Genetic Algorithm Optimization Scheme Research Articles

Total Energy-Based Control Design and Optimization for Lift-Plus-Cruise Aircraft

This paper presents a methodology for optimizing a Total Energy–based control system architecture for a lift-plus-cruise vertical takeoff and landing urban air mobility concept. The Total Energy Control System algorithm, which was originally developed for fixed-wing applications, is extended to also be applicable to hovering and transitioning flight. Control system parameters are optimized using a genetic algorithm optimization scheme, subject to constraints on dynamic stability and control response characteristics. Control system optimization and flight simulations are performed using the Modular Aircraft Dynamics and Control Algorithm Simulation Platform. Results presented include simulations of the optimized flight control system operation for maneuvering scenarios representative of hover, transition, and forward flight conditions as well as during transitions between vertical and forward flight modes. The presented results demonstrate the effectiveness of the proposed control system architecture and the demonstrated optimization methodology.

Full Envelope Flight Control System Design and Optimization for a Tilt-Wing Aircraft

Novel vertical take-off and landing advanced air mobility aircraft which are overactuated and transition between vertical and forward flight modes pose unique challenges for the design of safe and robust full-envelope fly-by-wire flight control systems. This paper presents a methodology for designing and optimizing a control system architecture for a tilt-wing urban air mobility concept. It features the total energy control system algorithm, which is extended to be applicable to hover and transitioning flight and explicit model following inner loops. Control system parameters are optimized using a genetic algorithm optimization scheme, subject to constraints on closed-loop dynamic stability and control response characteristics. Control system performance is demonstrated by simulation of lateral, longitudinal, and directional maneuvering for hover, transition, and forward flight conditions, followed by simulation of departure and arrival transitions while tracking a prescribed flightpath and speed profile in calm and turbulent air. The results demonstrate the effectiveness of the proposed control system architecture and the demonstrated optimization methodology.

GA-Based Voltage Optimization of Distribution Feeder with High-Penetration of DERs Using Megawatt-Scale Units

In this paper, genetic algorithm (GA)-based voltage optimization of a modified IEEE-34 node distribution feeder with high penetration of distributed energy resources (DERs) is proposed using two megawatt-scale reactive power sources. Traditional voltage support units present in distribution grids are not suitable for DER-rich feeders, while voltage support using small-scale DERs present in the feeder requires considerable communication effort to reach a global solution. In this work, two megawatt-scale units are placed to improve the voltage profile across the IEEE 34-node feeder, which has been modified to include several PV units and an energy storage unit. The megawatt-scale units are optimized using GA for fast and accurate operation. The performance of the proposed scheme is verified using simulation results with a multi-platform setup where the modified IEEE-34 node feeder is modeled in OpenDSS while the GA optimization scheme is programmed in MATLAB.

Model-free Sensor Placement for Water Distribution Networks using Genetic Algorithms and Clustering*

This paper presents a model-free methodology for the placement of pressure sensors in water distribution networks (WDNs) with the aim of performing leak detection/localization tasks. The approach is based on a custom genetic algorithm (GA) optimization scheme, which considers a population whose individuals are binary vectors encoding the network nodes with/without sensors. The optimization process pursues the minimization of a distance-based metric, computed considering the pipe distance from the possible sensors to the complete set of nodes of the network, hence removing the necessity of a hydraulic model of the WDN. The methodology is completed by means of an iterative clustering technique that seeks the enhancement of incoming individuals. The proposed methodology is tested over a well-known case study, L-TOWN from the BattLeDIM2020 challenge, in order to assess its performance.

Electric Vehicle Charging with Battery Scheduling and Multicriteria Optimization using Genetic Algorithm

The existing charging infrastructure needs expansion and upgrade with the growing fleet of electric vehicles (EV). The electric grids are largely affected by the uncontrolled charging cycles. To overcome this drawback, the hybrid charging stations are incorporated with battery storage and renewable energy sources. The power necessary from the grid can be buffered using a battery and renewable source attached to the charging station thereby avoiding the grid constraints and peaks. It has been a challenge to trace the origin of the battery’s energy till date. The battery energy storage and a simple photovoltaic system is incorporated in a hybrid EV charging station. Uncontrolled EV charging and its adverse effects can be overcome by this technology by accurately calculating the share of renewable energy derived from the battery. Multi-attribute utility theory is used for optimizing the EV charging level and scheduling the battery charging and discharging. Minimizing battery degradation and charging cost while maximizing the renewable energy from the battery and PV sources are the major criteria of optimization. Multicriteria optimization function is used along with the genetic algorithm optimization scheme to address the optimization issues. Optimal capacity of the battery and optimization strategy is affected by the preferences in decision making.

Cone Calorimeter and Thermogravimetric Analysis of Glass Phenolic Composites Used in Aircraft Applications

The increasing use of composite materials in aircraft cabins and structures poses significant challenges in order to maintain and improve the fire safety of aviation. In this work, the flammability characteristics of a commercial glass-fibre reinforced phenolic composite (GFRP) used for aircraft cabin partitions and furnishing are investigated experimentally. Thermogravimetric analysis under inert atmosphere at several heating rates provided information on the thermal decomposition process. The degradation process is modelled with one and two-step mechanisms using the Ozawa–Flynn–Wall iso-conversional method and the GPYRO numerical code which utilizes a genetic algorithm optimization scheme. The estimated activation energy and pre-exponential factor values, especially in the two-step case (77.18 and 104.69 kJ/mol and 2.60 × 106 and 3.19 × 106 min−1 for the first and the second step respectively), recover reasonably well the conversion degree and its derivative. Tests with a cone calorimeter (CC), performed at different incident heat fluxes, provided information on the reaction to fire characteristics of the material and the influence of the heat flux on the combustion process. In general, combustion proceeds in two stages, flaming and smoldering combustion. The CC results assisted by scanning electron microscopy photos provide information on the charring characteristics of the material. The critical heat flux for ignition and the corresponding ignition temperature are estimated, correlating heat fluxes with time to ignition. Thermally thin and thick models are considered, as well as a modified technique bridging the gap between these limit cases and therefore valid for thermally thin and thick but also intermediate conditions (more pertinent in the present case). The results for this latter approach are $$\dot{q}^{\prime\prime}_{ig,cr}$$ ~ 20 kW/m2 and Tig = 469°C, providing also complementing information on thermophysical properties, such as thermal diffusivity, α = 1.23 × 10−7 m2/s, thermal conductivity, k = 0.325 W/(m K) and specific heat capacity, c = 1.330 kJ/(kg K). This work provides information on the reaction to fire characteristics of GFRP, but also on physical and flammability properties in a form suitable to be used in numerical codes, for the prediction of fire and evacuation scenarios. The influence of the reinforcement structure on the fire behaviour of the composite is also illustrated and discussed.

Power enhancement of pontoon-type wave energy convertor via hydroelastic response and variable power take-off system

Wave energy has gained its popularity in recent decades due to the vast amount of untapped wave energy resources. There are numerous types of wave energy convertor (WEC) being proposed and to be economically viable, various means to enhance the power generation from WECs have been studied and investigated. In this paper, a novel pontoon-type WEC, which is formed by multiple plate-like modules connected by hinges, are considered. The power enhancement of this pontoon-type WEC is achieved by allowing certain level of structural deformation and by utilizing a series of optimal variable power take-off (PTO) system. The wave energy is converted into useful electricity by attaching the PTO systems on the hinge connectors such that the mechanical movements of the hinges could produce electricity. In this paper, various structural rigidity of the interconnected modules are considered by changing the material Young's modulus in order to investigate its impact on the power enhancement. In addition, the genetic algorithm optimization scheme is utilized to seek for the optimal PTO damping in the variable PTO system. It is observed that under certain condition, the flexible pontoon-type WEC with lesser connection joints is more effective in generating energy as compared to its rigid counterpart with higher connection joints. It is also found that the variable PTO system is able to generate greater energy as compared to the PTO system with constant/uniform PTO damping.

Effects of coupling anisotropic yield functions with the optimization process of extruded aluminum front rail geometries in crashworthiness

Using advanced constitutive models in simulation tools can improve predictive capabilities of automotive structures in crashworthiness applications. This work presents the influences of coupling anisotropic yield functions into the size optimization of extruded front rails to maximize energy absorption characteristics. Finite element simulations of the extrusion crush response are performed using the von Mises (1913), Hosford (1972) and Barlat et al. (2005) Yld2004-18p yield functions. Each yield function is implemented into a 2-dimensional plane stress and 3-dimensional element formulation to highlight the modeling differences prior to optimization. The simulations are also compared to the experimental dynamic crush response of the extrusion. The response surface methodology (RSM) with the artificial neural network (ANN) metamodeling technique is coupled with the genetic algorithm (GA) optimization scheme to improve the specific energy absorption (SEA) through maximizing energy absorption and minimizing mass. A constrained and unconstrained mass optimization study is performed to identify the sensitivity of global optimization to yield surface choice. Analytical models are derived to explain the influence of the yield surface on the convergence of optimization. The results highlight the importance of incorporating anisotropic yield functions into the optimization process.

Optimal Placement and Sizing of Fault Current Limiters in Distributed Generation Systems Using a Hybrid Genetic Algorithm

Distributed Generation (DG) connection in a power system tends to increase the short circuit level in the entire system which, in turn, could eliminate the protection coordination between the existing relays. Fault Current Limiters (FCLs) are often used to reduce the short-circuit level of the network to a desirable level, provided that they are dully placed and appropriately sized. In this paper, a method is proposed for optimal placement of FCLs and optimal determination of their impedance values by which the relay operation time, the number and size of the FCL are minimized while maintaining the relay coordination before and after DG connection. The proposed method adopts the removal of low-impact FCLs and uses a hybrid Genetic Algorithm (GA) optimization scheme to determine the optimal placement of FCLs and the values of their impedances. The suitability of the proposed method is demonstrated by examining the results of relay coordination in a typical DG network before and after DG connection.

Adjustable maneuvering time wave-form command shaping control with variable hoisting speeds

Classical input shaping is based on convolving a general input signal with a sequence of timed impulses. These impulses are chosen to match certain modal parameters of the system under control to eliminate residual vibrations in rest-to-rest maneuvers. This type of input shaping is strongly dependent on the system period. In this work, an adjustable maneuvering time wave form command shaper is presented. The equation of motion of a simple pendulum model of a crane is derived and solved in order to eliminate residual vibrations at the end of motion. Several cases are simulated numerically and validated experimentally on an experimental model of an overhead crane. Results show that the proposed command shaper is capable of eliminating residual vibrations effectively with a single continuous wave form command. The work is extended to include the effect of hoisting on the shaper performance. Several functions are used to simulate hoisting. To overcome the added complexity of hoisting on the system, an approximation technique is used to determine initial shaped command parameters, which are later used in a genetic algorithm optimization scheme. Numerical and experimental results prove that the proposed command shaper can effectively eliminate residual vibrations in rest-to-rest maneuvers.

Experimental investigations of the performance of a standing wave thermoacoustic refrigerator based on multi-objective genetic algorithm optimized parameters

This paper presents an experimental work based on the results from the Multi-objective Genetic Algorithm (MOGA) optimization scheme for a standing wave thermoacoustic refrigerator. In this study, the performance of the thermoacoustic refrigerator is based on the temperature difference measured at the end of extremities of the stack. The optimized variables are the stack length, stack center position and the plate spacing represented by the blockage ratio. Two different stacks were investigated: 1) spiral geometry build from Mylar, and 2) ready-made ceramic Celcor stack. Comparisons of the effects of the stack length, center position and plate spacing were completed between the optimized outcomes from MOGA and that measured experimentally. Results showed good agreement, confirming that values other than the optimized stack length of 4 cm, stack center position of 4 cm, and the stack separation gap of 0.36 mm did not give the desired high performance of the thermoacoustic refrigerator.

Iterative GA Optimization Scheme for Synthesis of Radiation Pattern of Linear Array Antenna

This research has proposed the iterative genetic algorithm (GA) optimization scheme to synthesize the radiation pattern of an aperiodic (nonuniform) linear array antenna. The aim of the iterative optimization is to achieve a radiation pattern with a side lobe level (SLL) of ≤−20 dB. In the optimization, the proposed scheme iteratively optimizes the array range (spacing) and the number of array elements, whereby the array element with the lowest absolute complex weight coefficient is first removed and then the second lowest and so on. The removal (the element reduction) is terminated once the SLL is greater than −20 dB (>−20 dB) and the elemental increment mechanism is triggered. The results indicate that the proposed iterative GA optimization scheme is applicable to the nonuniform linear array antenna and also is capable of synthesizing the radiation pattern with SLL ≤ −20 dB.

A New Compact Wideband MIMO Antenna—The Double-Sided Tapered Self-Grounded Monopole Array

We present a new compact wideband multiple input multiple output (MIMO) antenna—the double-sided 4-port arm-tapered self-grounded monopole array, briefly referred to as the butterfly antenna, in the communication. The antenna is very compact with low correlation between ports and high diversity gain. The genetic algorithm optimization scheme has been employed in the design. Simulation results have been verified against measurements. The measured reflection coefficients at all ports are below <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$-$</tex> </formula> 7 dB over 0.5–9 GHz and below <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex Notation="TeX">$-$</tex></formula> 4.5 dB over 0.4–0.5 GHz and 9–15 GHz. The measured correlation coefficients are below 0.4 over 0.4–15 GHz and lower than 0.1 in most of the frequency band. This new MIMO antenna is developed as a transmit antenna in reverberation chambers, and we believe that it will find more applications in other systems, such as micro base station antennas in wireless communication systems.

The Circular Eleven Antenna: A New Decade-Bandwidth Feed for Reflector Antennas With High Aperture Efficiency

Future ultra-wideband (UWB) radio telescopes require UWB feeds for reflector antennas, and many new UWB feed technologies have gained substantial progress to satisfy the tough specifications for future radio telescope projects, such as the square kilometer array (SKA). It has been noticed that, different from traditional narrow-band horn feeds, all UWB feeds are non-BOR (Body of Revolution) antennas. Therefore, BOR1 efficiency becomes an important characterization for the modern UWB feed technologies. We present a novel circular Eleven feed, constructed of “circularly” curved folded dipoles printed on flat circuit boards, in order to have high BOR1 efficiency at a low manufacture cost. The Genetic Algorithm (GA) optimization scheme has been applied to the design for achieving a low reflection coefficient. Simulated and measured results show that the circular Eleven feed has a reflection coefficient below -6 dB over 1.6-14 GHz and below -10 dB over 78% of the band, and an aperture efficiency higher than 60% over 1-10 GHz and 50% up to 14 GHz.

Optimal Rotor Structure Design of Interior Permanent Magnet Synchronous Machine based on Efficient Genetic Algorithm Using Kriging Model

In the recent past, genetic algorithm (GA) and evolutionary optimization scheme have become increasingly popular for the design of electromagnetic (EM) devices. However, the conventional GA suffers from computational drawback and parameter dependency when applied to a computationally expensive problem, such as practical EM optimization design. To overcome these issues, a hybrid optimization scheme using GA in conjunction with Kriging is proposed. The algorithm is validated by using two mathematical problems and by optimizing rotor structure of interior permanent magnet synchronous machine.

Rapid evaluation and damage assessment of instrumented highway bridges

SUMMARYThis study focuses on the use of strong motion data recorded during earthquakes and aftershocks to provide a preliminary assessment of the structural integrity and possible damage in bridges. A system identification technique is used to determine dynamical characteristics and high‐fidelity first‐order linear models of a bridge from low level earthquake excitations. A finite element model is developed and updated using a genetic algorithm optimization scheme to match the frequencies identified and to simulate data from a damaging earthquake for the bridge. Here, two criteria are used to determine the state of the structure. The first criteria uses the error between the data recorded or simulated by the calibrated nonlinear finite element model and the data predicted by the linear model. The second criteria compares relative displacements of the structure with displacement thresholds identified using a pushover analysis. The use of this technique can provide an almost immediate, yet reliable, assessment of the structural health of an instrumented bridge after a seismic event. Copyright © 2011 John Wiley &amp; Sons, Ltd.

Hierarchical synthesis system with hybrid DLO‐MOGA optimization

PurposeThe purpose of this paper is to present a hierarchical circuit synthesis system with a hybrid deterministic local optimization – multi‐objective genetic algorithm (DLO‐MOGA) optimization scheme for system‐level synthesis.Design/methodology/approachThe use of a local optimization with a deterministic algorithm based on linear equations which is computationally efficient and improves the feasibility of designs, allows reduction in the number of MOGA generations required to achieve convergence.FindingsThis approach reduces the total number of simulation iterations required for optimization. Reduction in run time enables use of full transistor‐level models for simulation of critical system‐level sub‐blocks. Consequently, for system‐level synthesis, simulation accuracy is maintained. The approach is demonstrated for the design of pipeline analog‐to‐digital converters on a 0.35 μm process.Originality/valueThe use of a hybrid DLO‐MOGA optimization approach is a new approach to improve hierarchical circuit synthesis time while preserving accuracy.

Experimental and Theoretical Study of Calcium Sulphate Precipitation in Porous Media Using Glass Micromodel

Mixing of two incompatible waters in water injection projects is usually associated with mineral scale formation and deposition in porous media. Deposition process dramatically affects the performance of water injection scenarios by reduction of porosity and mainly permeability of the rock. In this study, a series of experiments has been conducted to investigate the effect of different parameters on the gradual process of Calcium Sulphate precipitation. These include temperature, concentration of mixing brines, pressure, and flow rate. Due to the visual nature of the glass micromodel, a glass sandstone pattern with water-wet characteristics was used as porous medium to easily observe the scaling formation and distribution. In addition, tracing the movement of the solid particles is highly facilitated in this newly suggested experimental setup. The captured photos in microscopy scanning show that the deposition is initiated from the walls of the pores and throats and extend toward the middle space of porous medium and solid crystals look like chicken roost. For better understanding of the effect of any aforementioned parameter, the related permeability reduction curve versus injected pore volume of the brine solutions was plotted. The results indicated that as the temperature, brine concentration, and flow rate increase the scaling tendency increases as well. The pressure has a minor role on the process development. Deposition of CaSO4 manifests a functional form of permeability reduction due to the effect of different parameters. Therefore, an exponential functionality (correlation) was proposed which incorporates all physical parameters that affect the behavior of the system in dimensionless form. Reynolds number, scaling index, and deviation from equilibrium conditions are the backbone of this correlation. The adjustable exponents of the equation was determined and optimized by means of Genetic Algorithm optimization scheme. This meaningful correlation can also predict the core extracted data with reasonable accuracy.

Implementation of fractional-order electromagnetic potential through a genetic algorithm

Several phenomena present in electrical systems motivated the development of comprehensive models based on the theory of fractional calculus (FC). Bearing these ideas in mind, in this work are applied the FC concepts to define, and to evaluate, the electrical potential of fractional order, based in a genetic algorithm optimization scheme. The feasibility and the convergence of the proposed method are evaluated.

Optimal design of composite wing structures with blended laminates

In this paper we formulate the problem of wing box design optimization using composite laminates with blending constraints. The use of composite laminates necessitates the inclusion of fiber orientation angle of the layers as well as total thickness of the laminate as design variables in the design optimization problem. The wing box design problem is decomposed into several independent local panel design problems. In general such an approach results in a nonblended solution with no continuity of laminate lay ups across the panels, which may not only increase the lay up cost but may also be structurally unsafe due to discontinuities. The need for a blended solution increases the complexity of the problem many fold. In this paper we impose the blending constraints globally by using a guide based design methodology within the genetic algorithm optimization scheme and compare the results with the published ones. Two different blending schemes – outer and inner blending are presented. The result shows that the optimum design obtained using the current methodology has better continuity of laminate lay ups and also the reported weight of the composite wing box is on the lower side. Finally, a parametric study of the effect of global deflection constraint on the total weight of the optimum design is presented.