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Results for “parametric design framework”

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.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Computational Analysis for Rocket-Based Combined-Cycle Systems During Rocket-Only Operation

A series of Reynolds-averaged Navier-Stokes calculations were employed to study the performance of rocket-based combined-cycle systems operating in an all-rocket mode. This parametric series of calculations were executed within a statistical framework, commonly known as design of experiments. The parametric design space included four geometric and two flowfield variables set at three levels each, for a total of 729 possible combinations. A D-optimal design strategy was selected. It required that only 36 separate computational fluid dynamics (CFD) solutions be performed to develop a full response surface model, which quantified the linear, bilinear, and curvilinear effects of the six experimental variables. The axisymmetric, Reynolds-averaged Navier-Stokes simulations were executed with the NPARC v3.0 code. The response used in the statistical analysis was created from Isp efficiency data integrated from the 36 CFD simulations. The influence of turbulence modeling was analyzed by using both one- and two-equation models. Careful attention was also given to quantify the influence of mesh dependence, iterative convergence, and artificial viscosity upon the resulting statistical model. Thirteen statistically significant effects were observed to have an influence on rocket-based combined-cycle nozzle performance. It was apparent that the free-expansion process, directly downstream of the rocket nozzle, can influence the Isp efficiency. Numerical schlieren images and particle traces have been used to further understand the physical phenomena behind several of the statistically significant results.

Steffen, C. J., Jr.↗
NASA NTRS2012

Robustness Analysis and Optimally Robust Control Design via Sum-of-Squares

A control analysis and design framework is proposed for systems subject to parametric uncertainty. The underlying strategies are based on sum-of-squares (SOS) polynomial analysis and nonlinear optimization to design an optimally robust controller. The approach determines a maximum uncertainty range for which the closed-loop system satisfies a set of stability and performance requirements. These requirements, de ned as inequality constraints on several metrics, are restricted to polynomial functions of the uncertainty. To quantify robustness, SOS analysis is used to prove that the closed-loop system complies with the requirements for a given uncertainty range. The maximum uncertainty range, calculated by assessing a sequence of increasingly larger ranges, serves as a robustness metric for the closed-loop system. To optimize the control design, nonlinear optimization is used to enlarge the maximum uncertainty range by tuning the controller gains. Hence, the resulting controller is optimally robust to parametric uncertainty. This approach balances the robustness margins corresponding to each requirement in order to maximize the aggregate system robustness. The proposed framework is applied to a simple linear short-period aircraft model with uncertain aerodynamic coefficients.

Dorobantu, Andrei↗
NASA NTRS2012

Integrated Design Engineering Analysis (IDEA) Environment Automated Generation of Structured CFD Grids using Topology Methods

This report documents the work performed from March 2010 to March 2012. The Integrated Design and Engineering Analysis (IDEA) environment is a collaborative environment based on an object-oriented, multidisciplinary, distributed framework using the Adaptive Modeling Language (AML) as a framework and supporting the configuration design and parametric CFD grid generation. This report will focus on describing the work in the area of parametric CFD grid generation using novel concepts for defining the interaction between the mesh topology and the geometry in such a way as to separate the mesh topology from the geometric topology while maintaining the link between the mesh topology and the actual geometry.

Kamhawi, Hilmi N.↗
NASA NTRSDate not supplied

HelioSwarm: Relative Orbit Maintenance in Eccentric P/2 Lunar Resonant Orbit

Science missions employing multi-point measurements require planned and repeatable swarm geometries. Cis-lunar orbits enable heliophysics studies of solar wind but introduce new challenges in relative motion control. For a multi-satellite swarm in lunar-resonant orbit, insertion and maintenance maneuvers address orbit eccentricity and evolution, as well as three-body gravitational perturbations. Local Velocity-Normal-Conormal coordinates prove to be an effective framework for relative motion design and control. Parametric studies investigate maneuver placement efficiency in controlling relative motion in cis-lunar orbit.

Relative Motion↗
NASA NTRS1995

Parametric design and gridding through relational geometry

Relational Geometric Synthesis (RGS) is a new logical framework for building up precise definitions of complex geometric models from points, curves, surfaces and solids. RGS achieves unprecedented design flexibility by supporting a rich variety of useful curve and surface entities. During the design process, many qualitative and quantitative relationships between elementary objects may be captured and retained in a data structure equivalent to a directed graph, such that they can be utilized for automatically updating the complete model geometry following changes in the shape or location of an underlying object. Capture of relationships enables many new possibilities for parametric variations and optimization. Examples are given of panelization applications for submarines, sailing yachts, offshore structures, and propellers.

Letcher, John S., Jr.↗
NASA NTRS1989

SPRITE - A computer code for the optimization of space based heat pipe radiator systems

An integrated analytical tool has been developed for use in designing optimized space-based heat pipe radiator systems. This code, SPRITE-1, incorporates the thermal, structural, and reliability aspects of the radiator into a single framework from which a physically consistent design can be obtained. A parametric study of the integral heat pipe panel radiator was performed using SPRITE-1, and a preliminary minimum mass design was obtained. The radiator design is summarized, and the mass minimization method and results are presented.

Buksa, John J.↗
NASA NTRS2006

Hard and Soft Constraints in Reliability-Based Design Optimization

This paper proposes a framework for the analysis and design optimization of models subject to parametric uncertainty where design requirements in the form of inequality constraints are present. Emphasis is given to uncertainty models prescribed by norm bounded perturbations from a nominal parameter value and by sets of componentwise bounded uncertain variables. These models, which often arise in engineering problems, allow for a sharp mathematical manipulation. Constraints can be implemented in the hard sense, i.e., constraints must be satisfied for all parameter realizations in the uncertainty model, and in the soft sense, i.e., constraints can be violated by some realizations of the uncertain parameter. In regard to hard constraints, this methodology allows (i) to determine if a hard constraint can be satisfied for a given uncertainty model and constraint structure, (ii) to generate conclusive, formally verifiable reliability assessments that allow for unprejudiced comparisons of competing design alternatives and (iii) to identify the critical combination of uncertain parameters leading to constraint violations. In regard to soft constraints, the methodology allows the designer (i) to use probabilistic uncertainty models, (ii) to calculate upper bounds to the probability of constraint violation, and (iii) to efficiently estimate failure probabilities via a hybrid method. This method integrates the upper bounds, for which closed form expressions are derived, along with conditional sampling. In addition, an l(sub infinity) formulation for the efficient manipulation of hyper-rectangular sets is also proposed.

Crespo, L.uis G.↗
NASA NTRS2011

An Overview of NASA's Integrated Design and Engineering Analysis (IDEA) Environment

Historically, the design of subsonic and supersonic aircraft has been divided into separate technical disciplines (such as propulsion, aerodynamics and structures), each of which performs design and analysis in relative isolation from others. This is possible, in most cases, either because the amount of interdisciplinary coupling is minimal, or because the interactions can be treated as linear. The design of hypersonic airbreathing vehicles, like NASA's X-43, is quite the opposite. Such systems are dominated by strong non-linear interactions between disciplines. The design of these systems demands that a multi-disciplinary approach be taken. Furthermore, increased analytical fidelity at the conceptual design phase is highly desirable, as many of the non-linearities are not captured by lower fidelity tools. Only when these systems are designed from a true multi-disciplinary perspective, can the real performance benefits be achieved and complete vehicle systems be fielded. Toward this end, the Vehicle Analysis Branch at NASA Langley Research Center has been developing the Integrated Design and Engineering Analysis (IDEA) Environment. IDEA is a collaborative environment for parametrically modeling conceptual and preliminary designs for launch vehicle and high speed atmospheric flight configurations using the Adaptive Modeling Language (AML) as the underlying framework. The environment integrates geometry, packaging, propulsion, trajectory, aerodynamics, aerothermodynamics, engine and airframe subsystem design, thermal and structural analysis, and vehicle closure into a generative, parametric, unified computational model where data is shared seamlessly between the different disciplines. Plans are also in place to incorporate life cycle analysis tools into the environment which will estimate vehicle operability, reliability and cost. IDEA is currently being funded by NASA?s Hypersonics Project, a part of the Fundamental Aeronautics Program within the Aeronautics Research Mission Directorate. The environment is currently focused around a two-stage-to-orbit configuration with a turbine-based combined cycle (TBCC) first stage and a reusable rocket second stage. IDEA will be rolled out in generations, with each successive generation providing a significant increase in capability, either through increased analytic fidelity, expansion of vehicle classes considered, or by the inclusion of advanced modeling techniques. This paper provides the motivation behind the current effort, an overview of the development of the IDEA environment (including the contents and capabilities to be included in Generation 1 and Generation 2), and a description of the current status and detail of future plans.

Robinson, Jeffrey S.↗
NASA NTRS2000

Parametric Model of an Aerospike Rocket Engine

A suite of computer codes was assembled to simulate the performance of an aerospike engine and to generate the engine input for the Program to Optimize Simulated Trajectories. First an engine simulator module was developed that predicts the aerospike engine performance for a given mixture ratio, power level, thrust vectoring level, and altitude. This module was then used to rapidly generate the aerospike engine performance tables for axial thrust, normal thrust, pitching moment, and specific thrust. Parametric engine geometry was defined for use with the engine simulator module. The parametric model was also integrated into the iSIGHT multidisciplinary framework so that alternate designs could be determined. The computer codes were used to support in-house conceptual studies of reusable launch vehicle designs.

Korte, J. J.↗
NASA NTRS2000

Parametric Model of an Aerospike Rocket Engine

A suite of computer codes was assembled to simulate the performance of an aerospike engine and to generate the engine input for the Program to Optimize Simulated Trajectories. First an engine simulator module was developed that predicts the aerospike engine performance for a given mixture ratio, power level, thrust vectoring level, and altitude. This module was then used to rapidly generate the aerospike engine performance tables for axial thrust, normal thrust, pitching moment, and specific thrust. Parametric engine geometry was defined for use with the engine simulator module. The parametric model was also integrated into the iSIGHTI multidisciplinary framework so that alternate designs could be determined. The computer codes were used to support in-house conceptual studies of reusable launch vehicle designs.

Korte, J. J.↗
NASA NTRS2015

Under-Track CFD-Based Shape Optimization for a Low-Boom Demonstrator Concept

The detailed outer mold line shaping of a Mach 1.6, demonstrator-sized low-boom concept is presented. Cruise trim is incorporated a priori as part of the shaping objective, using an equivalent-area-based approach. Design work is performed using a gradient-driven optimization framework that incorporates a three-dimensional, nonlinear flow solver, a parametric geometry modeler, and sensitivities derived using the adjoint method. The shaping effort is focused on reducing the under-track sonic boom level using an inverse design approach, while simultaneously satisfying the trim requirement. Conceptual-level geometric constraints are incorporated in the optimization process, including the internal layout of fuel tanks, landing gear, engine, and crew station. Details of the model parameterization and design process are documented for both flow-through and powered states, and the performance of these optimized vehicles presented in terms of inviscid L/D, trim state, pressures in the near-field and at the ground, and predicted sonic boom loudness.

Wintzer, Mathias↗
NASA NTRS2010

Parametric Geometry, Structured Grid Generation, and Initial Design Study for REST-Class Hypersonic Inlets

Computational design and analysis of three-dimensional hypersonic inlets with shape transition has been a significant challenge due to the complex geometry and grid required for three-dimensional viscous flow calculations. Currently, the design process utilizes an inviscid design tool to produce initial inlet shapes by streamline tracing through an axisymmetric compression field. However, the shape is defined by a large number of points rather than a continuous surface and lacks important features such as blunt leading edges. Therefore, a design system has been developed to parametrically construct true CAD geometry and link the topology of a structured grid to the geometry. The Adaptive Modeling Language (AML) constitutes the underlying framework that is used to build the geometry and grid topology. Parameterization of the CAD geometry allows the inlet shapes produced by the inviscid design tool to be generated, but also allows a great deal of flexibility to modify the shape to account for three-dimensional viscous effects. By linking the grid topology to the parametric geometry, the GridPro grid generation software can be used efficiently to produce a smooth hexahedral multiblock grid. To demonstrate the new capability, a matrix of inlets were designed by varying four geometry parameters in the inviscid design tool. The goals of the initial design study were to explore inviscid design tool geometry variations with a three-dimensional analysis approach, demonstrate a solution rate which would enable the use of high-fidelity viscous three-dimensional CFD in future design efforts, process the results for important performance parameters, and perform a sample optimization.

Ferlemann, Paul G.↗
NASA NTRS1992

Reducing the complexity of software systems - A strategic software perspective

The results of a combined management and technical initiative aimed at reducing the size and complexity associated with developing operations planning, scheduling, and resource management software systems are presented. The initiative has produced operations concepts, functional requirements, system architectures, a comprehensive lexicon, and software tools to revolutionize the traditional software technology and development practices for planning, scheduling, and resource management systems used in space operations control centers. Examples of technology and practices to reduce complexity include a method for projecting design consequences from an operations concept, a universal architecture for heuristic algorithms, an object-oriented framework for describing large classes of problems that parametrically adapt to all domain peculiarities, the identification of general approaches which respond to changes with minimum impact on systems implementations, and a management structure for prototyping to minimize the risks of ill-conceived designs.

Hornstein, Rhoda S.↗
NASA NTRS2003

CAD-Based Aerodynamic Design of Complex Configurations using a Cartesian Method

A modular framework for aerodynamic optimization of complex geometries is developed. By working directly with a parametric CAD system, complex-geometry models are modified nnd tessellated in an automatic fashion. The use of a component-based Cartesian method significantly reduces the demands on the CAD system, and also provides for robust and efficient flowfield analysis. The optimization is controlled using either a genetic or quasi-Newton algorithm. Parallel efficiency of the framework is maintained even when subject to limited CAD resources by dynamically re-allocating the processors of the flow solver. Overall, the resulting framework can explore designs incorporating large shape modifications and changes in topology.

Nemec, Marian↗
NASA NTRS2005

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↗
NASA NTRS1988

A parametric LQ approach to multiobjective control system design

The synthesis of a constant parameter output feedback control law of constrained structure is set in a multiple objective linear quadratic regulator (MOLQR) framework. The use of intuitive objective functions such as model-following ability and closed-loop trajectory sensitivity, allow multiple objective decision making techniques, such as the surrogate worth tradeoff method, to be applied. For the continuous-time deterministic problem with an infinite time horizon, dynamic compensators as well as static output feedback controllers can be synthesized using a descent Anderson-Moore algorithm modified to impose linear equality constraints on the feedback gains by moving in feasible directions. Results of three different examples are presented, including a unique reformulation of the sensitivity reduction problem.

Kyr, Douglas E.↗
NASA NTRS2006

Implementing Scientific Simulation Codes Highly Tailored for Vector Architectures Using Custom Configurable Computing Machines

The motivation for this work comes from an observation that amidst the push for Massively Parallel (MP) solutions to high-end computing problems such as numerical physical simulations, large amounts of legacy code exist that are highly optimized for vector supercomputers. Because re-hosting legacy code often requires a complete re-write of the original code, which can be a very long and expensive effort, this work examines the potential to exploit reconfigurable computing machines in place of a vector supercomputer to implement an essentially unmodified legacy source code. Custom and reconfigurable computing resources could be used to emulate an original application's target platform to the extent required to achieve high performance. To arrive at an architecture that delivers the desired performance subject to limited resources involves solving a multi-variable optimization problem with constraints. Prior research in the area of reconfigurable computing has demonstrated that designing an optimum hardware implementation of a given application under hardware resource constraints is an NP-complete problem. The premise of the approach is that the general issue of applying reconfigurable computing resources to the implementation of an application, maximizing the performance of the computation subject to physical resource constraints, can be made a tractable problem by assuming a computational paradigm, such as vector processing. This research contributes a formulation of the problem and a methodology to design a reconfigurable vector processing implementation of a given application that satisfies a performance metric. A generic, parametric, architectural framework for vector processing implemented in reconfigurable logic is developed as a target for a scheduling/mapping algorithm that maps an input computation to a given instance of the architecture. This algorithm is integrated with an optimization framework to arrive at a specification of the architecture parameters that attempts to minimize execution time, while staying within resource constraints. The flexibility of using a custom reconfigurable implementation is exploited in a unique manner to leverage the lessons learned in vector supercomputer development. The vector processing framework is tailored to the application, with variable parameters that are fixed in traditional vector processing. Benchmark data that demonstrates the functionality and utility of the approach is presented. The benchmark data includes an identified bottleneck in a real case study example vector code, the NASA Langley Terminal Area Simulation System (TASS) application.

Rutishauser, David↗
NASA NTRS1988

A parametric LQ approach to multiobjective control system design

The synthesis of a constant parameter output feedback control law of constrained structure is set in a multiple-objective linear quadratic regulator (MOLQR) framework. The use of intuitive objective functions such as model-following ability and closed-loop trajectory sensitivity allows multiple-objective decision-making techniques, such as the surrogate worth tradeoff method, to be applied. For the continuous-time deterministic problem with an infinite time horizon, dynamic compensators as well as static output feedback controllers can be synthesized using a descent Anderson-Moore algorithm modified to impose linear equality constraints on the feedback gains by moving in feasible directions. Results of three different examples are presented, including a unique reformulation of the sensitivity reduction problem.

Kyr, Doug↗