Pub Date : 2025-03-01DOI: 10.1016/j.asej.2025.103322
Shahirah Hayati Mohd Salleh , Wan Hanna Melini Wan Mohtar , Khairul Nizam Abdul Maulud , Nuryazmeen Farhan Haron , Nuraziemah Abd Rashid , Nor Aslinda Awang
The complexity of physical processes in an estuary provides challenges to develop a functional and reliable model. There is a lack of systematic method in calibrating and validating the model in reducing the time of processing the model which can take a longer time of analysis. This study presents a systematic calibration and validation approach for the TELEMAC-2D hydrodynamic model of a tropical estuary with high river discharge. Key parameters, including tidal prior current speed, time steps, friction coefficient, iteration, velocity diffusivity, and Courant number, were optimized. Model sensitivity analysis was conducted, and the bottom friction was calibrated using the Nikuradse law. The model achieved strong agreement with observation data (R2 = 0.95, RMSE = 0.17, Ks = 0.32), demonstrating its reliability for simulating tropical estuarine hydrodynamics. This study emphasizes Courant number optimization, enhancing model stability, accuracy, and efficiency for reliable estuarine simulations and informed coastal management.
{"title":"Performance evaluation of high discharge estuarine hydrodynamic model","authors":"Shahirah Hayati Mohd Salleh , Wan Hanna Melini Wan Mohtar , Khairul Nizam Abdul Maulud , Nuryazmeen Farhan Haron , Nuraziemah Abd Rashid , Nor Aslinda Awang","doi":"10.1016/j.asej.2025.103322","DOIUrl":"10.1016/j.asej.2025.103322","url":null,"abstract":"<div><div>The complexity of physical processes in an estuary provides challenges to develop a functional and reliable model. There is a lack of systematic method in calibrating and validating the model in reducing the time of processing the model which can take a longer time of analysis. This study presents a systematic calibration and validation approach for the TELEMAC-2D hydrodynamic model of a tropical estuary with high river discharge. Key parameters, including tidal prior current speed, time steps, friction coefficient, iteration, velocity diffusivity, and Courant number, were optimized. Model sensitivity analysis was conducted, and the bottom friction was calibrated using the Nikuradse law. The model achieved strong agreement with observation data (R<sup>2</sup> = 0.95, RMSE = 0.17, <em>Ks</em> = 0.32), demonstrating its reliability for simulating tropical estuarine hydrodynamics. This study emphasizes Courant number optimization, enhancing model stability, accuracy, and efficiency for reliable estuarine simulations and informed coastal management.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 4","pages":"Article 103322"},"PeriodicalIF":6.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143528692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-01DOI: 10.1016/j.asej.2025.103328
Marwa Mansour
<div><div>This article suggests a millimeter-wave wideband large-data-rate on–off-keying (OOK) transmitter (Tx) analysis, design, and implementation for high-speed systems in 5G Applications. The on–off-keying transmitter comprises of a tunable source of RF signal, a wideband high-speed OOK modulator, and a broadband RF power amplifier (PA). A novel circuit topology for the tunable source of RF signal, which comprises of transformer-tank VCO, Gilbert-frequency doubler (FD), and two-stage driver amplifier (DA). The on–off-keying modulator is built by transconductance transistors cascoded with the switching transistors to obtain high on–off isolation. The broadband PA is constructed depending on the inverse class-F architecture, which comprises of Class-AB driver stage and inverse Class-F power stage with harmonic elimination and output matching networks. A new interleaved U-shaped high-coupling transformer design, a primary capacitor (<span><math><msub><mrow><mi>C</mi></mrow><mrow><mi>P</mi></mrow></msub></math></span>), and a secondary capacitor (<span><math><msub><mrow><mi>C</mi></mrow><mrow><mi>S</mi></mrow></msub></math></span>) are utilized as a triple band high-quality tank-circuit for the proposed VCO. Moreover, the new high-quality on-chip transformers are implemented for input, inter-stage, and output matching of the Tx elements, that are used to improve RF performance. The on–off-keying RF transmitter was designed using a 130 nm CMOS process and realized an output power (<span><math><msub><mrow><mi>P</mi></mrow><mrow><mrow><mi>o</mi></mrow><mrow><mi>u</mi></mrow><mrow><mi>t</mi></mrow></mrow></msub></math></span>) higher than 10 dBm and dissipates a power equal to 86.43 mW from 1.2 V DC-supply voltage. Each element was separately designed and simulated to define its performance metrics in the transmitter. The tunable source of RF signal works in a frequency range from 30 GHz to 40 GHz and gives a phase noise (PN) equal to −110.5 dBc/Hz at a 1 MHz frequency offset. The Figure of Merit (FoM) equals −194 dBc/Hz, the highest attained output power <span><math><msub><mrow><mi>P</mi></mrow><mrow><mrow><mi>o</mi></mrow><mrow><mi>u</mi></mrow><mrow><mi>t</mi></mrow></mrow></msub></math></span> equals to 8.2 dBm, consumes a die size equal to <span><math><msup><mrow><mn>0.076</mn><mrow><mi>m</mi></mrow><mrow><mi>m</mi></mrow></mrow><mn>2</mn></msup></math></span>, and dissipates a power equal to 4.7 mW. The OOK modulator provides good on–off isolation greater than 38 dB, a conversion gain equal to −0.25 dB, a data rate reach to 10 Gbps, an output 1 dB compression point (O1dB) equal to −2.29 dBm, the modulator die size equals to <span><math><msup><mrow><mn>0.079</mn><mrow><mi>m</mi></mrow><mrow><mi>m</mi></mrow></mrow><mn>2</mn></msup></math></span> and consumes a DC power equal to 11.23 mW. The class-F<sup>-1</sup> PA provides a constant <span><math><msub><mrow><mi>P</mi></mrow><mrow><mrow><mi>o</mi></mrow><mrow><mi>u</mi></mrow><mrow><mi>t</mi></m
{"title":"A mm-Wave On-Off-Keying radio transmitter with 10 GHz bandwidth employing 130 nm CMOS","authors":"Marwa Mansour","doi":"10.1016/j.asej.2025.103328","DOIUrl":"10.1016/j.asej.2025.103328","url":null,"abstract":"<div><div>This article suggests a millimeter-wave wideband large-data-rate on–off-keying (OOK) transmitter (Tx) analysis, design, and implementation for high-speed systems in 5G Applications. The on–off-keying transmitter comprises of a tunable source of RF signal, a wideband high-speed OOK modulator, and a broadband RF power amplifier (PA). A novel circuit topology for the tunable source of RF signal, which comprises of transformer-tank VCO, Gilbert-frequency doubler (FD), and two-stage driver amplifier (DA). The on–off-keying modulator is built by transconductance transistors cascoded with the switching transistors to obtain high on–off isolation. The broadband PA is constructed depending on the inverse class-F architecture, which comprises of Class-AB driver stage and inverse Class-F power stage with harmonic elimination and output matching networks. A new interleaved U-shaped high-coupling transformer design, a primary capacitor (<span><math><msub><mrow><mi>C</mi></mrow><mrow><mi>P</mi></mrow></msub></math></span>), and a secondary capacitor (<span><math><msub><mrow><mi>C</mi></mrow><mrow><mi>S</mi></mrow></msub></math></span>) are utilized as a triple band high-quality tank-circuit for the proposed VCO. Moreover, the new high-quality on-chip transformers are implemented for input, inter-stage, and output matching of the Tx elements, that are used to improve RF performance. The on–off-keying RF transmitter was designed using a 130 nm CMOS process and realized an output power (<span><math><msub><mrow><mi>P</mi></mrow><mrow><mrow><mi>o</mi></mrow><mrow><mi>u</mi></mrow><mrow><mi>t</mi></mrow></mrow></msub></math></span>) higher than 10 dBm and dissipates a power equal to 86.43 mW from 1.2 V DC-supply voltage. Each element was separately designed and simulated to define its performance metrics in the transmitter. The tunable source of RF signal works in a frequency range from 30 GHz to 40 GHz and gives a phase noise (PN) equal to −110.5 dBc/Hz at a 1 MHz frequency offset. The Figure of Merit (FoM) equals −194 dBc/Hz, the highest attained output power <span><math><msub><mrow><mi>P</mi></mrow><mrow><mrow><mi>o</mi></mrow><mrow><mi>u</mi></mrow><mrow><mi>t</mi></mrow></mrow></msub></math></span> equals to 8.2 dBm, consumes a die size equal to <span><math><msup><mrow><mn>0.076</mn><mrow><mi>m</mi></mrow><mrow><mi>m</mi></mrow></mrow><mn>2</mn></msup></math></span>, and dissipates a power equal to 4.7 mW. The OOK modulator provides good on–off isolation greater than 38 dB, a conversion gain equal to −0.25 dB, a data rate reach to 10 Gbps, an output 1 dB compression point (O1dB) equal to −2.29 dBm, the modulator die size equals to <span><math><msup><mrow><mn>0.079</mn><mrow><mi>m</mi></mrow><mrow><mi>m</mi></mrow></mrow><mn>2</mn></msup></math></span> and consumes a DC power equal to 11.23 mW. The class-F<sup>-1</sup> PA provides a constant <span><math><msub><mrow><mi>P</mi></mrow><mrow><mrow><mi>o</mi></mrow><mrow><mi>u</mi></mrow><mrow><mi>t</mi></m","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 3","pages":"Article 103328"},"PeriodicalIF":6.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143509039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-01DOI: 10.1016/j.asej.2025.103289
Lingdong Meng , Dong Li , Xiaofei Fu , Yejun Jin , Zezhao Liu , Ziyang Li , Tong Zhang , Ruishan Du , Xiaoling Zhang
Water injection in fault block oil and gas reservoirs can trigger fault activity, leading to leakage and potential earthquakes, which may cause significant natural and economic losses. The friction coefficient of the fault is a crucial factor in fault activity and stability. Analyzing this relationship is essential for evaluating fault stability. This study focuses on the Penglai fault zone in the Bohai Bay Basin, China, investigating the weakening mechanism of fault gouge on the friction coefficient and integrating key factors that control its heterogeneity. The friction strength of fault gouge was evaluated through circular shear experiments conducted under in situ geological conditions, establishing a method for characterizing the heterogeneity of friction strength. Based on these findings, a model for characterizing the heterogeneity of fault friction coefficients was developed. By integrating a 3D prediction model of clay content on fault surfaces, the spatial distribution of non-uniform friction coefficients across fault planes was determined. The research findings indicate a negative correlation between the steady-state friction coefficient and the maximum static friction coefficient with respect to fault shale content. Within a mud content range of 0% to 35%, the friction coefficient remains approximately constant at around 0.6 with minimal fluctuation. As the mud content increases from 35% to 40% to 65%, there is a gradual decrease in the friction coefficient, followed by a rapid decline when the mud content reaches 65% to 75%. This trend suggests an increased influence of mudstone on frictional sliding. As the mud content increases, leading to greater involvement of mudstone in frictional sliding, significant fluctuations in the friction coefficient are observed due to the combined effects of mudstone and quartz sandstone. Ultimately, when the mud content reaches 80% to 100%, the friction coefficient decreases further, with a reduced fluctuation range. This highlights the predominant role of shale content in influencing frictional sliding behavior. The method for characterizing fault-mud-content-related friction coefficients at various levels significantly enhances the accuracy of fault stability evaluations, thereby promoting the safe and efficient development of oil and gas reservoirs.
{"title":"Experimental study on the influence of shale content in fault zone on fault friction coefficient based on circular shear test","authors":"Lingdong Meng , Dong Li , Xiaofei Fu , Yejun Jin , Zezhao Liu , Ziyang Li , Tong Zhang , Ruishan Du , Xiaoling Zhang","doi":"10.1016/j.asej.2025.103289","DOIUrl":"10.1016/j.asej.2025.103289","url":null,"abstract":"<div><div>Water injection in fault block oil and gas reservoirs can trigger fault activity, leading to leakage and potential earthquakes, which may cause significant natural and economic losses. The friction coefficient of the fault is a crucial factor in fault activity and stability. Analyzing this relationship is essential for evaluating fault stability. This study focuses on the Penglai fault zone in the Bohai Bay Basin, China, investigating the weakening mechanism of fault gouge on the friction coefficient and integrating key factors that control its heterogeneity. The friction strength of fault gouge was evaluated through circular shear experiments conducted under in situ geological conditions, establishing a method for characterizing the heterogeneity of friction strength. Based on these findings, a model for characterizing the heterogeneity of fault friction coefficients was developed. By integrating a 3D prediction model of clay content on fault surfaces, the spatial distribution of non-uniform friction coefficients across fault planes was determined. The research findings indicate a negative correlation between the steady-state friction coefficient and the maximum static friction coefficient with respect to fault shale content. Within a mud content range of 0% to 35%, the friction coefficient remains approximately constant at around 0.6 with minimal fluctuation. As the mud content increases from 35% to 40% to 65%, there is a gradual decrease in the friction coefficient, followed by a rapid decline when the mud content reaches 65% to 75%. This trend suggests an increased influence of mudstone on frictional sliding. As the mud content increases, leading to greater involvement of mudstone in frictional sliding, significant fluctuations in the friction coefficient are observed due to the combined effects of mudstone and quartz sandstone. Ultimately, when the mud content reaches 80% to 100%, the friction coefficient decreases further, with a reduced fluctuation range. This highlights the predominant role of shale content in influencing frictional sliding behavior. The method for characterizing fault-mud-content-related friction coefficients at various levels significantly enhances the accuracy of fault stability evaluations, thereby promoting the safe and efficient development of oil and gas reservoirs.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 4","pages":"Article 103289"},"PeriodicalIF":6.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143534677","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}
Flash floods are recognized as a major threat to power distribution systems. Thus, enhancing distribution system resilience against this catastrophic natural hazard is essential and imperative. Commonly researchers have used two-dimensional (2D) surface flow models to evaluate flood risk on power systems. Though these 2D models can provide descriptions of overland flow propagation, they fail to provide overflow locations which are crucial in flash flood modelling. Furthermore, these models are computationally expensive, hence not suitable for real-time analysis. Therefore, this study presents a probabilistic flood model that is easy to develop and can handle heavy uncertainties related to urban flash flooding. In this respect, the Monte Carlo technique is employed to predict overflow locations in a grid-based environment. Considering rainfall intensity, soil moisture, and curvature of the surface, reinforcement learning is then leveraged to trace the flow path of floodwater from these overflow locations, to identify distribution substations at the risk of inundation. The proposed flood model is applied to IEEE 33-bus and a real 23-bus distribution systems considering a hypothetical terrain and validated on a real urban area. This work will assist decision-makers and utility operators in enhancing power system resiliency to urban flash floods while overcoming the barriers of limited data and time.
{"title":"Modeling impact of urban flash floods on power distribution system using Monte Carlo technique and reinforcement learning","authors":"Suhail Afzal , Hazlie Mokhlis , Hazlee Azil Illias , Abdullah Akram Bajwa , Hasmaini Mohamad , Nurulafiqah Nadzirah Mansor , Lilik Jamilatul Awalin , A.K. Ramasamy","doi":"10.1016/j.asej.2025.103325","DOIUrl":"10.1016/j.asej.2025.103325","url":null,"abstract":"<div><div>Flash floods are recognized as a major threat to power distribution systems. Thus, enhancing distribution system resilience against this catastrophic natural hazard is essential and imperative. Commonly researchers have used two-dimensional (2D) surface flow models to evaluate flood risk on power systems. Though these 2D models can provide descriptions of overland flow propagation, they fail to provide overflow locations which are crucial in flash flood modelling. Furthermore, these models are computationally expensive, hence not suitable for real-time analysis. Therefore, this study presents a probabilistic flood model that is easy to develop and can handle heavy uncertainties related to urban flash flooding. In this respect, the Monte Carlo technique is employed to predict overflow locations in a grid-based environment. Considering rainfall intensity, soil moisture, and curvature of the surface, reinforcement learning is then leveraged to trace the flow path of floodwater from these overflow locations, to identify distribution substations at the risk of inundation. The proposed flood model is applied to IEEE 33-bus and a real 23-bus distribution systems considering a hypothetical terrain and validated on a real urban area. This work will assist decision-makers and utility operators in enhancing power system resiliency to urban flash floods while overcoming the barriers of limited data and time.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 3","pages":"Article 103325"},"PeriodicalIF":6.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143509026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-01DOI: 10.1016/j.asej.2025.103327
Niyazi Furkan Bar, Mehmet Karakose
Quantum computing promises remarkable computational power with minimal energy consumption. However, the complexity of developing quantum circuits and codes hinders fully exploiting this potential. The study proposes an approach based on the automatic quantum circuit and code generation based on deep learning. It enables the resynthesis of existing circuits and the creation of new ones from undefined inputs. The system transforms inputs into reversible truth tables, generates a quantum unitary matrix, corrects errors, optimizes it, and converts it into a quantum code or circuit. This approach has been implemented on circuits and codes that involve up to five variables. Rigorous evaluations include both the Deep Neural Network and the overall approach. Although the DNN output does not guarantee absolute correctness, our approach compensates with supplementary processes, ensuring the precise generation of quantum codes and circuits. Comprehensive testing confirmed the approach's effectiveness in overcoming challenges in quantum circuit and code development.
{"title":"An approach for automated generation of quantum computing models using deep learning","authors":"Niyazi Furkan Bar, Mehmet Karakose","doi":"10.1016/j.asej.2025.103327","DOIUrl":"10.1016/j.asej.2025.103327","url":null,"abstract":"<div><div>Quantum computing promises remarkable computational power with minimal energy consumption. However, the complexity of developing quantum circuits and codes hinders fully exploiting this potential. The study proposes an approach based on the automatic quantum circuit and code generation based on deep learning. It enables the resynthesis of existing circuits and the creation of new ones from undefined inputs. The system transforms inputs into reversible truth tables, generates a quantum unitary matrix, corrects errors, optimizes it, and converts it into a quantum code or circuit. This approach has been implemented on circuits and codes that involve up to five variables. Rigorous evaluations include both the Deep Neural Network and the overall approach. Although the DNN output does not guarantee absolute correctness, our approach compensates with supplementary processes, ensuring the precise generation of quantum codes and circuits. Comprehensive testing confirmed the approach's effectiveness in overcoming challenges in quantum circuit and code development.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 4","pages":"Article 103327"},"PeriodicalIF":6.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143519076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-01DOI: 10.1016/j.asej.2025.103332
M.S. Karthik , P. Siva Kota Reddy , Rahul Makwana , Shivakrishna Dasi , Fehmi Gamaoun , Chander Prakash , T.V. Smitha
The current demand for reducing the drag coefficient represents one of the most significant challenges for all truck manufacturers. Fuel consumption can be improved via aerodynamic effects, which lower the vehicle’s drag coefficient. The external truck body design aids in lowering the drag coefficient, which lowers fuel consumption. The numerical study was executed using the Computational Fluid Dynamics package, which is STAR CCM+, to investigate the coefficient of drag and surface pressure distributions of the truck with add on. Truck geometries have been designed in Autodesk Fusion-360 within standard geometry with variations in shape and external drag-reducing devices. NASA’s experimental value of Generic Conventional Model had a drag coefficient of 0.4267. In contrast, the truck trailer geometry with add-ons had a drag coefficient of 0.35777 is obtained, resulting in a 19.28% decrease in the drag coefficient. Further, a 19.28% decrease could result in 7% fuel savings on a level road.
{"title":"Computational investigation on drag coefficient and pressure distribution of the truck with add-on","authors":"M.S. Karthik , P. Siva Kota Reddy , Rahul Makwana , Shivakrishna Dasi , Fehmi Gamaoun , Chander Prakash , T.V. Smitha","doi":"10.1016/j.asej.2025.103332","DOIUrl":"10.1016/j.asej.2025.103332","url":null,"abstract":"<div><div>The current demand for reducing the drag coefficient represents one of the most significant challenges for all truck manufacturers. Fuel consumption can be improved via aerodynamic effects, which lower the vehicle’s drag coefficient. The external truck body design aids in lowering the drag coefficient, which lowers fuel consumption. The numerical study was executed using the Computational Fluid Dynamics package, which is STAR CCM+, to investigate the coefficient of drag and surface pressure distributions of the truck with add on. Truck geometries have been designed in Autodesk Fusion-360 within standard geometry with variations in shape and external drag-reducing devices. NASA’s experimental value of Generic Conventional Model had a drag coefficient of 0.4267. In contrast, the truck trailer geometry with add-ons had a drag coefficient of 0.35777 is obtained, resulting in a 19.28% decrease in the drag coefficient. Further, a 19.28% decrease could result in 7% fuel savings on a level road.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 4","pages":"Article 103332"},"PeriodicalIF":6.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143534679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-01DOI: 10.1016/j.asej.2025.103329
Ahmed Amin , Almoataz Y. Abdelaziz , Mahmoud A. Attia , Mohamed Zakaria Kamh
Transmission network planners use switching to address a variety of issues, one of which is short circuit currents that exceed the capability of transmission substations. Transmission Switching (TS) can influence rotor angle transient stability (RATS). The alteration of the short-circuit power at points of interconnection of certain generators (POIs) due to switching can cause those generators to lose stability post-clearance of severe network faults. Therefore, it is imperative that RATS be taken into account when adopt switching in transmission networks. In the literature, analyses of generator angle separation only during and after fault incidence are used for predicting RATS issues. This can be quite challenging for network operators in terms of the available time for carrying out mitigating actions. Generation redispatch, among other measures, can be utilized to preserve RATS post-network switching. In previous work, the authors addressed the optimization of transmission network switching using steady state analysis as an inexpensive way to manage increased short circuit currents amid large-scale generation integration in some networks. This paper is the sequel of the previous work where the preservation of RATS amid such switching actions is addressed. An algorithm for preserving RATS after switching is proposed. The algorithm depends on the MATLAB regression learner that identifies the best heuristic technique for a solution with the least root mean square error (RMSE). PSS®E is utilized to run the simulations on a real-size practical extra-high voltage network. The results are then fed to the MATLAB regression learner, which identifies the relation between the impedance seen by each generator and the altered setpoints (e.g., generator dispatch). The algorithm therefore provides sufficient time for network operators to react to expected RATS issues since it anticipates these issues before fault events occur. Additionally, this algorithm enhances the industry-based software used for transient security assessment because it eliminates the need to run all the network contingencies every time if the relation between the impedance and the setpoints is kept within desirable values.
{"title":"Enhancing rotor angle stability of reconfigured transmission networks","authors":"Ahmed Amin , Almoataz Y. Abdelaziz , Mahmoud A. Attia , Mohamed Zakaria Kamh","doi":"10.1016/j.asej.2025.103329","DOIUrl":"10.1016/j.asej.2025.103329","url":null,"abstract":"<div><div>Transmission network planners use switching to address a variety of issues, one of which is short circuit currents that exceed the capability of transmission substations. Transmission Switching (TS) can influence rotor angle transient stability (RATS). The alteration of the short-circuit power at points of interconnection of certain generators (POIs) due to switching can cause those generators to lose stability post-clearance of severe network faults. Therefore, it is imperative that RATS be taken into account when adopt switching in transmission networks. In the literature, analyses of generator angle separation only during and after fault incidence are used for predicting RATS issues. This can be quite challenging for network operators in terms of the available time for carrying out mitigating actions. Generation redispatch, among other measures, can be utilized to preserve RATS post-network switching. In previous work, the authors addressed the optimization of transmission network switching using steady state analysis as an inexpensive way to manage increased short circuit currents amid large-scale generation integration in some networks. This paper is the sequel of the previous work where the preservation of RATS amid such switching actions is addressed. An algorithm for preserving RATS after switching is proposed. The algorithm depends on the MATLAB regression learner that identifies the best heuristic technique for a solution with the least root mean square error (RMSE). PSS®E is utilized to run the simulations on a real-size practical extra-high voltage network. The results are then fed to the MATLAB regression learner, which identifies the relation between the impedance seen by each generator and the altered setpoints (e.g., generator dispatch). The algorithm therefore provides sufficient time for network operators to react to expected RATS issues since it anticipates these issues before fault events occur. Additionally, this algorithm enhances the industry-based software used for transient security assessment because it eliminates the need to run all the network contingencies every time if the relation between the impedance and the setpoints is kept within desirable values.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 4","pages":"Article 103329"},"PeriodicalIF":6.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143548624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-01DOI: 10.1016/j.asej.2025.103331
Qitao Tang , Maryam Bavaghar
In intelligent wireless networks, achieving reliable communication between vehicles and infrastructure is critical for enhancing user experiences and addressing the demands of next-generation networks. However, maintaining robust connectivity is challenging due to urban environments and network variability in vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication systems. This paper proposes a novel framework for link adaptation and multi-objective resource optimization, leveraging power-domain non-orthogonal multiple access (NOMA) and blind reconfigurable intelligent surfaces (IRS). The proposed method incorporates a multi-agent Deep Reinforcement Learning (DRL) model, where each agent dynamically allocates resources by optimizing power control and scheduling based on real-time network data and traffic patterns. Our approach uses IRS to enhance signal quality and extend coverage even in complex and highly dynamic environments, while the multi-agent DRL framework with graph attention mechanisms enables decentralized and scalable resource management. The agents learn from the environment, adjusting resource allocation across multiple objectives, such as maximizing throughput, improving energy efficiency, and ensuring reliable connectivity. By optimizing power allocation and link adaptation, the framework addresses the challenges of channel variability and improves network performance without requiring precise channel state information (CSI). Simulation results show that the proposed approach achieved significant improvements in both energy efficiency and throughput compared to conventional methods such as NFVMCH and HetVNet. Additionally, the throughput of TRONICS scales effectively, reaching nearly 55 Mbps/Hz with 60 users per cluster, while competing methods only manage up to 26 Mbps/Hz, underscoring its advanced resource optimization capabilities.
{"title":"Link adaptation and multi-objective resource optimization in intelligent wireless networks using power-domain non-orthogonal multiple access","authors":"Qitao Tang , Maryam Bavaghar","doi":"10.1016/j.asej.2025.103331","DOIUrl":"10.1016/j.asej.2025.103331","url":null,"abstract":"<div><div>In intelligent wireless networks, achieving reliable communication between vehicles and infrastructure is critical for enhancing user experiences and addressing the demands of next-generation networks. However, maintaining robust connectivity is challenging due to urban environments and network variability in vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication systems. This paper proposes a novel framework for link adaptation and multi-objective resource optimization, leveraging power-domain non-orthogonal multiple access (NOMA) and blind reconfigurable intelligent surfaces (IRS). The proposed method incorporates a multi-agent Deep Reinforcement Learning (DRL) model, where each agent dynamically allocates resources by optimizing power control and scheduling based on real-time network data and traffic patterns. Our approach uses IRS to enhance signal quality and extend coverage even in complex and highly dynamic environments, while the multi-agent DRL framework with graph attention mechanisms enables decentralized and scalable resource management. The agents learn from the environment, adjusting resource allocation across multiple objectives, such as maximizing throughput, improving energy efficiency, and ensuring reliable connectivity. By optimizing power allocation and link adaptation, the framework addresses the challenges of channel variability and improves network performance without requiring precise channel state information (CSI). Simulation results show that the proposed approach achieved significant improvements in both energy efficiency and throughput compared to conventional methods such as NFVMCH and HetVNet. Additionally, the throughput of TRONICS scales effectively, reaching nearly 55 Mbps/Hz with 60 users per cluster, while competing methods only manage up to 26 Mbps/Hz, underscoring its advanced resource optimization capabilities.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 4","pages":"Article 103331"},"PeriodicalIF":6.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143562262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-01DOI: 10.1016/j.asej.2025.103319
Dan Du , Zetao Li
This paper presents an optimal fault-tolerant control (FTC) method for dynamic systems with distributed fault parameter uncertainty. According to the distributed characteristic of the fault parameter uncertainty domain and insufficient fault information, identify the controller parameter feasible domain on each distributed fault parameter uncertainty sub-domain, respectively. The intersection of all controller parameter feasible domains is the feasible domain of fault-tolerant controller parameters. The optimal fault-tolerant controller with an optimal performance index is obtained from the feasible domain of fault-tolerant controller parameters. Update the optimal fault-tolerant controller according to the increase in fault information. When the fault diagnosis procedure stops providing more useful fault information, the optimal fault-tolerant controller ceases its updates. After fully identifying the fault, an active fault-tolerant controller is designed based on the fault parameter values. An optimal fault-tolerant control algorithm based on quadratic stability control is introduced for distributed fault parameter uncertainty domains. Firstly, the currently distributed fault parameter uncertainty domain is determined based on insufficient fault information. Then, we design the quadratic stability controllers for each distributed uncertainty sub-domain of fault parameters to get the controller parameter feasible domain. The optimal fault-tolerant controller with an optimal performance index is obtained from the feasible domain of fault-tolerant controller parameters. Once the fault is identified, the optimal fault-tolerant control converges to the linear quadratic regulator (LQR) control. The simulation results confirm that the proposed method and algorithm are feasible and effective.
{"title":"Optimal Fault-Tolerant Control for Dynamic Systems with Distributed Fault Parameter Uncertainty Domains","authors":"Dan Du , Zetao Li","doi":"10.1016/j.asej.2025.103319","DOIUrl":"10.1016/j.asej.2025.103319","url":null,"abstract":"<div><div>This paper presents an optimal fault-tolerant control (FTC) method for dynamic systems with distributed fault parameter uncertainty. According to the distributed characteristic of the fault parameter uncertainty domain and insufficient fault information, identify the controller parameter feasible domain on each distributed fault parameter uncertainty sub-domain, respectively. The intersection of all controller parameter feasible domains is the feasible domain of fault-tolerant controller parameters. The optimal fault-tolerant controller with an optimal performance index is obtained from the feasible domain of fault-tolerant controller parameters. Update the optimal fault-tolerant controller according to the increase in fault information. When the fault diagnosis procedure stops providing more useful fault information, the optimal fault-tolerant controller ceases its updates. After fully identifying the fault, an active fault-tolerant controller is designed based on the fault parameter values. An optimal fault-tolerant control algorithm based on quadratic stability control is introduced for distributed fault parameter uncertainty domains. Firstly, the currently distributed fault parameter uncertainty domain is determined based on insufficient fault information. Then, we design the quadratic stability controllers for each distributed uncertainty sub-domain of fault parameters to get the controller parameter feasible domain. The optimal fault-tolerant controller with an optimal performance index is obtained from the feasible domain of fault-tolerant controller parameters. Once the fault is identified, the optimal fault-tolerant control converges to the linear quadratic regulator (LQR) control. The simulation results confirm that the proposed method and algorithm are feasible and effective.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 4","pages":"Article 103319"},"PeriodicalIF":6.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143534678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-01DOI: 10.1016/j.asej.2025.103334
Aida Abedzadeh Janiabadi, Saeid Hasheminejad
Using the superior specifications of S-transform (ST) a new algorithm is presented for the high impedance fault (HIF) detection in distribution systems. Here, ST is applied to one cycle of the current signal and all time and frequency information of the signal are extracted. Then, four numerical indices named as total harmonic distortion (THD), even harmonic energy (EHE), variation coefficient (VC) and phase deviation (PD) are calculated from the ST output. According to the values of the four indices and some predefined thresholds, HIF is discriminated from the normal situation and other events of the distribution system. Performance of the proposed algorithm is evaluated by the test signals simulated by PSCAD/EMTDC software and experimental test signals extracted from a real distribution network. Here, the total algorithm implementation time is 21 ms. With the presence of 30 dB gaussian white noise, the HIF identification accuracy is cleared to be 98.48 %.
{"title":"A new algorithm for the identification of high impedance faults in distribution systems utilizing S transform","authors":"Aida Abedzadeh Janiabadi, Saeid Hasheminejad","doi":"10.1016/j.asej.2025.103334","DOIUrl":"10.1016/j.asej.2025.103334","url":null,"abstract":"<div><div>Using the superior specifications of S-transform (ST) a new algorithm is presented for the high impedance fault (HIF) detection in distribution systems. Here, ST is applied to one cycle of the current signal and all time and frequency information of the signal are extracted. Then, four numerical indices named as total harmonic distortion (THD), even harmonic energy (EHE), variation coefficient (VC) and phase deviation (PD) are calculated from the ST output. According to the values of the four indices and some predefined thresholds, HIF is discriminated from the normal situation and other events of the distribution system. Performance of the proposed algorithm is evaluated by the test signals simulated by PSCAD/EMTDC software and experimental test signals extracted from a real distribution network. Here, the total algorithm implementation time is 21 ms. With the presence of 30 dB gaussian white noise, the HIF identification accuracy is cleared to be 98.48 %.</div></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":"16 4","pages":"Article 103334"},"PeriodicalIF":6.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143548606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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