Thermal Science and Engineering Progress最新文献

{"title":"Study on the difference between tectonic coal and raw coal oxidative spontaneous combustion","authors":"Hailin Jia ,&nbsp;Kaixuan Zhou ,&nbsp;Xiaoju Zhao ,&nbsp;Rongkun Pan ,&nbsp;Ligang Zheng ,&nbsp;Jiangkun Chao ,&nbsp;Daimin Hu ,&nbsp;Lin Li","doi":"10.1016/j.tsep.2025.103469","DOIUrl":"10.1016/j.tsep.2025.103469","url":null,"abstract":"<div><div>Industrial and elemental analysis experiments, low temperature liquid nitrogen adsorption experiments, TG/DSC comprehensive thermal analysis experiments and programmed temperature oxidation experiments were carried out on the fractured tectonic coal and raw coal in the same coal seam. The experimental results demonstrated that, compared with the raw coal, the tectonic coal exhibited an increase in pore volume and specific surface area, along with good pore connectivity. During the endothermic and exothermic reaction stages, the endothermic heat of the tectonic coal was lower than that of the raw coal. The gas production trends of the two types of coal intersected with the curves of the consumption rates of CO and oxygen. Before the intersection temperature, the gas production rate and oxygen consumption rate of the tectonic coal were higher than those of the raw coal, while after that, the gas production rate and oxygen consumption rate of the raw coal were higher. Based on the growth curves of CO and C₂H₄ gas production, the temperatures of the tectonic coal and the raw coal were different at the end of the slow oxidation stage and the beginning of the fast oxidation stage. Generally speaking, there are significant differences between tectonic coal and raw coal in physical and chemical structure and oxidation spontaneous combustion characteristics. In the slow oxidation stage, the oxidizing ability of tectonic coal is stronger, while the raw coal reacts more fiercely in the rapid oxidation stage.</div></div>","PeriodicalId":23062,"journal":{"name":"Thermal Science and Engineering Progress","volume":"60 ","pages":"Article 103469"},"PeriodicalIF":5.1,"publicationDate":"2025-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143580243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Motion training recognition based on thermal radiation imaging system and object detection: Human motion thermal image monitoring","authors":"Jie Zhao,&nbsp;Chang Liu,&nbsp;Huisheng Hou","doi":"10.1016/j.tsep.2025.103467","DOIUrl":"10.1016/j.tsep.2025.103467","url":null,"abstract":"<div><div>A human motion monitoring method based on thermal radiation image system and target detection technology is developed. The heat distribution of human body in motion is captured by thermal image, and the real-time recognition and analysis of human motion is realized by combining image processing and target detection algorithm. A complete set of thermal radiation optical image monitoring system is designed in this study. A high-sensitivity thermal imaging camera is used to capture the thermal radiation images of the human body in the process of motion, and these images are then transmitted to the data acquisition unit for preliminary data collation and storage. The image processing module preprocesses the acquired thermal images, and the preprocessed images are fed into the object detection algorithm, which is based on the deep learning framework and can recognize and classify different movements of the human body. The thermal radiation image monitoring system can accurately capture the thermal image of the human body in different motion states, and identify the movement type of the athlete in real time through the target detection algorithm. The system has a strong ability to capture the details of actions, and can identify the beginning, progress and end stages of actions. Compared with traditional monitoring methods, the thermal radiation light image monitoring system has obvious advantages in terms of data accuracy and real-time performance. This method can not only provide high precision movement recognition, but also has the advantages of non-contact and real-time monitoring, which greatly improves the efficiency and accuracy of sports training monitoring.</div></div>","PeriodicalId":23062,"journal":{"name":"Thermal Science and Engineering Progress","volume":"60 ","pages":"Article 103467"},"PeriodicalIF":5.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence and robots promote energy management and financial cost optimization in hybrid manufacturing enterprises","authors":"Chang Miao,&nbsp;Yan Xue","doi":"10.1016/j.tsep.2025.103464","DOIUrl":"10.1016/j.tsep.2025.103464","url":null,"abstract":"<div><div>Against the backdrop of global environmental pressures and energy shortages, mixed manufacturing enterprises are facing a dual challenge of improving energy efficiency and reducing production costs. Currently, many enterprises are seeking to achieve more efficient production and management through automation and intelligent means. The aim of this study is to construct a comprehensive model that optimizes the energy management and financial costs of hybrid manufacturing enterprises through industrial robots and artificial intelligence technology, enhancing their economic benefits and market competitiveness. This article reviews relevant work and analyzes the application of industrial robots in the manufacturing process, including modeling of robotic arm motion, machining scheduling, and manufacturing reliability. Subsequently, an energy management model based on thermal science was designed and its effectiveness was evaluated, combined with energy-saving diagnostic tools to assess the actual effectiveness of energy management. Finally, how artificial intelligence technology can optimize financial costs was discussed, and a series of specific optimization strategies were proposed. Research has found that by applying advanced robotic arm motion modeling technology and intelligent scheduling algorithms, hybrid manufacturing enterprises can significantly improve production efficiency and reduce energy consumption. The designed energy management model effectively evaluates the energy usage of enterprises and improves energy utilization efficiency through energy-saving diagnostic measures. By combining artificial intelligence with financial cost optimization strategies, the financial performance of enterprises has also been significantly improved.</div></div>","PeriodicalId":23062,"journal":{"name":"Thermal Science and Engineering Progress","volume":"60 ","pages":"Article 103464"},"PeriodicalIF":5.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Explainable AI in thermal modelling enhancing precision in thermal gradient monitoring for additive manufacturing using LSTM networks","authors":"Ajmeera Kiran ,&nbsp;Harish Kumar ,&nbsp;S. Sivanandam ,&nbsp;P.Gururama Senthilvel ,&nbsp;R.V.S. Lalitha ,&nbsp;C.S. Preetham Reddy","doi":"10.1016/j.tsep.2025.103465","DOIUrl":"10.1016/j.tsep.2025.103465","url":null,"abstract":"<div><div>The paper introduces an unprecedented technique for enhancing the measurement accuracy of thermal gradients in additive manufacturing by applying Explainable Artificial Intelligence (XAI) combined with Long Short-Term Memory (LSTM) networks. Temperature control during fabricating of thermoplastic and thermosetting polymer composites remains fundamental since it dictates the resulting material properties, structural integrity, and layer bonding. Our LSTM model predicts temperature changes during printing operations, providing stable manufacturing processes by reducing common defects, including warping deformation delamination and inconsistent curing. The framework now includes Layer-wise Relevance Propagation (LRP) and SHapley Additive exPlanations (SHAP) techniques to analyse crucial elements affecting temperature distribution.</div><div>The thermal model shows 0.183 °C MAE and 0.224 °C RMSE values, delivering 46.5 % better precision than previous thermal modelling approaches. Evaluation tests report system adjustments to take place after 86 ms during thermal perturbations and reach full stabilisation by 2.3 s. Its 97.3 % prediction accuracy rate and decision consistency make it dependable for optimal temperature processing control. The research creates a connection between automated thermal modelling and manufacturing through additive technology which leads to better process management together with material efficiency as well as environmentally responsible creation of polymer parts. The introduced framework shows great promise for use in the aerospace, automotive and biomedical sectors of additive manufacturing, which demand accurate thermal control.</div></div>","PeriodicalId":23062,"journal":{"name":"Thermal Science and Engineering Progress","volume":"60 ","pages":"Article 103465"},"PeriodicalIF":5.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exergy, emergoeconomic and emergoenvironmental analysis of ocean thermal energy conversion (OTEC) systems: An integration with solar, wind, and thermoelectric energy production","authors":"Hadi Kamfar ,&nbsp;Abolfazl Shojaeian ,&nbsp;Jaber Yousefi Seyf ,&nbsp;Najmeh Hajialigol","doi":"10.1016/j.tsep.2025.103459","DOIUrl":"10.1016/j.tsep.2025.103459","url":null,"abstract":"<div><div>Decentralized multi-generation systems using renewable energy sources have great potential for combating climate change and promoting sustainable development. This study models and analyzes an integrated solar-assisted system consisting of an organic Rankine cycle, a wind turbine, and a thermoelectric unit using EES software. Performance is evaluated through exergy, emergoeconomic, and emergoenvironmental analyses. The economic emergy coefficients are steam turbine (59.93%), evaporator (1.66%), working fluid pump 1 (37.25%), warm sea water pump2 (86.86%), cold sea water pump3 (86.97%), solar collector (100%), wind turbine (100%), and thermoelectric unit (100%). Environmental emergy coefficients are steam turbine (58.56%), evaporator (87.15%), working fluid pump 1 (48.97%), warm sea water pump2 (8.39%), cold sea water pump3 (7.68%), solar collector (100%), wind turbine (77.57%), and thermoelectric unit (100%). The system also reduces carbon dioxide emissions by 1.34 tons, highlighting the technical, economic, and environmental benefits of renewable energy integration.</div></div>","PeriodicalId":23062,"journal":{"name":"Thermal Science and Engineering Progress","volume":"60 ","pages":"Article 103459"},"PeriodicalIF":5.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143580248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of flow resistance on the operational stability of two-phase thermosyphon loop with different working fluids","authors":"Zhen Tong,&nbsp;Zhaolong Zhu,&nbsp;Wencheng Wang,&nbsp;Zekun Han","doi":"10.1016/j.tsep.2025.103463","DOIUrl":"10.1016/j.tsep.2025.103463","url":null,"abstract":"<div><div>When a two-phase thermosyphon loop (TPTL) operates in an oscillatory state, its service life may be shortened due to mechanical impacts. Limited research exists on improving TPTL stability. This study used a needle valve to adjust the flow resistance in the downcomer of a TPTL to analyze its impact on the operational stability of CO₂ and R134a TPTLs. Our research revealed that the operating states of the two TPTLs are affected differently by flow resistance. The fluctuating operation of the CO₂ TPTL is caused by the periodic changes in the flow regime within the loop. An increase in flow resistance led to higher circulating driving force by increasing vapor quality in the riser and decreasing vapor quality in the downcomer. This suppressed the operational instability of the CO₂ TPTL. However, the unstable operation of R134a TPTL resulted from the inherent instability of the stirred flow in the riser. Therefore, the change in flow resistance has almost no effect on the operational stability of the R134a TPTL. The findings of this study provide new insights for improving the operational stability of the CO₂ TPTL.</div></div>","PeriodicalId":23062,"journal":{"name":"Thermal Science and Engineering Progress","volume":"60 ","pages":"Article 103463"},"PeriodicalIF":5.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cell thermal modeling and muscle oxygenation measurement in sports based on thermal radiation infrared spectroscopy and sensors","authors":"Hong Yang ,&nbsp;Qiang Gao","doi":"10.1016/j.tsep.2025.103466","DOIUrl":"10.1016/j.tsep.2025.103466","url":null,"abstract":"<div><div>Cell thermal modeling and muscle oxygenation are key indicators to evaluate athletes’ physical fitness and fatigue status. Traditional measurement methods often rely on invasive techniques, which not only inconvenience athletes, but also affect their performance. The aim of this study is to develop a non-invasive method based on thermal radiation infrared spectroscopy and sensor technology. The thermal radiation infrared spectroscopy technology and high sensitivity sensor are used to collect the thermal radiation images of athletes in different sports states. Image processing technology was used to analyze the acquired thermal radiation images, and the characteristic parameters related to cell thermal modeling and muscle oxygenation were extracted. In order to verify the effectiveness of the proposed method, we conducted a comparison experiment with the traditional intrusive measurement method. Through comparative analysis, the consistency between the measurement results based on thermal radiation infrared spectroscopy and the traditional method is evaluated. The results show that the measurement method based on thermal radiation infrared spectroscopy and sensor technology can effectively monitor cell thermal modeling and muscle oxygenation. Compared with the traditional intrusive method, this method has advantages in both accuracy and real-time performance. The thermal radiation images clearly show the heat distribution of athletes in different sports states, and the characteristic parameters obtained through image analysis are closely related to the physical state of athletes.</div></div>","PeriodicalId":23062,"journal":{"name":"Thermal Science and Engineering Progress","volume":"60 ","pages":"Article 103466"},"PeriodicalIF":5.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 evaluation of modified wick belt configuration in rotating wick solar stills using different wick materials","authors":"Gokulnath R,&nbsp;E. Sam Elijah,&nbsp;Rohinikumar Bandaru","doi":"10.1016/j.tsep.2025.103457","DOIUrl":"10.1016/j.tsep.2025.103457","url":null,"abstract":"<div><div>Desalination is the process of removing dissolved salts from saline water. In this work, experimental investigations were conducted on different single slope rotating wick solar stills (RWSS) for improved performance. Water evaporation test was conducted to select the suitable wick materials for the system and the selected wick materials were subjected to water absorption and characterization study. The experiments were conducted on solar still with two different wick configurations, namely, LC rotating wick solar still (LCRWSS) and newly established inclined rotating wick solar still (IRWSS) with different wick materials, and solar still without wick (SSWW). The effect of glass cooling and external reflectors on the performance of the still were also studied. The maximum productivity and efficiency of the system were obtained for jute fabric as the wick material. The daily thermal efficiencies of LCRWSS and IRWSS, with jute wick, are 52.8 % and 57.3 % respectively which are higher than the efficiency of solar still without wick (SSWW), whose efficiency is 22.7 %. IRWSS has more productivity as well as efficiency than LCRWSS for all the wick materials considered. The efficiency of IRWSS increased to 63.8 % with the incorporation of external reflectors. The maximum efficiency of 74.3 % is obtained for IRWSS with reflectors and glass cooling. The contribution to productivity was found to be maximum by the top glass of the still compared to other sides. The distillate cost per litre obtained for SSWW and IRWSS are 0.094 $ and 0.0547 $, respectively.</div></div>","PeriodicalId":23062,"journal":{"name":"Thermal Science and Engineering Progress","volume":"60 ","pages":"Article 103457"},"PeriodicalIF":5.1,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 chemical reactor network approach for a gas-assisted iron dust flame in a laboratory-scale combustor","authors":"Sören Dübal ,&nbsp;Pascal Steffens ,&nbsp;Johannes Mich ,&nbsp;Daniel Braig ,&nbsp;Antje Vahl ,&nbsp;Leon L. Berkel ,&nbsp;Arne Scholtissek ,&nbsp;Tiziano Faravelli ,&nbsp;Christian Hasse ,&nbsp;Hendrik Nicolai ,&nbsp;Sandra Hartl","doi":"10.1016/j.tsep.2025.103435","DOIUrl":"10.1016/j.tsep.2025.103435","url":null,"abstract":"<div><div>Metal powders demonstrate promising performance when reacting with oxygen in laboratory-scale reactors, releasing the chemically stored energy as heat. To scale up this technology, chemical reactor network (CRN) modeling serves as a critical tool to bridge the gap between laboratory experiments and real-world applications. In this work, a multi-phase CRN is derived to analyze the iron oxidation and pollutant formation in a novel methane-assisted iron dust flame in a laboratory-scale combustor. State-of-the-art single particle oxidation models are employed to describe the conversion of iron particles, while gas phase combustion is modeled with a detailed kinetic mechanism within fully coupled reactors. The approach is validated for single particle combustion using the solid-gas plug flow reactor. It is demonstrated, that a reactor network model with four solid-gas perfectly stirred reactors accurately reproduces the flame structure of laminar iron flames. Subsequently, both ideal reactor models are combined in a multi-phase reactor network to analyze iron oxidation, evaporation and NOx formation in the swirl burner. The CRN design is based on a recent high-fidelity Large Eddy Simulation. The monodisperse description of the iron suspension within the CRN reveals that different initial particle diameters significantly influence the estimated evaporated mass, ranging from less than 0.5% for <span><math><mrow><mn>20</mn><mspace></mspace><mi>μ</mi><mi>m</mi></mrow></math></span> particles to approximately 4% for <span><math><mrow><mn>5</mn><mspace></mspace><mi>μ</mi><mi>m</mi></mrow></math></span> particles, while the overall iron conversion remains largely unaffected. Furthermore, sensitivity analyses highlight the critical role of the oxygen distribution and local gas temperatures within the reactor to effectively control NOx formation and potential nano-oxide emissions during iron combustion.</div></div>","PeriodicalId":23062,"journal":{"name":"Thermal Science and Engineering Progress","volume":"60 ","pages":"Article 103435"},"PeriodicalIF":5.1,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Parametric image design and visualization simulation based on infrared thermal image fusion algorithm","authors":"Guangyi Tang ,&nbsp;Xiaozhan Ma","doi":"10.1016/j.tsep.2025.103462","DOIUrl":"10.1016/j.tsep.2025.103462","url":null,"abstract":"<div><div>Infrared thermal image can provide intuitive information about the surface temperature distribution of objects, but the traditional infrared thermal image processing methods have problems such as low resolution and lack of detailed information, which limits its application in more complex scenes. This paper presents a parametric image design and visualization simulation method based on infrared thermal image fusion algorithm. This paper studies the use of highly sensitive infrared thermal imager to collect thermal image data of target objects under different conditions, and preprocesses the collected infrared thermal images. An algorithm based on multi-scale transformation and image fusion is designed to effectively fuse multiple infrared thermal image data sources, and a parametric design mechanism is introduced to allow users to adjust fusion parameters according to actual application scenarios. In this way, users can customise the generation of thermal images that meet specific needs. Through visual simulation technology, the fusion thermal radiation image is displayed in an intuitive way. In the simulation process, different environmental conditions and object characteristics can be simulated to evaluate the performance and applicability of thermal images in different scenarios. The results show that compared with the traditional method, the thermal radiation image generated by this method has a great improvement in resolution and detail performance. The proposed method not only improves the thermal image quality, but also enhances its applicability and flexibility through parametric design.</div></div>","PeriodicalId":23062,"journal":{"name":"Thermal Science and Engineering Progress","volume":"60 ","pages":"Article 103462"},"PeriodicalIF":5.1,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}