Article
Thermodynamics
Haoran Xu, Lingen Chen, Yanlin Ge, Huijun Feng
Summary: This paper utilizes finite time thermodynamics to analyze the Stirling heat engine and performs multi-objective optimization of the heat engine cycle using NSGA-II. The optimization of temperature ratio and volume compression ratio allows for a better balance among the four optimization objectives.
Article
Thermodynamics
Fawad Ahmed, Shunmin Zhu, Guoyao Yu, Ercang Luo
Summary: This article proposes a novel numerical model that combines a strong loss mechanism and the NSGA-II algorithm for the Stirling engine. Multi-objective optimization is performed on the GPU-3 Stirling engine using the NSGA-II algorithm, aiming to minimize losses and increase power output and efficiency. The optimization results are compared with experimental results, and the model is also applied to optimize the design of a beta-type free piston Stirling engine.
Article
Engineering, Environmental
Zhiqing Zhang, Rui Dong, Dongli Tan, Bin Zhang
Summary: In this research, a hybrid multi-objective optimization approach of FGRA-RSM-MOPSO was developed for Diesel Particulate Filter (DPF) to improve its performance. Sensitivity analysis was conducted to identify key structural factors affecting DPF performance. Mathematical relationships between key parameters, initial filtration efficiency, and pressure drop were established using response surface methodology. Multiobjective particle swarm optimization was then employed to optimize the DPF and select the optimal solution from the Pareto front. The optimized DPF showed significant improvements in initial filtration efficiency and pressure drop reduction.
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
(2023)
Article
Thermodynamics
Hakan Aygun, Mehmet Kirmizi, Ulas Kilic, Onder Turan
Summary: The application of small turbojet engines is increasing due to their high power to weight ratio and reliability. This study analyzes the effects of different design variables on the performance metrics of small turbojet engines. By using multi-objective genetic algorithm, particle swarm optimization, and grey wolf optimization, the study considers several performance metrics of the engines. The findings show that increasing turbine inlet temperature improves net thrust but increases specific fuel consumption, while increasing compressor pressure ratio decreases net thrust but reduces specific fuel consumption. The optimization results suggest that different optimization methods can be utilized depending on the specific mission of the turbojet engine.
Article
Thermodynamics
Pengfan Chen, Changyu Deng, Xinkui Luo, Wenlian Ye, Lulu Hu, Xiaojun Wang, Yingwen Liu
Summary: A numerical model that couples thermodynamics with dynamics was developed and experimentally verified in this study. A multi-objective optimization of Stirling engine performance was proposed based on a self-online machine learning optimization approach. The optimal design values resulted in increased dimensionless work and efficiency, while reducing thermal and power losses.
APPLIED THERMAL ENGINEERING
(2024)
Article
Thermodynamics
Hang-Suin Yang, Muhammad Aon Ali, Karumudi Venkata Ravi Teja, Yi-Feng Yen
Summary: The study focuses on optimizing the design of a kW-class beta-type Stirling engine with a rhombic drive mechanism for a concentrated solar power system, validating the simulation results with experimental data. The research demonstrates an increase in maximum shaft power of the prototype engine to 1503 W and improvements in thermal efficiency to 13.5% and mechanical efficiency to 94.3% can be achieved.
APPLIED THERMAL ENGINEERING
(2022)
Article
Computer Science, Information Systems
Weiwei Zhang, Ningjun Zhang, Weizheng Zhang, Gary G. Yen, Guoqing Li
Summary: A cluster-based immune-inspired algorithm using manifold learning is proposed for solving MMOPs, which can locate equivalent Pareto optimal solutions in the decision space while maintaining diversity and convergence of solutions.
INFORMATION SCIENCES
(2021)
Article
Computer Science, Information Systems
Yule Wang, Wanliang Wang, Ijaz Ahmad, Elsayed Tag-Eldin
Summary: This paper proposes a multi-objective quantum-inspired seagull optimization algorithm (MOQSOA) to optimize the convergence and distribution of solutions in multi-objective optimization problems. The algorithm utilizes opposite-based learning, seagull behavior simulation, and principles of quantum computing to enhance the performance of MOPs in terms of distribution and convergence.
Article
Computer Science, Artificial Intelligence
Ziwu Ren, Ruiqing Jiang, Fan Yang, Jie Qiu
Summary: This paper presents a multi-objective elitist feedback teaching-learning-based optimization algorithm for multi-objective optimization problems. By introducing a feedback phase at the end of the learner phase, which simulates the spare-time learning phenomenon, the algorithm improves its exploration capacity and convergence. The experimental results indicate that the proposed algorithm outperforms other algorithms in terms of qualitative and quantitative evaluations, and achieves competitive results in unconstrained benchmark test problems and constrained engineering optimization problems.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Energy & Fuels
Mohsen Rostami, Ehsanolah Assareh, Rahim Moltames, Tohid Jafarinejad
Summary: Stirling engines can operate at various temperatures, and dish Stirling systems are considered as suitable alternatives for high-temperature solar concentrator energy harvesting systems. By optimizing parameters, output power, thermal efficiency, and economic evaluation are considered as appropriate objective functions for multi-objective optimization.
ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS
(2021)
Article
Computer Science, Artificial Intelligence
Chang Peng, Bao Xun, Meng FanChao, Lu RuiWei
Summary: Under the increasingly severe fresh water supply pressure, wastewater treatment is considered to be the optimal strategy to satisfy the current and future water demand, thus being highly valued by most countries. However, there are some hard-to-measure effluent indicators in wastewater treatment, which brings significant difficulties to the monitoring of key indicators in sewage disposal process, thus imposing massive constraints on evaluation of effluent quality.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Physics, Multidisciplinary
Haoran Xu, Lingen Chen, Yanlin Ge, Huijun Feng
Summary: This paper combines the mechanical efficiency theory and finite time thermodynamic theory to optimize an irreversible Stirling heat-engine cycle. The results indicate that multi-objective optimization results are better when choosing appropriate decision-making strategies.
Article
Thermodynamics
Mohammad Hassan Khanjanpour, Mohammad Rahnama, Akbar A. Javadi, Mohammad Akrami, Ali Reza Tavakolpour-Saleh, Masoud Iranmanesh
Summary: In this study, a gamma-type MDT Stirling engine prototype is manufactured, evaluated, and structurally optimized. An inexpensive mathematical evaluation based on FDT approach led to the determination of the optimal swept volume ratio under 450K temperature difference. Experimental results showed good agreement with the theoretical approach, validating its effectiveness in optimizing MTD Stirling engines.
CASE STUDIES IN THERMAL ENGINEERING
(2021)
Article
Thermodynamics
Meng Liu, Bilin Zhang, Dongtai Han, Xueping Du, Huanguang Wang
Summary: This study investigates the heat transfer and flow characteristics of the parallel-plate regenerator (PPR), a critical component of the Stirling engine. It is found that axial heat conduction reduces regenerative effectiveness, and higher thermal conductivity of the plate leads to lower effectiveness. Additionally, larger plate thickness and smaller plate length increase axial heat conduction loss. Comparative experiments with wire mesh regenerator reveal that PPR has better flow characteristics and lower friction coefficient. By comparing the overall performances using a comprehensive index, it is concluded that PPR has better working performance. The adverse effect of axial heat conduction on PPR is mitigated by segmenting the regenerator, resulting in a 20% increase in regenerative effectiveness with an acceptable increase in pressure drop.
APPLIED THERMAL ENGINEERING
(2022)
Article
Automation & Control Systems
Vikas Palakonda, Jae-Mo Kang
Summary: This article proposes a preference-inspired differential evolution algorithm for multi and many-objective optimization, which effectively deals with a wide range of problems. The algorithm generates individuals with good convergence and distribution properties by utilizing a preference-inspired mutation operator and determining local knee points based on a clustering method. Experimental results demonstrate its superior performance compared to eight state-of-the-art algorithms on 35 benchmark problems.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Materials Science, Multidisciplinary
Jay Vora, Rakesh Chaudhari, Chintan Patel, Danil Yurievich Pimenov, Vivek K. Patel, Khaled Giasin, Shubham Sharma
Summary: In this study, laser cutting of Ti6Al4V was conducted and parameters were analyzed to optimize the process. A Pareto graph was generated to facilitate parameter selection.
Article
Computer Science, Artificial Intelligence
Bansi D. Raja, Vivek K. Patel, Vimal J. Savsani, Ali Riza Yildiz
Summary: This study compares the performance of various swarm intelligence-based algorithms proposed in 2020-2021 for real-life constraint optimization problems, evaluates the effects of constraint handling methods and output constraints, and presents statistical analysis to determine the significance and ranking of the algorithms.
ARTIFICIAL INTELLIGENCE REVIEW
(2023)
Article
Thermodynamics
Rahul Deharkar, Anurag Mudgal, Vivek Patel
Summary: The design and experimental performance of a detachable shell vertical tube evaporator with variation in feed water temperature is studied. The modified evaporator operates with a thin film of evaporating feed water on the outer surface of fluted tubes, resulting in high heat transfer coefficient. The presence of salt deposits on the outer surface makes the system easy to clean and maintain. Experimental results show that the evaporator performs well under certain conditions.
HEAT AND MASS TRANSFER
(2022)
Article
Chemistry, Physical
Rakesh Chaudhari, Parth Prajapati, Sakshum Khanna, Jay Vora, Vivek K. Patel, Danil Yurievich Pimenov, Khaled Giasin
Summary: Shape memory alloy, particularly nickel-titanium combination, can regain original shape after heating. Adding Al2O3 nanopowder in the machining process can enhance the properties of the alloy. The study found that Al2O3 nanopowder has the highest contributing effect, while T-on is the most influential parameter for surface roughness and recast layer thickness. The use of optimization algorithms generated optimal points for the machining process. The regression model and TLBO algorithm show great effectiveness in the machining of nanopowder-mixed WEDM process for Nitinol SMA.
Article
Chemistry, Multidisciplinary
Jay Vora, Nipun Parikh, Rakesh Chaudhari, Vivek K. Patel, Heet Paramar, Danil Yurievich Pimenov, Khaled Giasin
Summary: This study focused on the optimization of process parameters in multi-layer multi-bead deposition for wire-arc additive manufacturing (WAAM) using gas metal arc welding (GMAW). Regression equations were established and optimized using the Teaching-learning-based optimization (TLBO) algorithm. The success of the model and algorithm were validated through experimental trials. The optimum parametric settings for multi-layer deposition were determined, leading to successful manufacturing of a disbond-free multi-layer structure.
APPLIED SCIENCES-BASEL
(2022)
Article
Green & Sustainable Science & Technology
Bhaumik Modi, Anurag Mudgal, Bansi D. Raja, Vivek Patel
Summary: This article presents a design methodology and test results of a small-scale single effect LiBr/water absorption refrigeration system with a capacity of 1.5 Ton. The experiments show that the system achieves a maximum COP of 0.35 at a generator temperature of 92C, and increasing the evaporator temperature leads to an increase in the cooling load. The break-even point for this small-scale absorption refrigeration system is determined to be 4.5 years, making it an economically viable option.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2022)
Article
Chemistry, Analytical
Rakesh Chaudhari, Aniket Kevalramani, Jay Vora, Sakshum Khanna, Vivek K. Patel, Danil Yurievich Pimenov, Khaled Giasin
Summary: Nitinol shape memory alloys are widely used in various industries, and precise machining of Nitinol SMA is crucial for achieving better surface quality and geometric accuracy of devices. This study investigated the impact of near-dry WEDM technique on reducing environmental impact, and found the optimal combination of process parameters through parameter optimization.
Article
Materials Science, Multidisciplinary
Rakesh Chaudhari, Heet Parmar, Jay Vora, Vivek K. Patel
Summary: The study aimed to optimize gas metal arc welding-based wire-arc additive manufacturing variables for bead geometries on an SS 316L substrate. Multivariable regression equations were generated, and ANOVA was used to investigate the feasibility of the obtained regression equations. Heat transfer search optimization resulted in optimal combinations, with maximum bead height and minimum bead width achieved.
Article
Chemistry, Physical
Rakesh Chaudhari, Yug Shah, Sakshum Khanna, Vivek K. Patel, Jay Vora, Danil Yurievich Pimenov, Khaled Giasin
Summary: The effect of Al2O3 nano-powder on the EDM of Nitinol SMA was investigated. The concentrations of nano-powder, pulse-on-time, pulse-off-time, and current were selected as parameters for measuring the material removal rate, surface roughness, and tool wear rate. The study found that Al2O3 powder concentration, pulse-off-time, and pulse-on-time significantly affected the respective performance measures. The TLBO technique was employed to find the optimal parametric settings, resulting in improved output measures. The importance of different user and application requirements was considered, and SEM analysis confirmed the effectiveness of the study.
Article
Engineering, Multidisciplinary
Bansi D. Raja, Vivek K. Patel, Ali Riza Yildiz, Prakash Kotecha
Summary: This paper compares the performance of scientific law-inspired optimization algorithms for real-life constrained optimization applications. The algorithms are evaluated using a constrained engineering application of the Stirling heat engine system. The effects of constraint handling methods and output constraints on algorithm performance are analyzed and presented.
ENGINEERING OPTIMIZATION
(2023)
Article
Chemistry, Multidisciplinary
Rakesh Chaudhari, Izaro Ayesta, Mikesh Doshi, Sakshum Khanna, Vivek K. Patel, Jay Vora, Luis Norberto Lopez de Lacalle
Summary: Nickel-based superalloys are widely used in various fields, but their high hardness poses challenges in the fabrication process. This study explores the precise machining of a specific superalloy using wire electrical discharge machining (WEDM) and evaluates the influence of multi-walled carbon nanotubes (MWCNTs) through a multi-objective optimization. The research indicates that adjusting machining variables can effectively impact material removal rate, recast layer thickness, and surface roughness. Additionally, the addition of MWCNTs significantly improves machining performance.
Article
Engineering, Manufacturing
Jay Vora, Yug Shah, Sakshum Khanna, Vivek K. Patel, Manoj Jagdale, Rakesh Chaudhari
Summary: This study identified current, pulse-off-duration (Toff), and pulse-on-duration (Ton) as vital input factors for the WEDM process of Ti6Al4V. Empirical models were generated and validated using ANOVA, showing a significant impact of these factors on material removal rate (MRR) and surface roughness (SR). Additionally, the use of expanded graphite (EG) nano-powder was found to improve the WEDM process, increasing MRR by 45.35% and reducing SR by 36.16%.
JOURNAL OF MANUFACTURING AND MATERIALS PROCESSING
(2023)
Article
Chemistry, Physical
Jay Vora, Rudram Pandey, Pratik Dodiya, Vivek Patel, Sakshum Khanna, Vatsal Vaghasia, Rakesh Chaudhari
Summary: This study investigates and optimizes the bead geometries of SS-309L using a GMAW-based WAAM process. The Box-Behnken design approach is used for trials, and regression models are developed. The optimized parameters yield a maximum BH of 9.48 mm and a minimum BW of 5.90 mm for single-layer depositions.
Article
Engineering, Electrical & Electronic
Venish Suthar, Vinay Vakharia, Vivek K. K. Patel, Milind Shah
Summary: Intelligent fault diagnosis is crucial for timely information of mechanical components, especially rolling element bearings. This study proposes a novel approach for reliable compound fault identification in bearings with limited experimental data. Vibration signals from single ball bearings with compound faults and varied rotational speeds are pre-processed using the Hilbert-Huang transform and Kurtogram. Additional Kurtogram images are generated using the multiscale-SinGAN model to effectively train machine-learning models. Metaheuristic optimization algorithms are applied to feature vectors for identifying relevant features. Three machine-learning models are used for compound fault identifications, with extreme learning machines achieving 100% ten-fold cross-validation accuracy. Support vector machines achieve a minimum ten-fold cross-validation accuracy of 98.96%.
Proceedings Paper
Materials Science, Multidisciplinary
Aditya Nema, Vivek Patel, Abhishek Kumar, Ankit Oza, Ashish B. Jagani
Summary: This paper focuses on the optimization of process parameters for electrochemical discharge machining (ECDM) to effectively machine materials with poor machinability, such as glass, carbon fiber, composites, and silica reinforced composites. The objective is to maximize material removal rate and minimize tool wear rate.
MATERIALS TODAY-PROCEEDINGS
(2022)
Article
Thermodynamics
Yong Cheng, Fukai Song, Lei Fu, Saishuai Dai, Zhiming Yuan, Atilla Incecik
Summary: This paper investigates the accessibility of wave energy absorption by a dual-pontoon floating breakwater integrated with hybrid-type wave energy converters (WECs) and proposes a hydraulic-pneumatic complementary energy extraction method. The performance of the system is validated through experiments and comparative analysis.
Article
Thermodynamics
Jing Gao, Chao Wang, Zhanwu Wang, Jin Lin, Runkai Zhang, Xin Wu, Guangyin Xu, Zhenfeng Wang
Summary: This study aims to establish a new integrated method for biomass cogeneration project site selection, with a focus on the application of the model in Henan Province. By integrating Geographic Information System and Multiple Criterion Decision Making methods, the study conducts site selection in two stages, providing a theoretical reference for the construction of biomass cogeneration projects.
Article
Thermodynamics
Mert Temiz, Ibrahim Dincer
Summary: The current study presents a hybrid small modular nuclear reactor and solar-based system for sustainable communities, integrating floating and bifacial photovoltaic arrays with a small modular reactor. The system efficiently generates power, hydrogen, ammonia, freshwater, and heat for residential, agricultural, and aquaculture facilities. Thermodynamic analysis shows high energy and exergy efficiencies, as well as large-scale ammonia production meeting the needs of metropolitan areas. The hybridization of nuclear and solar technologies offers advantages of reliability, environmental friendliness, and cost efficiency compared to renewable-alone and fossil-based systems.
Editorial Material
Thermodynamics
Wojciech Stanek, Wojciech Adamczyk
Article
Thermodynamics
Desheng Xu, Yanfeng Li, Tianmei Du, Hua Zhong, Youbo Huang, Lei Li, Xiangling Duanmu
Summary: This study investigates the optimization of hybrid mechanical-natural ventilation for smoke control in complex metro stations. The results show that atrium fires are more significantly impacted by outdoor temperature variations compared to concourse/platform fires. The gathered high-temperature smoke inside the atrium can reach up to 900 K under a 5 MW train fire energy release. The findings provide crucial engineering insights into integrating weather data and adaptable ventilation protocols for smoke prevention/mitigation.
Article
Thermodynamics
Da Guo, Heping Xie, Mingzhong Gao, Jianan Li, Zhiqiang He, Ling Chen, Cong Li, Le Zhao, Dingming Wang, Yiwei Zhang, Xin Fang, Guikang Liu, Zhongya Zhou, Lin Dai
Summary: This study proposes a new in-situ pressure-preserved coring tool and elaborates its pressure-preserving mechanism. The experimental and field test results demonstrate that this tool has a high pressure-preservation capability and can maintain a stable pressure in deep wells. This study provides a theoretical framework and design standards for the development of similar technologies.
Article
Thermodynamics
Aolin Lai, Qunwei Wang
Summary: This study assesses the impact of China's de-capacity policy on renewable energy development efficiency (REDE) using the Global-MSBM model and the difference-in-differences method. The findings indicate that the policy significantly enhances REDE, promoting technological advancements and marketization. Moreover, regions with stricter environmental regulations experience a higher impact.
Article
Thermodynamics
Mostafa Ghasemi, Hegazy Rezk
Summary: This study utilizes fuzzy modeling and optimization to enhance the performance of microbial fuel cells (MFCs). By simulating and analyzing experimental data sets, the ideal parameter values for increasing power density, COD elimination, and coulombic efficiency were determined. The results demonstrate that the fuzzy model and optimization methods can significantly improve the performance of MFCs.
Article
Thermodynamics
Zhang Ruan, Lianzhong Huang, Kai Wang, Ranqi Ma, Zhongyi Wang, Rui Zhang, Haoyang Zhao, Cong Wang
Summary: This paper proposes a grey box model for fuel consumption prediction of wing-diesel hybrid vessels based on feature construction. By using both parallel and series grey box modeling methods and six machine learning algorithms, twelve combinations of prediction models are established. A feature construction method based on the aerodynamic performance of the wing and the energy relationship of the hybrid system is introduced. The best combination is obtained by considering the root mean square error, and it shows improved accuracy compared to the white box model. The proposed grey box model can accurately predict the daily fuel consumption of wing-diesel hybrid vessels, contributing to operational optimization and the greenization and decarbonization of the shipping industry.
Article
Thermodynamics
Huayi Chang, Nico Heerink, Junbiao Zhang, Ke He
Summary: This study examines the interaction between off-farm employment decisions between couples and household clean energy consumption in rural China, and finds that two-paycheck households are more likely to consume clean energy. The off-farm employment of women is a key factor driving household clean energy consumption to a higher level, with wage-employed wives having a stronger influence on these decisions than self-employed ones.
Article
Thermodynamics
Hanguan Wen, Xiufeng Liu, Ming Yang, Bo Lei, Xu Cheng, Zhe Chen
Summary: Demand-side management is crucial to smart energy systems. This paper proposes a data-driven approach to understand the relationship between energy consumption patterns and household characteristics for better DSM services. The proposed method uses a clustering algorithm to generate optimal customer groups for DSM and a deep learning model for training. The model can predict the possibility of DSM membership for a given household. The results demonstrate the usefulness of weekly energy consumption data and household socio-demographic information for distinguishing consumer groups and the potential for targeted DSM strategies.
Article
Thermodynamics
Xinglan Hou, Xiuping Zhong, Shuaishuai Nie, Yafei Wang, Guigang Tu, Yingrui Ma, Kunyan Liu, Chen Chen
Summary: This study explores the feasibility of utilizing a multi-level horizontal branch well heat recovery system in the Qiabuqia geothermal field. The research systematically investigates the effects of various engineering parameters on production temperature, establishes mathematical models to describe their relationships, and evaluates the economic viability of the system. The findings demonstrate the significant economic feasibility of the multi-level branch well system.
Article
Thermodynamics
Longxin Zhang, Songtao Wang, Site Hu
Summary: This investigation reveals the influence of tip leakage flow on the modern transonic rotor and finds that the increase of tip clearance size leads to a decline in rotor performance. However, an optimal tip clearance size can extend the rotor's stall margin.
Article
Thermodynamics
Kristian Gjoka, Behzad Rismanchi, Robert H. Crawford
Summary: This paper proposes a framework for assessing the performance of 5GDHC systems and demonstrates it through a case study in a university campus in Melbourne, Australia. The results show that 5GDHC systems are a cost-effective and environmentally viable solution in mild climates, and their successful implementation in Australia can create new market opportunities and potential adoption in other countries with similar climatic conditions.
Article
Thermodynamics
Jianwei Li, Guotai Wang, Panpan Yang, Yongshuang Wen, Leian Zhang, Rujun Song, Chengwei Hou
Summary: This study proposes an orientation-adaptive electromagnetic energy harvester by introducing a rotatable bluff body, which allows for self-regulation to cater for changing wind flow direction. Experimental results show that the output power of the energy harvester can be greatly enhanced with increased rotatory inertia of the rotating bluff body, providing a promising solution for harnessing wind-induced vibration energy.
