Pub Date : 2025-09-12DOI: 10.1016/j.jestch.2025.102178
Roman Sotner , Ladislav Polak , Lukas Langhammer , Darius Andriukaitis
This paper presents the implementation of commercially available CMOS devices with unfavorable properties, such as low output resistance, in an application designed to mitigate these limitations. By employing a specific topology and considering key design parameters, the proposed approach minimizes the adverse effects of low output resistance. This design focuses on a linearized operational transconductance amplifier (OTA) based on CMOS transistors, featuring with very low output resistance. This OTA is further integrated into an LC oscillator, where the associated disadvantages are suppressed through a specialized topology and careful selection of parameter values that are unaffected by the low OTA output resistance. The operational verification targets a frequency range of several hundred kHz and a linearly processed voltage range of several hundred mV. The linearized OTA-based low-gain amplifier/attenuator offers a linearity error within −7% (±500 mV). The proposed OTA implementation in the oscillator introduces highly simplified method for adjusting the oscillation condition using a single grounded element while minimizing the adverse effects of low output resistance of OTA. Additionally, the tunability of the oscillator using varactor diodes achieving a range from 120 kHz to 273 kHz for a voltage varying from 0 V to 5 V.
{"title":"Design adaptation of an electronically tunable oscillator using a low performance linearized CMOS operational transconductance amplifier","authors":"Roman Sotner , Ladislav Polak , Lukas Langhammer , Darius Andriukaitis","doi":"10.1016/j.jestch.2025.102178","DOIUrl":"10.1016/j.jestch.2025.102178","url":null,"abstract":"<div><div>This paper presents the implementation of commercially available CMOS devices with unfavorable properties, such as low output resistance, in an application designed to mitigate these limitations. By<!--> <!-->employing a specific topology and considering key design parameters, the proposed approach minimizes the adverse effects of low output resistance. This design focuses on a linearized operational transconductance amplifier (OTA) based on CMOS transistors, featuring with very low output resistance. This OTA is further integrated into an LC oscillator, where the associated disadvantages are suppressed through a specialized topology and careful selection of parameter values that are unaffected by the low OTA output resistance. The operational verification targets a frequency range of several hundred kHz and a linearly processed voltage range of several hundred mV. The linearized OTA-based low-gain amplifier/attenuator offers a linearity error within −7% (±500 mV). The proposed OTA implementation in the oscillator introduces highly simplified method for adjusting the oscillation condition using a single grounded element while minimizing the adverse effects of low output resistance of OTA. Additionally, the tunability of the oscillator using varactor diodes achieving a range from 120 <!--> <!-->kHz to 273 kHz for a voltage varying from 0 V to 5 V.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"71 ","pages":"Article 102178"},"PeriodicalIF":5.4,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145049873","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 : 2025-09-09DOI: 10.1016/j.jestch.2025.102172
Mustafa Yıldırım, Mahmut Ahmet Gözel
In this study, an innovative microwave sensor was designed based on a Complementary Elliptical Electric-LC (CEE-LC) resonator structure compact with a Branch Line Coupler (BLC) that can determine milk fat content and perform adulteration analysis. Firstly, the fat content measurements of the milk used in the study were performed using a Lactoscan brand milk analyzer to determine the proposed sensor performance: buffalo milk (BM) was determined to have 12.19 % fat content, goat milk (GM) 5.02 %, Jersey milk (JM) 6.81 %, and Simmental milk (SM) 4.10 %. Then, adulterated milk samples were created using JM-BM and water-BM mixtures to perform adulteration analysis using the proposed sensor. In the final stage of sample preparation, a common dielectric probe was used to measure the permittivity and electrical conductivity of all milk samples in the 10 MHz to 20 GHz frequency range. The resonance frequency of the S21, which provides transmission-zero (TZ) in the S-parameter of the proposed sensor, was determined to be 7.03 GHz. The CEE-LC resonator structure in the sensor was positioned on the ground surface projection of the transmission line between “port 1” and “port 2”. In the BM-water adulteration analysis, the resonance frequencies of the sensor at parameter S21 were measured as 2.40 GHz for only BM sample, 2.335 GHz for BM with 20 % water mixture, 2.295 GHz for BM with 40 % water, 2.260 GHz for BM with 60 % water, 2.215 GHz for BM with 80 % water, and 2.105 GHz for only water. Similarly, the proposed sensor detected the resonance frequencies of the S21 parameter in the adulteration analysis performed when JM mixed with the BM as 2.395 GHz for 20 % addition, 2.385 GHz for 40 % addition, 2.370 GHz for 60 % addition, 2.325 GHz for 80 % addition, and 2.32 GHz for pure JM. To increase the usability of the sensor in field applications, a portable measurement system was developed by integrating a voltage-controlled RF oscillator and a power detector. In DC voltage-based measurements, the output voltage increased from 1.23 V to 1.56 V as the milk fat content increased, indicating a correlation between the DC output voltage and fat content. In the adulteration analysis, it decreased from 1.55 V to 1.18 V as the water content in buffalo milk increased. During DC analyses, the 2.4 GHz resonant frequency of the BM, which has the TZ value for parameter S21 in the proposed sensor, was used to determine fat content and adulteration. Literature comparisons revealed that the proposed system exhibits superior performance compared to existing methods, especially in detecting water adulteration in buffalo milk.
{"title":"High-sensitivity microwave sensor for buffalo milk fat rate and adulteration analysis with branch line coupler","authors":"Mustafa Yıldırım, Mahmut Ahmet Gözel","doi":"10.1016/j.jestch.2025.102172","DOIUrl":"10.1016/j.jestch.2025.102172","url":null,"abstract":"<div><div>In this study, an innovative microwave sensor was designed based on a Complementary Elliptical Electric-LC (CEE-LC) resonator structure compact with a Branch Line Coupler (BLC) that can determine milk fat content and perform adulteration analysis. Firstly, the fat content measurements of the milk used in the study were performed using a Lactoscan brand milk analyzer to determine the proposed sensor performance: buffalo milk (BM) was determined to have 12.19 % fat content, goat milk (GM) 5.02 %, Jersey milk (JM) 6.81 %, and Simmental milk (SM) 4.10 %. Then, adulterated milk samples were created using JM-BM and water-BM mixtures to perform adulteration analysis using the proposed sensor. In the final stage of sample preparation, a common dielectric probe was used to measure the permittivity and electrical conductivity of all milk samples in the 10 MHz to 20 GHz frequency range. The resonance frequency of the S<sub>21</sub>, which provides transmission-zero (TZ) in the S-parameter of the proposed sensor, was determined to be 7.03 GHz. The CEE-LC resonator structure in the sensor was positioned on the ground surface projection of the transmission line between “port 1” and “port 2”. In the BM-water adulteration analysis, the resonance frequencies of the sensor at parameter S<sub>21</sub> were measured as 2.40 GHz for only BM sample, 2.335 GHz for BM with 20 % water mixture, 2.295 GHz for BM with 40 % water, 2.260 GHz for BM with 60 % water, 2.215 GHz for BM with 80 % water, and 2.105 GHz for only water. Similarly, the proposed sensor detected the resonance frequencies of the S<sub>21</sub> parameter in the adulteration analysis performed when JM mixed with the BM as 2.395 GHz for 20 % addition, 2.385 GHz for 40 % addition, 2.370 GHz for 60 % addition, 2.325 GHz for 80 % addition, and 2.32 GHz for pure JM. To increase the usability of the sensor in field applications, a portable measurement system was developed by integrating a voltage-controlled RF oscillator and a power detector. In DC voltage-based measurements, the output voltage increased from 1.23 V to 1.56 V as the milk fat content increased, indicating a correlation between the DC output voltage and fat content. In the adulteration analysis, it decreased from 1.55 V to 1.18 V as the water content in buffalo milk increased. During DC analyses, the 2.4 GHz resonant frequency of the BM, which has the TZ value for parameter S<sub>21</sub> in the proposed sensor, was used to determine fat content and adulteration. Literature comparisons revealed that the proposed system exhibits superior performance compared to existing methods, especially in detecting water adulteration in buffalo milk.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"71 ","pages":"Article 102172"},"PeriodicalIF":5.4,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145020752","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 : 2025-09-06DOI: 10.1016/j.jestch.2025.102183
Mohamed Khamies , Ahmed Fathy , Mohamed Hashem , Hammad Alnuman , Hossam Hassan Ali
Optimal integration of distributed generators (DGs) into unbalanced power distribution networks (PDNs) is critical for minimizing power losses and enhancing voltage stability. So, this study applies the novel walrus optimizer (WO) to determine the optimal placement, sizing, and power factors of DGs in unbalanced PDNs using the IEEE 123-bus system as realistic unbalanced network representative of real-world operating conditions. The unbalanced distribution IEEE 123-bus system is simulated in OpenDSS while the WO approach is implemented in Matlab and linked to OpenDSS for co-simulation. The primary goal is to reduce the network’s total active power loss while constraints of voltage and current restrictions, voltage control tap position limitations, DG generated power limits, and generation-demand power balance restrictions are examined. The proposed WO is rigorously benchmarked against established metaheuristics including skill optimization algorithm (SOA), giant trevally optimizer (GTO), osprey optimization algorithm (OOA), and equilibrium optimizer (EO). The fetched results demonstrate the WO’s superior efficacy as it succeeded in mitigating the network power loss by 70.48%, 83.47%, and 84.72% with installing Type I (active), Type II (reactive), and Type III (combined active and reactive) DGs, respectively. The corresponding voltage deviations are reduced by 18.44%, 16.41%, and 32.15%. These improvements significantly surpass those achieved by comparative algorithms highlighting the WO’s robustness in avoiding local optima and achieving faster convergence. The study concludes that, the WO effectively addresses the nonlinear complexities of PDNs, offering reliable tool for utilities to optimize DG integration. Its ability to concurrently optimize location, capacity, and power factors ensures tangible gains in grid efficiency and stability.
{"title":"A new methodology for optimal penetration of multiple type distributed generators based on large-scale unbalanced power distribution network","authors":"Mohamed Khamies , Ahmed Fathy , Mohamed Hashem , Hammad Alnuman , Hossam Hassan Ali","doi":"10.1016/j.jestch.2025.102183","DOIUrl":"10.1016/j.jestch.2025.102183","url":null,"abstract":"<div><div>Optimal integration of distributed generators (DGs) into unbalanced power distribution networks (PDNs) is critical for minimizing power losses and enhancing voltage stability. So, this study applies the novel walrus optimizer (WO) to determine the optimal placement, sizing, and power factors of DGs in unbalanced PDNs using the IEEE 123-bus system as realistic unbalanced network representative of real-world operating conditions. The unbalanced distribution IEEE 123-bus system is simulated in OpenDSS while the WO approach is implemented in Matlab and linked to OpenDSS for co-simulation. The primary goal is to reduce the network’s total active power loss while constraints of voltage and current restrictions, voltage control tap position limitations, DG generated power limits, and generation-demand power balance restrictions are examined. The proposed WO is rigorously benchmarked against established metaheuristics including skill optimization algorithm (SOA), giant trevally optimizer (GTO), osprey optimization algorithm (OOA), and equilibrium optimizer (EO). The fetched results demonstrate the WO’s superior efficacy as it succeeded<!--> <!-->in mitigating the network power loss by 70.48%, 83.47%, and 84.72% with installing Type I (active), Type II (reactive), and Type III (combined active and reactive) DGs, respectively. The corresponding voltage deviations are reduced by<!--> <!-->18.44%, 16.41%, and 32.15%. These improvements significantly surpass those achieved by comparative algorithms highlighting the WO’s robustness in avoiding local optima and achieving faster convergence. The study concludes that, the WO effectively addresses the nonlinear complexities of PDNs, offering reliable tool for utilities to optimize DG integration. Its ability to concurrently optimize location, capacity, and power factors ensures tangible gains in grid efficiency and stability.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"70 ","pages":"Article 102183"},"PeriodicalIF":5.4,"publicationDate":"2025-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145003669","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 : 2025-09-06DOI: 10.1016/j.jestch.2025.102165
Md. Nimul Hasan , Md. Fatin Ishraque , Sk.A. Shezan , Innocent Kamwa , Naveed Ahmad
In this study, a hybrid microgrid approach to energy management is demonstrated using the newly introduced Twin Fang Optimization (TFO) algorithm, which imitates the key characteristics of natural predator–prey dynamics by integrating the Grey Wolf Optimization (GWO) and Whale Optimization Algorithm (WOA). This novel metaheuristic methodology was specifically developed to overcome the limitations of conventional algorithms, aiming for more efficient resource distribution among solar PV, wind, and battery storage systems. Within this work, the proposed TFO algorithm was applied to optimize hybrid microgrids in two geographically distinct sites in Bangladesh and Canada having two unique climatic and operational conditions to test the algorithm’s versatility. The results show that TFO significantly improves system performance across multiple evaluation metrics. It achieved Multi-Criteria Function values of 0.03825 in Bangladesh and 0.03725 in Canada, outperforming GWO, WOA, and PSO. Additionally, the energy levelized costs were reduced to $0.0354/kWh in Bangladesh and $0.0361/kWh in Canada. In both locations, the system maintained the full Sustainable Energy Score (SES), ensuring zero carbon emission and energy loss. Furthermore, the Power Supply Reliability Index (PSRI) was minimized to 1.25% in Bangladesh and 2.45% in Canada, indicating a high system reliability. The results demonstrate that TFO significantly outperforms both GWO and WOA in three out of four test cases, with p-values consistently below the 0.05 threshold, confirming the robustness and effectiveness of TFO. These findings suggest that TFO is a promising approach for optimizing energy systems in real-world hybrid microgrid applications. A comparative performance analysis underscores the robustness, faster convergence, and stability of the TFO algorithm against other well-established methods. Overall, this research presents TFO as a promising tool for smart energy systems, setting a new benchmark for efficient and resilient hybrid microgrid management under diverse regional conditions.
{"title":"Novel twin fang algorithm for advanced optimization of energy coordination in hybrid power systems","authors":"Md. Nimul Hasan , Md. Fatin Ishraque , Sk.A. Shezan , Innocent Kamwa , Naveed Ahmad","doi":"10.1016/j.jestch.2025.102165","DOIUrl":"10.1016/j.jestch.2025.102165","url":null,"abstract":"<div><div>In this study, a hybrid microgrid approach to energy management is demonstrated using the newly introduced Twin Fang Optimization (TFO) algorithm, which imitates the key characteristics of natural predator–prey dynamics by integrating the Grey Wolf Optimization (GWO) and Whale Optimization Algorithm (WOA). This novel metaheuristic methodology was specifically developed to overcome the limitations of conventional algorithms, aiming for more efficient resource distribution among solar PV, wind, and battery storage systems. Within this work, the proposed TFO algorithm was applied to optimize hybrid microgrids in two geographically distinct sites in Bangladesh and Canada having two unique climatic and operational conditions to test the algorithm’s versatility. The results show that TFO significantly improves system performance across multiple evaluation metrics. It achieved Multi-Criteria Function values of 0.03825 in Bangladesh and 0.03725 in Canada, outperforming GWO, WOA, and PSO. Additionally, the energy levelized costs were reduced to $0.0354/kWh in Bangladesh and $0.0361/kWh in Canada. In both locations, the system maintained the full Sustainable Energy Score (SES), ensuring zero carbon emission and energy loss. Furthermore, the Power Supply Reliability Index (PSRI) was minimized to 1.25% in Bangladesh and 2.45% in Canada, indicating a high system reliability. The results demonstrate that TFO significantly outperforms both GWO and WOA in three out of four test cases, with p-values consistently below the 0.05 threshold, confirming the robustness and effectiveness of TFO. These findings suggest that TFO is a promising approach for optimizing energy systems in real-world hybrid microgrid applications. A comparative performance analysis underscores the robustness, faster convergence, and stability of the TFO algorithm against other well-established methods. Overall, this research presents TFO as a promising tool for smart energy systems, setting a new benchmark for efficient and resilient hybrid microgrid management under diverse regional conditions.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"70 ","pages":"Article 102165"},"PeriodicalIF":5.4,"publicationDate":"2025-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145003670","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}
In today’s evolving energy landscape, hybrid power systems integrating renewable and conventional sources are increasingly adopted to enhance sustainability. However, maintaining frequency stability remains a challenge due to the intermittent and unpredictable nature of renewable energy sources (RESs). This study presents a robust control strategy to enhance frequency regulation in a wind–solar–thermal hybrid grid using an advanced load frequency control (LFC) scheme. The proposed approach combines a novel fractional-order controller, termed fractional order integral accelerated with low-pass filter (N)-proportional tilt derivative (FOIAN-PTD), with coordinated capacitive energy storage (CES) and superconducting magnetic energy storage (SMES) systems. The FOIAN-PTD controller is fine tuned using the newly developed puma optimizer (PO), which outperforms existing algorithms such as GWO, ALO, AOA, ASO, QIO, and WOA in both convergence speed and control performance. Extensive simulations validate the superiority of the proposed method. The FOIAN-PTD controller achieves up to 89.3% improvement in overshoot and 88.9% in undershoot for frequency deviation in area-1 (), 90.7% and 84.3% improvement for area-2 (), and 95.1% and 90.6% improvement in tie-line power deviation (ΔPtie), respectively, when compared with traditional PID and recent FO controllers. Moreover, the CES integrated with FOIAN-PTD significantly outperforms SMES in dynamic response, further enhancing grid reliability under varying renewable penetration scenarios. Overall, this research provides a scalable and high-performance LFC framework for modern hybrid power grid, offering enhanced frequency stability and resilience.
{"title":"PO-optimized cascaded FOIAN-PTD strategy for frequency control of wind-PV-thermal power system with energy storage systems","authors":"Alaa A. Mahmoud , Khairy Sayed , Amil Daraz , Yogendra Arya , Mohamed Khamies","doi":"10.1016/j.jestch.2025.102173","DOIUrl":"10.1016/j.jestch.2025.102173","url":null,"abstract":"<div><div>In today’s evolving energy landscape, hybrid power systems integrating renewable and conventional sources are increasingly adopted to enhance sustainability. However, maintaining frequency stability remains a challenge due to the intermittent and unpredictable nature of renewable energy sources (RESs). This study presents a robust control strategy to enhance frequency regulation in a wind–solar–thermal hybrid grid using an advanced load frequency control (LFC) scheme. The proposed approach combines a novel fractional-order controller, termed fractional order integral accelerated with low-pass filter (N)-proportional tilt derivative (FOIAN-PTD), with coordinated capacitive energy storage (CES) and superconducting magnetic energy storage (SMES) systems. The FOIAN-PTD controller is fine tuned using the newly developed puma optimizer (PO), which outperforms existing algorithms such as GWO, ALO, AOA, ASO, QIO, and WOA in both convergence speed and control performance. Extensive simulations validate the superiority of the proposed method. The FOIAN-PTD controller achieves up to 89.3% improvement in overshoot and 88.9% in undershoot for frequency deviation in area-1 (<span><math><mrow><mi>Δ</mi><msub><mi>f</mi><mn>1</mn></msub></mrow></math></span>), 90.7% and 84.3% improvement for area-2 (<span><math><mrow><mi>Δ</mi><msub><mi>f</mi><mn>2</mn></msub></mrow></math></span>), and 95.1% and 90.6% improvement in tie-line power deviation (ΔP<sub>tie</sub>), respectively, when compared with traditional PID and recent FO controllers. Moreover, the CES integrated with FOIAN-PTD significantly outperforms SMES in dynamic response, further enhancing grid reliability under varying renewable penetration scenarios. Overall, this research provides a scalable and high-performance LFC framework for modern hybrid power grid, offering enhanced frequency stability and resilience.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"70 ","pages":"Article 102173"},"PeriodicalIF":5.4,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144996504","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 : 2025-08-30DOI: 10.1016/j.jestch.2025.102177
Menglei Zhang , Liwei Zhang , Lu Shen
Hybrid magnetic levitation system compared with pure electromagnetic levitation system, because of the introduction of permanent magnets, the hybrid levitation system is more sensitive to parameter uncertainty and external disturbance. The traditional control strategy is unable to meet the operational requirements of the hybrid levitation system. To solve this problem, an adaptive super-twisting sliding mode controller based on a neural network is designed to address unknown parameters and external disturbance. Firstly, this study analyses the impact of the introduction of permanent magnets on the controllability and safety of the system. An adaptive sliding mode controller is designed. To address the issue of model parameter uncertainty, a neural network is employed to fit the unknown quantities. Then, to further solve the chattering issue on the platform in the face of disturbances, an adaptive super-twisting controller was developed and designed based on the neural network controller. Finally, related experimental verification was carried out on a hybrid levitation experimental platform. The experimental results indicate that the proposed control strategy is able to maintain stable levitation of the platform even under external disturbance and ensure the airgap tracking and levitation safety of the system.
{"title":"Neural network-based adaptive super-twisting sliding mode control for hybrid magnetic levitation system with external disturbance","authors":"Menglei Zhang , Liwei Zhang , Lu Shen","doi":"10.1016/j.jestch.2025.102177","DOIUrl":"10.1016/j.jestch.2025.102177","url":null,"abstract":"<div><div>Hybrid magnetic levitation system compared with pure electromagnetic levitation system, because of the introduction of permanent magnets, the hybrid levitation system is more sensitive to parameter uncertainty and external disturbance. The traditional control strategy is unable to meet the operational requirements of the hybrid levitation system. To solve this problem, an adaptive super-twisting sliding mode controller based on a neural network is designed to address unknown parameters and external disturbance. Firstly, this study analyses the impact of the introduction of permanent magnets on the controllability and safety of the system. An adaptive sliding mode controller is designed. To address the issue of model parameter uncertainty, a neural network is employed to fit the unknown quantities. Then, to further solve the chattering issue on the platform in the face of disturbances, an adaptive super-twisting controller was developed and designed based on the neural network controller. Finally, related experimental verification was carried out on a hybrid levitation experimental platform. The experimental results indicate that the proposed control strategy is able to maintain stable levitation of the platform even under external disturbance and ensure the airgap tracking and levitation safety of the system.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"70 ","pages":"Article 102177"},"PeriodicalIF":5.4,"publicationDate":"2025-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144916434","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 : 2025-08-28DOI: 10.1016/j.jestch.2025.102175
Mustafa Güler , Mesut Samastı , Melih Yücesan , Muhammet Gül , Erkan Çelik , Miraç Nur Ciner , Ömer Algorabi
The rapid increase in municipal solid waste (MSW) generation, driven by population growth and unplanned urbanization, has made the location of organic waste collection and disposal facilities a critical issue for metropolitan cities. Improper waste management practices threaten environmental sustainability, human health, and urban futures. This study applies multicriteria decision-making (MCDM) methods to identify the optimal placement for a central composting facility in Istanbul. A novel MCDM mechanism was developed, building on existing methods and addressing a gap in the literature. While determining the criteria, academic studies on this subject were researched in depth and the criteria used in these studies were brought together to obtain 28 criteria. The study assessed 28 criteria using the Bayesian Best-Worst Method (BWM) to determine their relative importance. These weights were then integrated into a Geographic Information System (GIS) to produce a suitability map, highlighting the most appropriate locations for the facility. Based on this analysis, the Çatalca Karacabey region was identified as the optimal site, ensuring reduced environmental impact and improved efficiency in organic waste management. The study contributes both theoretically and practically to the field, offering a robust framework for sustainable waste facility siting and providing actionable insights for urban governance. The study provides valuable insights for facility siting and urban governance, while highlighting areas for future research.
{"title":"Selection of the central composting facility for organic wastes through the Bayesian best worst method and Geographic information system incorporation: The case of Istanbul","authors":"Mustafa Güler , Mesut Samastı , Melih Yücesan , Muhammet Gül , Erkan Çelik , Miraç Nur Ciner , Ömer Algorabi","doi":"10.1016/j.jestch.2025.102175","DOIUrl":"10.1016/j.jestch.2025.102175","url":null,"abstract":"<div><div>The rapid increase in municipal solid waste (MSW) generation, driven by population growth and unplanned urbanization, has made the location of organic waste collection and disposal facilities a critical issue for metropolitan cities. Improper waste management practices threaten environmental sustainability, human health, and urban futures. This study applies multicriteria decision-making (MCDM) methods to identify the optimal placement for a central composting facility in Istanbul. A novel MCDM mechanism was developed, building on existing methods and addressing a gap in the literature. While determining the criteria, academic studies on this subject were researched in depth and the criteria used in these studies were brought together to obtain 28 criteria. The study assessed 28 criteria using the Bayesian Best-Worst Method (BWM) to determine their relative importance. These weights were then integrated into a Geographic Information System (GIS) to produce a suitability map, highlighting the most appropriate locations for the facility. Based on this analysis, the Çatalca Karacabey region was identified as the optimal site, ensuring reduced environmental impact and improved efficiency in organic waste management. The study contributes both theoretically and practically to the field, offering a robust framework for sustainable waste facility siting and providing actionable insights for urban governance. The study provides valuable insights for facility siting and urban governance, while highlighting areas for future research.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"70 ","pages":"Article 102175"},"PeriodicalIF":5.4,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144908692","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 : 2025-08-28DOI: 10.1016/j.jestch.2025.102174
Ngoc-Tu Do , Trung Thanh Tran , Quoc Hoa Pham , Vu Khac Trai
This paper presents a nonlinear transient thermoelastic analysis of functionally graded sandwich (FGSW) plates with a metal core and FGM skin layers resting on partially elastic foundations (p-EF). A refined first-order shear deformation theory (r-FSDT) combined with Kármán-type geometric nonlinearity is employed, formulated using a weak-form Q4 finite element. The study incorporates temperature conduction through the plate thickness and accounts for temperature-dependent material properties, capturing realistic thermal effects. The governing equations are derived via Hamilton’s principle and solved by the Newmark-β time integration method coupled with Newton–Raphson iteration. The proposed approach’s accuracy is verified against available benchmark solutions. The novelty of this work lies in systematically investigating the nonlinear transient response of FGSW plates under dynamic loading in the presence of p-EF, which has received limited attention in the literature. Furthermore, a detailed parametric study examines the effects of geometrical parameters, material properties, foundation characteristics, and boundary conditions (BCs) on the dynamic behavior of FGSW plates.
{"title":"The nonlinear transient thermoelastic analysis of functionally graded sandwich plates rested on partially elastic foundations","authors":"Ngoc-Tu Do , Trung Thanh Tran , Quoc Hoa Pham , Vu Khac Trai","doi":"10.1016/j.jestch.2025.102174","DOIUrl":"10.1016/j.jestch.2025.102174","url":null,"abstract":"<div><div>This paper presents a nonlinear transient thermoelastic analysis of functionally graded sandwich (FGSW) plates with a metal core and FGM skin layers resting on partially elastic foundations (p-EF). A refined first-order shear deformation theory (r-FSDT) combined with Kármán-type geometric nonlinearity is employed, formulated using a weak-form Q4 finite element. The study incorporates temperature conduction through the plate thickness and accounts for temperature-dependent material properties, capturing realistic thermal effects. The governing equations are derived via Hamilton’s principle and solved by the Newmark-β time integration method coupled with Newton–Raphson iteration. The proposed approach’s accuracy is verified against available benchmark solutions. The novelty of this work lies in systematically investigating the nonlinear transient response of FGSW plates under dynamic loading in the presence of p-EF, which has received limited attention in the literature. Furthermore, a detailed parametric study examines the effects of geometrical parameters, material properties, foundation characteristics, and boundary conditions (BCs) on the dynamic behavior of FGSW plates.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"70 ","pages":"Article 102174"},"PeriodicalIF":5.4,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144908691","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}
This study aims to contribute to the United Nations’ Sustainable Development Goal (SDG) 7, which promotes affordable and clean energy by investigating the potential of solar photovoltaic systems (PVS) integration into EV charging infrastructure in evolving power networks for mutual benefits. The objective is to develop a coordinated control strategy for PVS-integrated EV charging stations that ensures seamless grid interaction with enhanced power quality. It focuses on modelling and coordinated control to achieve stable grid integration. Two distinct EV charging stations are considered in this work. Station 1 employs a conventional unidirectional power flow model, drawing power from the three-phase grid’s point of common coupling (PCC). The second station utilizes a PVS-based charging infrastructure connected to the PCC via a three-phase inverter. It facilitates power exchange with the distribution grid and charging stations, which addresses the reliability concerns of the PVS-based charging infrastructure. Coordinated control of the overall system is achieved through the dual Second-Order Generalized Integral (SOGI) based voltage and load current processing loops. This research ensures that the proposed dual SOGI-based controller maintains a unity power factor, reduces total harmonic distortion to below 3%, and eliminates the need for external filters meeting high grid power quality by ensuring power transfer between the grid and any charging stations. The PVS system mitigates harmonics and fulfills the reactive power demands of station 1 and local loads, obviating the necessity for separate filters and compensators. The developed control algorithm was tested on a hardware prototype under various loads and PV side conditions, demonstrating effective harmonics mitigation, reactive power compensation, and grid current balancing. The extensive hardware analysis conducted in steady state and dynamic operating modes confirms that the presented system improves voltage stability by over 20% and cuts network losses by more than 25%, establishing its effectiveness for next-generation sustainable EV infrastructure.
{"title":"PV-integrated coordinated control for enhanced grid performance in next-gen EV charging systems","authors":"Umashankar Subramaniam , S Saravanan , K.R.M Vijayachandrakala , Sivakumar Selvam","doi":"10.1016/j.jestch.2025.102176","DOIUrl":"10.1016/j.jestch.2025.102176","url":null,"abstract":"<div><div>This study aims to contribute to the United Nations’ Sustainable Development Goal (SDG) 7, which promotes affordable and clean energy by investigating the potential of solar photovoltaic systems (PVS) integration into EV charging infrastructure in evolving power networks for mutual benefits. The objective is to develop a coordinated control strategy for PVS-integrated EV charging stations that ensures seamless grid interaction with enhanced power quality. It focuses on modelling and coordinated control to achieve stable grid integration. Two distinct EV charging stations are considered in this work. Station 1 employs a conventional unidirectional power flow model, drawing power from the three-phase grid’s point of common coupling (PCC). The second station utilizes a PVS-based charging infrastructure connected to the PCC via a three-phase inverter. It facilitates power exchange with the distribution grid and charging stations, which addresses the reliability concerns of the PVS-based charging infrastructure. Coordinated control of the overall system is achieved through the dual Second-Order Generalized Integral (SOGI) based voltage and load current processing loops. This research ensures that the proposed dual SOGI-based controller maintains a unity power factor, reduces total harmonic distortion to below 3%, and eliminates the need for external filters meeting high grid power quality by ensuring power transfer between the grid and any charging stations. The PVS system mitigates harmonics and fulfills the reactive power demands of station 1 and local loads, obviating the necessity for separate filters and compensators. The developed control algorithm was tested on a hardware prototype under various loads and PV side conditions, demonstrating effective harmonics mitigation, reactive power compensation, and grid current balancing. The extensive hardware analysis conducted in steady state and dynamic operating modes confirms that the presented system improves voltage stability by over 20% and cuts network losses by more than 25%, establishing its effectiveness for next-generation sustainable EV infrastructure.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"70 ","pages":"Article 102176"},"PeriodicalIF":5.4,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144896356","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 : 2025-08-26DOI: 10.1016/j.jestch.2025.102164
Jiyou Shin , Jongsoo Han , Kyeongbeen Park , Myeongyun Doh , Tuan Luong , Nabih Pico , Hyungpil Moon
This paper introduces a practical approach to handle object tracking and path planning methodology for real-world multi-vehicle autonomous racing, interacting with more than 8 vehicles. Unlike previous autonomous racing systems, which primarily dealt with single or dual races, our proposed algorithm successfully handles real-world multi-vehicle scenarios, demonstrated in the “Autonomous Robot Racing Competition”(ARRC) with nine vehicles. The perception module utilizes a 16-channel LiDAR sensor to detect multiple obstacles on the racing track. To overcome the challenges posed by sparse point clouds, we introduce an orientation compensation method of multi-object detection on sparse point cloud conditions by applying the Extended Kalman Filter(EKF) tracking method. Our algorithm demonstrated 99.6% of the overall orientation accuracy compared to learning based methods that use 64-channel or higher resolution LiDAR. Moreover, it performed better when recognizing small objects with fewer points. The behavior predictive motion planning algorithm predicts dynamic multiple opponents’ trajectories and generates candidate paths considering two racing lanes and the states of other multiple vehicles applying the Frenet-Frame. The proposed algorithm is tested in a custom CARLA simulator for 20 scenarios with multi-vehicle interaction, and its effectiveness is demonstrated in the real-world 2023 ARRC. Our algorithm achieves safe overtaking, avoidance, and following maneuvers through multi-vehicle racing while adhering to the given racing rules.
{"title":"Practical implementation of obstacle avoidance strategies in the truly multi-vehicle Autonomous Robot Racing Competition","authors":"Jiyou Shin , Jongsoo Han , Kyeongbeen Park , Myeongyun Doh , Tuan Luong , Nabih Pico , Hyungpil Moon","doi":"10.1016/j.jestch.2025.102164","DOIUrl":"10.1016/j.jestch.2025.102164","url":null,"abstract":"<div><div>This paper introduces a practical approach to handle object tracking and path planning methodology for real-world multi-vehicle autonomous racing, interacting with more than 8 vehicles. Unlike previous autonomous racing systems, which primarily dealt with single or dual races, our proposed algorithm successfully handles real-world multi-vehicle scenarios, demonstrated in the “Autonomous Robot Racing Competition”(ARRC) with nine vehicles. The perception module utilizes a 16-channel LiDAR sensor to detect multiple obstacles on the racing track. To overcome the challenges posed by sparse point clouds, we introduce an orientation compensation method of multi-object detection on sparse point cloud conditions by applying the Extended Kalman Filter(EKF) tracking method. Our algorithm demonstrated 99.6% of the overall orientation accuracy compared to learning based methods that use 64-channel or higher resolution LiDAR. Moreover, it performed better when recognizing small objects with fewer points. The behavior predictive motion planning algorithm predicts dynamic multiple opponents’ trajectories and generates candidate paths considering two racing lanes and the states of other multiple vehicles applying the Frenet-Frame. The proposed algorithm is tested in a custom CARLA simulator for 20 scenarios with multi-vehicle interaction, and its effectiveness is demonstrated in the real-world 2023 ARRC. Our algorithm achieves safe overtaking, avoidance, and following maneuvers through multi-vehicle racing while adhering to the given racing rules.</div></div>","PeriodicalId":48609,"journal":{"name":"Engineering Science and Technology-An International Journal-Jestech","volume":"70 ","pages":"Article 102164"},"PeriodicalIF":5.4,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144896335","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}
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