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Results for “structural optimization”

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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Structural optimization and recent large ground antenna installations

Within the past several years, the Jet Propulsion Laboratory has designed and built major ground antenna structures in Spain, Australia, and California. One of the antennas at each location is a 70 meter-diameter structure that is a retrofit of the existing 64 meter antenna. The 64 meter existing antennas were first stripped back to a 34 meter interior and then completely new construction with deeper trusses was added to extend the interior to 70 meters. The 70 meter project included the rare opportunity to collect field data to compare with predictions of the finite-element analytical models. The new quadripod design was tested for its lower mode natural frequencies and the main reflector was measured by theodolite to determine deflections of subsets of the backup-structure deformations under load. The emphasis here is to examine measurement results and possibly provide some appreciation of the relationship of predictions made from the design model to actual measurements.

Levy, Roy↗
DOE OSTI2025

Optimizing structured surfaces for diffractive waveguides

We introduce universal diffractive waveguide designs that can match the performance of conventional dielectric waveguides and achieve various functionalities. Optimized using deep learning, diffractive waveguides can be cascaded to form any desired length and are comprised of transmissive diffractive surfaces that permit the propagation of desired modes with low loss and high mode purity. In addition to guiding the targeted modes through cascaded diffractive units, we also developed various waveguide components and introduced bent diffractive waveguides, rotating the direction of mode propagation, as well as spatial and spectral mode filtering and mode splitting diffractive waveguide designs, and mode-specific polarization control. This framework was experimentally validated in the terahertz spectrum to selectively pass certain spatial modes while rejecting others. Without the need for material dispersion engineering diffractive waveguides can be scaled to operate at different wavelengths, including visible and infrared spectrum, covering potential applications in, e.g., telecommunications, imaging, sensing and spectroscopy.

Applied optics↗
NASA NTRS1997

Efficient Approximation for Structural Optimization Under Multiple Constraints

The cooperative agreement covered work between August 1995 and August 1997. The focus of the work was efficient approximations of structural response and sensitivity. The effort proceeded in three directions as follows: (1) Development of an approximation extended to efficient sensitivity approximations and demonstrated for structural models for the High Speed Civil Transport; (2) Preliminary development of the adjoint method for calculating sensitivity derivatives; and (3) A review of method for fast exact reanalysis. Attachments of papers which were submitted during this period are included.

Haftka, Raphael T.↗
NASA NTRS1989

Recent developments in large-scale structural optimization

A brief discussion is given of mathematical optimization and the motivation for the development of more recent numerical search procedures. A review of recent developments and issues in multidisciplinary optimization is also presented. These developments are discussed in the context of the preliminary design of aircraft structures. A capability description of programs FASTOP, TSO, STARS, LAGRANGE, ELFINI and ASTROS is included.

Venkayya, Vipperla B.↗
NASA NTRS2003

Comparison of Structural Optimization Techniques for a Nuclear Electric Space Vehicle

The purpose of this paper is to utilize the optimization method of genetic algorithms (GA) for truss design on a nuclear propulsion vehicle. Genetic Algorithms are a guided, random search that mirrors Darwin s theory of natural selection and survival of the fittest. To verify the GA s capabilities, other traditional optimization methods were used to compare the results obtained by the GA's, first on simple 2-D structures, and eventually on full-scale 3-D truss designs.

Benford, Andrew↗
NASA NTRS1973

Structural optimization by methods of feasible directions.

A general design algorithm based on methods of feasible directions is presented. Zoutendijk's method of feasible directions is first presented as applied to structural design. This method is modified to improve numerical stability of the design process and is then further modified to deal efficiently with infeasible designs. The algorithm requires the analytic gradient of the objective function and the constraint functions which are active at a given stage in the design process. Gradient information is not required for nonactive constraints. Complex constraint functions may be ignored in the initial design stages because violation of these constraints is efficiently overcome later in the design process. The algorithm is demonstrated with elastic design of redundant trusses.

Vanderplaats, G. N.↗
NASA NTRS1996

Optimized Structures and Proton Affinities of Fluorinated Dimethyl Ethers: An Ab Initio Study

Ab initio methods have been used to investigate the proton affinity and the geometry changes upon protonation for the molecules (CH3)2O, (CH2F)2O, (CHF2)2O, and (CF3)2O. Geometry optimizations were performed at the MP2/3-2 I G level, and the resulting geometries were used for single-point energy MP2/6-31G calculations. The proton affinity calculated for (CH3)2O was 7 Kjoule/mole from the experimental value, within the desired variance of +/- 8Kjoule/mole for G2 theory, suggesting that the methodology used in this study is adequate for energy difference considerations. For (CF3)20, the calculated proton affinity of 602 Kjoule/mole suggests that perfluorinated ether molecules do not act as Lewis bases under normal circumstances; e.g. degradation of commercial lubricants in tribological applications.

Orgel, Victoria B.↗
DOE OSTI2020

Machine learning with bond information for local structure optimizations in surface science

Local optimization of adsorption systems inherently involves different scales: within the substrate, within the molecule, and between the molecule and the substrate. In this work, we show how the explicit modeling of different characteristics of the bonds in these systems improves the performance of machine learning methods for optimization. Furthermore, we introduce an anisotropic kernel in the Gaussian process regression framework that guides the search for the local minimum, and we show its overall good performance across different types of atomic systems. The method shows a speed-up of up to a factor of two compared with the fastest standard optimization methods on adsorption systems. Additionally, we show that a limited memory approach is not only beneficial in terms of overall computational resources but can also result in a further reduction of energy and force calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Computation of forces and stresses in solids: Towards accurate structural optimization with auxiliary-field quantum Monte Carlo

The accurate computation of forces and other energy derivatives has been a long-standing challenge for quantum Monte Carlo methods. A number of technical obstacles contribute to this challenge. We discuss how these obstacles can be removed with the auxiliary-field quantum Monte Carlo (AFQMC) approach. AFQMC is a general, high-accuracy, many-body total-energy method for molecules and solids. The implementation of back-propagation for pure estimators allows direct calculation of gradients of the energy via the Hellmann-Feynman theorem. A planewave basis with norm-conserving pseudopotentials is used for the study of periodic bulk materials. Completeness of the planewave basis minimizes the effect of so-called Pulay terms. The ionic pseudopotentials, which can be incorporated in AFQMC in exactly the same manner as in standard independent-electron methods, regulate the force and stress estimators and eliminate any potential divergence of the Monte Carlo variances. The resulting approach allows applications of full geometry optimizations in bulk materials. As a result, it also paves the way for many-body computations of the phonon spectrum in solids.

36 MATERIALS SCIENCE↗
NASA NTRS2014

Trim and Structural Optimization of Subsonic Transport Wings Using Nonconventional Aeroelastic Tailoring

Several minimum-mass aeroelastic optimization problems are solved to evaluate the effectiveness of a variety of novel tailoring schemes for subsonic transport wings. Aeroelastic strength and panel buckling constraints are imposed across a variety of trimmed maneuver loads. Tailoring with metallic thickness variations, functionally graded materials, composite laminates, tow steering, and distributed trailing edge control effectors are all found to provide reductions in structural wing mass with varying degrees of success. The question as to whether this wing mass reduction will offset the increased manufacturing cost is left unresolved for each case.

Stanford, Bret K.↗
NASA NTRS1984

Application of modern structural optimization to vibration reduction in rotorcraft

The helicopter rotor model consists of a four bladed hingeless rotor attached to a fuselage. The helicopter is assumed to be in trimmed forward flight. Each blade is assumed to have flap, lag, and torsional degrees of freedom. The fuselage degrees of freedom are not included in the analysis. Thus the aeroelastic stability and response analysis upon which this study is based is an isolated blade analysis. The helicopter rotor vibration reduction problem expressed as a general class of structural synthesis problems is given.

Friedmann, P. P.↗
NASA NTRS1992

On the use of ANN interconnection weights in optimal structural design

The present paper describes the use of interconnection weights of a multilayer, feedforward network, to extract information pertinent to the mapping space that the network is assumed to represent. In particular, these weights can be used to determine an appropriate network architecture, and an adequate number of training patterns (input-output pairs) have been used for network training. The weight analysis also provides an approach to assess the influence of each input parameter on a selected output component. The paper shows the significance of this information in decomposition driven optimal design.

Hajela, P.↗
NASA NTRS1984

The structural optimization of a spreader bar for twin lift helicopter operations

An optimization study was performed to develop a minimum weight spreader bar to allow two helicopters to lift the same payload. With this arrangement, the maximum payload that can be lifted is almost doubled without the expense of designing and building a new helicopter. The concept has had some limited use by civil helicopter operators using small helicopters and has been demonstrated in large scale by two CH-54's which successfully lifted a total load of 20 ton. To this point, rather heavy available beams or tower structures have been used for the spreader bar. Since the weight of the bar not only detracts from payload but also adds to the logistics problem, there are more than the usual incentives to minimize weight. Since the design requirement is for classic beam column with uniform side loads resulting from bar weight and aerodynamic drag, the design problem is particularly amenable to optimization. A study has been performed at Sikorsky to establish the minimum weight for a spreader bar sized to carry a load equal to the capacity of two Army BLACK HAWK helicopters. Toward this end, a computer program was written to analyze the spreader bar deflections and stresses and coupled to the NASA developed CONMIN optimization routines.

Dobyns, A.↗
NASA NTRS1982

Design, development and mechanization of a precision deployable truss with optimized structural efficiency for spaceborne applications

A deployable mast concept which meets the weight, size and stability requirements for a feed support structure for offset antennas up to 100 meters in diameter is discussed. A triangulated truss configuration, the use of tapered tubes which exhibit a high strength-to-weight ratio, and low CTE graphite-epoxy material are seen to provide an efficient, lightweight and stable truss suitable for an antenna feed support. A low stowage ratio of 30:1 is achieved through a unique preloaded hinge located at the center of each longeron and an autonomous deployment cage with a drive mechanism. Initial analysis and proof of concept hardware validated the basic mechanism and design assumptions and provided a basis for further investigation. The concept can readily accept variations in member size and thus lends itself to optimization for other potential uses where a stiff, lightweight deployable truss is needed.

Craighead, N. D.↗
DOE OSTI2025

Curiosity driven exploration to optimize structure–property learning in microscopy

Rapidly determining structure–property correlations in materials is an important challenge in better understanding fundamental mechanisms and greatly assists in materials design. In microscopy, imaging data provides a direct measurement of the local structure, while spectroscopic measurements provide relevant functional property information. Deep kernel active learning approaches have been utilized to rapidly map local structure to functional properties in microscopy experiments, but are computationally expensive for multi-dimensional and correlated output spaces. Here, we present an alternative lightweight curiosity algorithm which actively samples regions with unexplored structure–property relations, utilizing a deep-learning based surrogate model for error prediction. We show that the algorithm outperforms random sampling for predicting properties from structures, and provides a convenient tool for efficient mapping of structure–property relationships in materials science.

36 MATERIALS SCIENCE↗