Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “sequential optimal design”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Sensitivity of optimum solutions to problem parameters

Derivation of the sensitivity equations that yield the sensitivity derivatives directly, which avoids the costly and inaccurate perturb-and-reoptimize approach, is discussed and solvability of the equations is examined. The equations apply to optimum solutions obtained by direct search methods as well as those generated by procedures of the sequential unconstrained minimization technique class. Applications are discussed for the use of the sensitivity derivatives in extrapolation of the optimal objective function and design variable values for incremented parameters, optimization with multiple objectives, and decomposition of large optimization problems.

Sobieszczanski-Sobieski, J.↗
NASA NTRS1995

Parallel Computational Environment for Substructure Optimization

Design optimization of large structural systems can be attempted through a substructure strategy when convergence difficulties are encountered. When this strategy is used, the large structure is divided into several smaller substructures and a subproblem is defined for each substructure. The solution of the large optimization problem can be obtained iteratively through repeated solutions of the modest subproblems. Substructure strategies, in sequential as well as in parallel computational modes on a Cray YMP multiprocessor computer, have been incorporated in the optimization test bed CometBoards. CometBoards is an acronym for Comparative Evaluation Test Bed of Optimization and Analysis Routines for Design of Structures. Three issues, intensive computation, convergence of the iterative process, and analytically superior optimum, were addressed in the implementation of substructure optimization into CometBoards. Coupling between subproblems as well as local and global constraint grouping are essential for convergence of the iterative process. The substructure strategy can produce an analytically superior optimum different from what can be obtained by regular optimization. For the problems solved, substructure optimization in a parallel computational mode made effective use of all assigned processors.

Gendy, Atef S.↗
NASA NTRS2000

Recent Improvements in Aerodynamic Design Optimization on Unstructured Meshes

Recent improvements in an unstructured-grid method for large-scale aerodynamic design are presented. Previous work had shown such computations to be prohibitively long in a sequential processing environment. Also, robust adjoint solutions and mesh movement procedures were difficult to realize, particularly for viscous flows. To overcome these limiting factors, a set of design codes based on a discrete adjoint method is extended to a multiprocessor environment using a shared memory approach. A nearly linear speedup is demonstrated, and the consistency of the linearizations is shown to remain valid. The full linearization of the residual is used to precondition the adjoint system, and a significantly improved convergence rate is obtained. A new mesh movement algorithm is implemented and several advantages over an existing technique are presented. Several design cases are shown for turbulent flows in two and three dimensions.

Nielsen, Eric J.↗
NASA NTRS1993

Progress in multidisciplinary design optimization at NASA Langley

Multidisciplinary Design Optimization refers to some combination of disciplinary analyses, sensitivity analysis, and optimization techniques used to design complex engineering systems. The ultimate objective of this research at NASA Langley Research Center is to help the US industry reduce the costs associated with development, manufacturing, and maintenance of aerospace vehicles while improving system performance. This report reviews progress towards this objective and highlights topics for future research. Aerospace design problems selected from the author's research illustrate strengths and weaknesses in existing multidisciplinary optimization techniques. The techniques discussed include multiobjective optimization, global sensitivity equations and sequential linear programming.

Padula, Sharon L.↗
NASA NTRS2007

A Parametric Geometry Computational Fluid Dynamics (CFD) Study Utilizing Design of Experiments (DOE)

Design of Experiments (DOE) was applied to the LAS geometric parameter study to efficiently identify and rank primary contributors to integrated drag over the vehicles ascent trajectory in an order of magnitude fewer CFD configurations thereby reducing computational resources and solution time. SME s were able to gain a better understanding on the underlying flowphysics of different geometric parameter configurations through the identification of interaction effects. An interaction effect, which describes how the effect of one factor changes with respect to the levels of other factors, is often the key to product optimization. A DOE approach emphasizes a sequential approach to learning through successive experimentation to continuously build on previous knowledge. These studies represent a starting point for expanded experimental activities that will eventually cover the entire design space of the vehicle and flight trajectory.

Rhew, Ray D.↗
NASA NTRS1989

Optimum structural design with static aeroelastic constraints

The static aeroelastic performance characteristics, divergence velocity, control effectiveness and lift effectiveness are considered in obtaining an optimum weight structure. A typical swept wing structure is used with upper and lower skins, spar and rib thicknesses, and spar cap and vertical post cross-sectional areas as the design parameters. Incompressible aerodynamic strip theory is used to derive the constraint formulations, and aerodynamic load matrices. A Sequential Unconstrained Minimization Technique (SUMT) algorithm is used to optimize the wing structure to meet the desired performance constraints.

Bowman, Keith B↗
NASA NTRS1995

Parallel Monte Carlo Simulation for control system design

The research during the 1993/94 academic year addressed the design of parallel algorithms for stochastic robustness synthesis (SRS). SRS uses Monte Carlo simulation to compute probabilities of system instability and other design-metric violations. The probabilities form a cost function which is used by a genetic algorithm (GA). The GA searches for the stochastic optimal controller. The existing sequential algorithm was analyzed and modified to execute in a distributed environment. For this, parallel approaches to Monte Carlo simulation and genetic algorithms were investigated. Initial empirical results are available for the KSR1.

Schubert, Wolfgang M.↗
NASA NTRS1993

Integrated design of the CSI evolutionary structure: A verification of the design methodology

One of the main objectives of the Controls-Structures Interaction (CSI) program is to develop and evaluate integrated controls-structures design methodology for flexible space structures. Thus far, integrated design methodologies for a class of flexible spacecraft, which require fine attitude pointing and vibration suppression with no payload articulation, have been extensively investigated. Various integrated design optimization approaches, such as single-objective optimization, and multi-objective optimization, have been implemented with an array of different objectives and constraints involving performance and cost measures such as total mass, actuator mass, steady-state pointing performance, transient performance, control power, and many more. These studies have been performed using an integrated design software tool (CSI-DESIGN CODE) which is under development by the CSI-ADM team at the NASA Langley Research Center. To date, all of these studies, irrespective of the type of integrated optimization posed or objectives and constraints used, have indicated that integrated controls-structures design results in an overall spacecraft design which is considerably superior to designs obtained through a conventional sequential approach. Consequently, it is believed that validation of some of these results through fabrication and testing of a structure which is designed through an integrated design approach is warranted. The objective of this paper is to present and discuss the efforts that have been taken thus far for the validation of the integrated design methodology.

Maghami, Peiman G.↗
NASA NTRS2012

An Update on Design Tools for Optimization of CMC 3D Fiber Architectures

Objective: Describe and up-date progress for NASA's efforts to develop 3D architectural design tools for CMC in general and for SIC/SiC composites in particular. Describe past and current sequential work efforts aimed at: Understanding key fiber and tow physical characteristics in conventional 2D and 3D woven architectures as revealed by microstructures in the literature. Developing an Excel program for down-selecting and predicting key geometric properties and resulting key fiber-controlled properties for various conventional 3D architectures. Developing a software tool for accurately visualizing all the key geometric details of conventional 3D architectures. Validating tools by visualizing and predicting the Internal geometry and key mechanical properties of a NASA SIC/SIC panel with a 3D orthogonal architecture. Applying the predictive and visualization tools toward advanced 3D orthogonal SiC/SIC composites, and combining them into a user-friendly software program.

Lang, J.↗
NASA NTRSDate not supplied

Understanding Resilience Optimization Architectures With an Optimization Problem Repository

Optimizing a system’s resilience can be challenging, especially when it involves considering both the inherent resilience of a robust design and the active resilience of a health management system to a set of computationally-expensive hazard simulations. While prior work has developed specialized architectures to effectively and efficiently solve combined design and resilience optimization problems, the comparison of these architectures has been limited to a single case study. To further study resilience optimization formulations, this work develops a problem repository which includes previously-developed resilience optimization problems and additional problems presented in this work: a notional system resilience model, a pandemic response model, and a cooling tank hazard prevention model. This work then uses models in the repository at large to understand the characteristics of resilience optimization problems and study the applicability of optimization architectures and decomposition strategies. Based on the comparisons in the repository, applying an optimization architecture effectively requires understanding the alignment and coupling relationships between the design and resilience models, as well as the efficiency characteristics of the algorithms. While alignment determines the necessity of a surrogate of resilience cost in the upper-level design problem, coupling determines the overall applicability of a sequential, alternating, or bilevel structure. Additionally, the application of decomposition strategies is dependent on there being limited interactions between variable sets, which often does not hold when a resilience policy is parameterized in terms of actions to take in hazardous model states rather than specific given scenarios.

Resilience↗
NASA NTRS1984

ADS: A FORTRAN program for automated design synthesis, version 1.00

A new general-purpose optimization program for engineering design is described. ADS-1 (Automated Design Synthesis - Version 1) is a FORTRAN program for solution of nonlinear constrained optimization problems. The program is segmented into three levels, being strategy, optimizer, and one-dimensional search. At each level, several options are available so that a total of over 100 possible combinations can be created. Examples of available strategies are sequential unconstrained minimization, the Augmented Lagrange Multiplier method, and Sequential Linear Programming. Available optimizers include variable metric methods and the Method of Feasible Directions as examples and one-dimensional search options include polynomial interpolation and the Golden Section method as examples. Emphasis is placed on ease of use of the program. All information is transferred via a single parameter list. Default values are provided for all internal program parameters such as convergence criteria, and the user is given a simple means to over-ride these, if desired. The program is demonstrated with a simple structural design example.

Vanderplaats, G. N.↗
NASA NTRS1982

Combining analysis with optimization at Langley Research Center - An evolutionary process

Analytical and computational advances, at Langely Research Center (La RC), contributing to the evolution of computer programs combining analysis and optimization are presented, namely, strength sizing, concurrent strength and flutter sizing, and general optimization. Current work on a software system which executes the analysis and optimization in a sequential rather than concurrent mode is then described, as a step toward the long-term goal at La RC of developing the methodology for such systems. The software system is designated Enginering Analysis Language (EAL)/Programming Structural Synthesis System (PR)SSS), and work is being done on the incorporation of PROSSS into EAL. EAL language can perform most FORTRAN operations, including testing, branching, and looping, and its data base system can easily be accessed by any processor using FORTRAN callable utility subroutines. Some numerical results showing the accuracy of EAL/PROSSS are given.

Rogers, J. L., Jr.↗
NASA NTRS2001

Engine With Regression and Neural Network Approximators Designed

At the NASA Glenn Research Center, the NASA engine performance program (NEPP, ref. 1) and the design optimization testbed COMETBOARDS (ref. 2) with regression and neural network analysis-approximators have been coupled to obtain a preliminary engine design methodology. The solution to a high-bypass-ratio subsonic waverotor-topped turbofan engine, which is shown in the preceding figure, was obtained by the simulation depicted in the following figure. This engine is made of 16 components mounted on two shafts with 21 flow stations. The engine is designed for a flight envelope with 47 operating points. The design optimization utilized both neural network and regression approximations, along with the cascade strategy (ref. 3). The cascade used three algorithms in sequence: the method of feasible directions, the sequence of unconstrained minimizations technique, and sequential quadratic programming. The normalized optimum thrusts obtained by the three methods are shown in the following figure: the cascade algorithm with regression approximation is represented by a triangle, a circle is shown for the neural network solution, and a solid line indicates original NEPP results. The solutions obtained from both approximate methods lie within one standard deviation of the benchmark solution for each operating point. The simulation improved the maximum thrust by 5 percent. The performance of the linear regression and neural network methods as alternate engine analyzers was found to be satisfactory for the analysis and operation optimization of air-breathing propulsion engines (ref. 4).

Patnaik, Surya N.↗
NASA NTRS2008

Efficient Simulation Budget Allocation for Selecting an Optimal Subset

We consider a class of the subset selection problem in ranking and selection. The objective is to identify the top m out of k designs based on simulated output. Traditional procedures are conservative and inefficient. Using the optimal computing budget allocation framework, we formulate the problem as that of maximizing the probability of correc tly selecting all of the top-m designs subject to a constraint on the total number of samples available. For an approximation of this corre ct selection probability, we derive an asymptotically optimal allocat ion and propose an easy-to-implement heuristic sequential allocation procedure. Numerical experiments indicate that the resulting allocatio ns are superior to other methods in the literature that we tested, and the relative efficiency increases for larger problems. In addition, preliminary numerical results indicate that the proposed new procedur e has the potential to enhance computational efficiency for simulation optimization.

Chen, Chun-Hung↗
NASA NTRS2017

Low-Thrust Trajectory Optimization with Simplified SQP Algorithm

The problem of low-thrust trajectory optimization in highly perturbed dynamics is a stressing case for many optimization tools. Highly nonlinear dynamics and continuous thrust are each, separately, non-trivial problems in the field of optimal control, and when combined, the problem is even more difficult. This paper de-scribes a fast, robust method to design a trajectory in the CRTBP (circular restricted three body problem), beginning with no or very little knowledge of the system. The approach is inspired by the SQP (sequential quadratic programming) algorithm, in which a general nonlinear programming problem is solved via a sequence of quadratic problems. A few key simplifications make the algorithm presented fast and robust to initial guess: a quadratic cost function, neglecting the line search step when the solution is known to be far away, judicious use of end-point constraints, and mesh refinement on multiple shooting with fixed-step integration.In comparison to the traditional approach of plugging the problem into a “black-box” NLP solver, the methods shown converge even when given no knowledge of the solution at all. It was found that the only piece of information that the user needs to provide is a rough guess for the time of flight, as the transfer time guess will dictate which set of local solutions the algorithm could converge on. This robustness to initial guess is a compelling feature, as three-body orbit transfers are challenging to design with intuition alone. Of course, if a high-quality initial guess is available, the methods shown are still valid.We have shown that endpoints can be efficiently constrained to lie on 3-body repeating orbits, and that time of flight can be optimized as well. When optimizing the endpoints, we must make a trade between converging quickly on sub-optimal endpoints or converging more slowly on end-points that are arbitrarily close to optimal. It is easy for the mission design engineer to adjust this trade based on the problem at hand.The biggest limitation to the algorithm at this point is that multi-revolution transfers (greater than 2 revolutions) do not work nearly as well. This restriction comes in because the relationship between node 1 and node N becomes increasingly nonlinear as the angular distance grows. Trans-fers with more than about 1.5 complete revolutions generally require the line search to improve convergence. Future work includes: Comparison of this algorithm with other established tools; improvements to how multiple-revolution transfers are handled; parallelization of the Jacobian computation; in-creased efficiency for the line search; and optimization of many more trajectories between a variety of 3-body orbits.

Parrish, Nathan L.↗
NASA NTRS2003

Formation Tetrahedron Design for Phase I of the Magnetospheric Multiscale Mission

The Magnetospheric Multiscale Mission (MMS) is a NASA mission intended to make fundamental advancements in our understanding of the Earth's Magnetosphere. There are three processes that MMS will study including magnetic reconnection, charged particle acceleration, and turbulence. There are four phases in the nominal mission and this work addresses some of the outstanding issues in phase I. The nominal phase I orbit is 1.2 x 12 R(sub e) highly elliptic orbit with four spacecraft nominally forming a regular tetrahedron. In this paper we investigate the relative dynamics of the four MMS spacecraft about an assumed reference orbit. There are several tetrahedron dimensions required in Phase I of the mission and in this work we design optimal tetrahedrons for the 10 km baseline. The performance metric used in the optimization process is directly related to the science return, and is based on an extension of previous work performed by Glassmeier. The optimizer we use is a commercially available Sequential Quadratic Programming (SQP) routine. Multiple optimal solutions are found, and we characterize how the performance of the formation varies between different regions of the reference orbit.

Hughes, Steven P.↗
NASA NTRS1988

Knowledge elicitation for an operator assistant system in process control tasks

A knowledge based system (KBS) methodology designed to study human machine interactions and levels of autonomy in allocation of process control tasks is presented. Users are provided with operation manuals to assist them in normal and abnormal situations. Unfortunately, operation manuals usually represent only the functioning logic of the system to be controlled. The user logic is often totally different. A method is focused on which illicits user logic to refine a KBS shell called an Operator Assistant (OA). If the OA is to help the user, it is necessary to know what level of autonomy gives the optimal performance of the overall man-machine system. For example, for diagnoses that must be carried out carefully by both the user and the OA, interactions are frequent, and processing is mostly sequential. Other diagnoses can be automated, in which the case the OA must be able to explain its reasoning in an appropriate level of detail. OA structure was used to design a working KBS called HORSES (Human Orbital Refueling System Expert System). Protocol analysis of pilots interacting with this system reveals that the a-priori analytical knowledge becomes more structured with training and the situation patterns more complex and dynamic. This approach can improve the a-priori understanding of human and automatic reasoning.

Boy, Guy A.↗
NASA NTRS1996

Design Optimization for a Maglev System Employing Flux Eliminating Coils

Flux eliminating coils have received no little attention over the past thirty years as an alternative for realizing lift in a MAGLEV system. When the magnets on board the vehicle are displaced from the equilibrium or null flux point of these coils, they induce current in those coils which act to restore the coil to its null flux or centerline position. The question being addressed in this paper is that of how to choose the best coil for a given system. What appears at first glance to be an innocent question is in fact one that is actually quite involved, encompassing both the global economics and physics of the system. The real key in analyzing that question is to derive an optimization index or functional which represents the cost of the system subject to constraints, the primary constraint being that the vehicle lift itself at a certain threshold speed. Outlined in this paper is one scenario for realizing a total system design which uses sequential quadratic programming techniques.

Davey, Kent R.↗