Fast upsetting of circular cylinders of aluminium metal matrix composites: experimental results and numerical analysis

Cylindrical specimens of Al/Cu and Al/Li metal matrix composite (MMC) were subjected to dynamic compression at room temperature using an experimental drop hammer. Force-time and displacement-time traces were recorded. The experimental results are compared with theoretical results obtained using finite-difference analysis proposed in a previous paper by the authors [1]. The computational results obtained for the force-time histories agree reasonably with the experimental observation. Effect of strain rate and thermal softening on the mechanical behaviour of Al/Cu MMC and Al/Li MMC were examined

Experimental investigation of long-term performance of fiber-reinforced epoxy and polyurethane polymer composites

The primary challenge encountered by polymers and their composites when exposed to saline water is their inadequate ability to withstand wear and tear over time. With a potential to replace conventional materials the long-term performance of FRP composites is still a novice area. This manuscript thus, reports an experimental investigation and prediction of the durability of fiber-reinforced polymer composites exposed to seawater at different temperatures. E-glass/epoxy and E-glass/polyurethane samples were exposed to 23 °C, 45 °C and 65 °C seawater for up to 2700 days (90 months). Tensile tests evaluated the mechanical performance of the composite as a function of exposure time, and strength-based technique was used to assess the durability. The experimental results revealed that the tensile strength of E-glass/epoxy composite decreased by 6.3% and 48.9% after 90 months in seawater at 23 and 65 °C, respectively, whereas it declined by 37.6% and 63.6% respectively for E-glass/Polyurethane composite. The prolonged immersion in seawater results in plasticization and swelling in the composite material, which accelerates the fiber/matrix debonding. SEM micrographs indicate fiber/matrix debonding, potholing, fiber pull-out, river line marks, and matrix cracking which showcases deterioration in the tensile properties of both composites

Simultaneous stabilisation of power systems using geneticalgorithms

The paper considers the simultaneous stabilisation of a power system over a wide range of operating conditions via a single power system stabiliser using genetic algorithms. A power system operating at various load levels is treated as a finite set of plants. The problem of selecting the parameters of a power system stabiliser which simultaneously stabilises this set of plants is converted to a simple optimisation problem which is solved by a genetic algorithm and an eigenvalue-based objective function. A single-machine infinite bus system is considered to demonstrate the suggested techniqu

Power system output feedback stabilizer design via geneticalgorithms

The paper demonstrates the use of genetic algorithms to design output feedback power system stabilizers. Two methods are presented: in the first method, the problem is formulated as an optimization problem with a standard infinite time quadratic objective function. A digital simulation of the power system is then used in conjunction with the genetic algorithm to determine the output feedback gains. In the second method, the problem of selecting the output feedback gains is converted to a simple optimization problem with an eigenvalue based objective function, which is solved by a genetic algorithm. The design method does not need the specification of weighting matrices. Various objective functions are presented allowing the selection of the output feedback gains to place the closed loop eigenvalues in the left hand side of a vertical line in the complex s plane, within an open sector in the complex s plane, or within a vertical strip in the complex s plane. The effectiveness of the output feedback stabilizer in enhancing the dynamic stability of power systems is verified through eigenvalue analysis and simulation result

Analysis of power system stability enhancement via excitation and FACTS-based stabilizers

Power system stability enhancement via excitation and FACTS-based stabilizers is thoroughly investigated in this paper. This study presents a singular value decomposition-based approach to assess and measure the controllability of the poorly damped electromechanical modes by different control inputs. The design problem of a power system stabilizer and different FACTS-based stabilizers is formulated as an optimization problem. An eigenvalue-based objective function to increase the system damping and improve the system response is developed. Then, a real-coded genetic algorithm is employed to search for optimal controller parameters. In addition, the damping characteristics of the proposed schemes are also evaluated in terms of the damping torque coefficient with different loading conditions for better understanding of the coordination problem requirements. The proposed stabilizers are tested on a weakly connected power system with different loading conditions. The damping torque coefficient analysis, nonlinear simulation results, and eigenvalue analysis show the effectiveness and robustness of the proposed control schemes over a wide range of loading conditions

Power system output feedback stabilizer design via geneticalgorithms

The paper demonstrates the use of genetic algorithms to design output feedback power system stabilizers. Two methods are presented: in the first method, the problem is formulated as an optimization problem with a standard infinite time quadratic objective function. A digital simulation of the power system is then used in conjunction with the genetic algorithm to determine the output feedback gains. In the second method, the problem of selecting the output feedback gains is converted to a simple optimization problem with an eigenvalue based objective function, which is solved by a genetic algorithm. The design method does not need the specification of weighting matrices. Various objective functions are presented allowing the selection of the output feedback gains to place the closed loop eigenvalues in the left hand side of a vertical line in the complex s plane, within an open sector in the complex s plane, or within a vertical strip in the complex s plane. The effectiveness of the output feedback stabilizer in enhancing the dynamic stability of power systems is verified through eigenvalue analysis and simulation result

Robust Coordinated Design of Excitation and TCSC-Based Stabilizers Using genetic algorithms

Power system stability enhancement via robust coordinated design of a power system stabilizer (PSS) and a thyristor-controlled series capacitor (TCSC)-based stabilizer is thoroughly investigated in this paper. The coordinated design problem of robust excitation and TCSC-based controllers over a wide range of loading conditions and system configurations is formulated as an optimization problem with an eigenvalue-based objective function. The real-coded genetic algorithm (RCGA) is employed to search for optimal controller parameters. This study also presents a singular value decomposition (SVD)-based approach to assess and measure the controllability of the poorly damped electromechanical modes by different control inputs. The damping characteristics of the proposed control schemes are also evaluated in terms of the damping torque coefficient over a wide range of loading conditions. The proposed stabilizers were tested on a weakly connected power system. The damping torque coefficient analysis, nonlinear simulation results, and eigenvalue analysis show the effectiveness and robustness of the proposed approach over a wide range of loading conditions

Robust Coordinated Design of Excitation and TCSC-Based Stabilizers Using genetic algorithms

Power system stability enhancement via robust coordinated design of a power system stabilizer (PSS) and a thyristor-controlled series capacitor (TCSC)-based stabilizer is thoroughly investigated in this paper. The coordinated design problem of robust excitation and TCSC-based controllers over a wide range of loading conditions and system configurations is formulated as an optimization problem with an eigenvalue-based objective function. The real-coded genetic algorithm (RCGA) is employed to search for optimal controller parameters. This study also presents a singular value decomposition (SVD)-based approach to assess and measure the controllability of the poorly damped electromechanical modes by different control inputs. The damping characteristics of the proposed control schemes are also evaluated in terms of the damping torque coefficient over a wide range of loading conditions. The proposed stabilizers were tested on a weakly connected power system. The damping torque coefficient analysis, nonlinear simulation results, and eigenvalue analysis show the effectiveness and robustness of the proposed approach over a wide range of loading conditions

Analysis of power system stability enhancement via excitation and FACTS-based stabilizers

Power system stability enhancement via excitation and FACTS-based stabilizers is thoroughly investigated in this paper. This study presents a singular value decomposition-based approach to assess and measure the controllability of the poorly damped electromechanical modes by different control inputs. The design problem of a power system stabilizer and different FACTS-based stabilizers is formulated as an optimization problem. An eigenvalue-based objective function to increase the system damping and improve the system response is developed. Then, a real-coded genetic algorithm is employed to search for optimal controller parameters. In addition, the damping characteristics of the proposed schemes are also evaluated in terms of the damping torque coefficient with different loading conditions for better understanding of the coordination problem requirements. The proposed stabilizers are tested on a weakly connected power system with different loading conditions. The damping torque coefficient analysis, nonlinear simulation results, and eigenvalue analysis show the effectiveness and robustness of the proposed control schemes over a wide range of loading conditions

Genetic Algorithm Based Simultaneous Eigenvalue Placement Of Power Systems

This paper demonstrates the use of genetic algorithms to design a single output feedback control law for the simultaneous eigenvalue placement of a power system running over a wide range of operating conditions. The task of selecting the output feedback gains is converted to a simple optimization problem with an eigenvaluebased objective function, which is solved by a genetic algorithm. An objective function is presented allowing the selection of the output feedback gains to place the closed-loop eigenvalues in the left-hand side of a vertical line in the complex s-plane while shifting a specific mode of oscillation to a vertical strip and with bounds on the damping ratio. Simultaneous placement of the closed-loop eigenvalues of the power system operating at different loading conditions, using a single output feedback stabilizer, is demonstrated. The effectiveness of the output feedback stabilizer in enhancing the dynamic stability of power systems is verified through eigenvalue analysis and simulation results