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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 1,261 records · Page 70
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

A Case Study on the Application of a Structured Experimental Method for Optimal Parameter Design of a Complex Control System

This report documents a case study on the application of Reliability Engineering techniques to achieve an optimal balance between performance and robustness by tuning the functional parameters of a complex non-linear control system. For complex systems with intricate and non-linear patterns of interaction between system components, analytical derivation of a mathematical model of system performance and robustness in terms of functional parameters may not be feasible or cost-effective. The demonstrated approach is simple, structured, effective, repeatable, and cost and time efficient. This general approach is suitable for a wide range of systems.

Torres-Pomales, Wilfredo↗
DOE OSTI2018

Peptide design by optimization on a data-parameterized protein interaction landscape

Many applications in protein engineering require optimizing multiple protein properties simultaneously, such as binding one target but not others or binding a target while maintaining stability. Such multistate design problems require navigating a high-dimensional space to find proteins with desired characteristics. A model that relates protein sequence to functional attributes can guide design to solutions that would be hard to discover via screening. In this work, we measured thousands of protein–peptide binding affinities with the high-throughput interaction assay amped SORTCERY and used the data to parameterize a model of the alpha-helical peptide-binding landscape for three members of the Bcl-2 family of proteins: Bcl-x L , Mcl-1, and Bfl-1. We applied optimization protocols to explore extremes in this landscape to discover peptides with desired interaction profiles. Computational design generated 36 peptides, all of which bound with high affinity and specificity to just one of Bcl-x L , Mcl-1, or Bfl-1, as intended. We designed additional peptides that bound selectively to two out of three of these proteins. The designed peptides were dissimilar to known Bcl-2–binding peptides, and high-resolution crystal structures confirmed that they engaged their targets as expected. Excellent results on this challenging problem demonstrate the power of a landscape modeling approach, and the designed peptides have potential uses as diagnostic tools or cancer therapeutics.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1984

Structural synthesis: Precursor and catalyst

More than twenty five years have elapsed since it was recognized that a rather general class of structural design optimization tasks could be properly posed as an inequality constrained minimization problem. It is suggested that, independent of primary discipline area, it will be useful to think about: (1) posing design problems in terms of an objective function and inequality constraints; (2) generating design oriented approximate analysis methods (giving special attention to behavior sensitivity analysis); (3) distinguishing between decisions that lead to an analysis model and those that lead to a design model; (4) finding ways to generate a sequence of approximate design optimization problems that capture the essential characteristics of the primary problem, while still having an explicit algebraic form that is matched to one or more of the established optimization algorithms; (5) examining the potential of optimum design sensitivity analysis to facilitate quantitative trade-off studies as well as participation in multilevel design activities. It should be kept in mind that multilevel methods are inherently well suited to a parallel mode of operation in computer terms or to a division of labor between task groups in organizational terms. Based on structural experience with multilevel methods general guidelines are suggested.

Schmit, L. A.↗
NASA NTRS2014

DUKSUP: A Computer Program for High Thrust Launch Vehicle Trajectory Design and Optimization

From the late 1960's through 1997, the leadership of NASA's Intermediate and Large class unmanned expendable launch vehicle projects resided at the NASA Lewis (now Glenn) Research Center (LeRC). One of LeRC's primary responsibilities --- trajectory design and performance analysis --- was accomplished by an internally-developed analytic three dimensional computer program called DUKSUP. Because of its Calculus of Variations-based optimization routine, this code was generally more capable of finding optimal solutions than its contemporaries. A derivation of optimal control using the Calculus of Variations is summarized including transversality, intermediate, and final conditions. The two point boundary value problem is explained. A brief summary of the code's operation is provided, including iteration via the Newton-Raphson scheme and integration of variational and motion equations via a 4th order Runge-Kutta scheme. Main subroutines are discussed. The history of the LeRC trajectory design efforts in the early 1960's is explained within the context of supporting the Centaur upper stage program. How the code was constructed based on the operation of the Atlas/Centaur launch vehicle, the limits of the computers of that era, the limits of the computer programming languages, and the missions it supported are discussed. The vehicles DUKSUP supported (Atlas/Centaur, Titan/Centaur, and Shuttle/Centaur) are briefly described. The types of missions, including Earth orbital and interplanetary, are described. The roles of flight constraints and their impact on launch operations are detailed (such as jettisoning hardware on heating, Range Safety, ground station tracking, and elliptical parking orbits). The computer main frames on which the code was hosted are described. The applications of the code are detailed, including independent check of contractor analysis, benchmarking, leading edge analysis, and vehicle performance improvement assessments. Several of DUKSUP's many major impacts on launches are discussed including Intelsat, Voyager, Pioneer Venus, HEAO, Galileo, and Cassini.

high thrust trajectory design↗
NASA NTRS2018

Numerically Optimized Coronagraph Designs for the Habitable Exoplanet Imaging Mission (HabEx) Concept

The primary science goal of the Habitable Exoplanet Imaging Mission (HabEx), one of four candidate flagship missions under investigation, is to image and spectrally characterize Earth-like exoplanets. It is well known that pupil obscurations degrade coronagraphic performance and complicate coronagraph design, so HabEx is planned to have an off-axis, unobscured primary mirror. We utilize the circular symmetry of the aperture to investigate 1D-radial coronagraph optimization methods that are prohibitively time-consuming or intractable in 2D, such as diffractive pupil remapping and concurrent, multi-plane optimization. We also directly constrain sensitivities to dynamic, low-order Zernike aberrations, which are separable in polar coordinates and can thus be propagated as 1D-radial integrals. The mask technologies in our designs claim heritage from the extensive modeling and testbed experiments performed by the Wide-Field Infrared Survey Telescope (WFIRST) Coronagraph Instrument (CGI) project. In this paper, we detail our optimization methods and outline future work to complete our design survey.

Balasubramaian, Kunjithapatham↗
NASA NTRS1996

Development of a Composite Tailoring Technique for Airplane Wing

Development of a new composite beam modeling technique to represent the principal load-carrying member in the wing is reported along with the development of a formal design optimization procedure to investigate the effect of composite tailoring on aeroelastic stability and structural characteristics of airplane wings. The developed procedure is used to perform design optimization studies on realistic airplane configurations to investigate the various aeroelastic/structural/dynamic design issues.

Chattopadhyay, Aditi↗
NASA NTRSDate not supplied

Parametric Mechanism Design Through Numerical Optimization and Physics Simulation

Design-Build-Test approaches for developing spaceflight hardware are prohibitively time and cost intensive and often lead to suboptimal mechanism designs. Approaches that couple machine learning and high-fidelity physics simulation could eliminate the need for hardware prototyping and dramatically accelerate the engineering design cycle, ultimately reducing cost. This work presents a modular NASA-developed toolchain to optimize hardware mechanisms in a virtual environment using numerical optimization and multi-body physics simulation. The toolchain enables multi-objective optimization, generates parametric CAD files that can be further post-processed by an end user, and can be expanded to optimize full systems and non-mechanical parameters such as feedback control variables. We demonstrate the toolchain through an independently verifiable design problem that optimizes wheel radius to achieve a desired linear velocity in a rigid-body physics environment when the wheel rotates at a constant angular speed, and then post-process the parametric CAD file of the optimal design generated by the tool before ultimately manufacturing it via 3D printing. We end with a discussion of how the toolchain can incorporate other analysis tools, including finite element analysis, computational fluid dynamics, and granular media simulations.

Optimization↗
NASA NTRS1992

Approximation, abstraction and decomposition in search and optimization

In this paper, I discuss four different areas of my research. One portion of my research has focused on automatic synthesis of search control heuristics for constraint satisfaction problems (CSPs). I have developed techniques for automatically synthesizing two types of heuristics for CSPs: Filtering functions are used to remove portions of a search space from consideration. Another portion of my research is focused on automatic synthesis of hierarchic algorithms for solving constraint satisfaction problems (CSPs). I have developed a technique for constructing hierarchic problem solvers based on numeric interval algebra. Another portion of my research is focused on automatic decomposition of design optimization problems. We are using the design of racing yacht hulls as a testbed domain for this research. Decomposition is especially important in the design of complex physical shapes such as yacht hulls. Another portion of my research is focused on intelligent model selection in design optimization. The model selection problem results from the difficulty of using exact models to analyze the performance of candidate designs.

Ellman, Thomas↗
NASA NTRS2008

Optimized Non-Obstructive Particle Damping (NOPD) Treatment for Composite Honeycomb Structures

Non-Obstructive Particle Damping (NOPD) technology is a passive vibration damping approach whereby metallic or non-metallic particles in spherical or irregular shapes, of heavy or light consistency, and even liquid particles are placed inside cavities or attached to structures by an appropriate means at strategic locations, to absorb vibration energy. The objective of the work described herein is the development of a design optimization procedure and discussion of test results for such a NOPD treatment on honeycomb (HC) composite structures, based on finite element modeling (FEM) analyses, optimization and tests. Modeling and predictions were performed and tests were carried out to correlate the test data with the FEM. The optimization procedure consisted of defining a global objective function, using finite difference methods, to determine the optimal values of the design variables through quadratic linear programming. The optimization process was carried out by targeting the highest dynamic displacements of several vibration modes of the structure and finding an optimal treatment configuration that will minimize them. An optimal design was thus derived and laboratory tests were conducted to evaluate its performance under different vibration environments. Three honeycomb composite beams, with Nomex core and aluminum face sheets, empty (untreated), uniformly treated with NOPD, and optimally treated with NOPD, according to the analytically predicted optimal design configuration, were tested in the laboratory. It is shown that the beam with optimal treatment has the lowest response amplitude. Described below are results of modal vibration tests and FEM analyses from predictions of the modal characteristics of honeycomb beams under zero, 50% uniform treatment and an optimal NOPD treatment design configuration and verification with test data.

Panossian, H.↗
DOE OSTI2025

Analyze the real-time performance of the optimized fiber-PTR instrument

An instrument to perform in-reactor, real-time thermal property measurements of nuclear fuels and materials was recently designed, optimized, and tested at Massachusetts Institute of Technology Research Reactor. It was the second insertion experiments of a total of two rounds. Here we report the collection and analysis of the real-time captured thermal diffusivity data on the preloaded SiC. With the optimized design, the instrument temperature had been successfully raised as we expected. Only one probe (the top one) returned real-time thermal diffusivity in a time span of approximately two days. Measured thermal diffusivity of the preloaded SiC was significantly lower than the literature value at the same temperature, indicating a significant influence from the irradiation induced microstructure damage. Meanwhile, the real-time thermal diffusivity value continuously reduced with time, indicating the dynamic microstructure evolution. The possible reasons of the probes that did not return data were hypothesized. The further optimization of the instrument with the objective to improve the measurement accuracy and instrument survivability is also discussed.

36 MATERIALS SCIENCE↗
NASA NTRS1994

Design of high-efficiency, radiation-hard, GaInP/GaAs solar cells

In recently years, Ga(0.5)In((0.5)P/GaAs cells have drawn increased attention both because of their high efficiencies and because they are well suited for space applications. They can be grown and processed as two-junction devices with roughly twice the voltage and half the current of GaAs cells. They have low temperature coefficients, and have good potential for radiation hardness. We have previously reported the effects of electron irradiation on test cells which were not optimally designed for space. From those results we estimated that an optimally designed cell could achieve 20 percent after irradiation with 10(exp 15) cm(exp -2) 1 MeV electrons. Modeling studies predicted that slightly higher efficiencies may be achievable. Record efficiencies for EOL performance of other types of cells are significantly lower. Even the best Si and InP cells have BOL efficiencies lower than the EOL efficiency we report here. Good GaAs cells have an EOL efficiency of 16 percent. The InP/Ga(0.5)In(0.5)As two-junction, two-terminal device has a BOL efficiency as high as 22.2 percent, but radiation results for these cells were limited. In this study we use the previous modeling and irradiation results to design a set of Ga(0.5)In(0.5)P/GaAs cells that will demonstrate the importance of the design parameters and result in high-efficiency devices. We report record AMO efficiencies: a BOL efficiency of 25.7 percent for a device optimized for BOL performance and two of different designs with EOL efficiencies of 19.6 percent (at 10(exp 15) cm(exp -2) 1MeV electrons). We vary the bottom-cell base doping and the top-cell thickness to show the effects of these two important design parameters. We get an unexpected result indicating that the dopant added to the bottom-cell base also increases the degradation of the top cell.

Kurtz, Sarah R.↗
DOE OSTI2023

Exploration of superconducting multi-mode cavity architectures for quantum computing

Superconducting radio-frequency (SRF) cavities coupled to transmon circuits have proven to be a promising platform for building high-coherence quantum information processors. An essential aspect of this realization involves designing high quality factor three-dimensional superconducting cavities to extend the lifetime of quantum systems. To increase the computational capability of this architecture, we are exploring a multimode approach. This paper presents the design optimization process of a multi-cell SRF cavity to perform quantum computation based on an existing design developed in the scope of particle accelerator technology. We perform parametric electromagnetic simulations to evaluate and optimize the design. In particular, we focus on the analysis of the interaction between a nonlinear superconducting circuit known as the transmon and the cavity. This parametric design optimization is structured to serve as a blueprint for future studies on similar systems.

Reineri, Alessandro↗
DOE OSTI2014

Optimal experimental design for the detection of light atoms from high-resolution scanning transmission electron microscopy images

We report an innovative method to explore the optimal experimental settings to detect light atoms from scanning transmission electron microscopy (STEM) images. Since light elements play a key role in many technologically important materials, such as lithium-battery devices or hydrogen storage applications, much effort has been made to optimize the STEM technique in order to detect light elements. Therefore, classical performance criteria, such as contrast or signal-to-noise ratio, are often discussed hereby aiming at improvements of the direct visual interpretability. However, when images are interpreted quantitatively, one needs an alternative criterion, which we derive based on statistical detection theory. Using realistic simulations of technologically important materials, we demonstrate the benefits of the proposed method and compare the results with existing approaches.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1996

Use of the Collaborative Optimization Architecture for Launch Vehicle Design

Collaborative optimization is a new design architecture specifically created for large-scale distributed-analysis applications. In this approach, problem is decomposed into a user-defined number of subspace optimization problems that are driven towards interdisciplinary compatibility and the appropriate solution by a system-level coordination process. This decentralized design strategy allows domain-specific issues to be accommodated by disciplinary analysts, while requiring interdisciplinary decisions to be reached by consensus. The present investigation focuses on application of the collaborative optimization architecture to the multidisciplinary design of a single-stage-to-orbit launch vehicle. Vehicle design, trajectory, and cost issues are directly modeled. Posed to suit the collaborative architecture, the design problem is characterized by 5 design variables and 16 constraints. Numerous collaborative solutions are obtained. Comparison of these solutions demonstrates the influence which an priori ascent-abort criterion has on development cost. Similarly, objective-function selection is discussed, demonstrating the difference between minimum weight and minimum cost concepts. The operational advantages of the collaborative optimization

Braun, R. D.↗
DOE OSTI2018

Topology optimization beyond linear elasticity

Complex, non-linear path-dependent and transient response of engineering structures can today be numerically modeled with good accuracy. For linear systems, this modeling has successfully been combined with computational design optimization for many years. The combination of non-linear modeling and numerical design optimization is far less established. In the present paper we discuss some recent steps taken to close the gap between the use of linear and non-linear modeling with numerical optimization. Examples with nonlinear elasticity, finite strain plasticity and dynamic modeling combined with topology optimization are discussed.

42 ENGINEERING↗
NASA NTRS1972

An integrated computer system for preliminary design of advanced aircraft.

A progress report is given on the first phase of a research project to develop a system of Integrated Programs for Aerospace-Vehicle Design (IPAD) which is intended to automate to the largest extent possible the preliminary and detailed design of advanced aircraft. The approach used is to build a pilot system and simultaneously to carry out two major contractual studies to define a practical IPAD system preparatory to programing. The paper summarizes the specifications and goals of the IPAD system, the progress to date, and any conclusion reached regarding its feasibility and scope. Sample calculations obtained with the pilot system are given for aircraft preliminary designs optimized with respect to discipline parameters, such as weight or L/D, and these results are compared with designs optimized with respect to overall performance parameters, such as range or payload.

Fulton, R. E.↗
NASA NTRS2005

Preliminary Design of a Manned Nuclear Electric Propulsion Vehicle Using Genetic Algorithms

Nuclear electric propulsion (NEP) vehicles will be needed for future manned missions to Mars and beyond. Candidate designs must be identified for further detailed design from a large array of possibilities. Genetic algorithms have proven their utility in conceptual design studies by effectively searching a large design space to pinpoint unique optimal designs. This research combined analysis codes for NEP subsystems with a genetic algorithm. The use of penalty functions with scaling ratios was investigated to increase computational efficiency. Also, the selection of design variables for optimization was considered to reduce computation time without losing beneficial design search space. Finally, trend analysis of a reference mission to the asteroids yielded a group of candidate designs for further analysis.

Irwin, Ryan W.↗