Systems Engineering and Multidisciplinary Design Optimization Commons^™

Influence Of The Inherent Safety Principles On Quantitative Risk In Process Industry: Application Of Genetic Algorithm Process Optimization (Gapo), Mehdi Jahangiri, Abolfazl Moghadasi, Mojtaba Kamalinia, Farid Sadeghianjahromi, Sean Banaee

Community & Environmental Health Faculty Publications

Inherent safety (IS) refers to a set of measures that enhance the safety level of processes and equipment, rendering additional equipment and/or add-ons. The early design phase of processes is suited best for implementation of IS strategies as some of such strategies either are impossible to be implemented at the operation phase or substantially increase costs. The purpose of this study is to present a new approach called genetic algorithm process optimization (GAPO), by which processes can be made inherently safer even at the operation phase. This study simulates the IS principle, assessing its impact on quantitative risk and the …

A Multi-Objective Differential Evolution Algorithm For Engineering Design Optimization, Shantanu S. Muluk

Mechanical & Aerospace Engineering Theses & Dissertations

The current research investigation focuses on the development of a multi-objective global optimizer based on the differential evolution algorithm. A rotationally invariant version of the original differential evolution algorithm is adopted as the core component of the optimization procedure. The optimizer is applied to a number of multi-objective problems: constrained problems, problems of high dimensionality, and problems with non-convex Pareto fronts.

The effectiveness of the proposed optimization framework in real engineering design problems is demonstrated by carrying out an aerodynamic shape optimization of wind turbine airfoils. The investigation focuses on both thin and thick airfoils. The produced Pareto-optimal airfoil shapes …

Kalman Filtering With State Constraints: A Survey Of Linear And Nonlinear Algorithms, Daniel J. Simon

Electrical and Computer Engineering Faculty Publications

The Kalman filter is the minimum-variance state estimator for linear dynamic systems with Gaussian noise. Even if the noise is non-Gaussian, the Kalman filter is the best linear estimator. For nonlinear systems it is not possible, in general, to derive the optimal state estimator in closed form, but various modifications of the Kalman filter can be used to estimate the state. These modifications include the extended Kalman filter, the unscented Kalman filter, and the particle filter. Although the Kalman filter and its modifications are powerful tools for state estimation, we might have information about a system that the Kalman filter …

Prioritizing Satellite Payload Selection Via Optimization, Benjamin S. Kallemyn

Theses and Dissertations

This thesis develops optimization models for prioritizing payloads for inclusion on satellite buses with volume, power, weight and budget constraints. The first model considers a single satellite launch for which the budget is uncertain and constellation requirements are not considered. Subsequently, we include constellation requirements and provide a more enhanced model. Both single-launch models provide a prioritized list of payloads to include on the launch before the budget is realized. The single-launch models are subsequently extended to a sequence of multiple launches in two cases, both of which incorporate an explicit dependence on the constellation composition at each launch epoch. …

Most Probable Point-Based Design Optimization, Akhil R. Tipnis

Mechanical & Aerospace Engineering Theses & Dissertations

Modem products ranging from simple components to complex systems should be designed to be optimal and reliable. The challenge of modem engineering is to ensure that manufacturing costs are reduced and design cycle times are minimized while achieving requirements for performance and reliability. If the market for the product is competitive, improved quality and reliability can generate very strong competitive advantages. Reliability based design optimization plays a very important role in designing almost any kind of product. This investigation focuses on the development of the hybrid PMNRIA approach which uses the active-in-reliability concept for reliability based design optimization. The efficiency …

An Approach For Multidisciplinary Design Optimization, Robert V. Krueger

Mechanical & Aerospace Engineering Theses & Dissertations

Multidisciplinary Design Optimization (MDO) is an optimization technique that allows complex designs to be improved by managing conflicting goals in such a fashion so as to improve the overall design. This thesis presents a nonhierarchic MDO formulation and gives a general explanation of how it is to be applied to various appropriate problems. In addition, this thesis evaluates the viability of this MDO technique by applying it to two distinct, multidisciplinary problems that have been used as examples in other literature. The first example problem is a combined aerodynamic/structural problem and the second example is an alkylation process problem. First, …

Multipoint Quadratic Approximation For Numerical Optimization, Michael A. Blaylock

Theses and Dissertations

A quadratic approximation for nonlinear functions is developed in order to realize computational savings in solving numerical optimization problems. Function and gradient information accumulated from multiple design points during the iteration history is used in estimating the Hessian matrix. The approximate Hessian matrix is the available for a second order Taylor series approximation to the functions of interest. Several truss and frame models will be used to demonstrate the effectiveness of the new Multipoint Quadratic Approximation (MQA) in solving structural optimization problems.