Advanced Theory and Simulations最新文献

{"title":"Effect of Metallic and Ceramic Coatings on Structural Behavior of Heavy‐Duty V8 Engine Using Finite Element Analysis","authors":"Hafsa Khan, Fatima Tu Zahra, Syed Masood Arif Bukhari, Naveed Husnain, Muhammad Farooq Zaman, Hassan Raza, Muhammad Tuoqeer Anwar, Ammar Tariq, Farrukh Arsalan Siddiqui, Wasif Ahmed","doi":"10.1002/adts.202500151","DOIUrl":"https://doi.org/10.1002/adts.202500151","url":null,"abstract":"This research aims to compare the effects of material coatings on the structural behavior of a V8 engine block to identify the most suitable coating material that can enhance structural integrity and functionality under different pressures. SolidWorks 20.0 is used for designing V8 engine block, and ANSYS Workbench 19.0 for coating simulations. Six coating materials are selected including Zirconia (ZrO<jats:sub>2</jats:sub>), Alumina (Al<jats:sub>2</jats:sub>O<jats:sub>5</jats:sub>), Tungsten Carbide (WC), Nickel (Ni), Silicon Nitride (Si<jats:sub>3</jats:sub>N<jats:sub>4</jats:sub>) and Silicon Carbide (SiC). These coatings are applied to the interior surface of the engine cylinders, with a thickness of 0.4 mm. The performance of each coating material is analyzed under three different pressure conditions, 6.90, 8.27, and 9.65 MPa. The results yielded that Tungsten Carbide is the optimal material for coating a V8 engine when used with the base material of Aluminium, as it displayed the lowest values of deformation, stress, and strain. As a result, the structural behavior is improved by 30% as compared to the base material. Moreover, the factor of safety exhibit a significant increase. Based on the results, the Tungsten Carbide coating can significantly reduce stress levels and increase the safety factor, thereby potentially improving the durability and performance of the V8 engine block.","PeriodicalId":7219,"journal":{"name":"Advanced Theory and Simulations","volume":"230 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143933441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tailoring the Bandgap of Doped GaS Nanosheets for Optoelectronic, Spintronic, and Sustainable Energy Applications","authors":"Mohamed M. Fadlallah, Safwat Abdel‐Azeim","doi":"10.1002/adts.202500322","DOIUrl":"https://doi.org/10.1002/adts.202500322","url":null,"abstract":"Gallium sulfide (GaS) sheet encounters obstacles in electronic and photocatalytic applications due to its large bandgap of 3.6 eV. To boost up the applicability of GaS sheets, the effects of substitutional mono metal and nonmetal dopants (3d transition metals, Ge, As, Se, In, Sn, Sb) at the Ga‐site on their chemical stability, photocatalytic behavior, and physical properties such as electronic, magnetic, and optical characteristics are investigated, using hybrid density functional theory. Results reveal that the majority of the doped GaS (MD‐GaS) exhibit thermodynamic stability. The magnetic properties of MD‐GaS nanosheets change with doping for MD = Ti, V, Cr, Mn, Fe, Ni, Co, Zn, and Se, transforming the sheets into diluted magnetic semiconductors. In contrast, doping with Sc, Cu, As, In, and Sb retains the semiconductor properties of the pristine sheet. Ge‐ and Sn‐doped GaS nanosheets show potential for 2D spintronic applications. While many dopants enhance visible light absorption, they introduce mid‐gap states or unfavorable valence band edges, making them less suitable for photocatalysis. However, As‐ and Sb‐doped GaS are promising sheets for photocatalytic Co<jats:sub>2</jats:sub> reduction and water splitting under visible light making it a potential material for clean fuel production.","PeriodicalId":7219,"journal":{"name":"Advanced Theory and Simulations","volume":"35 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143933422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting Fiber Length Characteristics of Recycled Cotton and Cellulose Fiber Blends Using Machine Learning Models","authors":"Tuser Tirtha Biswas, Michael Will, Nawar Kadi","doi":"10.1002/adts.202500086","DOIUrl":"https://doi.org/10.1002/adts.202500086","url":null,"abstract":"As the textile industry faces growing challenges related to sustainability, recycled fiber blending for making new yarns has emerged as a key area for reducing environmental impacts. This study aims to investigate the role of fiber length features in predicting the quality of blended yarns, particularly focusing on natural-based fiber blends such as recycled cotton (ReCo) and Lyocell. Machine learning models, including Random Forest, Gradient Boosting, and Support Vector Regression, alongside linear and polynomial regressions, are used to predict fiber properties based on empirical data. The results show fiber length features from the Staple Diagram and Fibrogram as the most significant factors. Hyperparameter tuning has enhanced model accuracy, especially for Random Forest and Gradient Boosting, showing significant reductions in error metrics. Cross-validation is performed to ensure the reliability of the models and prevent overfitting during the predictive analysis of fiber length features. Shapley Additive Explanations (SHAP) analysis reveals that specific fiber length ranges have the most influence on model predictions, highlighting their importance in optimizing blended yarn properties. These findings contribute to advancing sustainable textile production through data-driven approaches and textile fiber blend optimization.","PeriodicalId":7219,"journal":{"name":"Advanced Theory and Simulations","volume":"26 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143933212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Issue Information (Adv. Theory Simul. 5/2025)","authors":"","doi":"10.1002/adts.202570010","DOIUrl":"https://doi.org/10.1002/adts.202570010","url":null,"abstract":"","PeriodicalId":7219,"journal":{"name":"Advanced Theory and Simulations","volume":"8 5","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adts.202570010","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143939363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Reinforcement Learning Approach to Advance Non-Fullerene Acceptor-Based Semi-Transparent Organic Solar Cell","authors":"Erman Cokduygulular, Muhammed Yusuf Aykut, Caglar Cetinkaya","doi":"10.1002/adts.202500334","DOIUrl":"https://doi.org/10.1002/adts.202500334","url":null,"abstract":"This study uses deep Q-learning reinforcement learning to introduce a novel optimization framework for semi-transparent organic solar cells (ST-OSCs). This approach integrates the Transfer Matrix Method with artificial intelligence to streamline design processes by addressing the dual challenge of achieving high visible light transparency and efficient photovoltaic performance. The research focuses on PBDB-T:ITIC-based active layers coupled with asymmetrical dielectric-metal-dielectric transparent contacts, optimizing layer thicknesses and material properties. The deep Q-learning algorithm efficiently navigates the complex design space, achieving a maximum average visible transmittance of 48.97% while maintaining strong photo-current density. This optimization balances transparency and absorption, which are critical for ST-OSCs, by reducing reflection losses and enhancing photon management. The study demonstrates the effectiveness of reinforcement learning in handling intricate multi-layer ST-OSCs, surpassing traditional optimization techniques. Results highlight the potential of adaptive learning algorithms in identifying high-performance material configurations, minimizing computational costs, and ensuring precision. This work underscores the transformative role of AI in renewable energy technologies, offering scalable, sustainable solutions to modern energy challenges. By advancing the integration of artificial intelligence and material science, this study opens new pathways for optimizing renewable energy technologies and improving the performance of optoelectronic devices.","PeriodicalId":7219,"journal":{"name":"Advanced Theory and Simulations","volume":"51 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143933247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Analysis of Elusive Relationships in Floating Zone Growth Using Data Mining Techniques (Adv. Theory Simul. 5/2025)","authors":"Lucas Vieira,&nbsp;Robert Menzel,&nbsp;Martin Holena,&nbsp;Natasha Dropka","doi":"10.1002/adts.202570009","DOIUrl":"https://doi.org/10.1002/adts.202570009","url":null,"abstract":"<p>High-purity silicon single crystals are grown using the Floating Zone (FZ) method, a key process in the semiconductor industry and crucial for renewable energy applications. In article 2400781, Lucas Vieira, Natasha Dropka, and co-workers apply data mining techniques to FZ simulations, uncovering complex relationships between growth parameters and process stability. The findings offer insights for optimizing the process through parameter engineering.\u0000\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":7219,"journal":{"name":"Advanced Theory and Simulations","volume":"8 5","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adts.202570009","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143939362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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":"Ab Initio Study of the Electronic, Thermodynamic, Thermoelectric, and Optical Properties of HfSeS in the (100), (110), and (111) Crystallographic Directions","authors":"S. Dahri, A. Jabar, L. Bahmad, L. B. Drissi, R. Ahl Laamara","doi":"10.1002/adts.202500072","DOIUrl":"https://doi.org/10.1002/adts.202500072","url":null,"abstract":"In this article, the results of theoretical calculations are presented on the structural, electronic, thermodynamic, thermoelectric, and optical properties of the compound HfSeS grown in the (100), (110), and (111) crystallographic directions. These properties are studied with the aid of calculations based on density functional theory, using the Generalized Gradient Approximation (GGA) approximation and spin‐orbit coupling (SOC). These electronic calculations reveal that HfSeS exhibits an indirect band gap of the M‐Γ type for all directions, with strong alignment between the results obtained employing the GGA and SOC approaches. For the study of optical properties, pressure is applied to better understand the properties of the material under various conditions. The thermodynamic properties of HfSeS are calculated, including heat capacities, thermal expansion, Debye temperature, and entropy, under elevated pressures and temperatures. These calculations are performed using the quasi‐harmonic Debye model integrated into the Gibbs2 code, and the results are analyzed in detail to better understand the thermodynamic properties of the material under various conditions. Finally, the thermoelectric properties such as the Seebeck coefficient and the electronic thermal conductivity are analyzed.","PeriodicalId":7219,"journal":{"name":"Advanced Theory and Simulations","volume":"3 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143933425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment and Comparative Study of Free and Commercial Numerical Software Packages for Lithium‐Ion Battery Modeling","authors":"Kenneth C. Nwanoro, Michael P. Mercer, Harry E. Hoster","doi":"10.1002/adts.202500302","DOIUrl":"https://doi.org/10.1002/adts.202500302","url":null,"abstract":"Currently, several competing computational frameworks, including free, open‐source, and commercial packages exist, that enable users to perform purely electrochemical simulations based on the Doyle‐Fuller‐Newman (DFN) model or simulations additionally coupled with thermal/mechanical physics. In this paper, the performance of several numerical software packages is reviewed and evaluated based on the ease of model setup, spatial dimension capability, and model accuracy. In the absence of standardized benchmark tests, a series of discharge simulations under various operating conditions, such as static and dynamic electric vehicle driving cycle loads, as well as galvanostatic intermittent titration techniques (GITTs), provide rigorous test methods to evaluate and benchmark battery modeling software packages. Two different lithium‐ion battery (LIB) parameter sets enable complete assessment of the software packages in terms of accuracy, validity, and solver sensitivity. The careful selection of actual operating condition simulations and independent evaluation tests serves as a benchmark for LIB electrochemical simulation packages and can help users of these packages develop their analyses with confidence in the validity of their results. It is hoped that this paper will serve as a reference for new and established researchers and simulation engineers in LIB simulation to gain knowledge about the capabilities of existing lithium‐ion simulation packages.","PeriodicalId":7219,"journal":{"name":"Advanced Theory and Simulations","volume":"5 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143933424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Performance of Micro Adiabatic Compressed Air Energy Storage System with Different Final Pressure of Air Storage Tank","authors":"Linhua Zhang, Mengjie Zhang, Yongxing Song, Zhiwen Wang, Yi Ge, Fajie Pu, Ziyuan Geng","doi":"10.1002/adts.202401298","DOIUrl":"https://doi.org/10.1002/adts.202401298","url":null,"abstract":"Micro adiabatic compressed air energy storage (A-CAES) systems have emerged as a research hotspot due to their flexible compatibility with distributed energy systems. This study establishes a thermodynamic model of a micro A-CAES system based on a pneumatic motor (PM). The research systematically examines the influence of final gas tank pressure (Pf) within the range of 1.5–3.0 MPa on system performance, with particular focus on monitoring the response characteristics of pneumatic motor inlet pressure, air mass flow rate, and power output. Meanwhile, the expansion stage is divided into a stable operation stage and an unstable operation stage. The research results show that the final pressure of the gas storage tank affects the stable operation stage of the pneumatic motor, but has no obvious impact on the unstable operation stage. The round-trip efficiency of the system reaches the highest value of 5.4% when Pf = 2.5 MPa; the comprehensive efficiency reaches the highest value of 26.6% when Pf = 2 MPa; and the efficiency improvement index reaches the highest value of 21.5% when Pf = 1.5 MPa. Through the economic analysis, it is found that the economic performance of this system is optimal when Pf = 2 MPa.","PeriodicalId":7219,"journal":{"name":"Advanced Theory and Simulations","volume":"17 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144000614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal Charging of Lithium-Ion Batteries: An Electro-Thermal Model Approach Using Maximum Possible Optimization","authors":"Kamala Kumari Duru, Praneash Venkatachalam, Syed Ali Hussain, Asha Anish Madhavan, Sangaraju Sambasivam, Sujith Kalluri","doi":"10.1002/adts.202500320","DOIUrl":"https://doi.org/10.1002/adts.202500320","url":null,"abstract":"Electric vehicle (EV) charging has recently become one of the most pressing issues. Given the growing demand for lithium-ion batteries (LIBs) in electric vehicles, this study analyzes optimization methods for improving existing approaches to speed up charging while reducing temperature rise. This work formulates a double-objective function for battery charging based on an electrothermal model. The focused objective function is comprised of a combination of two different fitness functions. Optimization of charging current is made dynamically following a battery's temperature. These experimental findings validate the proposed charging strategy's effectiveness in delivering the optimal current profile. This approach demonstrably achieves a well-calibrated balance between competing performance objectives. By adopting the suggested strategy, any increase in the battery's temperature can be maintained within an acceptable temperature range. The proposed constant current constant voltage (CCCV) charging method takes a total charging time of 1874 s, with a temperature shift from 26 to 45.78 &lt;span data-altimg=\"/cms/asset/7fbfed2e-7e97-4aa8-acab-eecbe19f61f4/adts70005-math-0001.png\"&gt;&lt;/span&gt;&lt;mjx-container ctxtmenu_counter=\"1\" ctxtmenu_oldtabindex=\"1\" jax=\"CHTML\" role=\"application\" sre-explorer- style=\"font-size: 103%; position: relative;\" tabindex=\"0\"&gt;&lt;mjx-math aria-hidden=\"true\" location=\"graphic/adts70005-math-0001.png\"&gt;&lt;mjx-semantics&gt;&lt;mjx-mrow data-semantic-annotation=\"clearspeak:unit\" data-semantic-children=\"2,3\" data-semantic-content=\"4\" data-semantic- data-semantic-role=\"implicit\" data-semantic-speech=\"Superscript ring Baseline normal upper C\" data-semantic-type=\"infixop\"&gt;&lt;mjx-msup data-semantic-children=\"0,1\" data-semantic- data-semantic-parent=\"5\" data-semantic-role=\"unknown\" data-semantic-type=\"superscript\"&gt;&lt;mjx-mrow data-semantic- data-semantic-parent=\"2\" data-semantic-role=\"unknown\" data-semantic-type=\"empty\"&gt;&lt;/mjx-mrow&gt;&lt;mjx-script style=\"vertical-align: 0.363em;\"&gt;&lt;mjx-mo data-semantic- data-semantic-parent=\"2\" data-semantic-role=\"multiplication\" data-semantic-type=\"operator\" size=\"s\"&gt;&lt;mjx-c&gt;&lt;/mjx-c&gt;&lt;/mjx-mo&gt;&lt;/mjx-script&gt;&lt;/mjx-msup&gt;&lt;mjx-mo data-semantic-added=\"true\" data-semantic- data-semantic-operator=\"infixop,⁢\" data-semantic-parent=\"5\" data-semantic-role=\"multiplication\" data-semantic-type=\"operator\" style=\"margin-left: 0.056em; margin-right: 0.056em;\"&gt;&lt;mjx-c&gt;&lt;/mjx-c&gt;&lt;/mjx-mo&gt;&lt;mjx-mi data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic- data-semantic-parent=\"5\" data-semantic-role=\"latinletter\" data-semantic-type=\"identifier\"&gt;&lt;mjx-c&gt;&lt;/mjx-c&gt;&lt;/mjx-mi&gt;&lt;/mjx-mrow&gt;&lt;/mjx-semantics&gt;&lt;/mjx-math&gt;&lt;mjx-assistive-mml display=\"inline\" unselectable=\"on\"&gt;&lt;math altimg=\"urn:x-wiley:25130390:media:adts70005:adts70005-math-0001\" display=\"inline\" location=\"graphic/adts70005-math-0001.png\" xmlns=\"http://www.w3.org/1998/Math/MathML\"&gt;&lt;semantics&gt;&lt;mrow data-semantic-=\"\" data-semantic-annotation=\"clearspeak:unit\" data-semantic-children","PeriodicalId":7219,"journal":{"name":"Advanced Theory and Simulations","volume":"230 1","pages":""},"PeriodicalIF":3.3,"publicationDate":"2025-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143932668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}