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At least 649 records · Page 36

Optimal cure cycle design of a resin-fiber composite laminate

A unified computed aided design method was studied for the cure cycle design that incorporates an optimal design technique with the analytical model of a composite cure process. The preliminary results of using this proposed method for optimal cure cycle design are reported and discussed. The cure process of interest is the compression molding of a polyester which is described by a diffusion reaction system. The finite element method is employed to convert the initial boundary value problem into a set of first order differential equations which are solved simultaneously by the DE program. The equations for thermal design sensitivities are derived by using the direct differentiation method and are solved by the DE program. A recursive quadratic programming algorithm with an active set strategy called a linearization method is used to optimally design the cure cycle, subjected to the given design performance requirements. The difficulty of casting the cure cycle design process into a proper mathematical form is recognized. Various optimal design problems are formulated to address theses aspects. The optimal solutions of these formulations are compared and discussed.

Hou, Jean W.↗

Design and Optimization of a 3-Stage Axial Supercritical CO2 Compressor

This paper presents the detailed design and optimization of a three-stage axial supercritical carbon dioxide (sCO2) compressor to support the advancement of sCO 2 power cycles, recognized for their efficiency and compactness in energy conversion. The three-stage design is a scaled model of the original nine-stage 100 MW design. The aerodynamic design and structural analysis were performed at the University of Cincinnati, and the results are presented. The first stage of the design has been meticulously manufactured and experimentally tested at University of Notre Dame Turbomachinery Laboratory. The design process starts with the preliminary design process, considering the required operating boundary conditions and geometrical constraints for full stage design. The design is then scaled down to 3-stage based on the power limitation. The definition for design parameters has been inspired from the EEE HPC design and tweaked to fit the sCO 2 operation. Axisymmetric analysis is performed next and the parametric geometry modeler -Tblade3 has been used to create 3D blade geometry from the results which can then be exported for the 3D CFD analysis and optimization. An efficiency of 89.85% is predicted for the final design at the design point.

Compressor↗

Design and optimization of a self-deploying single axis tracking PV array

This study was performed in order to design a tracking photovoltaic (PV) array and optimize the design for maximum specific power. The design considerations were minimal deployment time, high reliability, and small stowage volume. The array design was self-deployable, from a compact stowage configuration, using a passive pressurized gas deployment mechanism. The array structural components consist of a combination of beams, columns, and cables used to deploy and orient a flexible PV blanket. Each structural component of the design was analyzed to determine the size necessary to withstand the various forces to which it would be subjected. An optimization was performed to determine the array dimensions and blanket geometry which produce the maximum specific power. The optimization was performed for both lunar and Martian environments with 4 types of PV blankets (silicon, GaAs/Ge, GaAs CLEFT, and amorphous silicon). For the lunar environment, the amorphous silicon array produced the highest specific power, whereas, for Mars the GaAs CLEFT array produced the highest specific power. A comparison was made to a fixed PV tent array of similar design. The tracking array produced a higher specific power with all types of the PV blankets examined except amorphous silicon at both locations.

Colozza, Anthony J.↗

Design and optimization of a self-deploying single axis tracking PV array

This study was performed in order to design a tracking photovoltaic (PV) array and optimize the design for maximum specific power. The design considerations were minimal deployment time, high reliability, and small stowage volume. The array design was self-deployable, from a compact stowage configuration, using a passive pressurized gas deployment mechanism. The array structural components consist of a combination of beams, columns, and cables used to deploy and orient a flexible PV blanket. Each structural component of the design was analyzer to determine the size necessary to withstand the various forces to which it would be subjected. An optimization was performed to determine the array dimensions and blanket geometry which produce the maximum specific power. The optimization was performed for both lunar and Martian environments with 4 types of PV blankets (silicon, GaAs/Ge, GaAs CLEFT, and amorphous Silicon). For the lunar environment, the amorphous silicon array produced the highest specific power, whereas, for Mars the GaAs CLEFT array produced the highest specific power. A comparison was made to a fixed PV tent array of similar design. The tracking array produced a higher specific power with all types of the PV blankets examined except amorphous silicon at both locations.

Colozza, Anthony J.↗

Airfoil Design and Optimization by the One-Shot Method

An efficient numerical approach for the design of optimal aerodynamic shapes is presented in this paper. The objective of any optimization problem is to find the optimum of a cost function subject to a certain state equation (governing equation of the flow field) and certain side constraints. As in classical optimal control methods, the present approach introduces a costate variable (Lagrange multiplier) to evaluate the gradient of the cost function. High efficiency in reaching the optimum solution is achieved by using a multigrid technique and updating the shape in a hierarchical manner such that smooth (low-frequency) changes are done separately from high-frequency changes. Thus, the design variables are changed on a grid where their changes produce nonsmooth (high-frequency) perturbations that can be damped efficiently by the multigrid. The cost of solving the optimization problem is approximately two to three times the cost of the equivalent analysis problem.

Kuruvila, G.↗

Contribution to the optimal shape design of two-dimensional internal flows with embedded shocks

We explore the practicability of optimal shape design for flows modeled by the Euler equations. We define a functional whose minimum represents the optimality condition. The gradient of the functional with respect to the geometry is calculated with the Lagrange multipliers, which are determined by solving a co-state equation. The optimization problem is then examined by comparing the performance of several gradient-based optimization algorithms. In this formulation, the flow field can be computed to an arbitrary order of accuracy. Finally, some results for internal flows with embedded shocks are presented, including a case for which the solution to the inverse problem does not belong to the design space.

Iollo, Angelo↗

Optimal Input Design for Aircraft Stability and Control Flight Testing

Flight testing to characterize aircraft stability and control is a complex and expensive task that involves restrictive practical constraints. Methods are examined for optimizing the inputs applied to aircraft controls during flight test maneuvers to produce informative flight data. Theory underpinning optimal input design for stability and control flight testing is explained. The merits and limitations of optimal inputs are discussed, along with optimization approaches and practical considerations involved in applying optimal inputs in a real flight test environment. Simulated and flight test case studies of optimal multiple-input design for aircraft stability and control flight testing are presented and discussed.

optimal input design↗

F-18 High Alpha Research Vehicle (HARV) parameter identification flight test maneuvers for optimal input design validation and lateral control effectiveness

Flight test maneuvers are specified for the F-18 High Alpha Research Vehicle (HARV). The maneuvers were designed for open loop parameter identification purposes, specifically for optimal input design validation at 5 degrees angle of attack, identification of individual strake effectiveness at 40 and 50 degrees angle of attack, and study of lateral dynamics and lateral control effectiveness at 40 and 50 degrees angle of attack. Each maneuver is to be realized by applying square wave inputs to specific control effectors using the On-Board Excitation System (OBES). Maneuver descriptions and complete specifications of the time/amplitude points define each input are included, along with plots of the input time histories.

Morelli, Eugene A.↗

Branch target buffer design and optimization

Consideration is given to two major issues in the design of branch target buffers (BTBs), with the goal of achieving maximum performance for a given number of bits allocated to the BTB design. The first issue is BTB management; the second is what information to keep in the BTB. A number of solutions to these problems are reviewed, and various optimizations in the design of BTBs are discussed. Design target miss ratios for BTBs are developed, making it possible to estimate the performance of BTBs for real workloads.

Perleberg, Chris H.↗

Multidisciplinary Design, Analysis, and Optimization (MDO) for Co-Designed Transmission & Distribution Electric Grid Planning

This paper describes early experiences and example use cases applying multi-disciplinary design analysis and optimization (MDO) to the integrated design of power grids. Adapted from aerospace, MDO enables combining multiple existing tools into a coordinated optimization. Here we use MDO to simultaneously capture integrated transmission-distribution and investment-engineering trade-offs in an automated framework. Example use cases showcase prototype interactions among existing grid models using MDO and hint at the types of integrated analyses enabled by this approach. In addition, we share experiences and thoughts on grid-specific challenges and opportunities to help advance further work in this area.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Voter-comparator-switch optimization study

The design optimization and simulation effort of the voter-comparator switch (VCS) element are described. The VCS is an adaptive voter element that performs failure detection and reconfiguration function in a computer system designed to tolerate any three single failures in a fail operational fail operational fail safe manner. Detailed logic equations were developed and the design was evaluated and refined using a logic level fault simulator.

Jurison, J.↗

Sensitivity analysis in multipole-accelerated panel methods for potential flow

In the design of an airframe, the effect of changing the geometry on resulting computations is necessary for design optimization. The geometry is defined in terms of a series of design variables, including design variables to define the wing planform, tail, canard, pylon, and nacelle. Design optimization in this research is based on how these design variable affect the potential flow. The potential flow is computed as a function of the geometry and location of a series of panels describing the airframe, which are in turn a function of the design variables. Multipole accelerated panel methods improve the computational complexity of the problem and thus are an attractive approach. To utilize the methods in design optimization, it was necessary to define the appropriate sensitivity derivatives. The overhead incurred from finding the sensitivity derivatives in conjunction with the original computation should be small. This research developed the background for multipole-accelerated panel methods and the framework for finding sensitivity derivatives in the methods. Potential flow panel codes are commonly used for powered-lift aerodynamic predictions for three dimensional geometries. Given an airframe which has been discretized into a series of panels to define the airframe geometry, potential is computed as a function of the influence of all panels on all other panels. This is a computationally intensive problem for which efficient solutions are desired to improve the computational time and to allow greater resolution by use of more panels. One such solution is the use of hierarchical multipole methods which entail approximations of the effects of far-field terms. Hierarchical multipole methods have become prevalent in molecular dynamics and gravitational physics, and have been introduced into the fields of capacitance calculations, computational fluid dynamics, and electromagnetics. The methods utilize multipole expansions to describe the effect of bodies (i.e. particles, astrophysical bodies, panels, etc.) within a sphere on points distant from the sphere, where the influence diminishes as a function of distance. The expansions are exact with infinite series, however, for practical computations, the series are truncated and accuracy is selected based on the number of terms retained in the expansions. A hierarchical tree structure groups bodies together based on proximity to allow definition of multipole expansions for each group. The multipole expansions are then used to compute the effect of the bodies in a group on distant bodies.

Leathrum, James F., Jr.↗

Accuracy Assessment of Response Surface Approximations for Supersonic Turbine Design

There is a growing trend to employ CFD tools to supply the necessary information for design optimization of fluid dynamics components/systems. Such results are prone to uncertainties due to reasons including discretization. errors, incomplete convergence of computational procedures, and errors associated with physical models such as turbulence closures. Based on this type of information, gradient-based optimization algorithms often suffer from the noisy calculations, which can seriously compromise the outcome. Similar problems arise from the experimental measurements. Global optimization techniques, such as those based on the response surface (RS) concept are becoming popular in part because they can overcome some of these barriers. However, there are also fundamental issues related to such global optimization technique such as RS. For example, in high dimensional design spaces, typically only a small number of function evaluations are available due to computational and experimental costs. On the other hand, complex features of the design variables do not allow one to model the global characteristics of the design space with simple quadratic polynomials. Consequently a main challenge is to reduce the size of the region where we fit the RS, or make it more accurate in the regions where the optimum is likely to reside. Response Surface techniques using either polynomials or and Neural Network (NN) methods offer designers alternatives to conduct design optimization. The RS technique employs statistical and numerical techniques to establish the relationship between design variables and objective/constraint functions, typically using polynomials. In this study, we aim at addressing issues related to the following questions: (1) How to identify outliers associated with a given RS representation and improve the RS model via appropriate treatments? (2) How to focus on selected design data so that RS can give better performance in regions critical to design optimization? (3) How to combine NN and polynomial techniques for improving the accuracy of the RS model?

Papila, Nilay↗

Optimization and design of three-dimensional aerodynamic configurations of arbitrary shape by a vortex lattice method

A new method based on vortex lattice theory has been developed which can be applied to the combined analysis, induced drag optimization, and aerodynamic design of three-dimensional configurations of arbitrary shape. Geometric and aerodynamic constraints can be imposed on both the optimization and the design process. The method is compared with several known analytical solutions and is applied to several different design and optimization problems, including formation flight and wingtip fins for the Boeing KC-135 tanker airplane. Good agreement has been observed between the theoretical predictions and the wind tunnel test results for the KC-135 modification.

Feifel, W. M.↗

Executive Summary for CIF22 Project: End-to-End Mission Design & Trajectory Optimization

The goal of this project was the integration of NASA's Copernicus and Genesis trajectory design tools to create a new capability for end-to-end mission design and optimization of all flight phases, including Earth ascent, lunar ascent, rendezvous, and lunar descent. This capability is a critical component needed for the next generation of complex human spaceflight design and operations (Orion, HLS, Gateway, Mars) and can serve as a pathfinder for developing a future autonomous, onboard trajectory optimizer. The result was the creation of a new Copernicus/Genesis plugin, which allows a Genesis trajectory (e.g., ascent or descent) to be incorporated into a Copernicus mission, enabling an end-to-end optimization. Inputs from Copernicus are sent to Genesis, which runs and produces output sent back to Copernicus. Thus, the full power of the Genesis tool is available in Copernicus and can be used for a wide variety of applications.

Jacob Williams↗

Design and optimization of radiation-hardened isolated converters for Jovian environments

This paper presents the design and optimization of a class of flexible, high efficiency, multiple output capable, radiation-hardened isolated DC/DC converters for Jovian environments. The proposed converters achieve lower electromagnetic emission, better thermal management and higher efficiency. A new series of radiation-hardened isolated GaN gate driver circuit is proposed for space applications. Experimental results based on two prototype units implemented in the laboratory verify the performance of the proposed isolated converters.

Carr, Gregory↗

Problems in large-scale structural optimization

A general design optimization model for large complex systems is defined. Major features of the model that challenge various optimization algorithms are discussed. Requirements of a model optimization algorithm are identified. Objectives of the study of various algorithms are defined and a basis for conducting such a study is developed. Primal as well as transformation methods are analytically studied and a unified viewpoint of various methods is presented. Several numerical examples are solved using different methods to study their performance. Conclusions drawn from the study are presented and discussed. Areas of future research in nonlinear programming as well as structural optimization are identified and discussed.

Arora, J. S.↗