Pub Date : 2025-04-02DOI: 10.1016/j.csite.2025.106079
Yin Liu , Shijie Deng , Hu Wen , Shangrong Jiang , Jun Guo , Dailin Li , Changming Chen
It is important to accurately calculate coal spontaneous combustion (CSC) characteristic parameters for preventing and controlling coal fire disasters. Previous studies have shown that the process of CSC has nonlinear variation characteristics with temperature and O2 concentration. Based on this, non-linear improved model of coal oxidation characteristic parameters is constructed in this study, and compared with the linear model calculation case. The results show a power function non-linear relation of coal oxidation characteristic parameters with O2 concentration. The improved model can more accurately calculate the O2 consumption rate (OCR), gas formation rate (GFR) and heat release intensity (HRI) in CSC. In contrast, Linear model can more conveniently and quickly obtain the characteristics of coal oxidation. The transcendental equation dichotomy solution of the reaction order considers the actual attenuation characteristics of O2 in coal sample at the airflow direction, and the calculation result is more accurate. The average O2 concentration hypothesis method can be used to calculate the reaction order more quickly, and the results are consistent. With an increase in temperature, the O2 content sensitivity of the oxidation characteristic parameters first decreases and then increases. These findings have theoretical value for preventing and controlling coal fire disasters.
{"title":"Nonlinear improvement of mathematical model of coal oxidation heat release and case study of oxygen concentration effect","authors":"Yin Liu , Shijie Deng , Hu Wen , Shangrong Jiang , Jun Guo , Dailin Li , Changming Chen","doi":"10.1016/j.csite.2025.106079","DOIUrl":"10.1016/j.csite.2025.106079","url":null,"abstract":"<div><div>It is important to accurately calculate coal spontaneous combustion (CSC) characteristic parameters for preventing and controlling coal fire disasters. Previous studies have shown that the process of CSC has nonlinear variation characteristics with temperature and O<sub>2</sub> concentration. Based on this, non-linear improved model of coal oxidation characteristic parameters is constructed in this study, and compared with the linear model calculation case. The results show a power function non-linear relation of coal oxidation characteristic parameters with O<sub>2</sub> concentration. The improved model can more accurately calculate the O<sub>2</sub> consumption rate (OCR), gas formation rate (GFR) and heat release intensity (HRI) in CSC. In contrast, Linear model can more conveniently and quickly obtain the characteristics of coal oxidation. The transcendental equation dichotomy solution of the reaction order considers the actual attenuation characteristics of O<sub>2</sub> in coal sample at the airflow direction, and the calculation result is more accurate. The average O<sub>2</sub> concentration hypothesis method can be used to calculate the reaction order more quickly, and the results are consistent. With an increase in temperature, the O<sub>2</sub> content sensitivity of the oxidation characteristic parameters first decreases and then increases. These findings have theoretical value for preventing and controlling coal fire disasters.</div></div>","PeriodicalId":9658,"journal":{"name":"Case Studies in Thermal Engineering","volume":"70 ","pages":"Article 106079"},"PeriodicalIF":6.4,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143777632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-02DOI: 10.1016/j.csite.2025.106080
Reving Masoud Abdulhakeem , Ali Kircay , Rakan Khalil Antar
This study investigates the design and performance of an asymmetrical 49-level cascaded inverter specifically developed for renewable energy applications. The inverter's operation is analyzed under three distinct scenarios: utilizing DC battery sources configured in a per-unit voltage ratio (1:2:7:14), employing DC batteries with actual voltage levels (40:80:280:560 V), and replacing the DC sources with photovoltaic (PV) modules. The simulation results demonstrate the inverter's exceptional capability to produce high-quality sinusoidal output voltage and current waveforms with significantly low harmonic distortion. In the per-unit voltage configuration, the inverter achieves an RMS voltage (VoRMS) of 16.9719V and an RMS current (IoRMS) of 1.0569A, with a total harmonic distortion of 0.71216 % for voltage (THDVo) and 0.093319 % for current (THDIo). When configured with actual voltage levels, the system delivers VoRMS = 679.0492V and IoRMS = 4.265A, with THDVo of 0.71227 % and THDIo of 0.16719 %. With PV modules system, the inverter achieves VoRMS = 692.7293V and IoRMS = 43.1367A, and the THD values for output voltage and current were 1.2926 % and 0.33963 %, respectively. These results highlight the inverter's versatility and efficiency in providing high-quality power output while maintaining minimal harmonic distortion, making it a promising solution for modern renewable energy systems and industrial applications.
{"title":"Design an asymmetrical 49-level inverter fed by battery and PV energy sources","authors":"Reving Masoud Abdulhakeem , Ali Kircay , Rakan Khalil Antar","doi":"10.1016/j.csite.2025.106080","DOIUrl":"10.1016/j.csite.2025.106080","url":null,"abstract":"<div><div>This study investigates the design and performance of an asymmetrical 49-level cascaded inverter specifically developed for renewable energy applications. The inverter's operation is analyzed under three distinct scenarios: utilizing DC battery sources configured in a per-unit voltage ratio (1:2:7:14), employing DC batteries with actual voltage levels (40:80:280:560 V), and replacing the DC sources with photovoltaic (PV) modules. The simulation results demonstrate the inverter's exceptional capability to produce high-quality sinusoidal output voltage and current waveforms with significantly low harmonic distortion. In the per-unit voltage configuration, the inverter achieves an RMS voltage (<em>V</em>o<sub><em>RMS</em></sub>) of 16.9719V and an RMS current (<em>I</em>o<sub><em>RMS</em></sub>) of 1.0569A, with a total harmonic distortion of 0.71216 % for voltage (THD<sub><em>V</em>o</sub>) and 0.093319 % for current (THD<sub><em>I</em>o</sub>). When configured with actual voltage levels, the system delivers <em>V</em>o<sub><em>RMS</em></sub> = 679.0492V and <em>I</em>o<sub><em>RMS</em></sub> = 4.265A, with THD<sub><em>V</em>o</sub> of 0.71227 % and THD<sub><em>I</em>o</sub> of 0.16719 %. With PV modules system, the inverter achieves <em>V</em>o<sub><em>RMS</em></sub> = 692.7293V and <em>I</em>o<sub><em>RMS</em></sub> = 43.1367A, and the THD values for output voltage and current were 1.2926 % and 0.33963 %, respectively. These results highlight the inverter's versatility and efficiency in providing high-quality power output while maintaining minimal harmonic distortion, making it a promising solution for modern renewable energy systems and industrial applications.</div></div>","PeriodicalId":9658,"journal":{"name":"Case Studies in Thermal Engineering","volume":"70 ","pages":"Article 106080"},"PeriodicalIF":6.4,"publicationDate":"2025-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143783761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-01DOI: 10.1016/j.csite.2025.106075
Hüseyin Zahit Demirağ
This computational investigation primarily explores the impact of three factors on thermo-hydraulic performance: the dimensionless distance ratio (z/L = −0.1 to 0.5), Heated Surface [HS] orientation (HS-Up, HS-Down), and Delta Winglet [DW] positioning (DW-PU, DW-PD). The numerical model applies steady-state RANS and energy equations with the (SST) k-ω turbulence model, assuming incompressibility, constant thermophysical properties, and ignoring radiation and buoyancy effects. A comprehensive analysis of resulting data reveals that the DW-PD configuration yields lower Darcy friction factors across all z/L ratios compared to DW-PU layout, exhibiting reductions of 6.35 % at z/L = −0.1 and 3.49 % at z/L = 0.5. The DW-PD setup with HS-Down demonstrates the best thermal performance among all configurations and dimensionless distance ratios (except z/L = −0.1). Moreover, the optimum dimensionless distance ratios for achieving the highest Nusselt numbers are determined as z/L = 0.1 for HS-Up and z/L = 0.2 for HS-Down under both configurations. The computational data indicates that the difference between the maximum and minimum Thermal Enhancement Factor [TEF] is approximately 23.78 % and the highest TEF = 1.25, is achieved with the utilization of DW-PD at z/L = 0.2 for HS-Down at Re = 5000. This study underscores the critical significance of examining all these parameters to attain the highest thermal performance.
{"title":"The impact of vortex generator positioning and heated surface orientation on thermal performance and flow dynamics in asymmetrically heated duct","authors":"Hüseyin Zahit Demirağ","doi":"10.1016/j.csite.2025.106075","DOIUrl":"10.1016/j.csite.2025.106075","url":null,"abstract":"<div><div>This computational investigation primarily explores the impact of three factors on thermo-hydraulic performance: the dimensionless distance ratio (<em>z/L</em> = −0.1 to 0.5), Heated Surface [HS] orientation (HS-Up, HS-Down), and Delta Winglet [DW] positioning (DW-PU, DW-PD). The numerical model applies steady-state RANS and energy equations with the (SST) k-<em>ω</em> turbulence model, assuming incompressibility, constant thermophysical properties, and ignoring radiation and buoyancy effects. A comprehensive analysis of resulting data reveals that the DW-PD configuration yields lower Darcy friction factors across all <em>z/L</em> ratios compared to DW-PU layout, exhibiting reductions of 6.35 % at <em>z/L</em> = −0.1 and 3.49 % at <em>z/L</em> = 0.5. The DW-PD setup with HS-Down demonstrates the best thermal performance among all configurations and dimensionless distance ratios (except <em>z/L</em> = −0.1). Moreover, the optimum dimensionless distance ratios for achieving the highest Nusselt numbers are determined as <em>z/L</em> = 0.1 for HS-Up and <em>z/L</em> = 0.2 for HS-Down under both configurations. The computational data indicates that the difference between the maximum and minimum Thermal Enhancement Factor [TEF] is approximately 23.78 % and the highest TEF = 1.25, is achieved with the utilization of DW-PD at <em>z/L</em> = 0.2 for HS-Down at Re = 5000. This study underscores the critical significance of examining all these parameters to attain the highest thermal performance.</div></div>","PeriodicalId":9658,"journal":{"name":"Case Studies in Thermal Engineering","volume":"70 ","pages":"Article 106075"},"PeriodicalIF":6.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143767850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-28DOI: 10.1016/j.csite.2025.106043
Ruijia Yuan, Fan Shi, Azher M. Abed, Mohamed Shaban, Sarminah Samad, Ahmad Almadhor, Barno Abdullaeva, Mouloud Aoudia, Salem Alkhalaf, Samah G. Babiker
Innovative heat recovery, CO2 capture, and energy storage methodologies are pivotal for developing sustainable and eco-friendly solutions for the energy sector. Hence, this study proposes implementing an oxyfuel combustion process for a biogas power plant, modified by an innovative heat recovery method and a CO2 capture-liquefaction technique. Furthermore, the design incorporates high-temperature water electrolysis to produce hydrogen, which is then introduced into a hydrogen liquefaction process utilizing a Claude cycle for adequate long-term storage. The research employs thermodynamic, exergoeconomic, and net present value assessments, accompanied by an extensive parametric study and optimization process. Hence, a machine learning algorithm is implemented using artificial neural networks combined with the NSGA-II method for multi-criteria optimization, focusing on exergy efficiency, net present value, and products' sum unit cost as objective functions. The implemented optimization reduces the optimization time to under 30 min, which is significantly more efficient than traditional heuristic techniques, which typically require several hours for similar systems. This optimization framework is highly applicable to both industrial and district energy systems. This approach enhances predictive analytics and streamlines resource management. In industrial environments, it effectively optimizes energy use and production processes by examining various operational factors, which leads to cost reductions and improved efficiency via predictive maintenance and cohesive energy strategies. The optimal outcomes reveal the mentioned objective functions' values at 47.22 %, 58.73 M$, and 33.53 $/GJ, respectively. Under these optimal conditions, liquid carbon dioxide and liquid hydrogen outputs are quantified at 4931 lit/h and 1848 lit/h, respectively. Finally, the proposed system can omit CO2 emissions by 1.36 kg/kWh under optimal conditions, which reflects a 5.60 % better performance than the base case. Furthermore, the products’ sum unit cost decreases by 3.09 %, indicating efficient cost savings linked to the products.
{"title":"Numerical thermodynamic-economic study and machine learning-based optimization of an innovative biogas-driven integrated power plant combined with sustainable liquid CO2 and liquid H2 production-storage processes","authors":"Ruijia Yuan, Fan Shi, Azher M. Abed, Mohamed Shaban, Sarminah Samad, Ahmad Almadhor, Barno Abdullaeva, Mouloud Aoudia, Salem Alkhalaf, Samah G. Babiker","doi":"10.1016/j.csite.2025.106043","DOIUrl":"https://doi.org/10.1016/j.csite.2025.106043","url":null,"abstract":"Innovative heat recovery, CO<ce:inf loc=\"post\">2</ce:inf> capture, and energy storage methodologies are pivotal for developing sustainable and eco-friendly solutions for the energy sector. Hence, this study proposes implementing an oxyfuel combustion process for a biogas power plant, modified by an innovative heat recovery method and a CO<ce:inf loc=\"post\">2</ce:inf> capture-liquefaction technique. Furthermore, the design incorporates high-temperature water electrolysis to produce hydrogen, which is then introduced into a hydrogen liquefaction process utilizing a Claude cycle for adequate long-term storage. The research employs thermodynamic, exergoeconomic, and net present value assessments, accompanied by an extensive parametric study and optimization process. Hence, a machine learning algorithm is implemented using artificial neural networks combined with the NSGA-II method for multi-criteria optimization, focusing on exergy efficiency, net present value, and products' sum unit cost as objective functions. The implemented optimization reduces the optimization time to under 30 min, which is significantly more efficient than traditional heuristic techniques, which typically require several hours for similar systems. This optimization framework is highly applicable to both industrial and district energy systems. This approach enhances predictive analytics and streamlines resource management. In industrial environments, it effectively optimizes energy use and production processes by examining various operational factors, which leads to cost reductions and improved efficiency via predictive maintenance and cohesive energy strategies. The optimal outcomes reveal the mentioned objective functions' values at 47.22 %, 58.73 M$, and 33.53 $/GJ, respectively. Under these optimal conditions, liquid carbon dioxide and liquid hydrogen outputs are quantified at 4931 lit/h and 1848 lit/h, respectively. Finally, the proposed system can omit CO<ce:inf loc=\"post\">2</ce:inf> emissions by 1.36 kg/kWh under optimal conditions, which reflects a 5.60 % better performance than the base case. Furthermore, the products’ sum unit cost decreases by 3.09 %, indicating efficient cost savings linked to the products.","PeriodicalId":9658,"journal":{"name":"Case Studies in Thermal Engineering","volume":"67 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143724020","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}
Honeycomb volumetric solar receivers have emerged as promising candidates for concentrating solar power applications because of their thermal and mechanical properties, enabling the efficient heating of fluids. Despite their potential, challenges remain in optimizing channel design and operating conditions to enhance thermodynamic performance. This study identifies design and operating configurations that maximize the thermodynamic performance and structural reliability of silicon carbide honeycomb volumetric solar receivers, focusing on thermal efficiency and factor of safety. We adopted a multi-objective optimization approach by integrating computational fluid dynamics, heat transfer, and thermal stress analysis. To streamline computational efforts, the Taguchi method was employed, reducing the number of required simulations while maintaining a relative error below 5 %. A critical mass flow to absorbed power ratio of 5 × 10−6 (kg/s)/W was identified, beyond which thermal efficiency stabilizes, providing practical guidance for operational optimization. The optimal configuration achieved a thermal efficiency of 89.3 % and a factor of safety of 87.3 %, with a channel width of 3 mm, a thickness of 0.3 mm, an outlet static pressure of −70 Pa, and a radiation flux of 650 kW/m2. These findings establish a robust framework for optimizing honeycomb receivers, addressing thermal and structural performance while maintaining simplicity in manufacturing processes.
{"title":"Multi-objective optimization on thermo-structural performance of honeycomb absorbers for concentrated solar power systems","authors":"Masoud Behzad , Sébastien Poncet , Cristóbal Sarmiento-Laurel","doi":"10.1016/j.csite.2025.106068","DOIUrl":"10.1016/j.csite.2025.106068","url":null,"abstract":"<div><div>Honeycomb volumetric solar receivers have emerged as promising candidates for concentrating solar power applications because of their thermal and mechanical properties, enabling the efficient heating of fluids. Despite their potential, challenges remain in optimizing channel design and operating conditions to enhance thermodynamic performance. This study identifies design and operating configurations that maximize the thermodynamic performance and structural reliability of silicon carbide honeycomb volumetric solar receivers, focusing on thermal efficiency and factor of safety. We adopted a multi-objective optimization approach by integrating computational fluid dynamics, heat transfer, and thermal stress analysis. To streamline computational efforts, the Taguchi method was employed, reducing the number of required simulations while maintaining a relative error below 5 %. A critical mass flow to absorbed power ratio of 5 × 10<sup>−6</sup> (kg/s)/W was identified, beyond which thermal efficiency stabilizes, providing practical guidance for operational optimization. The optimal configuration achieved a thermal efficiency of 89.3 % and a factor of safety of 87.3 %, with a channel width of 3 mm, a thickness of 0.3 mm, an outlet static pressure of −70 Pa, and a radiation flux of 650 kW/m<sup>2</sup>. These findings establish a robust framework for optimizing honeycomb receivers, addressing thermal and structural performance while maintaining simplicity in manufacturing processes.</div></div>","PeriodicalId":9658,"journal":{"name":"Case Studies in Thermal Engineering","volume":"70 ","pages":"Article 106068"},"PeriodicalIF":6.4,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143746817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-26DOI: 10.1016/j.csite.2025.106060
Fanchen Kong , Mingxuan Huang , Shuo Zhang , Zhouhang Hu , Shanquan Liu , Guifang Wu , Mingsheng Tang , Huiming Zou , Changqing Tian
CO2 linear compressors are critical for sustainable and energy-efficient refrigeration systems due to the eco-friendly properties of CO2. However, the unique characteristics of CO2 compressors introduce significant challenges in piston stroke control. The large pressure difference between suction and discharge conditions requires high operating currents to overcome gas forces, resulting in substantial piston offsets. These offsets interact with nonlinear parameter variations, elevating the risk of resonant frequency shifts and potential valve collisions. Accurate piston stroke measurement is essential to address these issues, but traditional methods relying on displacement sensors are costly. This study presents an innovative artificial neural network (ANN) method for sensorless piston stroke measurement in CO2 linear compressors. The proposed model requires only six inputs: voltage, current, frequency, active power, suction pressure, and discharge pressure. Optimized ANN parameters enable high prediction accuracy, with an average R2 of 0.955, RMSE of 0.206, and an average error of 2.24 % on the testing set. Furthermore, a simple stroke adjustment method based on the ANN model is proposed, allowing for effective stroke control and natural frequency calculation.
{"title":"Artificial neural network-based online stroke detection for CO2 linear refrigeration compressors","authors":"Fanchen Kong , Mingxuan Huang , Shuo Zhang , Zhouhang Hu , Shanquan Liu , Guifang Wu , Mingsheng Tang , Huiming Zou , Changqing Tian","doi":"10.1016/j.csite.2025.106060","DOIUrl":"10.1016/j.csite.2025.106060","url":null,"abstract":"<div><div>CO<sub>2</sub> linear compressors are critical for sustainable and energy-efficient refrigeration systems due to the eco-friendly properties of CO<sub>2</sub>. However, the unique characteristics of CO<sub>2</sub> compressors introduce significant challenges in piston stroke control. The large pressure difference between suction and discharge conditions requires high operating currents to overcome gas forces, resulting in substantial piston offsets. These offsets interact with nonlinear parameter variations, elevating the risk of resonant frequency shifts and potential valve collisions. Accurate piston stroke measurement is essential to address these issues, but traditional methods relying on displacement sensors are costly. This study presents an innovative artificial neural network (ANN) method for sensorless piston stroke measurement in CO<sub>2</sub> linear compressors. The proposed model requires only six inputs: voltage, current, frequency, active power, suction pressure, and discharge pressure. Optimized ANN parameters enable high prediction accuracy, with an average R<sup>2</sup> of 0.955, RMSE of 0.206, and an average error of 2.24 % on the testing set. Furthermore, a simple stroke adjustment method based on the ANN model is proposed, allowing for effective stroke control and natural frequency calculation.</div></div>","PeriodicalId":9658,"journal":{"name":"Case Studies in Thermal Engineering","volume":"70 ","pages":"Article 106060"},"PeriodicalIF":6.4,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143746816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-25DOI: 10.1016/j.csite.2025.106042
Ceren Eda Delikurt, Meltem Kizilca Coruh
Trona ore, a naturally occurring sodium carbonate mineral, is a crucial raw material in various industrial applications, particularly soda ash production. Despite its significance, trona's thermal decomposition kinetics and underlying reaction mechanisms remain underexplored, limiting the optimization of industrial-scale processing methods. This study comprehensively investigates the non-isothermal thermal decomposition of trona using thermogravimetric analysis under different heating rates in an N2 atmosphere. To determine the activation energy (Ea) and reaction mechanisms governing the decomposition process, FWO, KAS, Tang, Starink, and CR methods were applied. The results indicate that the thermal decomposition follows a nucleation-controlled reaction mechanism P4 with activation energy values ranging from 122 to 131 kJ mol−1, demonstrating that the process occurs through a single-step reaction. The thermodynamic analysis revealed that the decomposition process is endothermic, as indicated by the positive ΔH values, while the ΔS values suggest an increase in molecular randomness during decomposition. Additionally, ΔG calculations indicate that the reaction is non-spontaneous, necessitating external energy input. These findings provide critical insights into trona's kinetic and thermodynamic behavior, bridging the knowledge gap between experimental analysis and industrial processing applications. Unlike previous studies, this research comprehensively evaluates trona's decomposition behavior, offering valuable data for reactor design and process optimization.
{"title":"Chemical kinetic models, reaction mechanism estimation, and thermodynamic parameters for the non-isothermal decomposition of trona ore","authors":"Ceren Eda Delikurt, Meltem Kizilca Coruh","doi":"10.1016/j.csite.2025.106042","DOIUrl":"10.1016/j.csite.2025.106042","url":null,"abstract":"<div><div>Trona ore, a naturally occurring sodium carbonate mineral, is a crucial raw material in various industrial applications, particularly soda ash production. Despite its significance, trona's thermal decomposition kinetics and underlying reaction mechanisms remain underexplored, limiting the optimization of industrial-scale processing methods. This study comprehensively investigates the non-isothermal thermal decomposition of trona using thermogravimetric analysis under different heating rates in an N<sub>2</sub> atmosphere. To determine the activation energy (Ea) and reaction mechanisms governing the decomposition process, FWO, KAS, Tang, Starink, and CR methods were applied. The results indicate that the thermal decomposition follows a nucleation-controlled reaction mechanism <em>P</em><sub><em>4</em></sub> with activation energy values ranging from 122 to 131 kJ mol<sup>−1</sup>, demonstrating that the process occurs through a single-step reaction. The thermodynamic analysis revealed that the decomposition process is endothermic, as indicated by the positive <em>ΔH</em> values, while the <em>ΔS</em> values suggest an increase in molecular randomness during decomposition. Additionally, <em>ΔG</em> calculations indicate that the reaction is non-spontaneous, necessitating external energy input. These findings provide critical insights into trona's kinetic and thermodynamic behavior, bridging the knowledge gap between experimental analysis and industrial processing applications. Unlike previous studies, this research comprehensively evaluates trona's decomposition behavior, offering valuable data for reactor design and process optimization.</div></div>","PeriodicalId":9658,"journal":{"name":"Case Studies in Thermal Engineering","volume":"69 ","pages":"Article 106042"},"PeriodicalIF":6.4,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143696638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-25DOI: 10.1016/j.csite.2025.106057
Xu Han, Ting Li, Guangchun Liu, Suresh Vellaiyan
This study presents a comparative evaluation of two distinct nanoadditives: a metal-based additive (copper oxide, CuO) and a carbon-based additive (carbon nanotubes, CNTs), focusing on their effects on engine performance and emissions when blended with a biofuel derived from pomelo peel waste (PWB) and conventional diesel fuel (CDF). The PWB bio-oil was extracted via thermal distillation, and a 30 % PWB + CDF blend (CDF30PWB) was further modified with 100 ppm of CuO and CNT nanoparticles. Characterization of CuO and CNT confirmed their catalytic potential for fuel enhancement. Results indicate that CDF30PWB improved brake thermal efficiency (BTE) by 6.09 % compared to CDF, while CNT and CuO further increased BTE by 1.63 % and 3.12 %, respectively. Brake-specific fuel consumption (BSFC) was reduced by 3.95 % for CDF30PWB, with CNT achieving an additional 3.69 % reduction and CuO lowering BSFC by 2.1 %. Emissions analysis showed that hydrocarbon (HC) and carbon monoxide (CO) emissions were reduced by 8.13 % and 2.61 %, respectively, for CDF30PWB, while CNT-enhanced fuel achieved further reductions of 14.59 % (HC) and 14.93 % (CO), and CuO reduced them by 4.29 % and 8.5 %, respectively. NOx emissions increased by 5.15 % with CDF30PWB, but CuO incorporation led to a 12.56 % reduction, and CNTs reduced NOx by 8.45 %. Smoke opacity was lowered by 9.88 % with CuO and 11.05 % with CNTs. Economic analysis highlighted that CuO achieved a 19 % potential cost reduction. This study concludes that CuO is more effective in NOx mitigation at a lower cost, while CNTs optimize engine performance and reduce HC and CO emissions.
{"title":"Comparative evaluation and economic analysis of metal- and carbon-based nanoadditives in low-viscous waste-derived biofuel blends for diesel engines","authors":"Xu Han, Ting Li, Guangchun Liu, Suresh Vellaiyan","doi":"10.1016/j.csite.2025.106057","DOIUrl":"https://doi.org/10.1016/j.csite.2025.106057","url":null,"abstract":"This study presents a comparative evaluation of two distinct nanoadditives: a metal-based additive (copper oxide, CuO) and a carbon-based additive (carbon nanotubes, CNTs), focusing on their effects on engine performance and emissions when blended with a biofuel derived from pomelo peel waste (PWB) and conventional diesel fuel (CDF). The PWB bio-oil was extracted via thermal distillation, and a 30 % PWB + CDF blend (CDF30PWB) was further modified with 100 ppm of CuO and CNT nanoparticles. Characterization of CuO and CNT confirmed their catalytic potential for fuel enhancement. Results indicate that CDF30PWB improved brake thermal efficiency (BTE) by 6.09 % compared to CDF, while CNT and CuO further increased BTE by 1.63 % and 3.12 %, respectively. Brake-specific fuel consumption (BSFC) was reduced by 3.95 % for CDF30PWB, with CNT achieving an additional 3.69 % reduction and CuO lowering BSFC by 2.1 %. Emissions analysis showed that hydrocarbon (HC) and carbon monoxide (CO) emissions were reduced by 8.13 % and 2.61 %, respectively, for CDF30PWB, while CNT-enhanced fuel achieved further reductions of 14.59 % (HC) and 14.93 % (CO), and CuO reduced them by 4.29 % and 8.5 %, respectively. NOx emissions increased by 5.15 % with CDF30PWB, but CuO incorporation led to a 12.56 % reduction, and CNTs reduced NOx by 8.45 %. Smoke opacity was lowered by 9.88 % with CuO and 11.05 % with CNTs. Economic analysis highlighted that CuO achieved a 19 % potential cost reduction. This study concludes that CuO is more effective in NOx mitigation at a lower cost, while CNTs optimize engine performance and reduce HC and CO emissions.","PeriodicalId":9658,"journal":{"name":"Case Studies in Thermal Engineering","volume":"33 1","pages":""},"PeriodicalIF":6.8,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143724019","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}
Pub Date : 2025-03-24DOI: 10.1016/j.csite.2025.106046
Yongbo Cui , Chengliang Fan , Wenhao Zhang , Xiaoqing Zhou
Dedicated outdoor air systems (DOAS) can utilize high cooling water temperatures to achieve independent temperature and humidity control, which improves the energy efficiency of the system. Although many studies have investigated the energy consumption of DOAS under conventional controls, there is a lack of a cooling load (sensible load and latent load) decoupling control method to optimize DOAS operation. To address this challenge, this study introduces an Attention-Convolutional neural network-Long short-term memory (ACL) model, a hybrid deep learning framework explicitly designed for DOAS cooling load prediction. Unlike traditional approaches, the proposed ACL model decouples sensible and latent cooling loads, enabling precise load forecasting. First, a convolutional neural network (CNN) extracts critical cooling load features from building datasets. Finally, the ACL model-based control strategy is implemented through a co-simulation framework to optimize DOAS operating parameters. The results show demonstrate that the ACL model achieves an average prediction error of 5.7 %, with mean absolute proportional errors of 2.8 % for sensible cooling load and 1.9 % for latent cooling load. Moreover, the optimized ACL control strategy reduces DOAS power consumption by 7.7 %, ensuring energy-efficient operation in high-temperature, high-humidity environments. This study provides a new cooling load decoupling prediction control approach for DOAS, offering substantial energy savings.
{"title":"Decoupling prediction of cooling load and optimizing control for dedicated outdoor air systems by using a hybrid artificial neural network method","authors":"Yongbo Cui , Chengliang Fan , Wenhao Zhang , Xiaoqing Zhou","doi":"10.1016/j.csite.2025.106046","DOIUrl":"10.1016/j.csite.2025.106046","url":null,"abstract":"<div><div>Dedicated outdoor air systems (DOAS) can utilize high cooling water temperatures to achieve independent temperature and humidity control, which improves the energy efficiency of the system. Although many studies have investigated the energy consumption of DOAS under conventional controls, there is a lack of a cooling load (sensible load and latent load) decoupling control method to optimize DOAS operation. To address this challenge, this study introduces an Attention-Convolutional neural network-Long short-term memory (ACL) model, a hybrid deep learning framework explicitly designed for DOAS cooling load prediction. Unlike traditional approaches, the proposed ACL model decouples sensible and latent cooling loads, enabling precise load forecasting. First, a convolutional neural network (CNN) extracts critical cooling load features from building datasets. Finally, the ACL model-based control strategy is implemented through a co-simulation framework to optimize DOAS operating parameters. The results show demonstrate that the ACL model achieves an average prediction error of 5.7 %, with mean absolute proportional errors of 2.8 % for sensible cooling load and 1.9 % for latent cooling load. Moreover, the optimized ACL control strategy reduces DOAS power consumption by 7.7 %, ensuring energy-efficient operation in high-temperature, high-humidity environments. This study provides a new cooling load decoupling prediction control approach for DOAS, offering substantial energy savings.</div></div>","PeriodicalId":9658,"journal":{"name":"Case Studies in Thermal Engineering","volume":"69 ","pages":"Article 106046"},"PeriodicalIF":6.4,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143696097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
During the operation of two-phase thermosyphon loops (TPTLs), different types of oscillations may occur, affecting their safety and performance. Although existing research has preliminarily explored the use of valve regulation to eliminate oscillatory operations in TPTLs, the effects of valves on different types of oscillations have not been verified. In this study, valve regulation was applied to two types of oscillation in a CO2 TPTL. The distinct effects of the valve on each type of oscillation were analyzed in conjunction with their respective mechanisms through experiment. For natural circulation oscillations, valve regulation can effectively suppress fluctuations within the loop. When the valve opening (θ) reduced from 100 % to 75 %, the TPTL transitioned from oscillatory to stable operation. However, the thermal performance of the TPTL remained nearly unaffected. For geyser boiling, valve regulation cannot alter the oscillatory operating state within the loop. Even when the θ was reduced from 100 % to 25 %, the TPTL remained in an oscillatory operating state. The results provide a deeper understanding of the influencing mechanisms of valve regulation and offer insights into the active regulation of TPTLs.
{"title":"Effect of valve regulation on the operating state of a CO2 two-phase thermosyphon loop","authors":"Zhen Tong, Wencheng Wang, Peng Wang, Zekun Han, Huili Yu, Songtao Hu","doi":"10.1016/j.csite.2025.106055","DOIUrl":"10.1016/j.csite.2025.106055","url":null,"abstract":"<div><div>During the operation of two-phase thermosyphon loops (TPTLs), different types of oscillations may occur, affecting their safety and performance. Although existing research has preliminarily explored the use of valve regulation to eliminate oscillatory operations in TPTLs, the effects of valves on different types of oscillations have not been verified. In this study, valve regulation was applied to two types of oscillation in a CO<sub>2</sub> TPTL. The distinct effects of the valve on each type of oscillation were analyzed in conjunction with their respective mechanisms through experiment. For natural circulation oscillations, valve regulation can effectively suppress fluctuations within the loop. When the valve opening (<em>θ</em>) reduced from 100 % to 75 %, the TPTL transitioned from oscillatory to stable operation. However, the thermal performance of the TPTL remained nearly unaffected. For geyser boiling, valve regulation cannot alter the oscillatory operating state within the loop. Even when the <em>θ</em> was reduced from 100 % to 25 %, the TPTL remained in an oscillatory operating state. The results provide a deeper understanding of the influencing mechanisms of valve regulation and offer insights into the active regulation of TPTLs.</div></div>","PeriodicalId":9658,"journal":{"name":"Case Studies in Thermal Engineering","volume":"69 ","pages":"Article 106055"},"PeriodicalIF":6.4,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143704201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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