correlation results, additional modeling was conducted to simulate the worst case power mapping conditions for the processor chip along with a more accurate power distribution. The additional modeling results provided further insights into the maximum current capabilities for the LGA socket based on the temperature increase from the resistive heating in the socket contacts.

Errors in micro-electro-mechanical systems inertial measurement and a review on present practices of error modelling

Micro-electro-mechanical systems (MEMS) technology-based accelerometers and gyroscopes are small size, mass produced, low cost inertial sensors, which are now being used in aerospace, underwater vehicles, automotive, robotics, mobiles, gaming consoles, prosthetic devices and many other applications. MEMS inertial sensors are available in many grades in market and selecting the appropriate grade sensor is very important. Owing to interaction of different types of energies, different noises are generated in MEMS devices; these noises cause significant change in output and the first section of this paper illustrates that. In application, where MEMS inertial sensors are used, the accuracy, repeatability and reproducibility of inertia measurement is probed primarily by complex testing, using extensive range of physical stimuli. Noises in inertial measurement are generally dealt by designing a unit measurement model. Noises are treated as additive error in linear unit model and are modelled using various techniques so that errors can be compensated to improve the accuracy. This paper reviews the theory, framework and methodology used in the error model of a MEMS inertial sensor and stochastic modelling of measurement. Experimental results from the most commonly used Allan variance techniques are discussed. Error modelling methodology, consisting of testing and calibration methods, designing thermal model, stochastic modelling and parameter estimation techniques, is illustrated. Figures and tables under each section summarize features, merits, limitation and future research scope. This paper should serve as a single reference for researchers and engineers working on application specific system design and instrumentation using MEMS inertial sensors. Conclusion from the study should help in selecting the appropriate grade of sensor as well as the best error modelling as per the trade-off existing between accuracy and development cost of error modelling.

Analytical Thermal Model for Fast Stator Winding Temperature Prediction

This paper introduces an innovative thermal modeling technique which accurately predicts the winding temperature of electrical machines, both at transient and steady state conditions, for applications where the stator Joule losses are the dominant heat source. The model is an advanced variation of the classical lumped-parameter thermal network approach, with the expected degree of accuracy but at a much lower computational cost. A seven-node thermal network is first implemented and an empirical procedure to fine-tuning the critical parameters is proposed. The derivation of the low computational cost model from the thermal network is thoroughly explained. A simplification of the seven-node thermal network with an equivalent three-node thermal network is then implemented, and the same procedure is applied to the new network for deriving an even faster low computational cost model. The proposed model is then validated against experimental results carried on a permanent magnet synchronous machine which is part of an electro-mechanical actuator designed for an aerospace application. A comparison between the performance of the classical lumped-parameter thermal network and the proposed model is carried out, both in terms of accuracy of the stator temperature prediction and of the computational time required.

Guest Editorial Special Section on Energy Storage Systems

Energy storage is revolutionizing transportation by proving a sustainable alternative to fossil fuels, and opening new opportunities as flexible grid bidirectional storage through vehicle-to-grid services. In order to fully exploit these new transportation opportunities, advances still need to be achieved in energy storage, and batteries, in particular, to improve range, cost, and lifetime. Current trends show a higher penetration in road transportation compared with other sectors, but with promising roadmaps for marine, aerospace, and rail sectors. Therefore, the body of work required to achieve these roadmaps spans from electrochemical, thermal, and electrical simulations to better understand the battery operation to system integration design within the powertrain and the grid. This Special Section provides with new knowledge on the full research and development spectrum, by presenting battery electrochemical and thermal modeling techniques, design of storage solutions for electrified vehicle recharging stations, energy management for electric vehicles and simulation, and design and deployment of energy storage for rail and material handling applications.