Ali Sarosh

Simulated annealing based artificial bee colony algorithm for global numerical optimization

Abstract Artificial bee colony (ABC) algorithm is a global optimization algorithm, which has been shown to be competitive with some conventional swarm algorithm, such as genetic algorithm (GA) and particle swarm optimization (PSO). However, there is still an insufficiency in ABC algorithm, in that it has poor convergence rate in some situations. Inspired by simulated annealing algorithm, a simulated annealing based ABC algorithm (SAABC) is proposed. Simulated annealing algorithm is introduced into employed bees search process to improve the exploitation of the algorithm. The experimental results are tested on a set of numerical benchmark functions with different dimensions. That show that SAABC algorithm can outperform ABC and global best guided ABC algorithms in most of the experiments.

An improved particle swarm optimizer for parametric optimization of flexible satellite controller

Abstract Parametric optimization of flexible satellite controller is an essential for almost all modern satellites. Particle swarm algorithm is a global optimization algorithm but it suffers from two major shortcomings, that of, premature convergence and low searching accuracy. To solve these problems, this paper proposes an improved particle swarm optimization (IPSO) which substitute “poorly-fitted-particles” with a cross operation. Based on decision possibility, the cross operation can interchange local optima between three particles. Thereafter the swarm is split in two halves, and random number (s) get generated by crossing the dimension of particle from both halves. This produces a new swarm. Now the new swarm and old swarm are mixed, and based on relative fitness a half of the particles are selected for the next generation. As a result of the cross operation, IPSO can easily jump out of local optima, has improved searching accuracy and accelerates the convergence speed. Some test functions with different dimensions are used to analyze the performance of IPSO algorithm. Simulation results show that the IPSO has more advantages than standard PSO and Genetic Algorithm PSO (GAPSO). In that it has a more stable performance and lower level of complexity. Thus the IPSO is applied for parametric optimization of flexible satellite control, for a satellite having solar wings and antennae. Simulation results shows that the IPSO can effectively get the best controller parameters vis-a-vis the other optimization methods.

A TIPSO algorithm assessment for aerothermodynamic optimization of hypersonic compression systems

A two-step improved particle swarm optimization (TIPSO) algorithm was recently proposed and used for the optimization of flexible satellite-control parameters. It was found to be much more stable and much less complex than other evolutionary algorithms. In this article the efficacy of the TIPSO algorithm is investigated for multidisciplinary optimization of aerothermodynamic parameters of performance, cowl deflection angle and shock–boundary layer separation on a cone-derived, wedge-integrated hypersonic (waverider) compression system. This algorithm uses an aggregate objective function. Optimization results from the TIPSO algorithm are compared with those obtained from a hybrid genetic algorithm, particle swarm optimization using an inertial weight approach and a multi-objective genetic algorithm. Since optimality of the forebody configuration is the basic requirement, the optimization variables selected are the isolator exit Mach number, static pressure ratio across the forebody–inlet configuration, cycle temperature ratio and cowl (inlet) deflection angle, which is the maximum deflection angle corresponding to the optimum oblique shock angle generated by the inlet cowl. Simulation results show that for the given case study only the TIPSO algorithm can locate the globally best aerothermodynamic–geometric parameters, compared with all the other optimization methods.

An Aerothermodynamic and Mass-Model Integrated Optimization Framework for Highly-Integrated Forebody-Inlet Configurations

A framework methodology for multidisciplinary multiobjective optimization and analysis is proposed. It is based on analytical aerothermodynamics and mass-modeling parameters of highly-integrated forebody-inlet configuration and representative hypersonic flight vehicle respectively. A complex configuration for a highly-integrated waverider forebody attached to planar compression ramps and planar sidewalled-inlet system is studied. Optimization and analytical solutions are obtained using SHWAMIDOF-FI design tool. Results show substantial improvement in geometric, performance and flow parameters as compared to baseline configuration.

STS Forebody Material Selection Method Using Integrated Aerothermodynamic Optimization Approach

Ceramic matrix composites have been recommended for space applications. Accordingly, in this paper, a material selection method for the forebody of a space transportation system is demonstrated. The methodology is based on mass-model coupled aerothermodynamic design of a highly-integrated forebody-inlet system that uses the multidisciplinary optimization capability of the TIPSO (Two-steps Improved PSO) algorithm. The design optimization and hence material parameters are evolved using the newly developed SHWAMIDOF-FI tool. This paper focuses on validating the selection of carbon composite material by optimizing the configuration parameters for integrating a cone-derived forebody into planar wedge surfaces and an inlet-isolator assembly, so as to form a mixed internal-external compression system. Surface temperature, thermal conductivity, tensile strength and emissivity are used as primary parameters for selection of a forebody material. The optimization results validate that a carbon fibre reinforced carbon and silicon carbide (C/C-SiC) dual matrix composite is best suited for the application

Artificial Bee Colony Algorithm for Parametric Optimization of Spacecraft Attitude Tracking Controller

To satisfy the rapidly and accurately attitude tracking for spacecraft, artificial bee colony (ABC) algorithm is introduced to the controller parametric optimization of spacecraft attitude tracking. The spacecraft attitude tracking dynamics model, kinematics model and a sliding model controller using radial basis function neural network are build up. The concept of ABC algorithm is presented and the steps are also given. For the fitness function of ABC algorithm, the weighted index of error and angular velocity error with the simulation time are used. The optimization result compared between particle swarm optimization (PSO) and ABC algorithm shows the efficient of the ABC algorithm. The simulation result with the optimized controller shows that the controller could guarantee robustness against uncertainties and external disturbances increased.

A Cognitive-Heuristic Framework for Optimization of Spaceplane-System Configurations

A cognitive-heuristic framework for interconnecting analytical aerothermodynamics and mass-modeling parameters to heuristic optimizer is proposed. It evaluates a complex highly-integrated forebody-inlet configuration and representative hypersonic spaceplane based on minimal input data of flight altitude and Mach number only. SHWAMIDOF-FI design tool is used which incorporates salient features of multi-stage cognitive work approach integrated to heuristic optimization. Results show substantial improvement in geometric, performance, and flow parameters as compared to baseline configuration.

Real Time Distress Monitoring of Soft Soil Highway Embankment

Highway embankments constructed over soft soil foundation exhibit pronounced settlement/geotechnical distresses resulting in reduced service life of communication infrastructure; necessitates real time monitoring system. Upgradation/maintenances of road infrastructure is a continuous practice, worldwide. Construction of Swat Motorway in Pakistan is one such mega project at hand, where high water table and soft foundation strata is encountered. This paper attempts to explore and evaluate the modern procedural developments in highway embankments; acquisition, interpretation and processing of real time data associated with soft soil monitoring systems using Micro Electro Mechanical Sensors (MEMS). The authors are of the view that findings of the research would help proposing innovative methodology in reducing foundation hazards related to highways, minimizing maintenance cost and help improving roadways serviceability.

Counterspace Operations and Nascent Space Powers

ABSTRACT In twenty-first-century warfare, satellites have become indispensable for gaining dominance in battlespace. This highlights the need to protect space assets while countering the qualitative edge that space can provide to adversarial actions. Hence, “counterspace operations” continue to gain the attention of military planners and researchers around the globe. Although it is the major space powers that have developed requisite capability and are showing more concerns for space security, these concerns are global in nature. As such, there is a need to develop a framework that can be utilized by nascent space powers to ensure protection of their space assets. This research work is intended to draw the attention of policymakers, space-technology protagonists, and military personnel, particularly of nascent space powers, to these global concerns. It gives an overview of counterspace operations and explores the doctrinal view-point of major military space powers for safeguarding their own space programs and negating the advantage of space to the enemy. Based upon this, a step-by-step approach is proposed for nascent space powers for embodying of elements of counterspace operations to remain protected during peace, crisis, or war.

An Aerothermodynamic Design Approach for Scramjet Combustors and Comparative Performance of Low-Efficiency Systems

This paper is aimed at development of an integrated approach based on analytical and computational aerothermodynamics for the special case of design of a 75% (low process-efficiency), hydrogen-fuelled, constant area combustor of a hypersonic airbreathing propulsion (HAP) system thereafter undertaking study of two types of HAP systems. The results of configurational aerothermodynamics implied that the most appropriate constant area configuration had a 30 degrees downstream wall-mounted fuel injector with a single acoustically stable cavity placed downstream of the fuel injection point. Moreover for identical flow inlet parameters and system configurations at lower levels of thermodynamic process efficiencies, the constant combustor-area (i.e. Scramjet 1) engine is superior in its performance to the constant combustor-pressure (i.e. Scramjet 2) engine for all values of fuel-air ratios.