Engineering Science and Technology-An International Journal-Jestech最新文献

{"title":"Boost pressure influence on combustion, emission characteristics, and performance of diesel engines with various fuel types","authors":"Hüseyin Söyler","doi":"10.1016/j.jestch.2025.101983","DOIUrl":"10.1016/j.jestch.2025.101983","url":null,"abstract":"<div><div>This study investigates the effects of varying boost pressure levels on engine performance, combustion characteristics, and emissions using different fuel types (diesel, B50, B100) under various engine loads. The results show that increasing boost pressure generally enhances engine performance by raising in-cylinder pressure and heat release rates. For instance, at 75 % engine load, the cylinder pressure increased by 18.7 % for diesel and 15.9 % for B100 when the boost pressure was raised from −20 % to + 20 %. Similarly, combustion efficiency improved, with ignition delay reduced by approximately 4.1 % for diesel and 6.5 % for B100 under the same conditions. However, higher boost pressure also led to increased Brake Specific Fuel Consumption (BSFC), particularly for biodiesel fuels; for B100, BSFC increased from 297.1 g/kWh to 304.95 g/kWh at 50 % engine load. In terms of emissions, higher boost pressure significantly decreased CO and HC emissions by up to 7.5 % and 15.3 %, respectively, for B100. Nevertheless, NOx emissions increased by 5.3 % due to the oxygen content of biodiesel. Soot emissions were notably reduced, with a maximum reduction of 58.4 % observed at 75 % engine load and + 20 % boost pressure for diesel fuel. These findings underscore the need for additional strategies to control NOx emissions, especially for biodiesel applications. In conclusion, optimizing boost pressure is critical for improving engine performance and emissions. Biodiesel and its blends, despite their higher NOx emissions, provide significant environmental benefits due to their cleaner combustion characteristics. This study contributes valuable insights for designing more efficient and sustainable internal combustion engines.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"63 ","pages":"Article 101983"},"PeriodicalIF":5.1,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143211294","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}

{"title":"Enhancing voice spoofing detection in noisy environments using frequency feature masking augmentation","authors":"Soyul Han ,&nbsp;Jaejin Seo ,&nbsp;Sunmook Choi ,&nbsp;Taein Kang ,&nbsp;Sanghyeok Chung ,&nbsp;Seungeun Lee ,&nbsp;Seoyoung Park ,&nbsp;Seungsang Oh ,&nbsp;Il-Youp Kwak","doi":"10.1016/j.jestch.2025.101972","DOIUrl":"10.1016/j.jestch.2025.101972","url":null,"abstract":"<div><div>In the rapidly evolving landscape of voice-related technology, high-tech companies are developing multifaceted voice assistants, tailored to their specific organizational goals. This technological evolution, however, introduces heightened security vulnerabilities such as voice spoofing attacks. To address voice spoofing challenges, various competitions like ASVspoof 2015, 2017, 2019, 2021, and ADD 2022 have emerged. ADD 2022’s Track 1 aimed to classify genuine and fake speech signals in the presence of noise. Our exploratory data analysis revealed that for a given speech sample, noisy signals tend to occur within similar frequency bands. If a model is heavily reliant on data within frequency ranges that contains noise, its performance will be suboptimal. To address this issue, we propose a data augmentation technique called Frequency Feature Masking (FFM), which randomly masks frequency bands. FFM helps prevent overfitting and enhances the model’s robustness by avoiding reliance on specific frequency bands. Furthermore, we propose a frequency band masking method using a bell-shaped filter. This allows for smooth transitions between masked and unmasked frequencies, enabling the model to naturally mimic frequency variations in real speech signals. We compare the performance of various data augmentation methods with FFM in two spoofing detection datasets, ASVspoof 2019 LA and ADD 2022. The proposed FFM augmentation achieves state-of-the-art results in both datasets. The ADD 2022 dataset showed an improvement of approximately 51% after the application of FFM, while there was a 54% improvement in the ASVspoof 2019 LA dataset. In addition, we have made the code and demo used in the experiment publicly available.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"63 ","pages":"Article 101972"},"PeriodicalIF":5.1,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143211335","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}

{"title":"Chaotic Puma Optimizer Algorithm for controlling wheeled mobile robots","authors":"Mohamed Kmich ,&nbsp;Nawal El Ghouate ,&nbsp;Ahmed Bencharqui ,&nbsp;Hicham Karmouni ,&nbsp;Mhamed Sayyouri ,&nbsp;S.S. Askar ,&nbsp;Mohamed Abouhawwash","doi":"10.1016/j.jestch.2025.101982","DOIUrl":"10.1016/j.jestch.2025.101982","url":null,"abstract":"<div><div>The control of wheeled mobile robots plays a crucial role in many fields, including automation, logistics, security, and even space exploration. This paper presents a significant improvement in the control of wheeled mobile robots based on an enhanced version of the Puma optimization algorithm by integrating chaotic maps in both optimization phases, exploration and exploitation. The Chaotic Puma Optimizer Algorithm (CPOA) has been tested and proven effective on CEC’2022 benchmarks and three complex engineering problems. It has outperformed standard and improved metaheuristic algorithms in controlling nonlinear and time-varying wheeled mobile robots. The results show a notable improvement in terms of response time and stability, thus expanding the potential applications of this optimizer in various fields of engineering and robotics.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"63 ","pages":"Article 101982"},"PeriodicalIF":5.1,"publicationDate":"2025-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143131177","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}

{"title":"Hybrid photovoltaic and thermoelectric generator systems with thermal wheel Ventilation: A sustainable approach to residential heating and cooling","authors":"Tian Congxiang ,&nbsp;Zhu Guoqing ,&nbsp;Yang Yong","doi":"10.1016/j.jestch.2025.101968","DOIUrl":"10.1016/j.jestch.2025.101968","url":null,"abstract":"<div><div>The growing need for sustainable energy solutions in residential buildings has driven research into renewable energy integration. While photovoltaic (PV) systems are well-explored, the combination of PV with thermal wheel (TW) systems and thermoelectric generator (TEG) units in thermoelectric ventilation (TEV) systems remains less studied. This paper investigates a hybrid system combining a concentrating PV (CPV)-TEG and a TW-TEV system for residential heating and cooling. Using energy and exergy analysis, two performance indicators, the Energy Proficiency Indicator (PIen) and the Exergy Proficiency Indicator (PIex), were introduced and calculated for a building in Jingzhou, Hubei, China. Results revealed peak PIen and PIex values of 2.44 and 33.55 in September and April, respectively. Additionally, increasing the number of thermoelectric coolers from 10 to 50 enhanced average yearly PIen and PIex by 60.45% and 81.32%. This study’s findings are significant for urban planners and engineers aiming to reduce energy consumption and emissions, offering a practical approach to sustainable building technologies.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"62 ","pages":"Article 101968"},"PeriodicalIF":5.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143168703","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}

{"title":"State-of-the-art and future trends in electric vehicle charging infrastructure: A review","authors":"Sudev V.,&nbsp;Sindhu M.R.","doi":"10.1016/j.jestch.2025.101946","DOIUrl":"10.1016/j.jestch.2025.101946","url":null,"abstract":"<div><div>In this era of global warming and climate change, the trend towards “GO GREEN” is gaining significant attention because of its advantages for the world in general and society in particular. One of the most significant aspects of this “GO GREEN” is the sustainable mobility sector, which focuses not only on reducing the usage of fossil fuels but also on enhancing the efficiency of the transportation system. The most critical infrastructure required in the sustainable transportation ecosystem is the Electric Vehicle Charging Stations (EVCS) as it plays a crucial role in increasing the acceptance of Electric Vehicles (EVs). However, a detailed study of the existing EVCS infrastructure is vital for further deepening the research in this area so that future EVCS infrastructure can be developed by overcoming current shortcomings and addressing the needs of the EV ecosystem. Given this fact, this paper investigates in detail the significant aspects, current progress, and future trends associated with the EVCS and its sub-units like power converters, Energy Storage Systems (ESS), charging technologies, etc. This paper primarily focuses on the power converters and the charging technologies as this forms the ‘heart’ of an EVCS, while also elaborating on other associated topics like ESS, EVCS classification, etc. This paper also discusses in detail the issues faced while charging EVs in extreme weather conditions by considering the case of EVs not charging in Chicago in January 2024 and also discusses how the new charging techniques like Constant Current Constant Temperature Constant Voltage (CCCTCV) can help in overcoming such issues. Various important papers in these areas, their contributions, and shortcomings are deliberated in this paper. This paper also highlights the important power converter topologies and charging technologies, their features, characteristics, advantages and disadvantages, and their application scope in the EV ecosystem. The combination of conventional power converters with advanced control techniques, dynamic charging techniques, and post-Li-ion ESS will help in building a futuristic, reliable, and resilient EVCS infrastructure.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"62 ","pages":"Article 101946"},"PeriodicalIF":5.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143169382","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}

{"title":"Optimizing intelligent residential scheduling based on policy black box and adaptive clustering federated deep reinforcement learning","authors":"Wei Zhang,&nbsp;Yiyang Li","doi":"10.1016/j.jestch.2025.101951","DOIUrl":"10.1016/j.jestch.2025.101951","url":null,"abstract":"<div><div>In the context of user-side demand response, flexible resources in buildings such as air conditioners and electric vehicles are characterized by small individual capacities, large aggregate scales, and geographically dispersed distributions, necessitating integration by intelligence buildings (IRs). However, the optimization scheduling of IR clusters often involves detailed energy consumption data, posing privacy issues such as revealing household routines. The traditional aggregator-IRs bi-level architecture typically employs centralized or game-theoretic strategies for optimization scheduling, which struggle to balance efficiency and privacy simultaneously. To address this issue, this paper proposes a bi-level optimization scheduling strategy that balances efficiency and privacy. First, deep reinforcement learning models are established for both the aggregator and the IRs to address efficiency. Then, the trained demand response models of the IRs are encapsulated into strategy black boxes and uploaded to the aggregator’s deep reinforcement learning model. Throughout this process, the aggregator remains unaware of the user-side data, thus protecting user privacy. Additionally, considering that training IR strategy black box models is a parallel and similar process, this paper introduces the paradigm of federated learning to reduce learning costs and improve training efficiency on the IRs side. Furthermore, an adaptive clustering federated deep reinforcement learning method is proposed to address the heterogeneity of the IRs. Finally, case studies demonstrate the feasibility and effectiveness of the proposed method.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"62 ","pages":"Article 101951"},"PeriodicalIF":5.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143170275","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}

{"title":"Experimental investigation of the performance and energy consumption efficiency of elliptical gear hydraulic pump and evaluation by Taguchi method","authors":"Mithat Yanikören","doi":"10.1016/j.jestch.2024.101941","DOIUrl":"10.1016/j.jestch.2024.101941","url":null,"abstract":"<div><div>This study presents an approach based on the Taguchi method to evaluate the energy consumption performance of spur and elliptical gear hydraulic pumps. Output flow is one of the essential indicators of gear pump performance. Taguchi L8 experimental design with two factors and mixed level design was applied to determine the gear pump performances. Rotational speed (200, 600, 1000 and 1400 rpm) and pump type (spur and elliptical) is selected as experimental parameters. Thus, the effect of the rotational speed of an elliptical gear pump on the gear pump flow and energy consumption performance is experimentally analyzed. The results of the analysis showed that the elliptical gear pump delivered approximately 120 % higher volumetric flow rate. In terms of pressure performance, the elliptical gear pump showed an advantage of around 87 %, providing higher pressure, especially at low speeds. In terms of energy consumption, the elliptical gear pump has been experimentally proven to consume approximately 145 % less energy at low speeds. It is also found that there is less temperature difference in the hydraulic fluid during operation of the elliptical gear pump. In addition, the elliptical gear pump exhibited a similar behavior tendency under high-loads as in the partia-loaded case.Elliptical gear pump can be said to be a new type of volumetric pump, which is better than the commonly used spur gear pump, especially in terms of output flow and energy consumption performance.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"62 ","pages":"Article 101941"},"PeriodicalIF":5.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143170276","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}

{"title":"A review of artificial intelligence techniques for optimizing friction stir welding processes and predicting mechanical properties","authors":"Roosvel Soto-Diaz ,&nbsp;Mauricio Vásquez-Carbonell ,&nbsp;Jose Escorcia-Gutierrez","doi":"10.1016/j.jestch.2025.101949","DOIUrl":"10.1016/j.jestch.2025.101949","url":null,"abstract":"<div><div>The implementation of artificial intelligence (AI) has been instrumental in the optimization of friction stir welding (FSW) parameters. Artificial intelligence (AI) techniques, including artificial neural networks (ANN) and adaptive neuro-fuzzy inference systems (ANFIS), were utilized to predict mechanical properties such as ultimate tensile strength (UTS) and optimize pivotal welding parameters, such as rotational speed, feed rate, axial force, and tilt angle. These methodologies enabled precise real-time control, thus improving the quality and consistency of the resulting welded joints. The objective of this study was to conduct a comprehensive review of the application of artificial intelligence (AI) techniques in friction stir welding (FSW). The objective of the study was to synthesize existing research using AI to predict mechanical properties and optimize welding parameters. Furthermore, the study aimed to illustrate how artificial intelligence has improved the caliber and dependability of FSW joints through real-time observation and defect identification. A systematic literature review was conducted according to the PRISMA guidelines to identify relevant studies on the utilization of AI in FSW. A search algorithm was applied to databases such as ScienceDirect and Web of Science, resulting in the identification of 27 relevant scientific papers. The selection criteria were designed to identify studies that employed AI techniques for the prediction and optimization of FSW parameters. The principal findings indicated the pervasive deployment of 34 distinct AI techniques, with ANN being the most prevalent. Hybrid models combining AI with optimization algorithms, such as particle swarm optimization (PSO) and genetic algorithms, were particularly effective. These models demonstrated high precision in predicting tensile strength and detecting internal defects, significantly improving joint quality. In conclusion, AI applications in FSW have proven essential for optimizing welding processes, with hybrid AI models showing superior performance. The continued integration of AI in FSW is expected to enhance the efficiency and reliability of welding operations, offering significant industrial advantages.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"62 ","pages":"Article 101949"},"PeriodicalIF":5.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143170284","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}

{"title":"Front Matter 1 - Full Title Page (regular issues)/Special Issue Title page (special issues)","authors":"","doi":"10.1016/S2215-0986(25)00046-1","DOIUrl":"10.1016/S2215-0986(25)00046-1","url":null,"abstract":"","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"62 ","pages":"Article 101991"},"PeriodicalIF":5.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143133990","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}

{"title":"A dual-band microwave sensor for glucose measurements utilizing an enclosed split ring metamaterial-based array","authors":"Abhishek Kandwal ,&nbsp;Ziheng Ju ,&nbsp;Louis W.Y. Liu ,&nbsp;Rohit Jasrotia ,&nbsp;Choon Kit Chan ,&nbsp;Zedong Nie ,&nbsp;Ali M. Almuhlafi ,&nbsp;Hamsakutty Vettikalladi","doi":"10.1016/j.jestch.2025.101947","DOIUrl":"10.1016/j.jestch.2025.101947","url":null,"abstract":"<div><div>Diabetes is currently a major public health concern, partly exacerbated by the recent outbreak of coronavirus. Most of the published EM-wave based glucose sensors of this date allow a glucose concentration to be determined through a resonance frequency shift, inevitably with a questionable accuracy. To overcome the accuracy problem, a dual-band glucose sensor with dimensions 50 mm × 20 mm is proposed in this work to enable a glucose concentration to be measured at one resonance frequency band and cross-checked at another. An array of split-ring resonators (SRRs) was fabricated at a rectangular sensing area on the top surface of a 0.3 mm thick PET substrate, forming a metasurface with dual resonance bands at 4.5 GHz and 9.2 GHz. The backside of the PET substrate was fabricated with a defected ground plane designed to suppress the Q-factor associated with 4.5 GHz while leaving the Q-factor associated with 9.2 GHz unchanged. During a glucose concentration measurement, a drop of glucose solution was applied to the rectangular metasurface sensing area. The glucose concentration was determined in the form of a resonance frequency shift of the reflection coefficient at 4.5 GHz and a magnitude change of the reflection coefficient at 9.2 GHz. Consistent with our theoretical prediction, the fabricated sensor has indeed exhibited a dual resonant band characteristics, with one resonance occurring at 4.5 GHz and the other at 9.2 GHz. By measuring the reflection coefficient near 4.5 GHz, a positive and linear correlation in the log scale was observed between the glucose concentration and the resonant frequency shift with a sensitivity of 0.6 <span><math><mrow><mi>MHz</mi><mo>/</mo><mrow><mo>(</mo><mi>mg</mi><mspace></mspace><mspace></mspace><msup><mrow><mi>dL</mi></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup><mo>)</mo></mrow></mrow></math></span>. At 9.2 GHz, there was no significant resonant frequency shift with varying glucose concentrations, but the magnitude of the reflection coefficient changed with the glucose concentration nonlinearly in an amount-dependent manner, with a sensitivity of 16.6 dB per unit glucose concentration within the clinical diabetic range. Overall, the log scale of the glucose concentration has exhibited a positive and linear correlation within the clinical diabetic range with both the resonant frequency shift at 4.5 GHz and the magnitude change at 9.2 GHz, thereby allowing the glucose concentration to be measured at 4.5 GHz and further cross-checked at 9.2 GHz at the same time.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"62 ","pages":"Article 101947"},"PeriodicalIF":5.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143168704","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}