Thermal Model Research Articles

Evidence for and Against Temperate Ice in Antarctic Shear Margins From Radar‐Depth Sounding Data

AbstractThe majority of ice mass loss from Antarctica flows through narrow, fast sliding regions of ice. The lateral boundaries of these regions, termed shear margins, are characterized by lateral shear strains in excess of ∼10−3 yr−1. Shear heating within these margins could warm ice significantly–even to the melting point–but other processes such as lateral advection of cold ice and fabric development compete with this effect. Radar observations can help constrain where temperate ice exists because englacial temperature increases electric conductivity which increases radar attenuation. We utilize the temperature‐dependent attenuation of ice to develop a novel method for constraining englacial temperature in shear margins by combining existing thermal models with very high frequency radar depth‐sounding data. We find evidence supporting temperate shear margins in 18 locations and find evidence for non‐temperate margins in 37 locations, notably in the Amundsen Sea Embayment.

Thermal Optimization Strategies for Li-Ion Batteries: Predictive Temperature Algorithm

Abstract Performance, safety, and longevity of batteries are all strongly impacted by thermal management, which is an essential component of battery design and operation. This work examines how accurate temperature control can result in significant improvements in performance and reliability with a focus on battery thermal heating. Predicting the temperature achieved by the battery during operation not only avoids conditions that lead to thermal runaway, but also guarantees that the battery is used optimally within an optimal temperature range. Within the optimal temperature range several advantages are observed. First, battery efficiency improves significantly as electrochemical processes occur more efficiently. Furthermore, by lowering the possibility of short circuits and improving overall battery safety, thermal stability aids in the prevention of undesirable phenomena like dendrite growth. By lessening the deterioration brought on by thermal degradation processes, thermal optimization also affects battery longevity. Based on experimental tests, a Finite Element Model (FEM) is developed. A model for thermal runaway propagation is established by combining thermal runaway and conduction models with an Arrhenius law-based combustion model. The study employed a cylindrical Li-Ion cell to conduct tests, taking into account three parameters: discharge rate (CRate), ambient temperature (Tamb), and initial battery temperature (T0). An algorithm based on the three variables was developed using the simulation results. The algorithm enables the accurate prediction of rising battery temperature during use, facilitating the setting of an optimal maximum discharge rate considering initial and ambient temperatures, thereby ensuring optimal performance within the desired temperature range.

GRAPHITE FOAM STRUCTURES AS AN EFFECTIVE MEANS TO COOL HIGH-PERFORMANCE ELECTRONICS

Due to their unique heat transfer features, graphite foams are used in the current analysis to form heat sinks effective enough to dissipate extreme heat generated within high-performance electronics. The heat sinks proposed are formed from foamed-baffles arranged either in parallel or perpendicular to the coolant paths through the staggered slots in between to alleviate the penalty of pressure drop while maintaining high heat dissipation capability. Two different sorts of dielectric coolants namely, air and the FC-3283 electronic liquid developed by 3MTM, have been utilized to directly dissipate the heat generated. The feasibility of the currently proposed heat sinks has been examined numerically based on the volume averaging concept of porous media employing the local thermal non-equilibrium model to account for interstitial heat exchange between the foam solid matrix and the fluid particles flowing across. A wide range of design parameters has been tested including the heat sink configuration along with structural characteristics of the graphite foam used. It has been found that foam baffles oriented perpendicular to the path of coolant flow can dissipate heat by about 50% better than those parallel to it, but with higher pressure losses. It has also been found that heat dissipation capability, for a certain orientation of baffles, can be improved by up to 100% when the foam pore size is doubled with outstanding saving in pressure losses by up to 300%. The impact of operating conditions, including the coolant flowrate and the heat flux applied, has also been inspected. The currently proposed heat sinks have been found efficient to meet the thermal demands of high-performance electronics and sweep away the extreme heat generated there with reasonable cost of pressure drop, where the proper selection of design parameters in light of the operating conditions applied can prevent the emergence of hot spots entirely. Extreme operating conditions, i.e. with heat density of up to 10W/cm2 for air-cooled heat sinks and 100W/cm2 for those cooled with FC-3283, can be well managed when a heat sink is configured from baffles that are oriented perpendicularly to the coolant flow path and formed of graphite foam having low porosity (∅=0.8) and larger pore size 

Large time existence and asymptotic stability of the generalized solution to flow and thermal explosion model of reactive real micropolar gas

We study the long time behavior of the generalized solution of the flow and thermal explosion model of the reactive real micropolar gas. The dynamics of the chemical reaction involved and the usual laws of conservation of mass, momentum, angular momentum, and energy generate a complex governing system of partial differential equations. The fluid is nonideal and non‐Newtonian. In this work, we prove that the problem can be solved in an infinite time domain and establish the asymptotic properties of the solution. Namely, we conclude that for certain parameter values, the solution stabilizes exponentially to a steady‐state solution, while for others the stabilization occurs but at power decay rate. At the end, we conducted a few numerical tests whereby we experimentally confirmed theoretical findings about long‐term behavior of the solution.

Abstract PO1-07-12: Inverse modeling with surface temperature accurately detects the presence of breast cancer

Abstract Breast cancer affects over 250,000 women in the United States every year. Patient outcomes including overall survival significantly decline with large sized tumors and nodal involvement on initial presentation. The introduction of mammogram screening has been instrumental in the early detection of cancer. However, it has lower sensitivity in dense breast tissue and limited specificity which leads to unnecessary additional invasive testing. Several methods such as magnetic resonance imaging (MRI), computed tomography (CT) and ultrasound imaging are used as adjunctive methods. However, there is still a need for cost-effective techniques without additional radiation exposure for breast cancer screening for use with mammography. We propose an adjunctive screening method using surface temperature measurements and inverse breast modeling for early detection of breath cancer. Methods: We enrolled patients who presented with mammogram detected breast tumors that were confirmed to be cancerous lesions by biopsy. We used prone position steady state infrared imaging of bilateral breasts to measure surface temperatures and multi-view MRI images to create patient specific 3D breast models. The inverse technique applies Levenberg-Marquard algorithms (LMA) and utilizes commercial software for thermal transport modeling. The inverse technique predicts a heat generation map normalized for baseline surface temperatures to localize the presence of an underlying tumor. Results: A total of 25 breast tumors (diameter range from 5 to 27 mm) from 24 patients were included in the analysis with a median patient age of 67 years. One patient had bilateral breast tumors. Mammogram data showed inclusion of mixed breast tissue composition including dense and extremely dense breast tissue. LMA accurately detected the tumor in all 25 patients with maximum absolute errors of 7 mm in location of the tumor in the breast and 1.78 mm in diameter. The accuracy of detection was not affected by tumor histology which included invasive ductal and lobular carcinomas, ductal and lobular carcinoma in-situ and atypical ductal hyperplasia. No heat sensitive tumors were detected in the 23 contralateral breasts which acted as internal negative controls. Conclusion: Infrared temperature profiles and inverse modeling successfully detected malignant breast tumors with no missed tumors or false positive results and could be used as adjunctive screening along with mammography, especially in patients with dense breast tissue. Citation Format: Nithya Sritharan, Carlos Gutierrez, Isaac Perez-Raya, Jose-Luis Gonzalez-Hernandez, Alyssa Owens, Donnette Dabydeen, Lori Medeiros, Satish Kandlikar, Pradyumna Phatak. Inverse modeling with surface temperature accurately detects the presence of breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-07-12.

Cooling and optimizing urban heat island based on a thermal knowledge-informed multi-type ant colony model

In the context of rapid urbanization and global warming, the urban heat island (UHI) intensifies the risk of heat-related mortality, endangering the health of urban residents. Urban greening effectively mitigates severe urban heating climates, but increasing green space without restrictions is undesirable due to the scarcity of urban land. Accurately characterizing the scope and intensity of UHI and determining the spatial location of the area that needs to be optimized are necessary. In this study, an inverse S-shaped function was used to fit the urban-rural temperature attenuation, whose parameters explicitly describe the properties of UHI. Additionally, a thermal knowledge-informed multi-type ant colony model was proposed to cool UHI automatically. A case study of Wuhan showed that: (1) the fitting effect of the inverse S-shaped function is desirable with the adjusted R2 exceeding 0.97, and the derived parameters with clear physical meanings avoid subjectivity in describing thermal characteristics; (2) high-level heat island of the main urban areas can be reduced by 7.7%–8.5% after land use optimization; and (3) a comparison with the traditional multi-type ant colony model verifies that the model proposed in this study can avoid excessive dispersion of the optimized pixels whose land use types are modified and achieve more reasonable and stable optimization results. This study provides useful exploratory tools for sustainable urban planning, heat mitigation solutions, and other urban retrofitting.

Temperature stratification in a molecular shock: Analysis of the emission of H2 pure rotational lines in IC443G

Context. Supernovae remnants (SNRs) represent a major source of feedback from stars on the interstellar medium of galaxies. During the latest stage of supernova explosions (which lasts 10–100 kyr), shock waves produced by the initial blast modify the chemistry of gas and dust, inject kinetic energy in the surroundings, and may alter star formation characteristics. Simultaneously, γ-ray emission is generated by the interaction between the ambient medium and cosmic rays, in particular those locally accelerated in the early stages of the explosion. Aims. We aim to estimate the total molecular mass, local density, and total column density of H2 and the temperature structure in a shocked clump interacting with the supernova remnant IC443 located in a region where cosmic rays interact with the interstellar medium. Measuring the mass of the dense and neutral component of the medium is a prerequisite to understanding the chemistry, energetics, and GeV to TeV γ-ray emission. Methods. Assuming that the emission of H2 pure rotational lines is produced by a collection of gas layers with variable temperature, we compared Spitzer/IRS emission maps for the ν = 0–0 S(0) to S(7) lines with a thermal admixture model. Our description is based on a power-law distribution of thermalized components with temperatures varying between Tmin = 25 K and Tmax = 1500 K. Results. Our thermal admixture model allows the level populations of H2 to be described by a power-law distribution dN = ΛT−ΓdT, with Γ ~ 2.2−4.7. We measured a total mass MH2 = 220−80+110 M⊙ across the Spitzer/IRS field of observations. Conclusions. Our analysis shows that an estimate of the cold molecular gas temperature is paramount to accurately constraining the H2 mass, although the mass remains affected by significant uncertainties due to the assumptions on the gas temperature distribution.

Research on thermal stratification of surge line in the marine reactor based on fluid-solid thermal coupling model

Due to the requirements of ship movement, the power of the marine reactor is constantly changing, and the expansion and contraction of the primary coolant make the fluid flow in and out through the surge line. This paper establishes a fluid-solid thermal coupling model for the thermal stratification of a Marine reactor surge line. The low Reynolds number eddy viscosity model and the curvature modification of the bending pipe are used in this model. Qiao experiment is provided to verify the model's applicability to the thermal stratification analysis. The typical working conditions of the Marine reactor are analyzed, and the results show that: the temperature difference between the top and bottom of the pipe changes constantly with the fluctuation of the fluid, the maximum temperature difference in the horizontal section is 59.6K, and the maximum temperature difference in the vertical area is 23.9K. The maximum stress fluctuation of the horizontal section is 36MPa, while that of the vertical section is 5MPa. In the non-destructive testing, many small pits were found in the horizontal section of the pipeline, while no obvious damage was found on the surface of the vertical section, which is consistent with the results of our numerical analysis.

Optimization of MTI structure based on material characteristics under extreme aerodynamic heating environment

Thermal insulation structure is a key factor to protect a high-speed aircraft to work safely and complete various tasks. The multilayer thermal insulation (MTI) structure has attracted much attention because of its light weight and good thermal insulation effect. The performance of an MTI structure is not only related to its physical sizes, but also closely related to the material optimization and temperature influences. A transient nonlinear thermal transfer model of the MTI structure is established, and a numerical solution strategy of the nonlinear thermal transfer model is proposed. Considering material selection, introducing the temperature influence of materials, and taking the geometric dimensions and equivalent mechanical properties of the MTI structures as constraints, an optimization frame of the MTI structures is established. Then two intelligent methods are adopted to solve the problem. Using the aerodynamic heating environment of X-43 flight trajectory, the results of a typical high-speed aircraft show that the proposed optimization framework can reduce the structural mass density from 13.95 kg‧m−2 to 9.10 kg‧m−2 by about 34.8 %. The temperature effect analysis shows that the temperature variation has an important influence on the optimization results. If the temperature effect on material properties is not considered, the optimized design scheme may not meet the temperature design constraints (The maximum temperature of the inner surface is 410 K, far exceeding the maximum allowable temperature of 320 K) which further leads to structural failures. Finally, the reliability and rationality of the optimization scheme are verified by a finite element model (FEM). The equivalent modulus of the optimized MTI structure is 146 GPa and the mass area density of the MTI structure is 7.7 kg‧m−2. The optimization design method of an MTI structure proposed in the current paper provides a technical support and lays a foundation for the overall design of a high-speed aircraft.

Improving the thermal comfort model for students in naturally ventilated schools: Insights from a holistic study in the Mediterranean climate

The thermal comfort models defined in existing standards are usually ineffective in predicting students’ mean thermal sensation. Accordingly, overheating and overcooling are frequently reported, which affect students’ well-being and cause unnecessary energy waste. Existing studies have not further explored the model improvement strategies for educational buildings. Hence, this research aims to improve the mean thermal sensation prediction model for students in naturally ventilated schools by incorporating correlated factors, based on a holistic field survey in the Mediterranean climate. The results indicate that the modified extended predicted mean vote of thermal adaptations reinforced around thermal neutrality has the highest accuracy among all validated adaptive predicted mean vote models. However, the performance of the adaptive predicted mean vote models is limited by the deficiencies of the original predicted mean vote model. The overall performance of the improved models was doubled after introducing the identified correlated factors, but the intrinsic error of the predicted mean vote index can slightly affect the models. As a result, the improved model built directly with the identified correlated factors achieved the best performance. Moreover, the potential of the machine learning models is limited by the volume of the mean thermal sensation vote data that can often be obtained, therefore conventional models such as multiple linear regression can be considered an effective and practical tool for developing the mean thermal sensation vote models. The findings of this study benefit the well-being of students and the energy conservation of educational buildings.

Multiphysics integrated model of NMC111 battery module for micro-mobility applications using PCM as intercell material

The widespread use of e-bikes and e-scooters powered by lithium-ion batteries in urban settings has heightened safety concerns, particularly the risk of thermal runaway, which can result in dangerous incidents. The surge in battery-related fire incidents highlights the critical need for a deep understanding of thermal runaway phenomena. This study addresses this imperative by introducing a Multiphysics model combining pseudo-bidimensional electrochemical for simulating electrical performance, lumped thermal model for simulating the heat transfer behavior inside the module, and a thermal runaway kinetic model for propagation evaluation. This approach facilitates precise predictions of battery performance and proactively addresses safety concerns by incorporating thermal behavior simulations and predicting potential thermal runaway events. The model proposed allows the evaluation of different strategies for improving battery safety and performance, such as phase change materials and thermal insulators. Simulations reveal that implementing sodium hydrogen phosphate dodecahydrate (Na2HPO4··12H2O) as an intercell material substantially enhances thermal management. This material reduced the maximum temperature of the battery module by up to 30% during critical thermal runaway events. Additionally, it slowed the rate of temperature increase by 50%, significantly decreasing the possibility of adjacent cells reaching thermal runaway conditions. The research findings demonstrate the effectiveness of advanced thermal management strategies using PCMs to prevent potentially catastrophic thermal events in battery modules typical of micro-mobility devices.

Numerical analysis and process optimization of electron beam melting for superalloys

This study aims to determine the optimal parameters for the electron beam melting process by employing a modified transient three-dimensional thermal model. The validity of the thermal model is confirmed through experimental results. Moreover, the proposed method establishes mathematical relationships between the resulting molten pool temperature and process parameters. A broader range of process parameters for a new Ni-Co-based superalloy was achieved by investigating the effects of scanning velocities (10-100 mm/s), scanning radius (20-60 mm), and melting mass (1500-3100 g) on temperature at various electron beam power levels (10-30 kW). Regression models were established between scanning velocities-temperature, and scanning radius-temperature under different electron beam power levels. These models laid the foundation for real-time automatic control of molten pool temperature. Significantly, orthogonal experimental design and response surface method are employed to conduct a multi-objective optimization based on sixteen experiments and three parameters. The results of multi-objective optimization indicate that with a smelting mass of 1.5 kg, an electron beam power of 11 kW, a scanning radius of 60 mm, and a scanning velocity of 75 mm/s, the energy consumption is 34.95 kW·h, and the theoretical mass loss of Ni element is 0.002 kg. The desirability is 91.2 %.

Design and multi-criteria optimization and financial assessment of an innovative combined power plant and desalination process

Geothermal power generation programs are crucial due to their long-term sustainability and environmentally friendly characteristics, particularly for potential energy-based applications in the future. Innovative designs can yield improve efficien by mitigating irreversibility, resulting in enhanced power production. Hence, this study investigates an innovative cascade thermal design model that employs geothermal resources to enhance the efficiency and output of low-temperature power generation systems, specifically through the integration of organic flash and organic Rankine cycles. Additionally, this model introduces a novel cogeneration approach by incorporating a desalination unit based on humidification-dehumidification processes, aiming to concurrently produce electricity and fresh water. Employing a combination of thermodynamic analysis and financial assessment, the system's performance was simulated and optimized in MATLAB, using the Multi-Objective Particle Swarm Optimization (MOPSO) method. A sensitivity analysis preceded the optimization, leading to the development of three distinct optimization scenarios focused on balancing power and freshwater production, maximizing exergetic efficiency and net present value, and optimizing fixed capital investment for maximum financial viability. The results highlight the second scenario as particularly effective, achieving a power generation of 254.3 kW, an exergetic efficiency of 44.84%, and a net present value of $405,099. Conversely, the third scenario offers the best balance between freshwater production capacity (0.504 kg/s), fixed capital investment ($820,822), and a payback period of 7.12 years. This research demonstrates the potential of integrating advanced thermal models with geothermal resources for sustainable and efficient energy and freshwater production, marking a significant step forward in the development of eco-friendly cogeneration systems.

Effect of temperature step-changes and ramps on physiological and psychological responses of occupants in office buildings in summer

Thermal conditions with step changes and ramps in air temperature (Ta) are universal in buildings. However, a comprehensive understanding of the influences of these dynamic thermal factors on thermal comfort remains elusive. This study investigated the physiological and psychological responses 16 healthy college students, including thermal sensation vote (TSV), thermal pleasure (TP), positive and negative affect schedule (PANAS), skin temperature, blood pressure, wrist pulse, and electroencephalography (EEG). The experimental procedure included step-changes from an office room (26°C) to a meeting room under five different Ta (22/24/26/28/30°C) and subsequent ramping (down/up/cycles) back to 26°C. After these different warm/cool thermal experiences, TSVs (-0.2 to 0.2) were insignificantly different and TPs (0.2 to 1.6) were significantly different (P = 0.006) at neutral condition of 26°C. Specifically, TPs under neutral conditions were higher after a warmer thermal experience than after a cooler thermal experience. Under the same Ta, TSVs were significantly lower (P=0.031) by approximately 0.5, when Ta ramping down compared to ramping up and stable warm conditions. The cheek temperature showed stronger correlations with TP and PANAS scores than with other body parts. The blood pressure was weakly correlated with TSV but exhibited a strong relationship with TP. Moreover, the TP and positive emotions exhibited strong negative correlations with wrist pulses and EEG at Theta (4–8 Hz). whereas negative emotions showed almost no correlation. These findings offer insights into refining the prevailing thermal comfort models when considering dynamic thermal factors in shaping thermal perceptions.

Developing a combined rotating and air-circulating system for improving radio frequency heating uniformity and controlling Aspergillus in almond kernels

It is important to improve radio frequency (RF) heating uniformity for developing effective pathogen control protocols before storage of almonds. The purpose of this study was to design a combined rotating and air-circulating system (CRACS) in the RF cavity for improving sample temperature uniformity during pasteurization, drying, and cooling of almond kernels. The results showed that the optimal rotating speed of 15 r/min and loading volume ratio of 60% of CRACS were determined to achieve the required RF pasteurization level. The pasteurization protocol was developed based on the above selected parameters of CRACS, RF heating/drying, and forced air cooling. Compared to the five-layer container (five single layers stacked vertically) used for RF pasteurization of almond kernels, the RF heating uniformity in almond kernels using CRACS was clearly improved, resulting in moisture content reduction of only 0.70% wet basis (w.b.). The pasteurization validation curve of almond kernels in CRACS was closer to the predicted survival one based on the cumulative thermal lethal time model, suggesting that CRACS was suitable for the effective RF pasteurization of almond kernels. The moisture content and color values of almond kernels after RF pasteurization were beneficial for maintaining their long-term storage and stable quality. This CRACS in the RF system may provide a practical and effective technology for pasteurizing almond kernels.

Thermal lens investigation of the CdSe quantum dots using dual beam z-scan technique

We highlighted on the thermal lens (TL) effect of Cadmium Selenide quantum dots (CdSe QDs) using dual beam z-scan technique. The thermal lens nonlinear optical properties of CdSe QDs were investigated by applying the two CW laser beams (λ = 532 nm and λ = 632.8 nm). The thermal lens parameters of the CdSe solutions, such as: the on-axis phase shift (θ), the thermal diffusivity (D), and thermal diffusion time (tc) were extracted using the theoretical thermal lens model. Our results give new insight into the CdSe QDs dissolved in toluene and are valuable for further development of semiconductor QDs optical devices.

Numerical simulation of mass and heat transfer for water extraction from icy lunar regolith

The confirmation of water ice’s existence in the permanent shadow area led to extensive research in the field of water ice mining from icy lunar regolith. A priori numerical simulation of water ice mining is necessary for guiding the development of lunar water ice mining schemes more reasonably. A 2D axisymmetric numerical simulation model capable of simulating the thermal extraction process about mining water ice from icy lunar regolith is constructed, which is executed in the COMSOL Multiphysics. The thermal extraction cases of lunar regolith with different initial water ice content and heating fluxes are simulated. The EER (energy efficiency ratio) is used to evaluate the efficiency of thermal extraction. The results show that the EER is higher as the initial water ice content is increased, which means more power is used to heat water and less power is used to heat the regolith. The icy lunar regolith with initial water ice content higher than 5.0 wt% is found to be more valuable, over which the EER at the end of thermal extraction will not increase much as the initial water ice content increases. However, the higher heating flux leads to the lower EER at the end of thermal extraction. The speed and economics of thermal extraction are suggested to be weighted before the mission’s implementation. The status of thermal diffusion (thermal transpiration) is studied, and the results indicate that thermal diffusion and advection both can be ignored in thermal extraction modeling, unless the average magnitude of temperature gradient and pressure gradient exceed the maximum of 75764 K/m and 11053 Pa/m in our calculation cases, respectively.

Mechanical behavior of dissimilar AL6XN-IN718 welded joint obtained by cold metal transfer

Cold metal transfer (CMT) welding process was used to join the AL6XN super-austenitic stainless steel to a nickel-based super alloy IN718. Microhardness, tensile and low cycle fatigue tests were carried out to determine the mechanical properties of the welded joint. The heat used to perform the weld decreases the microhardness in the heat affected zone (HAZ) of the IN718 material. A decrement of about 50% with respect to the base material (∼410 HV0.2) was observed, which is attributed to the microstructural transformation produced by the weld thermal cycles, inducing the partial dissolution of the γ´´ phase in the nickel matrix. In contrast, the HAZ on the AL6XN side, the microhardness tends to be similar with respect to the base material (∼203 HV0.2). In terms of the fracture energy, determined from the stress-strain plot, the welded joint decreases about 60-65% with respect to the base materials. This tendency was also observed in the case of the Charpy impact test behavior. From the low cycle fatigue test, it was observed that AL6XN material and AL6XN-IN718, performed better than the IN718 alloy, i.e. more tolerance to the strain cyclic, increasing the number of cycles to failure. A 3-D transient thermal conduction finite element model was developed to correlate the thermal history with the microstructural transformation on the HAZ and mechanical properties. The weld thermal cycles are in good agreement with the experimental measurements obtained by K-type thermocouples.

Evaluation and application research on thermal comfort of mining face in hot and humid mines

The hot and humid environment in the coal mines negatively affects miners' health and mental health. This paper analyzes the factors that affect the human body heat dissipation, puts forward the concept of dressing rate, and uses the dressing rate to correct the human skin heat dissipation loss and sweat evaporation heat dissipation loss in the underground environment. A human-body thermal comfort model suitable for the hot and humid mine environment is constructed. Then the evaluation index UPMV of thermal comfort in hot and humid mines is proposed, and the mathematical model of human thermal comfort evaluation is constructed which improves the accuracy of human thermal comfort evaluation in hot and humid mines. Lastly, a software system of thermal comfort evaluation for hot and humid mines is developed, which is used to evaluate the thermal comfort of the human body at different working points of horizontal mining roadway in Shoushan mine, and the accuracy of the evaluation model is validated. The research results provide a theoretical basis for the evaluation system of human thermal comfort in hot and humid environments, and provide a reference for a scientific and reasonable arrangement of underground production.

Integrating few-shot personalized thermal comfort model and reinforcement learning for HVAC demand response optimization

Heating, ventilation, and air conditioning (HVAC) is the most common equipment to maintain personalized thermal comfort (PTC), and a valuable demand response (DR) resource. The challenges to be addressed in HVAC DR optimization include uncertainties of environment, PTC varies by users and rapid decision-making. This paper proposed a fast HVAC DR optimization method that integrates deep reinforcement learning (DRL) and few-shot PTC model. Firstly, we established an HVAC DR optimization framework integrated few-shot PTC model and DRL, in which the few-shot PTC model was utilized to generate user’s PTC temperature range served as the constraint and state variable of DRL. Secondly, we proposed a few-shot PTC model, which only required several field samples and had excellent engineering usability. Thirdly, we designed the HVAC DR optimization algorithm considering user’s PTC based on proximal policy optimization, which automatically dealt with the uncertainties and made rapid decisions for setting HVAC setpoints of temperature dynamically. Simulation results show that the few-shot PTC model only requires 9 field samples, which is less than 1% of existing advanced methods. Furthermore, the proposed method converges within 12.6 min under uncertainties on an i7-12700 processor, which is only about 1/2 of the standard deep deterministic policy gradient.