The growing need for clean energy has made solar panels an essential solution. However, the nonlinear behavior of photovoltaic (PV) systems under varying weather conditions necessitates advanced control strategies to ensure optimal energy harvesting. This paper presents an enhanced Maximum Power Point Tracking (MPPT) approach that integrates the conventional Perturb and Observe (P&O) method with an Indirect Adaptive Fuzzy Controller (IAFC). While P&O is known for its simplicity, it suffers from steady-state oscillations and slow response during environmental changes. To address these issues, the IAFC adaptively adjusts the perturbation step using a Lyapunov-based rule to improve convergence and minimize power fluctuations. The proposed method achieves Maximum Power Point tracking within less than 0.025 s, compared to 0.05 s for the conventional P&O algorithm. This enhances the credibility of our dynamic performance claim. Specifically, unlike prior fuzzy-P&O hybrids with fixed rule sets, our method leverages Lyapunov-based adaptation to dynamically adjust the control action, improving convergence and robustness under changing conditions. We also included a quantitative metric showing a 75% reduction in power fluctuations compared to conventional P&O. Simulation results under varying sunlight conditions demonstrate fast convergence and improved power stability. The proposed IAFC method clearly outperforms classical P&O in tracking accuracy, responsiveness, and overall energy yield.

The growing need for clean energy has made solar panels an essential solution. However, the nonlinear behavior of photovoltaic (PV) systems under varying weather conditions necessitates advanced control strategies to ensure optimal energy harvesting. This paper presents an enhanced Maximum Power Point Tracking (MPPT) approach that integrates the conventional Perturb and Observe (P&O) method with an Indirect Adaptive Fuzzy Controller (IAFC). While P&O is known for its simplicity, it suffers from steady-state oscillations and slow response during environmental changes. To address these issues, the IAFC adaptively adjusts the perturbation step using a Lyapunov-based rule to improve convergence and minimize power fluctuations. The proposed method achieves Maximum Power Point tracking within less than 0.025 s, compared to 0.05 s for the conventional P&O algorithm. This enhances the credibility of our dynamic performance claim. Specifically, unlike prior fuzzy-P&O hybrids with fixed rule sets, our method leverages Lyapunov-based adaptation to dynamically adjust the control action, improving convergence and robustness under changing conditions. We also included a quantitative metric showing a 75% reduction in power fluctuations compared to conventional P&O. Simulation results under varying sunlight conditions demonstrate fast convergence and improved power stability. The proposed IAFC method clearly outperforms classical P&O in tracking accuracy, responsiveness, and overall energy yield.

The growing need for clean energy has made solar panels an essential solution. However, the nonlinear behavior of photovoltaic (PV) systems under varying weather conditions necessitates advanced control strategies to ensure optimal energy harvesting. This paper presents an enhanced Maximum Power Point Tracking (MPPT) approach that integrates the conventional Perturb and Observe (P&O) method with an Indirect Adaptive Fuzzy Controller (IAFC). While P&O is known for its simplicity, it suffers from steady-state oscillations and slow response during environmental changes. To address these issues, the IAFC adaptively adjusts the perturbation step using a Lyapunov-based rule to improve convergence and minimize power fluctuations. The proposed method achieves Maximum Power Point tracking within less than 0.025 s, compared to 0.05 s for the conventional P&O algorithm. This enhances the credibility of our dynamic performance claim. Specifically, unlike prior fuzzy-P&O hybrids with fixed rule sets, our method leverages Lyapunov-based adaptation to dynamically adjust the control action, improving convergence and robustness under changing conditions. We also included a quantitative metric showing a 75% reduction in power fluctuations compared to conventional P&O. Simulation results under varying sunlight conditions demonstrate fast convergence and improved power stability. The proposed IAFC method clearly outperforms classical P&O in tracking accuracy, responsiveness, and overall energy yield.

This paper compares two approaches for detecting and analyzing acoustic microwaves in piezoelectric materials, specifically in Lithium Niobate (LiNbO3) substrates. The first method focuses on modeling the propagation of acoustic microwaves in piezoelectric structures, utilizing an interdigital transducer (IDT) to excite the electroelastic waves. This method investigates various wave types, such as secondary surface waves, leaky waves, bulk waves, and skimming bulk waves, and applies wavelet transform for efficient detection. Two wavelet functions—Mexican-hat and Morlet—are compared based on their ability to detect acoustic wave singularities, with an emphasis on their efficiency in processing microwave signals. The second method introduces a machine learning approach using support vector machines (SVM) to detect ultrasonic pulses and identify previously undetectable waves. By classifying real and imaginary parts of the coefficient attenuation and acoustic velocity, this method provides more accurate values and facilitates the modeling of ultrasonic pulse propagation. While the wavelet-based approach focuses on signal processing for wave detection, the SVM-based method excels in detecting complex wave patterns that traditional methods may overlook, offering higher precision in ultrasonic pulse modeling and the realization of acoustic microwave devices.

This paper compares two approaches for detecting and analyzing acoustic microwaves in piezoelectric materials, specifically in Lithium Niobate (LiNbO3) substrates. The first method focuses on modeling the propagation of acoustic microwaves in piezoelectric structures, utilizing an interdigital transducer (IDT) to excite the electroelastic waves. This method investigates various wave types, such as secondary surface waves, leaky waves, bulk waves, and skimming bulk waves, and applies wavelet transform for efficient detection. Two wavelet functions—Mexican-hat and Morlet—are compared based on their ability to detect acoustic wave singularities, with an emphasis on their efficiency in processing microwave signals. The second method introduces a machine learning approach using support vector machines (SVM) to detect ultrasonic pulses and identify previously undetectable waves. By classifying real and imaginary parts of the coefficient attenuation and acoustic velocity, this method provides more accurate values and facilitates the modeling of ultrasonic pulse propagation. While the wavelet-based approach focuses on signal processing for wave detection, the SVM-based method excels in detecting complex wave patterns that traditional methods may overlook, offering higher precision in ultrasonic pulse modeling and the realization of acoustic microwave devices.

This paper compares two approaches for detecting and analyzing acoustic microwaves in piezoelectric materials, specifically in Lithium Niobate (LiNbO3) substrates. The first method focuses on modeling the propagation of acoustic microwaves in piezoelectric structures, utilizing an interdigital transducer (IDT) to excite the electroelastic waves. This method investigates various wave types, such as secondary surface waves, leaky waves, bulk waves, and skimming bulk waves, and applies wavelet transform for efficient detection. Two wavelet functions—Mexican-hat and Morlet—are compared based on their ability to detect acoustic wave singularities, with an emphasis on their efficiency in processing microwave signals. The second method introduces a machine learning approach using support vector machines (SVM) to detect ultrasonic pulses and identify previously undetectable waves. By classifying real and imaginary parts of the coefficient attenuation and acoustic velocity, this method provides more accurate values and facilitates the modeling of ultrasonic pulse propagation. While the wavelet-based approach focuses on signal processing for wave detection, the SVM-based method excels in detecting complex wave patterns that traditional methods may overlook, offering higher precision in ultrasonic pulse modeling and the realization of acoustic microwave devices.

The present work focuses on the experimental characterisation and numerical validation of the in-plane mechanical properties of IM2-12K/Epocast 50-A1 composite for structural damage prediction. Consequently, a series of tensile, compressive, shear, and flexural tests were systematically conducted on specimens prepared with specific lay-up configurations, while the fibre volume fraction was measured using the ashing method. The experimental results demonstrated that the composite under investigation exhibited high tensile strength and stiffness along the fibre direction, moderate compressive properties, and lower shear strength. This behaviour is indicative of anisotropic properties. Moreover, a three-dimensional finite element simulation of the tensile and three-point flexural tests was subsequently conducted, employing a Hashin-based failure initiation criterion. In order to achieve this objective, the key material properties were incorporated into a user-defined material subroutine (VUMAT), thereby enabling the modelling of progressive damage mechanisms, encompassing both fibre and matrix failures. The numerical predictions exhibited excellent agreement with the experimental data, thereby validating both the measured properties and the robustness of the modelling strategy. The present study establishes a validated mechanical dataset and a predictive model, providing a reliable foundation for the design and simulation of the performance of IM2-12K/Epocast 50-A1 in advanced engineering applications.

The present work focuses on the experimental characterisation and numerical validation of the in-plane mechanical properties of IM2-12K/Epocast 50-A1 composite for structural damage prediction. Consequently, a series of tensile, compressive, shear, and flexural tests were systematically conducted on specimens prepared with specific lay-up configurations, while the fibre volume fraction was measured using the ashing method. The experimental results demonstrated that the composite under investigation exhibited high tensile strength and stiffness along the fibre direction, moderate compressive properties, and lower shear strength. This behaviour is indicative of anisotropic properties. Moreover, a three-dimensional finite element simulation of the tensile and three-point flexural tests was subsequently conducted, employing a Hashin-based failure initiation criterion. In order to achieve this objective, the key material properties were incorporated into a user-defined material subroutine (VUMAT), thereby enabling the modelling of progressive damage mechanisms, encompassing both fibre and matrix failures. The numerical predictions exhibited excellent agreement with the experimental data, thereby validating both the measured properties and the robustness of the modelling strategy. The present study establishes a validated mechanical dataset and a predictive model, providing a reliable foundation for the design and simulation of the performance of IM2-12K/Epocast 50-A1 in advanced engineering applications.

The present work focuses on the experimental characterisation and numerical validation of the in-plane mechanical properties of IM2-12K/Epocast 50-A1 composite for structural damage prediction. Consequently, a series of tensile, compressive, shear, and flexural tests were systematically conducted on specimens prepared with specific lay-up configurations, while the fibre volume fraction was measured using the ashing method. The experimental results demonstrated that the composite under investigation exhibited high tensile strength and stiffness along the fibre direction, moderate compressive properties, and lower shear strength. This behaviour is indicative of anisotropic properties. Moreover, a three-dimensional finite element simulation of the tensile and three-point flexural tests was subsequently conducted, employing a Hashin-based failure initiation criterion. In order to achieve this objective, the key material properties were incorporated into a user-defined material subroutine (VUMAT), thereby enabling the modelling of progressive damage mechanisms, encompassing both fibre and matrix failures. The numerical predictions exhibited excellent agreement with the experimental data, thereby validating both the measured properties and the robustness of the modelling strategy. The present study establishes a validated mechanical dataset and a predictive model, providing a reliable foundation for the design and simulation of the performance of IM2-12K/Epocast 50-A1 in advanced engineering applications.

The present work focuses on the experimental characterisation and numerical validation of the in-plane mechanical properties of IM2-12K/Epocast 50-A1 composite for structural damage prediction. Consequently, a series of tensile, compressive, shear, and flexural tests were systematically conducted on specimens prepared with specific lay-up configurations, while the fibre volume fraction was measured using the ashing method. The experimental results demonstrated that the composite under investigation exhibited high tensile strength and stiffness along the fibre direction, moderate compressive properties, and lower shear strength. This behaviour is indicative of anisotropic properties. Moreover, a three-dimensional finite element simulation of the tensile and three-point flexural tests was subsequently conducted, employing a Hashin-based failure initiation criterion. In order to achieve this objective, the key material properties were incorporated into a user-defined material subroutine (VUMAT), thereby enabling the modelling of progressive damage mechanisms, encompassing both fibre and matrix failures. The numerical predictions exhibited excellent agreement with the experimental data, thereby validating both the measured properties and the robustness of the modelling strategy. The present study establishes a validated mechanical dataset and a predictive model, providing a reliable foundation for the design and simulation of the performance of IM2-12K/Epocast 50-A1 in advanced engineering applications.

The present work focuses on the experimental characterisation and numerical validation of the in-plane mechanical properties of IM2-12K/Epocast 50-A1 composite for structural damage prediction. Consequently, a series of tensile, compressive, shear, and flexural tests were systematically conducted on specimens prepared with specific lay-up configurations, while the fibre volume fraction was measured using the ashing method. The experimental results demonstrated that the composite under investigation exhibited high tensile strength and stiffness along the fibre direction, moderate compressive properties, and lower shear strength. This behaviour is indicative of anisotropic properties. Moreover, a three-dimensional finite element simulation of the tensile and three-point flexural tests was subsequently conducted, employing a Hashin-based failure initiation criterion. In order to achieve this objective, the key material properties were incorporated into a user-defined material subroutine (VUMAT), thereby enabling the modelling of progressive damage mechanisms, encompassing both fibre and matrix failures. The numerical predictions exhibited excellent agreement with the experimental data, thereby validating both the measured properties and the robustness of the modelling strategy. The present study establishes a validated mechanical dataset and a predictive model, providing a reliable foundation for the design and simulation of the performance of IM2-12K/Epocast 50-A1 in advanced engineering applications.

The present work focuses on the experimental characterisation and numerical validation of the in-plane mechanical properties of IM2-12K/Epocast 50-A1 composite for structural damage prediction. Consequently, a series of tensile, compressive, shear, and flexural tests were systematically conducted on specimens prepared with specific lay-up configurations, while the fibre volume fraction was measured using the ashing method. The experimental results demonstrated that the composite under investigation exhibited high tensile strength and stiffness along the fibre direction, moderate compressive properties, and lower shear strength. This behaviour is indicative of anisotropic properties. Moreover, a three-dimensional finite element simulation of the tensile and three-point flexural tests was subsequently conducted, employing a Hashin-based failure initiation criterion. In order to achieve this objective, the key material properties were incorporated into a user-defined material subroutine (VUMAT), thereby enabling the modelling of progressive damage mechanisms, encompassing both fibre and matrix failures. The numerical predictions exhibited excellent agreement with the experimental data, thereby validating both the measured properties and the robustness of the modelling strategy. The present study establishes a validated mechanical dataset and a predictive model, providing a reliable foundation for the design and simulation of the performance of IM2-12K/Epocast 50-A1 in advanced engineering applications.

The present work focuses on the experimental characterisation and numerical validation of the in-plane mechanical properties of IM2-12K/Epocast 50-A1 composite for structural damage prediction. Consequently, a series of tensile, compressive, shear, and flexural tests were systematically conducted on specimens prepared with specific lay-up configurations, while the fibre volume fraction was measured using the ashing method. The experimental results demonstrated that the composite under investigation exhibited high tensile strength and stiffness along the fibre direction, moderate compressive properties, and lower shear strength. This behaviour is indicative of anisotropic properties. Moreover, a three-dimensional finite element simulation of the tensile and three-point flexural tests was subsequently conducted, employing a Hashin-based failure initiation criterion. In order to achieve this objective, the key material properties were incorporated into a user-defined material subroutine (VUMAT), thereby enabling the modelling of progressive damage mechanisms, encompassing both fibre and matrix failures. The numerical predictions exhibited excellent agreement with the experimental data, thereby validating both the measured properties and the robustness of the modelling strategy. The present study establishes a validated mechanical dataset and a predictive model, providing a reliable foundation for the design and simulation of the performance of IM2-12K/Epocast 50-A1 in advanced engineering applications.

The present work focuses on the experimental characterisation and numerical validation of the in-plane mechanical properties of IM2-12K/Epocast 50-A1 composite for structural damage prediction. Consequently, a series of tensile, compressive, shear, and flexural tests were systematically conducted on specimens prepared with specific lay-up configurations, while the fibre volume fraction was measured using the ashing method. The experimental results demonstrated that the composite under investigation exhibited high tensile strength and stiffness along the fibre direction, moderate compressive properties, and lower shear strength. This behaviour is indicative of anisotropic properties. Moreover, a three-dimensional finite element simulation of the tensile and three-point flexural tests was subsequently conducted, employing a Hashin-based failure initiation criterion. In order to achieve this objective, the key material properties were incorporated into a user-defined material subroutine (VUMAT), thereby enabling the modelling of progressive damage mechanisms, encompassing both fibre and matrix failures. The numerical predictions exhibited excellent agreement with the experimental data, thereby validating both the measured properties and the robustness of the modelling strategy. The present study establishes a validated mechanical dataset and a predictive model, providing a reliable foundation for the design and simulation of the performance of IM2-12K/Epocast 50-A1 in advanced engineering applications.

Urban planning plays a critical role in sustainable city development by guiding urban expansion efficiently. In Algeria, the master plan for development and urban planning (PDAU) designates specific areas for city growth, yet the suitability of these areasfor urban extension often remains unassessed using systematic methods. Most PDAU, including the plan for Setif City established in 2016, rely on planning approaches and data that risk becoming outdated due to rapid urban changes and evolving spatial dynamics. As a result, there is a pressing need to critically assess and validate these designated extension zones using updated, objective analytical tools. This study addresses this gap by applying an integrated approach combining Geographic Information Systems (GIS) and the Analytic Hierarchy Process (AHP) to evaluate land suitability for urban extension in Setif City. Fifteen socio-economic, physical, environmental, and accessibility criteria were applied to assess areas designated in the PDAU. The methodology enables a multi-criteria, data-driven analysis to prioritize zones for sustainable urban growth. About 21.5% of the study area is categorized as very high suitability, and most of these sites are concentrated around the edges of the city.36.7% is classified as high suitability, according to the suitability analysis for future urban expansion. Moderately and poorly suitable areas make up 23.79% and 13% of the total. Merely 5% of the land is deemed to be extremely unsuitable for the extension. The findings support evidence-based urban planning, offering actionable insights for policymakers and urban planners. This study contributes methodologically by demonstrating the effective integration of AHP with GIS in an Algerian context, encouraging replication and further research in similar urban environments.

Urban planning plays a critical role in sustainable city development by guiding urban expansion efficiently. In Algeria, the master plan for development and urban planning (PDAU) designates specific areas for city growth, yet the suitability of these areasfor urban extension often remains unassessed using systematic methods. Most PDAU, including the plan for Setif City established in 2016, rely on planning approaches and data that risk becoming outdated due to rapid urban changes and evolving spatial dynamics. As a result, there is a pressing need to critically assess and validate these designated extension zones using updated, objective analytical tools. This study addresses this gap by applying an integrated approach combining Geographic Information Systems (GIS) and the Analytic Hierarchy Process (AHP) to evaluate land suitability for urban extension in Setif City. Fifteen socio-economic, physical, environmental, and accessibility criteria were applied to assess areas designated in the PDAU. The methodology enables a multi-criteria, data-driven analysis to prioritize zones for sustainable urban growth. About 21.5% of the study area is categorized as very high suitability, and most of these sites are concentrated around the edges of the city.36.7% is classified as high suitability, according to the suitability analysis for future urban expansion. Moderately and poorly suitable areas make up 23.79% and 13% of the total. Merely 5% of the land is deemed to be extremely unsuitable for the extension. The findings support evidence-based urban planning, offering actionable insights for policymakers and urban planners. This study contributes methodologically by demonstrating the effective integration of AHP with GIS in an Algerian context, encouraging replication and further research in similar urban environments.

Urban planning plays a critical role in sustainable city development by guiding urban expansion efficiently. In Algeria, the master plan for development and urban planning (PDAU) designates specific areas for city growth, yet the suitability of these areasfor urban extension often remains unassessed using systematic methods. Most PDAU, including the plan for Setif City established in 2016, rely on planning approaches and data that risk becoming outdated due to rapid urban changes and evolving spatial dynamics. As a result, there is a pressing need to critically assess and validate these designated extension zones using updated, objective analytical tools. This study addresses this gap by applying an integrated approach combining Geographic Information Systems (GIS) and the Analytic Hierarchy Process (AHP) to evaluate land suitability for urban extension in Setif City. Fifteen socio-economic, physical, environmental, and accessibility criteria were applied to assess areas designated in the PDAU. The methodology enables a multi-criteria, data-driven analysis to prioritize zones for sustainable urban growth. About 21.5% of the study area is categorized as very high suitability, and most of these sites are concentrated around the edges of the city.36.7% is classified as high suitability, according to the suitability analysis for future urban expansion. Moderately and poorly suitable areas make up 23.79% and 13% of the total. Merely 5% of the land is deemed to be extremely unsuitable for the extension. The findings support evidence-based urban planning, offering actionable insights for policymakers and urban planners. This study contributes methodologically by demonstrating the effective integration of AHP with GIS in an Algerian context, encouraging replication and further research in similar urban environments.

Urban planning plays a critical role in sustainable city development by guiding urban expansion efficiently. In Algeria, the master plan for development and urban planning (PDAU) designates specific areas for city growth, yet the suitability of these areasfor urban extension often remains unassessed using systematic methods. Most PDAU, including the plan for Setif City established in 2016, rely on planning approaches and data that risk becoming outdated due to rapid urban changes and evolving spatial dynamics. As a result, there is a pressing need to critically assess and validate these designated extension zones using updated, objective analytical tools. This study addresses this gap by applying an integrated approach combining Geographic Information Systems (GIS) and the Analytic Hierarchy Process (AHP) to evaluate land suitability for urban extension in Setif City. Fifteen socio-economic, physical, environmental, and accessibility criteria were applied to assess areas designated in the PDAU. The methodology enables a multi-criteria, data-driven analysis to prioritize zones for sustainable urban growth. About 21.5% of the study area is categorized as very high suitability, and most of these sites are concentrated around the edges of the city.36.7% is classified as high suitability, according to the suitability analysis for future urban expansion. Moderately and poorly suitable areas make up 23.79% and 13% of the total. Merely 5% of the land is deemed to be extremely unsuitable for the extension. The findings support evidence-based urban planning, offering actionable insights for policymakers and urban planners. This study contributes methodologically by demonstrating the effective integration of AHP with GIS in an Algerian context, encouraging replication and further research in similar urban environments.

Urban planning plays a critical role in sustainable city development by guiding urban expansion efficiently. In Algeria, the master plan for development and urban planning (PDAU) designates specific areas for city growth, yet the suitability of these areasfor urban extension often remains unassessed using systematic methods. Most PDAU, including the plan for Setif City established in 2016, rely on planning approaches and data that risk becoming outdated due to rapid urban changes and evolving spatial dynamics. As a result, there is a pressing need to critically assess and validate these designated extension zones using updated, objective analytical tools. This study addresses this gap by applying an integrated approach combining Geographic Information Systems (GIS) and the Analytic Hierarchy Process (AHP) to evaluate land suitability for urban extension in Setif City. Fifteen socio-economic, physical, environmental, and accessibility criteria were applied to assess areas designated in the PDAU. The methodology enables a multi-criteria, data-driven analysis to prioritize zones for sustainable urban growth. About 21.5% of the study area is categorized as very high suitability, and most of these sites are concentrated around the edges of the city.36.7% is classified as high suitability, according to the suitability analysis for future urban expansion. Moderately and poorly suitable areas make up 23.79% and 13% of the total. Merely 5% of the land is deemed to be extremely unsuitable for the extension. The findings support evidence-based urban planning, offering actionable insights for policymakers and urban planners. This study contributes methodologically by demonstrating the effective integration of AHP with GIS in an Algerian context, encouraging replication and further research in similar urban environments.

Urban planning plays a critical role in sustainable city development by guiding urban expansion efficiently. In Algeria, the master plan for development and urban planning (PDAU) designates specific areas for city growth, yet the suitability of these areasfor urban extension often remains unassessed using systematic methods. Most PDAU, including the plan for Setif City established in 2016, rely on planning approaches and data that risk becoming outdated due to rapid urban changes and evolving spatial dynamics. As a result, there is a pressing need to critically assess and validate these designated extension zones using updated, objective analytical tools. This study addresses this gap by applying an integrated approach combining Geographic Information Systems (GIS) and the Analytic Hierarchy Process (AHP) to evaluate land suitability for urban extension in Setif City. Fifteen socio-economic, physical, environmental, and accessibility criteria were applied to assess areas designated in the PDAU. The methodology enables a multi-criteria, data-driven analysis to prioritize zones for sustainable urban growth. About 21.5% of the study area is categorized as very high suitability, and most of these sites are concentrated around the edges of the city.36.7% is classified as high suitability, according to the suitability analysis for future urban expansion. Moderately and poorly suitable areas make up 23.79% and 13% of the total. Merely 5% of the land is deemed to be extremely unsuitable for the extension. The findings support evidence-based urban planning, offering actionable insights for policymakers and urban planners. This study contributes methodologically by demonstrating the effective integration of AHP with GIS in an Algerian context, encouraging replication and further research in similar urban environments.