Engineering Commons^™

Constrained Biogeography-Based Optimization For Invariant Set Computation,, Arpit Shah, Daniel Simon, Hanz Richter

Hanz Richter

We discuss the application of biogeography-based optimization (BBO) to invariant set approximation. BBO is a recently developed evolutionary algorithm (EA) that is motivated by biogeography, which is the study and science of the geographical migration of biological species. Invariant sets are sets in the state space of a dynamic system such that if the state begins in the set, then it remains in the set for all time. Invariant sets have applications in many constrained control problems, and their computation amounts to a constrained optimization problem. We therefore frame the invariant set computation problem as a constrained optimization problem, and …

Probe-Pulse Optimization For Nonresonant Suppression In Hybrid Fs/Ps Coherent Anti-Stokes Raman Scattering At High Temperature, Joseph D. Miller, Mikhail N. Slipchenko, Terrence R. Meyer

Terrence R Meyer

Hybrid femtosecond/picosecond coherent anti-Stokes Raman scattering (fs/ps CARS) offers accurate thermometry at kHz rates for combustion diagnostics. In high-temperature flames, selection of probe-pulse characteristics is key to simultaneously optimizing signal-to-nonresonant-background ratio, signal strength, and spectral resolution. We demonstrate a simple method for enhancing signal-to-nonresonant-background ratio by using a narrowband Lorentzian filter to generate a time-asymmetric probe pulse with full-width-half-maximum (FWHM) pulse width of only 240 fs. This allows detection within just 310 fs after the Raman excitation for eliminating nonresonant background while retaining 45% of the resonant signal at 2000 K. The narrow linewidth is comparable to that of a …

Stochastic Modeling And Optimization Of Multi-Plant Capacity Planning Problem, Anoop Verma, Nagesh Shukla, S.K Tyagi, Nishikant Mishra

Nagesh Shukla

n this paper the problem of capacity planning under risk from demand and price/cost uncertainty of the finished products is addressed. The deterministic model is extended into a two-stage stochastic model with fixed recourse by means of various expected levels of demand as random. A recourse penalty is also included in the objective for both shortage and surplus in the finished products. The model is analyzed to quantify the risk using Markowitz mean-variance model.

Seismic Isolation Of A Highly Skewed, Prestressed Concrete Girder Bridge, Bradley Robson, Issam Harik, David Allen

Issam E. Harik

A relatively new approach for designing or retrofitting highway bridges in seismic zones involves isolating the superstructure from the substructure. Through experimental and analytical investigations, this study evaluates the effectiveness of isolating one particular bridge: a highly skewed, prestressed concrete, slab-on-girder bridge. Dynamic testing of the bridge was performed using the pullback, quick-release method. A three dimensional finite element model of the bridge was created. It was refined, or calibrated, to match experimentally determined natural frequencies and mode shapes. Time-history analyzes, using site-specific acceleration records, were conducted for the seismically isolated bridge model and an identical, non-isolated bridge model.

For …

Solving Machine Loading Problem Of Fms: An Artificial Intelligence (Ai) Based Random Search Optimization Approach, Anoop Prakash, Nagesh Shukla, Ravi Shankar, Manoj Tiwari

Nagesh Shukla

Artificial intelligence (AI) refers to intelligence artificially realized through computation. AI has emerged as one of the promising computer science discipline originated in mid-1950. Over the past few decades, AI based random search algorithms, namely, genetic algorithm, ant colony optimization, and so forth have found their applicability in solving various real-world problems of complex nature. This chapter is mainly concerned with the application of some AI based random search algorithms, namely, genetic algorithm (GA), ant colony optimization (ACO), simulated annealing (SA), artificial immune system (AIS), and tabu search (TS), to solve the machine loading problem in flexible manufacturing system. Performance …

Optimization Of System Reliability Using Chaos-Embedded Self-Organizing Hierarchical Particle Swarm Optimization, M Bachlaus, N Shukla, M Tiwari, R Shankar

Nagesh Shukla

This paper addresses a reliability optimization problem, where the motive is to select the best components for series and series-parallel systems such that system reliability becomes maximized while simultaneously minimizing the cost, weight, and volume. Previous formulation of the problem has implicit restrictions, i.e. it either maximizes system reliability or minimizes the cost. Thus, in order to give a realistic view to the model, a comprehensive objective function has been formulated by combining the normalized values of reliability, cost, weight, and volume. In this paper, a chaos-embedded hierarchical particle swarm optimization (CE-HPSO) algorithm has been proposed to solve the problems …

Optimization Of Threshold Values For Estimators Based On Single-Bit Quantized Sensors Using Genetic Algorithms, Nishant Unnikrishnan, Ajay Mahajan, Antonios Mengoulis, R. Viswanathan

Dr. Ajay Mahajan

The paper considers the problem of signal parameter estimation using a collection of distributed sensors called a sensor pack. Each sensor quantizes its data to one-bit information and sends it to a fusion processor for the estimation of the parameter. Estimation of a constant signal in additive noise is considered. Estimators are formulated based on one-bit sensor data and their mean squared error (MSE) performances are evaluated through simulation studies. It is shown that selecting certain threshold values for quantizing the sensor outputs can lower the MSE. Genetic algorithms are used to find the optimal threshold values for the sensors. …

Particle Swarm Optimization Approach For Maximizing The Yield Of A Coal Preparation Plant, Vishal Gupta, Hussain Unjawala, Ajay Mohan Mahajan, Manoj Mohanty

Dr. Ajay Mahajan

This paper presents the use of particle swarm optimization to maximize the clean coal yield of a coal preparation plant that typically has multiple cleaning circuits that produce the same product quality so that the blend of clean coal meets the targeted product quality contraints. Particle swarm is used for the yield optimization while satisfying multiple product quality restraints. The results show a 2.73% increase in the yield can be achieved leading to additional revenue of $5,460,000 per annum for a plant producing 10 million tons of clean coal per year without significantly adding to the implementation/operation cost.

Genetic Algorithms — A Novel Technique To Optimize Coal Preparation Plants, Vishal Gupta, Manoj Mohanty, Ajay Mahajan, S. Biswal

Dr. Ajay Mahajan

A coal preparation plant typically operates with multiple cleaning circuits based on the particle size distribution of run-of-mine coal. Clean coal product from a plant commonly has to satisfy multiple product quality constraints, including product ash, product sulfur, heating value, moisture content, etc. Numerous studies in the past illustrate that the optimal yield of the plant can be obtained by operating each circuit to produce the same incremental product quality. This equal incremental product quality approach optimizes the plant yield considering only one product quality at a time. Thus, when required to simultaneously satisfy multiple product quality constraints, the process …

Performance Optimization Of A Coal Preparation Plant Using Genetic Algorithms, Vishal Gupta, Manoj Mohanty, Ajay Mahajan, Surendra Biswal

Dr. Ajay Mahajan

A coal preparation plant typically has multiple cleaning circuits based on size of coal particles. The traditional way of optimizing the plant output and meeting the product constraints such as ash, sulfur and moisture content is to equalize the average product quality from each circuit. The present study includes multiple incremental product quality approach to optimize the clean coal recovery while satisfying the product constraints. The plant output was optimized at the given constraints of 7.5% ash and 1.3% sulfur. It was observed that utilizing incremental product quality process gives 2.13% higher yield which can generate additional revenue of $4,260,000 …

Optimizing The Robot Arm Movement Time Using Virtual Reality Robotic Teaching System

Faculty of Engineering University of Malaya

Robots play an important role in performing operations such as welding, drilling and screwing parts in manufacturing. Optimizing the robot arm movement time between different points is an important task which will minimize the make-span and maximize the production rate. But robot programming is a complex task whereby the user needs to teach and control the robot in order to perform a desired action. In order to address the above problem, an integrated 3-dimensional (3D) simulation software and virtual reality (VR) system is developed to simplify and speed up tasks and therefore enhance the quality of manufacturing processes. This system …

Stiffness Performance Of Polyethylene Terephthalate Modified Asphalt Mixtures Estimation Using Support Vector Machine-Firefly Algorithm

Faculty of Engineering University of Malaya

Predicting asphalt pavement performance is an important matter which can save cost and energy. To ensure an accurate estimation of performance of the mixtures, new soft computing techniques can be used. In this study, in order to estimate the stiffness property of Polyethylene Terephthalate (PET) modified asphalt mixture, different soft computing methods were developed, namely: support vector machine-firefly algorithm (SVM-FFA), genetic programming (GP), artificial neural network (ANN) and support vector machine. The support vector machine-firefly algorithm (SVM-FFA) is a metaheuristic search algorithm developed according to the socially dashing manners of fireflies in nature. To develop the models, experiments were performed. …

A New Low-Profile Inverted A-Shaped Patch Antenna For Multi-Band Operations

Faculty of Engineering University of Malaya

This paper presents the design and analysis of a compact modified inverted-A shape multi-band patch antenna for WiMAX and C-band telecommunication satellite applications. The proposed antenna has simple geometrical structure which consist of 20 mm x 20 mm radiating patch with slot loading and fed by 4 mm long microstrip line. The proposed antenna is designed and analyzed by using commercially available full-wave 3D high frequency electromagnetic simulator namely Ansys HFSS. The optimized design of the proposed multi-band patch antenna is fabricated on 1.6 mm thick fiberglass polymer resin dielectric material substrate with reduced ground plane by using in-house PCB …

Fuzzy Logic Based Model For Predicting Surface Roughness Of Machined Al-Si-Cu-Fe Die Casting Alloy Using Different Additives-Turning

Faculty of Engineering University of Malaya

This paper presents a fuzzy logic artificial intelligence technique for predicting the machining performance of Al-Si-Cu-Fe die casting alloy treated with different additives including strontium, bismuth and antimony to improve surface roughness. The Pareto-ANOVA optimization method was used to obtain the optimum parameter conditions for the machining process. Experiments were carried out using oblique dry CNC turning. The machining parameters of cutting speed, feed rate and depth of cut were optimized according to surface roughness values. The results indicated that a cutting speed of 250 m/min, a feed rate of 0.05 mm/rev, and a depth of cut of 0.15 mm …

Estimation Of The Effect Of Catalyst Physical Characteristics On Fenton-Like Oxidation Efficiency Using Adaptive Neuro-Fuzzy Computing Technique

Faculty of Engineering University of Malaya

Catalyst size, which determines surface area, is one of the major factors in catalytic performance. In this study, response surface methodology (RSM) and an adaptive neuro-fuzzy inference system (ANFIS) were applied to quantify the effects of physical characteristics of magnetite on Fenton-like oxidation efficiency of methylene blue. For this purpose, two magnetite samples (M and N) were used and characterized by XRD, BET surface area, particle size analyzer and FE-SEM. Central composite design (CCD) was applied to design the experiments, develop regression models, optimize and evaluate the individual and interactive effects of five independent variables: H2O2 and catalyst concentrations, pH, …