Open Access. Powered by Scholars. Published by Universities.®
- Discipline
- Institution
- Publication
- Publication Type
Articles 1 - 19 of 19
Full-Text Articles in Engineering
Process Modeling And Optimization Strategies, Sandip K. Lahiri
Process Modeling And Optimization Strategies, Sandip K. Lahiri
Dr. Sandip Kumar Lahiri
This paper presents artificial intelligence-based process modeling and optimization strategies, namely, support vector regression – differential evolution (SVR-DE) for modeling and optimization of catalytic industrial ethylene oxide (EO) reactor. In the SVR-DE approach, a support vector regression model is constructed for correlating process data comprising values of operating and performance variables. Next, model inputs describing process operating variables are optimized using Differential Evolution (DE) with a view to maximize the process performance. DE possesses certain unique advantages over the commonly used gradient-based deterministic optimization algorithms. The SVR-DE is a new strategy for chemical process modeling and optimization. The major advantage …
Biogeography-Based Optimization, Daniel J. Simon
Biogeography-Based Optimization, Daniel J. Simon
Electrical and Computer Engineering Faculty Publications
Biogeography is the study of the geographical distribution of biological organisms. Mathematical equations that govern the distribution of organisms were first discovered and developed during the 1960s. The mindset of the engineer is that we can learn from nature. This motivates the application of biogeography to optimization problems. Just as the mathematics of biological genetics inspired the development of genetic algorithms (GAs), and the mathematics of biological neurons inspired the development of artificial neural networks, this paper considers the mathematics of biogeography as the basis for the development of a new field: biogeography-based optimization (BBO). We discuss natural biogeography and …
Product Family Design Using Smart Pareto Filters, Jonathan D. Yearsley
Product Family Design Using Smart Pareto Filters, Jonathan D. Yearsley
Theses and Dissertations
Product families are frequently used to provide consumers with a variety of appealing products and to help maintain reasonably low production costs for manufacturers. Three common objectives in the design of product families are used to balance the interests of both consumers and manufacturers. These objectives are to maximize (i) product performance, (ii) product distinctiveness as perceived by the consumer, and (iii) product commonality as seen by the manufacturer. In this thesis, three methods are introduced that use multiobjective optimization and Smart Pareto filtering to satisfy the three objectives of product family design. The methods are progressive in nature and …
Design Of A Three-Passage Low Reynolds Number Turbine Cascade With Periodic Flow Conditions, Daniel R. Rogers
Design Of A Three-Passage Low Reynolds Number Turbine Cascade With Periodic Flow Conditions, Daniel R. Rogers
Theses and Dissertations
A numerical method for modeling a low Reynolds number turbine blade, the L1M, is presented along with the pitfalls encountered. A laminar solution was confirmed to not accurately predict the flow features known in low Reynolds number turbine blade flow. Three fully turbulent models were then used to try to predict the separation and reattachment of the flow. These models were also found to be insufficient for transitioning flows. A domain was created to manually trip the laminar flow to turbulent flow using a predictive turbulence transition model. The trip in the domain introduced an instability in the flow field …
Process Modeling And Optimization Strategies Integrating Neural Networks And Differential Evolution, Nadeem Muhammed Khalfe
Process Modeling And Optimization Strategies Integrating Neural Networks And Differential Evolution, Nadeem Muhammed Khalfe
Nadeem Khalfe
This article presents an artificial intelligence-based process modeling and optimization strategy, namely artificial neural networks—differential evolution (ANN-DE) for modeling and optimizing catalytic industrial ethylene oxide (EO) reactors. In the ANN-DE approach, an artificial neural network model is constructed for correlating process data comprising values of operating and performance variables. Next, model inputs describing process operating variables are optimized using DEs with a view to maximizing the process performance. The DE possesses certain unique advantages over the commonly used gradient-based deterministic optimization algorithms. The ANN-DE is a new strategy for chemical process modeling and optimization. The major advantage of the strategy …
Control Strategy Optimization For A Parallel Hybrid Electric Vehicle, Andrew Meintz, Mehdi Ferdowsi
Control Strategy Optimization For A Parallel Hybrid Electric Vehicle, Andrew Meintz, Mehdi Ferdowsi
Electrical and Computer Engineering Faculty Research & Creative Works
The efficiency improvement of parallel hybrid electric vehicles (HEVs) is strongly dependent on how the supervisory control of a vehicle determines the power split between the internal combustion engine (ICE) and the electric motor of the vehicle. This paper presents a classification of current supervisory control techniques with distinction between dynamic and static control methods; a description of the simulation software ADvanced Vehicle SimulatOR (ADVISOR) with Matlab Simulink for simulation of a rule-based control strategy, and proposed optimization methods.
Discrete-Time Ripple Correlation Control For Maximum Power Point Tracking, Jonathan W. Kimball, Philip T. Krein
Discrete-Time Ripple Correlation Control For Maximum Power Point Tracking, Jonathan W. Kimball, Philip T. Krein
Electrical and Computer Engineering Faculty Research & Creative Works
Ripple correlation control (RCC) is a high-performance real-time optimization technique that has been applied to photovoltaic maximum power point tracking. This paper extends the previous analog technique to the digital domain. The proposed digital implementation is less expensive, more flexible, and more robust. with a few simplifications, the RCC method is reduced to a sampling problem; that is, if the appropriate variables are sampled at the correct times, the discrete-time RCC (DRCC) algorithm can quickly find the optimal operating point. First, the general DRCC method is derived and stability is proven. Then, DRCC is applied to the photovoltaic maximum power …
Optimization Constrained Cad Framework With Iso-Performing Design Generator, Kelly Eric Bowman
Optimization Constrained Cad Framework With Iso-Performing Design Generator, Kelly Eric Bowman
Theses and Dissertations
Design decisions have a large impact early in the design process. Optimization methods can help engineers improve their early decision making, however, design problems are often ill-posed for optimization at this early stage. This thesis develops engineering methods to use optimization during embodiment design, despite these difficulties. One common difficulty in designing mechanical systems is in handling the effects that design changes in one subsystem have on another. This is made more difficult in early engineering design, when design information is preliminary. Increased efforts have been made to use numerical optimization methods in early engineering design – because of the …
Optimization And Characterization Of Biodiesel Production From Cottonseed And Canola Oil, Hem Joshi
Optimization And Characterization Of Biodiesel Production From Cottonseed And Canola Oil, Hem Joshi
All Theses
Transesterification of cottonseed oil and canola oil was carried out using low molecular weight alcohols and potassium hydroxide. For cottonseed oil, a central composite design with eight factorial, six center and six axial points was used to study the effect of catalyst concentration, molar ratio of ethanol to cottonseed oil and reaction temperature on percentage yield and percentage initial absorbance (%A385nm) of the biodiesel. Catalyst concentration and molar ratio of ethanol to cottonseed oil were the most influential variables affecting percentage conversion and percentage initial absorbance. Maximum percentage yield of 98 % is predicted at a catalyst concentration of 1.07 …
Differential Evolution Particle Swarm Optimization For Digital Filter Design, Bipul Luitel, Ganesh K. Venayagamoorthy
Differential Evolution Particle Swarm Optimization For Digital Filter Design, Bipul Luitel, Ganesh K. Venayagamoorthy
Electrical and Computer Engineering Faculty Research & Creative Works
In this paper, swarm and evolutionary algorithms have been applied for the design of digital filters. Particle swarm optimization (PSO) and differential evolution particle swarm optimization (DEPSO) have been used here for the design of linear phase finite impulse response (FIR) filters. Two different fitness functions have been studied and experimented, each having its own significance. The first study considers a fitness function based on the passband and stopband ripple, while the second study considers a fitness function based on the mean squared error between the actual and the ideal filter response. DEPSO seems to be promising tool for FIR …
Parametric Optimization Design System For A Fluid Domain Assembly, Matthew Jackson Fisher
Parametric Optimization Design System For A Fluid Domain Assembly, Matthew Jackson Fisher
Theses and Dissertations
Automated solid modeling, integrated with computational fluid dynamics (CFD) and optimization of a 3D jet turbine engine has never been accomplished. This is due mainly to the computational power required, and the lack of associative parametric modeling tools and techniques necessary to adjust and optimize the design. As an example, the fluid domain of a simple household fan with three blades may contain 500,000 elements per blade passage. Therefore, a complete turbine engine that includes many stages, with sets of thirty or more blades each, will have hundreds of millions of elements. The fluid domains associated with each blade creates …
Optimization Model For National Water Master Planning: Design And Documentation, Richard C. Peralta
Optimization Model For National Water Master Planning: Design And Documentation, Richard C. Peralta
Civil and Environmental Engineering Faculty Publications
Physical distribution system and Balancing and Allocation and Transfer modules descriptors.
Hurricane Evacuation: Origin, Route And Destination, Vinayak Dixit
Hurricane Evacuation: Origin, Route And Destination, Vinayak Dixit
Electronic Theses and Dissertations
Recent natural disasters have highlighted the need to evacuate people as quickly as possible. During hurricane Rita in 2005, people were stuck in queue buildups and large scale congestions, due to improper use of capacity, planning and inadequate response to vehicle breakdown, flooding and accidents. Every minute is precious in situation of such disaster scenarios. Understanding evacuation demand loading is an essential part of any evacuation planning. One of the factors often understood to effect evacuation, but not modeled has been the effect of a previous hurricane. This has also been termed as the 'Katrina Effect', where, due to the …
New Heuristic And Metaheuristic Approaches Applied To The Multiple-Choice Multidimensional Knapsack Problem, Chaitr Hiremath
New Heuristic And Metaheuristic Approaches Applied To The Multiple-Choice Multidimensional Knapsack Problem, Chaitr Hiremath
Browse all Theses and Dissertations
The knapsack problem has been used to model various decision making processes. Industrial applications find the need for satisfying additional constraints and these necessities lead to the variants and extensions of knapsack problems which are complex to solve. Heuristic algorithms have been developed by many researchers to solve the variants of knapsack problems. Empirical analysis has been done to compare the performance of these heuristics. Little research has been done to find out why certain algorithms perform well on certain test problems while not so well on other test problems. There has been little work done to gain knowledge of …
Evolutionary Methodology For Optimization Of Image Transforms Subject To Quantization Noise, Michael Ray Peterson
Evolutionary Methodology For Optimization Of Image Transforms Subject To Quantization Noise, Michael Ray Peterson
Browse all Theses and Dissertations
Lossy image compression algorithms sacrifice perfect imagereconstruction in favor of decreased storage requirements. Modelossy compression schemes, such as JPEG2000, rely upon the discrete wavelet transform (DWT) to achieve high levels of compression while minimizing the loss of information for image reconstruction. Some compression applications require higher levels of compression than those achieved through application of the DWT and entropy coding. In such lossy systems, quantization provides high compression rates at the cost of increased distortion. Unfortunately, as the amount of quantization increases, the performance of the DWT for accurate image reconstruction deteriorates. Previous research demonstrates that a genetic algorithm can …
System Design Of Undersea Vehicles With Multiple Sources Of Uncertainty, Todd W. Benanzer
System Design Of Undersea Vehicles With Multiple Sources Of Uncertainty, Todd W. Benanzer
Browse all Theses and Dissertations
The work performed investigates the system design and optimization of an undersea vehicle. The system design is driven by the available components, the missions the vehicle is required to perform, and the performance the system configuration yields. The system design consists of three design modules: path planning, component selection and sizing, and structural analysis. The path planning module uses a novel application of the Particle Swarm Optimization algorithm named Path Planning by Additive Freedom. Additionally, the unknown aspects of the mission space through which the path propagates are dealt with using an uncertainty quantification method known as Evidence Theory. Component …
A Stochastic Production Planning Model Under Uncertain Demand, Meenakshi Prajapati
A Stochastic Production Planning Model Under Uncertain Demand, Meenakshi Prajapati
Browse all Theses and Dissertations
Production planning plays a vital role in the management of manufacturingfacilities. The problem is to determine the production loading plan consisting of the quantity of production and the workforce level - to fulfill a future demand. Although the deterministic version of the problem has been widely studied in the literature, the stochastic production planning problem has not. The application of production planning models could be limited if the stochastic nature of the problem, for example, uncertainty in future demand, is not addressed. This study addresses such a stochastic production planning problem under uncertain demand and its application in an enclosure …
Synthesis Design Of Artificial Magnetic Metamaterials Using A Genetic Algorithm, Chien Hsun Chen, P. Y. Chen, H. Wang, J. H. Tsai, W. X. Ni
Synthesis Design Of Artificial Magnetic Metamaterials Using A Genetic Algorithm, Chien Hsun Chen, P. Y. Chen, H. Wang, J. H. Tsai, W. X. Ni
Chien Hsun Chen
In this article, we present a genetic algorithm (GA) as one branch of artificial intelligence (AI) for the optimization-design of the artificial magnetic metamaterial whose structure is automatically generated by computer through the filling element methodology. A representative design example, metamaterials with permeability of negative unity, is investigated and the optimized structures found by the GA are presented. It is also demonstrated that our approach is effective for the synthesis of functional magnetic and electric metamaterials with optimal structures. This GA-based optimization-design technique shows great versatility and applicability in the design of functional metamaterials.
Analysis And Optimization Of Mobile Phone Antenna Radiation Performance In The Presence Of Head And Hand Phantoms, Erdem Ofli, Chung-Huan Li, Nicolas Chavannes, Niels Kuster
Analysis And Optimization Of Mobile Phone Antenna Radiation Performance In The Presence Of Head And Hand Phantoms, Erdem Ofli, Chung-Huan Li, Nicolas Chavannes, Niels Kuster
Turkish Journal of Electrical Engineering and Computer Sciences
A commercial clam shell phone CAD model is used to numerically investigate the effect of a hand phantom on mobile phone antenna radiation performance. The simulation results show that the grip of the hand phantom is the most important parameter to antenna performance. The antenna is converted into a parameterized form, then optimized to achieve the targeted multi-band performance in real-usage conditions.