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Sobieski, Jaroslaw

Publications and source records attributed to Sobieski, Jaroslaw.

Integrated System-Level Optimization for Concurrent Engineering With Parametric Subsystem Modeling

The introduction of concurrent design practices to the aerospace industry has greatly increased the productivity of engineers and teams during design sessions as demonstrated by JPL's Team X. Simultaneously, advances in computing power have given rise to a host of potent numerical optimization methods capable of solving complex multidisciplinary optimization problems containing hundreds of variables, constraints, and governing equations. Unfortunately, such methods are tedious to set up and require significant amounts of time and processor power to execute, thus making them unsuitable for rapid concurrent engineering use. This paper proposes a framework for Integration of System-Level Optimization with Concurrent Engineering (ISLOCE). It uses parametric neural-network approximations of the subsystem models. These approximations are then linked to a system-level optimizer that is capable of reaching a solution quickly due to the reduced complexity of the approximations. The integration structure is described in detail and applied to the multiobjective design of a simplified Space Shuttle external fuel tank model. Further, a comparison is made between the new framework and traditional concurrent engineering (without system optimization) through an experimental trial with two groups of engineers. Each method is evaluated in terms of optimizer accuracy, time to solution, and ease of use. The results suggest that system-level optimization, running as a background process during integrated concurrent engineering sessions, is potentially advantageous as long as it is judiciously implemented.

Schuman, Todd

A Response Surface Methodology for Bi-Level Integrated System Synthesis (BLISS)

The report describes a new method for optimization of engineering systems such as aerospace vehicles whose design must harmonize a number of subsystems and various physical phenomena, each represented by a separate computer code, e.g., aerodynamics, structures, propulsion, performance, etc. To represent the system internal couplings, the codes receive output from other codes as part of their inputs. The system analysis and optimization task is decomposed into subtasks that can be executed concurrently, each subtask conducted using local state and design variables and holding constant a set of the system-level design variables. The subtasks results are stored in form of the Response Surfaces (RS) fitted in the space of the system-level variables to be used as the subtask surrogates in a system-level optimization whose purpose is to optimize the system objective(s) and to reconcile the system internal couplings. By virtue of decomposition and execution concurrency, the method enables a broad workfront in organization of an engineering project involving a number of specialty groups that might be geographically dispersed, and it exploits the contemporary computing technology of massively concurrent and distributed processing. The report includes a demonstration test case of supersonic business jet design.

Altus, Troy David

Evaluation of Methods for Multidisciplinary Design Optimization (MDO)

A new MDO method, BLISS, and two different variants of the method, BLISS/RS and BLISS/S, have been implemented using iSIGHT's scripting language and evaluated in this report on multidisciplinary problems. All of these methods are based on decomposing a modular system optimization system into several subtasks optimization, that may be executed concurrently, and the system optimization that coordinates the subtasks optimization. The BLISS method and its variants are well suited for exploiting the concurrent processing capabilities in a multiprocessor machine. Several steps, including the local sensitivity analysis, local optimization, response surfaces construction and updates are all ideally suited for concurrent processing. Needless to mention, such algorithms that can effectively exploit the concurrent processing capabilities of the compute servers will be a key requirement for solving large-scale industrial design problems, such as the automotive vehicle problem detailed in Section 3.4.

Kodiyalam, Srinivas

An efficiency study of the simultaneous analysis and design of structures

The efficiency of the Simultaneous Analysis and Design (SAND) approach in the minimum weight optimization of structural systems subject to strength and displacement constraints as well as size side constraints is investigated. SAND allows for an optimization to take place in one single operation as opposed to the more traditional and sequential Nested Analysis and Design (NAND) method, where analyses and optimizations alternate. Thus, SAND has the advantage that the stiffness matrix is never factored during the optimization retaining its original sparsity. One of SAND's disadvantages is the increase in the number of design variables and in the associated number of constraint gradient evaluations. If SAND is to be an acceptable player in the optimization field, it is essential to investigate the efficiency of the method and to present a possible cure for any inherent deficiencies.

Striz, Alfred G.

Mathematical Model For Engineering Analysis And Optimization

Computational support for engineering design process reveals behavior of designed system in response to external stimuli; and finds out how behavior modified by changing physical attributes of system. System-sensitivity analysis combined with extrapolation forms model of design complementary to model of behavior, capable of direct simulation of effects of changes in design variables. Algorithms developed for this method applicable to design of large engineering systems, especially those consisting of several subsystems involving many disciplines.

Sobieski, Jaroslaw

Using Derivatives Of Higher Order In Sensitivity Analysis

"What if" questions answered exactly, without using "increment-and-reevaluate" approach, and without finite differencing of system analysis, by use of sensitivity analysis to calculate first derivatives of behaviors of coupled systems with respect to design variables. If problem strongly nonlinear, efficiency improved by making derivatives of higher orders available to search algorithms. Extension effected by recursive application of same implicit function theorem that underlies previous method. Useful in design calculations for almost any system, including structures, machines, and distribution networks. Feedback control of processes improved by inclusion of derivative terms of higher order.

Sobieski, Jaroslaw