Resit Unal

System of Systems Engineering

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Response Surface Model Building and Multidisciplinary Optimization Using D-Optimal Designs

This paper discusses response surface methods for approximation model building and multidisciplinary design optimization. The response surface methods discussed are central composite designs, Bayesian methods and Doptimal designs. An over-determined D-optimal design is applied to a configuration design and optimization study of a wing-body, launch vehicle. Results suggest that over determined Doptimal designs may provide an efficient approach for approximation model building and for multidisciplinary design optimization.

Multidisciplinary Conceptual Design Optimization of Space Transportation Systems

This paper presents a recent history of progress both in disciplinary modeling and in optimization methods and frameworks for space transportation systems conceptual design and analysis. The disciplinary models and process typically used for space transportation analyses are identified, including physicsbased and empirical models. The diverse characteristics of these disciplinary models require equally diverse integration and optimization approaches to enable implementation of automated, multidisciplinary design systems. Two general approaches are described for integrating these disciplinary models into computational frameworks for automated vehicle synthesis and optimization. Several optimization approaches are discussed including parameter, gradient-based, stochastic, and collaborative methods. Representative examples are given of multidisciplinary applications of optimization methods to the launch vehicle conceptual design problem. A primary goal for the future is to enable a space transportation design-to-cost capability.

Dual-Fuel Propulsion in Single-Stage Advanced Manned Launch System Vehicle

As part of the United States Advanced Manned Launch System study to determine a follow-on, or complement, to the Space Shuttle, a reusable single-stage-to-orbit concept utilizing dual-fuel rocket propulsion has been examined. Several dual-fuel propulsion concepts were investigated. These include: a separate-engine concept combining Russian RD-170 kerosene-fueled engines with space shuttle main engine-derivative engines: the kerosene- and hydrogen-fueled Russian RD-701 engine; and a dual-fuel, dual-expander engine. Analysis to determine vehicle weight and size characteristics was performed using conceptual-level design techniques. A response-surface methodology for multidisciplinary design was utilized to optimize the dual-fuel vehicles with respect to several important propulsion-system and vehicle design parameters, in order to achieve minimum empty weight. The tools and methods employed in the analysis process are also summarized. In comparison with a reference hydrogen- fueled single-stage vehicle, results showed that the dual-fuel vehicles were from 10 to 30% lower in empty weight for the same payload capability, with the dual-expander engine types showing the greatest potential.

Propulsion system design optimization using the Taguchi method

The authors discuss the Taguchi method as an approach to design optimization for quality. The method is briefly explained, and its application is illustrated for a propulsion system design optimization study for an advanced space transportation vehicle. The results suggest that the Taguchi method is a systematic and efficient approach that can aid in designing for performance, quality, and cost. Principal benefits include significant time and resource savings and the determination of parametric sensitivities and interactions. >

Using dual response surfaces to reduce variability in launch vehicle design: A case study

Space transportation system conceptual design is a multidisciplinary process containing considerable element of risk. Uncertainties from one engineering discipline may propagate to another through linking parameters and the final system output may have an accumulation of risk. This may lead to significant deviations from expected performance. An estimate of variability or design risk therefore becomes essential for a robust design. This study utilizes the dual response surface approach to quantify variability in critical performance characteristics during conceptual design phase of a launch vehicle. Using design of experiments methods and disciplinary design analysis codes, dual response surfaces are constructed for the mean and standard deviation to quantify variability in vehicle weight and sizing analysis. Next, an optimum solution is sought to minimize variability subject to a constraint on mean weight. In this application, the dual response surface approach lead to quantifying and minimizing variability without much increase in design effort.

A Model for Allocating Resources to Research Programs by Evaluating Technical Importance and Research Productivity

Abstract Research management requires practical and effective decision tools to support selection of investment alternatives. In recent years, many research organizations have changed from a discipline orientation to a focus on integrated programs and related outcomes. For managers of these high-profile research programs, it is critical to understand which activities are most important, considering both technical impact and cost-effectiveness. This article proposes a model that integrates quality function deployment and data envelopment analysis to perform this essential task. Based on information from these two decision science tools, the model develops a two-axis evaluation space for research alternatives. By locating particular activities in this decision space, a program manager can compare and prioritize alternative research investments.

Application of Taguchi methods to dual mixture ratio propulsion system optimization for SSTO vehicles

The application of advanced technologies to future launch vehicle designs would allow the introduction of a rocket-powered, single-stage-to-orbit (SSTO) launch system early in the next century. For a selected SSTO concept, a dual mixture ratio, staged combustion cycle engine that employs a number of innovative technologies was selected as the baseline propulsion system. A series of parametric trade studies are presented to optimize both a dual mixture ratio engine and a single mixture ratio engine of similar design and technology level. The effect of varying lift-off thrust-to-weight ratio, engine mode transition Mach number, mixture ratios, area ratios, and chamber pressure values on overall vehicle weight is examined. The sensitivity of the advanced SSTO vehicle to variations in each of these parameters is presented, taking into account the interaction of each of the parameters with each other. This parametric optimization and sensitivity study employs a Taguchi design method. The Taguchi method is an efficient approach for determining near-optimum design parameters using orthogonal matrices from design of experiments (DOE) theory. Using orthogonal matrices significantly reduces the number of experimental configurations to be studied. The effectiveness and limitations of the Taguchi method for propulsion/vehicle optimization studies as compared to traditional single-variable parametric trade studies is also discussed.

Application of Taguchi methods to propulsion system optimization for SSTO vehicles

The application of advanced technologies to future launch vehicle designs would allow the introduction of a rocket-powered, single-stage-to-orbit (SSTO) launch system early in the next century* For a selected SSTO concept, a dual mixture ratio, staged combustion cycle engine was selected as the baseline propulsion system. A series of parametric trade studies are presented to optimize both a dual mixture ratio engine and a single mixture ratio engine of similar design and technology level. The effect of varying lift-off thrust-to-weight ratio, engine mode transition Mach number, mixture ratios, area ratios, and chamber pressure values on overall vehicle weight is examined. The sensitivity of the advanced SSTO vehicle to variations in each of these parameters is presented, taking into account the interaction of each of the parameters with each other. This parametric optimization and sensitivity study employs a Taguchi design method. The Taguchi method is an efficient approach for determining near optimum design parameters using orthogonal matrices from design of experiments (DOE) theory. Using orthogonal matrices significantly reduces the number of experimental configurations to be studied. The effectiveness and limitations of the Taguchi method are also discussed.

Design for Quality Using Response Surface Methods: An Alternative to Taguchi's Parameter Design Approach

ABSTRACTThis article presents the response surface methodology as an alternative approach to Taguchis parameter design methods for optimizing designs for quality. The method is briefly explained, and its application is illustrated by an example of a preliminary design study of an advanced space transportation vehicle. The results indicate that the response surface methodology is a systematic and efficient approach that can help engineering managers design for quality, performance, and cost.