Applied Thermal Engineering最新文献

{"title":"Effect of optical errors on the thermal–hydraulic performance of direct-steam-generation parabolic trough collector","authors":"Shuaishuai Liu,&nbsp;Bin Yang,&nbsp;Xiaohui Yu","doi":"10.1016/j.applthermaleng.2025.126591","DOIUrl":"10.1016/j.applthermaleng.2025.126591","url":null,"abstract":"<div><div>Parabolic trough solar direct-steam-generation (PTC-DSG) technology is one of the favorable technologies to achieve low-carbon future by cleverly integrating clean energy with green carriers. There are various optical errors under actual operation, which cause heat flow distribution distortion and affect the performance of PTC-DSG, but there is a relative lack of research on the absorber tube’s two-phase flow and heat transfer performance under different optical errors. The coupled optical-thermal-flow model of the PTC-DSG collector is established in this paper based on Monte Carlo ray tracing method, Finite Volume method and Eulerian multiphase flow model. The absorber tube’s heat transfer performance and two-phase flow under slope error (<em>σ_s</em>), tracking error (<em>σ_t</em>) and absorber installation error (<em>σ_x</em> and <em>σ_y</em>) are comprehensively investigated. The results revealed that the circumferential temperature distribution distortion caused by optical errors has a significant impact on the absorber tube’s heat transfer performance and reliability. <em>σ_s</em> made the temperature distribution more uniform, but significantly reduced the maximum circumferential temperature (<em>T_a,</em>_max), circumferential temperature difference (CTD), collector efficiency (<em>η_c</em>), and vapor volume fraction (VVF) of the absorber tube, and reduced the threat to the DSG collector. High <em>σ_t</em> (&gt;8 mrad) significantly affects the absorber tube’s two-phase flow and heat transfer performance with rapid reduction of <em>T_a,</em>_max, CTD and VVF, and <em>η_c</em> in evaporation and superheating stages are also reduced by about 33.3 % and 34.2 %, respectively. The effects of <em>σ_x</em> and <em>σ_y</em> on the absorber tube’s flow heat transfer performance are small, but significantly affect its circumferential temperature distribution and CTD. <em>σ_y</em> (&gt;0 mm) causes the most inhomogeneous circumferential temperature distribution, which threatens the DSG collector’s safety. Moreover, the absorber tube at low operating pressure has higher <em>η_c</em> and VVF, but correspondingly higher CTD. Compared to the evaporation stage, the absorber tube in the superheating stage is subjected to greater thermal loads but also has higher <em>η_c</em>, especially at low operating pressure.</div></div>","PeriodicalId":8201,"journal":{"name":"Applied Thermal Engineering","volume":"273 ","pages":"Article 126591"},"PeriodicalIF":6.1,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143869683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Parameter analysis and multi-objective optimization of organic Rankine cycle coupled vapor compression cycle using PSO-BPNN model","authors":"Zhiqi Wang ,&nbsp;Qianghui Yi ,&nbsp;Yabin Zhao ,&nbsp;Kao Zhang ,&nbsp;Xiaoxia Xia ,&nbsp;Zheng Xiao ,&nbsp;Jiaqi Huang ,&nbsp;Tao Gong","doi":"10.1016/j.applthermaleng.2025.126583","DOIUrl":"10.1016/j.applthermaleng.2025.126583","url":null,"abstract":"<div><div>The accuracy of predictive models is crucial for evaluating and optimizing the performance of organic Rankine cycle combined with vapor compression refrigeration (ORC-VCR) cycles. This paper establishes a PSO-BPNN prediction model by optimizing the weight and threshold of the back-propagation neural network (BPNN) using particle swarm optimization (PSO). A small ORC-VCR device with a cooling capacity of 3 kW is constructed, and 142 steady-state experimental data are obtained for training the developed model. Then, the influence of operating parameters on the system performance is investigated. In addition, operating parameters are optimized to maximize the cooling capacity and coefficient of performance (COP). The average absolute error of PSO-BPNN model for cooling capacity and COP is about 2.2 %, which is 34 % and 46 % lower than the BPNN model. Compared with the flow rate of cooling water, its temperature has a greater impact on the system performance. The vapor compression cycle has an optimal flow rate to obtain the maximum cooling capacity and COP of the combined system. Through multi-objective optimization, the optimal cooling capacity and COP of the ORC-VCR system are 4.41 kW and 0.32, which are 32 % and 14 % higher than the maximum values observed in the experimental data.</div></div>","PeriodicalId":8201,"journal":{"name":"Applied Thermal Engineering","volume":"273 ","pages":"Article 126583"},"PeriodicalIF":6.1,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143864570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance investigation and machine learning modeling of PV panels equipped with PCM based passive cooling systems","authors":"Hussain Shawish ,&nbsp;Murat Özdenefe ,&nbsp;Sertan Erdem","doi":"10.1016/j.applthermaleng.2025.126588","DOIUrl":"10.1016/j.applthermaleng.2025.126588","url":null,"abstract":"<div><div>In this work performance of two PCM based passive cooling systems for PV panels was investigated. The cooling systems were in the form of rectangular PCM containers, one equipped with fins while the other with porous medium. Outdoor experiments were conducted in winter and summer to examine both daytime cooling and nighttime heat rejection of the two containers, and to explore the performance variation across the two seasons. Moreover, machine learning models were generated to predict the PV panel’s temperature and power for the considered systems. Both systems effectively cooled the PV panels in winter during the day and achieved sufficient heat rejection during the night. However, the porous medium container had superior performance, achieving around 3.40 °C average temperature reduction and up to 3.56 % enhancement in efficiency. In summer where PV temperatures are much higher, the porous medium container underperformed while the finned container resulted in noticeable cooling achieving 3.42 °C temperature reduction and up to 6.58 % increase in efficiency. On other hand, the finned container encountered insufficient heat rejection at night. Machine learning models generated using ANN illustrated acceptable prediction accuracy with coefficient of determination (R²) of 0.98 for winter and 0.99 for summer. The mean square errors (MSE) in the predicted PV’s temperature and power were 1.08 °C2 and 0.27 W² for winter and 1.57 °C² and 0.11 W² for summer, respectively. The findings of the study highlights the season-dependent nature of different PCM based passive cooling systems.</div></div>","PeriodicalId":8201,"journal":{"name":"Applied Thermal Engineering","volume":"274 ","pages":"Article 126588"},"PeriodicalIF":6.1,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143873739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance Analyses of a novel operation strategy for data Centre’s centralized Water-Cooling system to match personalized cooling demands","authors":"Rang Tu ,&nbsp;Yuyao Ge ,&nbsp;Xiaomin Chang ,&nbsp;Lanbin Liu ,&nbsp;Xu Yang","doi":"10.1016/j.applthermaleng.2025.126553","DOIUrl":"10.1016/j.applthermaleng.2025.126553","url":null,"abstract":"<div><div>Large data centres usually have multiple IT rooms with diverse heat dissipation requirements, and centralized water-cooling systems are normally employed as the cooling system. This study proposes a novel energy-efficient operation strategy for centralised water-cooling systems in data centres, which meets personalised cooling demands in different IT rooms. First, a numerical model was built for the centralised water-cooling system. Based on the numerical model, performances of three operation strategies, that is, regular strategy (RS) with fixed chilled water operating parameters, unified operation strategy (OS1), and personalised operation strategy (OS2), were compared under typical working conditions. The results show that OS1 and OS2 have similar energy-saving performance, achieving energy efficiency improvements of 19 % to 89 % under typical daily operating conditions compared to the operational results of RS. However, the supply and return air temperatures consistently deviated from the set-point temperatures under OS1, whereas OS2 achieved supply–demand matching by adjusting them to the set-point temperatures according to individual room cooling demands. Finally, a data centre in Guangzhou was used to evaluate the performance of OS2 by comparing with historic operating results. Under OS2, energy consumption was reduced by 24.41 %–9.56 %, and the annual average PUE decreased from 1.271 to 1.229–1.254, when the terminal temperature difference of natural cooling source was 0–6 °C.</div></div>","PeriodicalId":8201,"journal":{"name":"Applied Thermal Engineering","volume":"273 ","pages":"Article 126553"},"PeriodicalIF":6.1,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143869119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A comprehensive method for exploratory data analysis and preprocessing the ASHRAE database for machine learning","authors":"Amir Rahmanparast ,&nbsp;Muhammed Milani ,&nbsp;Muhammet Camci ,&nbsp;Yakup Karakoyun ,&nbsp;Ozgen Acikgoz ,&nbsp;Ahmet Selim Dalkilic","doi":"10.1016/j.applthermaleng.2025.126556","DOIUrl":"10.1016/j.applthermaleng.2025.126556","url":null,"abstract":"<div><div>Thermal comfort prediction is crucial for building energy efficiency and occupant comfort. ML methods are commonly used to predict thermal comfort. This research presents a comprehensive process for exploring and preprocessing the ASHRAE Database, providing a substantial dataset comprising 107,583 records of thermal comfort observations to create ML algorithms that can estimate Fanger’s PMV. With the most detailed cleaning and preprocessing stages in the literature, which included the imputation of missing values and the management of outliers, the final dataset is reduced to 55,443 records for the analyses. For practical applications and indoor comfort assessments, its estimation offers significant advantages due to its speed, ease of use, and cost-effectiveness. This study aimed to investigate which parameters are important in Fanger’s PMV model and which subset of variables is best for variable selection using different feature selection and analysis methods. The T_a and T_r had a high correlation value of 0.92, indicating a robust link between these two variables. The study employed Feature importance, the SelectKBest, SHAP, P-box, and PDP analyses, which showed consistency and suggested condensing the first six elements into three, and also was validated with the Chinese Database with 41,977 entries. The study targeted three parameters: T_a, clo, and M, using less expensive and simple measurement devices. To evaluate the accuracy of the research performance, RF and SVM models were created based on these three parameters. The results indicated that they have the accuracies of 85% and 70%, respectively, which are far better than the conventional models.</div></div>","PeriodicalId":8201,"journal":{"name":"Applied Thermal Engineering","volume":"273 ","pages":"Article 126556"},"PeriodicalIF":6.1,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143869679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancement of film cooling effectiveness fed by internal crossflow using inlet expansion standard shaped hole","authors":"Mohamed Qenawy ,&nbsp;Tianyuan Liu ,&nbsp;Mona Ali ,&nbsp;Hengjie Guo","doi":"10.1016/j.applthermaleng.2025.126550","DOIUrl":"10.1016/j.applthermaleng.2025.126550","url":null,"abstract":"<div><div>Recent efforts have highlighted asymmetric and deteriorated coolant distribution behind crossflow-fed shaped holes, primarily due to in-hole vortical structures. In this study, inlet-expansion standard-shaped hole (IESSH) is proposed and investigated using large eddy simulation at channel-to-mainstream velocity ratio of <span><math><mrow><msub><mrow><mi>VR</mi></mrow><mrow><mi>ch</mi></mrow></msub></mrow></math></span> = 0.3–––0.7, coolant-to-mainstream velocity ratio of <span><math><mrow><msub><mrow><mi>VR</mi></mrow><mi>c</mi></msub></mrow></math></span> = 0.4–––1.2, and corresponding inlet velocity (channel-to-coolant) ratio of <span><math><mrow><msub><mrow><mi>VR</mi></mrow><mrow><mi>in</mi></mrow></msub></mrow></math></span> = 0.15–––1.75. Results show significant performance improvements for inlet-expansion at the windward, leeward, and forward hole edges. While the standard shaped hole serves as the baseline with degraded and biased coolant distribution, the IESSH design demonstrates symmetric coolant spreading and higher effectiveness. Specifically, the IESSH design exhibits wider and stronger vorticity at the entrance, enhancing coolant ingestion from both top and bottom channel flows, particularly at lower inlet velocities. Higher <span><math><mrow><msub><mrow><mi>VR</mi></mrow><mrow><mi>in</mi></mrow></msub></mrow></math></span> values lead to lower discharge coefficients, resulting in insufficient coolant and reduced effectiveness, whereas lower <span><math><mrow><msub><mrow><mi>VR</mi></mrow><mrow><mi>in</mi></mrow></msub></mrow></math></span> values feature higher discharge coefficients, improving coolant distribution. Notably, the IESSH design consistently shows higher discharge coefficients and cooling effectiveness, especially in transition and mixing regimes (<span><math><mrow><msub><mrow><mi>VR</mi></mrow><mrow><mi>in</mi></mrow></msub></mrow></math></span> &gt; 0.45). An operating range of 0.4 &lt; <span><math><mrow><msub><mrow><mi>VR</mi></mrow><mrow><mi>in</mi></mrow></msub></mrow></math></span> &lt; 1.5 is recommended for efficient performance, where the IESSH leverages enhanced coolant momentum. Very low <span><math><mrow><msub><mrow><mi>VR</mi></mrow><mrow><mi>in</mi></mrow></msub></mrow></math></span> (<span><math><mrow><msub><mrow><mi>VR</mi></mrow><mrow><mi>in</mi></mrow></msub></mrow></math></span> &lt; 0.25) values can lead to inefficiencies due to higher momentum and coolant lift-off. The findings provide valuable insights into the relationship between hole-inlet geometrical configurations and flow conditions, promoting advancements in cooling technology.</div></div>","PeriodicalId":8201,"journal":{"name":"Applied Thermal Engineering","volume":"273 ","pages":"Article 126550"},"PeriodicalIF":6.1,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143869121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel adaptive adjustment Kolmogorov-Arnold network for heat load prediction in district heating systems","authors":"Junda Zhu ,&nbsp;Junhong Yang ,&nbsp;Xuyang Cui ,&nbsp;Mengbo Peng ,&nbsp;Xinyue Liang","doi":"10.1016/j.applthermaleng.2025.126552","DOIUrl":"10.1016/j.applthermaleng.2025.126552","url":null,"abstract":"<div><div>Heat load prediction plays a crucial role in optimizing control and resource allocation within district heating systems. However, accurate heat load forecasting remains challenging due to its reliance on historical data, numerous influencing factors, and the complexity of predicting future demand. Traditional prediction models based on multilayer perceptrons (MLPs) often face issues related to scalability, interpretability, data requirements, and suboptimal long-term performance. In this study, we propose a novel adaptive adjustment Kolmogorov-Arnold Network (KAN) method for heat load forecasting. By analyzing changes in the shapes of spline functions, we enhance the model’s interpretability, allowing for better understanding of its responses to input features. Moreover, the model can dynamically adjust the positions of spline functions based on the distribution of input data, adapting its grid distribution to capture local features and nonlinear relationships more effectively. This enables the model to maintain strong performance even when data is limited, unlike traditional models which rely on linear weights. The proposed model was validated using real operational data from a campus heating system, consisting of 901 data points collected between November 15, 2022, and December 31, 2022. The model was compared against four advanced baseline models. Results show that as the time series length increases and data availability decreases, the KAN model consistently achieves an R2 value of 0.98. On both the 3-hour and 6-hour timescales, the KAN model outperforms the four traditional models, with maximum improvements in prediction accuracy of 16.8 % and 62.6 %, respectively. Additionally, MAE increased by 69.6 % and 79.2 %, while RMSE improved by 99.6 % and 99.5 %. These results demonstrate that the proposed method excels in terms of stability, reliability, and efficiency. The adaptive forecasting capability offers a promising direction for enhancing the performance and responsiveness of district heating systems.</div></div>","PeriodicalId":8201,"journal":{"name":"Applied Thermal Engineering","volume":"274 ","pages":"Article 126552"},"PeriodicalIF":6.1,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143869793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing thermo-hydraulic performance in flow boiling with hybrid nanofluids in double-layered wavy microchannel heat sink","authors":"Santanu Borah,&nbsp;Dipankar Bhanja","doi":"10.1016/j.applthermaleng.2025.126488","DOIUrl":"10.1016/j.applthermaleng.2025.126488","url":null,"abstract":"<div><div>This study uses water-based nanofluids to investigate the thermo-hydraulic performance of flow boiling in single-layer and double-layer wavy microchannels. A numerical analysis employing the Volume of Fluid-Discrete Phase Model (VOF-DPM) evaluates mono nanofluids (Al₂O₃, MWCNT, CuO, SiO₂, TiO₂) and hybrid nanofluids (MWCNT-TiO₂, Al₂O₃-CuO, SiO₂-CuO, MWCNT-Al₂O₃, SiO₂-TiO₂) across varying concentrations. Results identify 2 % nanoparticle concentration as optimal, with performance degradation at higher levels due to increased viscosity and nanoparticle agglomeration. MWCNT and MWCNT-TiO₂ hybrid nanofluids demonstrate superior heat transfer performance among the tested fluids. The double-layer microchannel configuration significantly enhances heat transfer, reduces hotspots, and ensures uniform heat distribution compared to single-layer designs. An optimal MWCNT: TiO₂ ratio of 1.5:0.5 achieves the highest Nusselt number and performance factor, leveraging the thermal conductivity of MWCNT and the wettability of TiO₂. Geometric parameters such as wavelength and amplitude further influence performance, with larger wavelengths and moderate amplitudes striking a balance between heat transfer and frictional losses. This work establishes double-layer wavy microchannels with MWCNT-TiO₂ hybrid nanofluids as a promising solution for advanced thermal management applications.</div></div>","PeriodicalId":8201,"journal":{"name":"Applied Thermal Engineering","volume":"273 ","pages":"Article 126488"},"PeriodicalIF":6.1,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143864573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing thermal management in concentrated photovoltaic cells using supercritical carbon dioxide","authors":"Shokoufeh Mizani ,&nbsp;Morteza Khoshvaght-Aliabadi ,&nbsp;Yong Tae Kang","doi":"10.1016/j.applthermaleng.2025.126555","DOIUrl":"10.1016/j.applthermaleng.2025.126555","url":null,"abstract":"<div><div>A key challenge for liquid-based cooling in concentrated photovoltaic systems is the significant rise in coolant temperature along the flow path, which degrades thermal performance and increases temperature non-uniformity. This study introduces supercritical carbon dioxide as a novel coolant for concentrated photovoltaic systems and compares its thermal performance with that of water under varying operating conditions. The cooling system incorporates a heat sink with four different channel sizes, assessed under medium, high, and ultrahigh concentration ratios. The results indicate that the supercritical carbon dioxide-based system outperforms the water-based system at medium concentration ratios, with greater benefits in smaller channels under high and ultrahigh concentration ratios. Furthermore, the hydraulic performance of the supercritical carbon dioxide-based system improves significantly in smaller channels. The supercritical carbon dioxide-based system lowers cell temperature and improves uniformity, reducing the maximum cell temperature by 4.3 K and temperature difference from 6.4 K to 2.6 K at high concentration ratios. At ultrahigh concentration ratios, smaller channels further enhance performance by increasing heat rejection per unit pumping power. In conclusion, considering the need for effective cooling at high and ultrahigh concentration ratios, along with uniform and reduced cell temperatures and low pumping power, replacing conventional liquid-based systems with supercritical carbon dioxide-based units offers notable efficiency advantages for next-generation concentrated photovoltaic systems.</div></div>","PeriodicalId":8201,"journal":{"name":"Applied Thermal Engineering","volume":"274 ","pages":"Article 126555"},"PeriodicalIF":6.1,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143869855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-physical field coupling model for thermal evolution analysis in coal mine goaf: a numerical investigation","authors":"Pengyu Zhang ,&nbsp;Xiaokun Chen","doi":"10.1016/j.applthermaleng.2025.126551","DOIUrl":"10.1016/j.applthermaleng.2025.126551","url":null,"abstract":"<div><div>Spontaneous coal combustion in goaf areas represents one of the most severe thermodynamic hazards in coal mining operations, characterized by its concealment, complex air leakage patterns, and challenging control measures. The accurate localization of high-temperature zones is crucial for mitigating potential spontaneous combustion risks. Unlike previous studies that focus primarily on hazardous area delineation, this study establishes a novel multi-physical field coupling model incorporating temperature, pressure, and gas concentration fields, with defined source terms for oxygen consumption and coal oxidation heat release, to evaluate the position and migration of high-temperature zones. The dynamic mesh technique is innovatively employed to simulate the temporal evolution of temperature fields during actual mining processes. A sensitivity analysis investigates the influence of key control factors, including face advance rate, ventilation volume, and residual coal thickness, on spontaneous combustion risks. Results indicate that increased ventilation flow leads to higher temperatures in high-temperature zones and greater distances from the working face; accelerating face advance rate effectively suppresses spontaneous combustion; while increased residual coal thickness causes high-temperature zones to migrate toward the working face. Based on these relationships, a multivariate function model is developed to predict the location of high-temperature zones with high accuracy. This predictive model provides theoretical guidance for mitigating spontaneous combustion hazards in goaf areas.</div></div>","PeriodicalId":8201,"journal":{"name":"Applied Thermal Engineering","volume":"273 ","pages":"Article 126551"},"PeriodicalIF":6.1,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143869630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}