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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

A Bell-Curved Based Algorithm for Mixed Continuous and Discrete Structural Optimization

An evolutionary based strategy utilizing two normal distributions to generate children is developed to solve mixed integer nonlinear programming problems. This Bell-Curve Based (BCB) evolutionary algorithm is similar in spirit to (mu + mu) evolutionary strategies and evolutionary programs but with fewer parameters to adjust and no mechanism for self adaptation. First, a new version of BCB to solve purely discrete optimization problems is described and its performance tested against a tabu search code for an actuator placement problem. Next, the performance of a combined version of discrete and continuous BCB is tested on 2-dimensional shape problems and on a minimum weight hub design problem. In the latter case the discrete portion is the choice of the underlying beam shape (I, triangular, circular, rectangular, or U).

Kincaid, Rex K.↗
NASA NTRS1989

NASA Workshop on Computational Structural Mechanics 1987, part 3

Computational Structural Mechanics (CSM) topics are explored. Algorithms and software for nonlinear structural dynamics, concurrent algorithms for transient finite element analysis, computational methods and software systems for dynamics and control of large space structures, and the use of multi-grid for structural analysis are discussed.

Sykes, Nancy P.↗
DOE OSTI2023

High-Level Synthesis of Irregular Applications: A Case Study on Influence Maximization

The Influence Maximization problem is the problem of identifying a small cohort of actors from a broader population that, when initially activated in a diffusion process, are expected to result in a large number of activations in the population. While the problem is known to be NP-hard, several approximation algorithms have been devised by leveraging its submodular structure. While these algorithms are theoretically efficient, they are computationally very expensive in practice. This work advances the current state-of-the-art parallelization scheme for the IMM algorithm by devising the adoption of custom hardware accelerators implemented on FPGAs by leveraging High Level Synthesis from OpenCL. We study the performance of our proposed approach by exploring optimizations tailored at improving the parallel efficiency of the accelerators and highlight their effects and limitations in accelerating complex graph analytic applications. Our experimental evaluation shows that FPGA acceleration can improve the performance of the LT diffusion model up to 1.72x for the entire application and up to 2.90x for its most important kernel with respect to a CPU only parallel execution. The FPGA acceleration of the LT model shows also a 1.54x reduction in energy consumption when compared to a parallel CPU only run.

Neff, Reece W.↗
DOE OSTI2025

Development of a TSR-based method for understanding structural relationships of cofactors and local environments in photosystem I

All chemical forms of energy and oxygen on Earth are generated via photosynthesis where light energy is converted into redox energy by two photosystems (PS I and PS II). There is an increasing number of PS I 3D structures deposited in the Protein Data Bank (PDB). The Triangular Spatial Relationship (TSR)-based algorithm converts 3D structures into integers (TSR keys). A comprehensive study was conducted, by taking advantage of the PS I 3D structures and the TSR-based algorithm, to answer three questions: (i) Are electron cofactors including P700, A -1 and A 0 , which are chemically identical chlorophylls, structurally different? (ii) There are two electron transfer chains (A and B branches) in PS I. Are the cofactors on both branches structurally different? (iii) Are the amino acids in cofactor binding sites structurally different from those not in cofactor binding sites? The key contributions and important findings include: (i) a novel TSR-based method for representing 3D structures of pigments as well as for quantifying pigment structures was developed; (ii) the results revealed that the redox cofactor, P700, are structurally conserved and different from other redox factors. Similar situations were also observed for both A -1 and A 0 ; (iii) the results demonstrated structural differences between A and B branches for the redox cofactors P700, A -1 , A 0 and A 1 as well as their cofactor binding sites; (iv) the tryptophan residues close to A 0 and A 1 are structurally conserved; (v) The TSR-based method outperforms the Root Mean Square Deviation (RMSD) and the Ultrafast Shape Recognition (USR) methods. The structural analyses of redox cofactors and their binding sites provide a foundation for understanding the unique chemical and physical properties of each redox cofactor in PS I, which are essential for modulating the rate and direction of energy and electron transfers.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

A novel imaging technique for measuring kinematics of light-weight flexible structures

A new imaging algorithm is proposed to capture the kinematics of flexible, thin, light structures including frequencies and motion amplitudes for real time analysis. The studied case is a thin flexible beam that is preset at different angles of attack in a wind tunnel. As the angle of attack is increased beyond a critical value, the beam was observed to undergo a static deflection that is ensued by limit cycle oscillations. Imaging analysis of the beam vibrations shows that the motion consists of a superposition of the bending and torsion modes. The proposed algorithm was able to capture the oscillation amplitudes as well as the frequencies of both bending and torsion modes. The analysis results are validated through comparison with measurements from a piezoelectric sensor that is attached to the beam at its root.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

GMFOLD: Subgraph matching for high-throughput DNA-aptamer secondary structure classification and machine learning interpretability

Aptamers are oligonucleotide receptors that bind to their targets with high affinity. Here, we consider aptamers comprised of single-stranded DNA that undergo target-binding-induced conformational changes, giving rise to unique secondary and tertiary structures. Given a specific aptamer primary sequence, there are well-established computational tools (notably mfold) to predict the secondary structure via free energy minimization algorithms. While mfold generates secondary structures for individual sequences, there is a need for a high-throughput process whereby thousands of DNA structures can be predicted in real-time for use in an interactive setting, when combined with aptamer selections that generate candidate pools that are too large to be experimentally interrogated. We developed a new Python code for high-throughput aptamer secondary structure determination (GMfold). GMfold uses subgraph matching methods to group aptamer candidates by secondary structure similarities. We also improve an open-source code, SeqFold, to incorporate subgraph matching concepts. We represent each secondary structure as a lowest-energy bipartite subgraph matching of the DNA graph to itself. These new tools enable thousands of DNA sequences to be compared based on their secondary structures, using machine-learning algorithms. This process is advantageous when analyzing sequences that arise from aptamer selections via systematic evolution of ligands by exponential enrichment (SELEX). This work is a building block for future machine-learning-informed DNA-aptamer selection processes to identify aptamers with improved target affinity and selectivity and advance aptamer biosensors and therapeutics.

Aptamer↗
DOE OSTI2015

Identify Structural Flaw Location and Type with an Inverse Algorithm of Resonance Inspection

To evaluate the fitness-for-service of a structural component and to quantify its remaining useful life, aging and service-induced structural flaws must be quantitatively determined in service or during scheduled maintenance shutdowns. Resonance inspection (RI), a non-destructive evaluation (NDE) technique, distinguishes the anomalous parts from the good parts based on changes in the natural frequency spectra. Known for its numerous advantages, i.e., low inspection cost, high testing speed, and broad applicability to complex structures, RI has been widely used in the automobile industry for quality inspection. However, compared to other contemporary direct visualization-based NDE methods, a more widespread application of RI faces a fundamental challenge because such technology is unable to quantify the flaw details, e.g. location, dimensions, and types. In this study, the applicability of a maximum correlation-based inverse RI algorithm developed by the authors is further studied for various flaw cases. It is demonstrated that a variety of common structural flaws, i.e. stiffness degradation, voids, and cracks, can be accurately retrieved by this algorithm even when multiple different types of flaws coexist. The quantitative relations between the damage identification results and the flaw characteristics are also developed to assist the evaluation of the actual state of health of the engineering structures.

non-destructive evaluation, resonance inspection, ↗
NASA NTRS1999

Implementation of Interaction Algorithm to Non-Matching Discrete Interfaces Between Structure and Fluid Mesh

This paper presents software for solving the non-conforming fluid structure interfaces in aeroelastic simulation. It reviews the algorithm of interpolation and integration, highlights the flexibility and the user-friendly feature that allows the user to select the existing structure and fluid package, like NASTRAN and CLF3D, to perform the simulation. The presented software is validated by computing the High Speed Civil Transport model.

Chen, Shu-Po↗
DOE OSTI2018

ROY Revisited, Again: The Eighth Solved Structure

X-ray powder diffraction and crystal structure prediction (CSP) algorithms were used in synergy to establish the crystal structure of the eighth polymorph of 5-methyl-2-[(2-nitrophenyl)amino]-3-thiophenecarbonitrile (ROY), form R05. R05 crystallizes in the monoclinic space group P2_1 with lattice parameters a = 11.479(4) Å, b = 11.030(1) Å, c = 10.840(6) Å, β = 118.23(1)°. This is both the first acentric ROY polymorph, and the first with Z' > 1. The torsion angles defined by the S-C-N-C atom sequence of each molecule in the asymmetric unit are -34.0° and 44.9°. These angles fall between those previously determined for the red and orange forms of ROY. Hirshfeld surface analysis was employed to understand the crystal packing and intermolecular interactions in R05 and an updated energy stability ranking was determined using computational methods. Finally, although the application of CSP was critical to the structure solution of R05, energy stability rankings determined using a series of DFT vdW-inclusive models substantially deviate from experiment, indicating that ROY polymorphism continues to be a challenge for CSP.

36 MATERIALS SCIENCE↗
NASA NTRS1981

Recent developments in quasi-Newton methods for structural analysis and synthesis

Unlike the Newton-Raphson method, quasi-Newton methods by virture of the updates and step length control procedures are globally convergent and hence better suited for the solution of nonlinear problems of structural analysis and synthesis. Extension of quasi-Newton algorithms to large scale problems has led to the development of sparse update algorithms and to economical strategies for evaluating sparse Hessians. Ill-conditioning problems have led to the development of self-scaled variable metric and conjugate gradient algorithms, as well as the use of the singular perturbation theory. This paper emphasizes the effectiveness of such quasi-Newton algorithms for nonlinear structural analysis and synthesis.

Kamat, M. P.↗
NASA NTRS1993

A novel VLSI processor architecture for supercomputing arrays

Design of the processor element for general purpose massively parallel supercomputing arrays is highly complex and cost ineffective. To overcome this, the architecture and organization of the functional units of the processor element should be such as to suit the diverse computational structures and simplify mapping of complex communication structures of different classes of algorithms. This demands that the computation and communication structures of different class of algorithms be unified. While unifying the different communication structures is a difficult process, analysis of a wide class of algorithms reveals that their computation structures can be expressed in terms of basic IP,IP,OP,CM,R,SM, and MAA operations. The execution of these operations is unified on the PAcube macro-cell array. Based on this PAcube macro-cell array, we present a novel processor element called the GIPOP processor, which has dedicated functional units to perform the above operations. The architecture and organization of these functional units are such to satisfy the two important criteria mentioned above. The structure of the macro-cell and the unification process has led to a very regular and simpler design of the GIPOP processor. The production cost of the GIPOP processor is drastically reduced as it is designed on high performance mask programmable PAcube arrays.

Venkateswaran, N.↗
NASA NTRS1988

Structural dynamics analysis using an unsymmetric block Lanczos algorithm

A method for reducing the order of a dynamical model of a large structure with arbitrary damping is developed analytically and demonstrated. A Lanczos algorithm is described which can reduce square unsymmetric system matrices to block-tridiagonal form, and a procedure for defining the reduced-order model from the right and left Lanczos vectors is outlined. Results for sample problems involving the 8-DOF FEM model of a beam-rotor assembly subjected to random and stepped external forces are presented in extensive graphs and briefly characterized.

Craig, Roy R., Jr.↗
DOE OSTI2016

Unexpected series of regular frequency spacing of δ Scuti stars in the non-asymptotic regime - I. The methodology

In this study, a sequence search method was developed to search the regular frequency spacing in δ Scuti stars through visual inspection and an algorithmic search. We searched for sequences of quasi-equally spaced frequencies, containing at least four members per sequence, in 90 δ Scuti stars observed by CoRoT. We found an unexpectedly large number of independent series of regular frequency spacing in 77 δ Scuti stars (from one to eight sequences) in the non-asymptotic regime. We introduce the sequence search method presenting the sequences and echelle diagram of CoRoT 102675756 and the structure of the algorithmic search. Four sequences (echelle ridges) were found in the 5–21 d –1 region where the pairs of the sequences are shifted (between 0.5 and 0.59 d –1 ) by twice the value of the estimated rotational splitting frequency (0.269 d –1 ). The general conclusions for the whole sample are also presented in this paper. The statistics of the spacings derived by the sequence search method, by FT (Fourier transform of the frequencies), and the statistics of the shifts are also compared. In many stars more than one almost equally valid spacing appeared. The model frequencies of FG Vir and their rotationally split components were used to formulate the possible explanation that one spacing is the large separation while the other is the sum of the large separation and the rotational frequency. In CoRoT 102675756, the two spacings (2.249 and 1.977 d –1 ) are in better agreement with the sum of a possible 1.710 d –1 large separation and two or one times, respectively, the value of the rotational frequency.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

ExaSP2

ExaSP2 is a reference implementation of typical linear algebra algorithms and workloads for a quantum molecular dynamics (QMD) electronic structure code. The algorithm is based on a recursive second-order Fermi-Operator expansion method (SP2) and is tailored for density functional based tight-binding calculations of material systems.

Negre, Christian↗
NASA NTRS2000

An Architecture for Real-Time Interpretation and Visualization of Structural Sensor Data in a Laboratory Environment

A visualization system is being developed out of the need to monitor, interpret, and make decisions based on the information from several thousand sensors during experimental testing to facilitate development and validation of structural health monitoring algorithms. As an added benefit the system will enable complete real-time sensor assessment of complex test specimens. Complex structural specimens are routinely tested that have hundreds or thousands of sensors. During a test, it is impossible for a single researcher to effectively monitor all the sensors and subsequently interesting phenomena occur that are not recognized until post-test analysis. The ability to detect and alert the researcher to these unexpected phenomena as the test progresses will significantly enhance the understanding and utilization of complex test articles. Utilization is increased by the ability to halt a test when the health monitoring algorithm response is not satisfactory or when an unexpected phenomenon occurs, enabling focused investigation potentially through the installation of additional sensors. Often if the test continues, structural changes make it impossible to reproduce the conditions that exhibited the phenomena. The prohibitive time and costs associated with fabrication, sensoring, and subsequent testing of additional test articles generally makes it impossible to further investigate the phenomena. A scalable architecture is described to address the complex computational demands of structural health monitoring algorithm development and laboratory experimental test monitoring. The researcher monitors the test using a photographic quality 3D graphical model with actual sensor locations identified. In addition, researchers can quickly activate plots displaying time or load versus selected sensor response along with the expected values and predefined limits. The architecture has several key features. First, distributed dissimilar computers may be seamlessly integrated into the information flow. Second, virtual sensors may be defined that are complex functions of existing sensors or other virtual sensors. Virtual sensors represent a calculated value not directly measured by particular physical instrument. They can be used, for example, to represent the maximum difference in a range of sensors or the calculated buckling load based on the current strains. Third, the architecture enables autonomous response to preconceived events, where by the system can be configured to suspend or abort a test if a failure is detected in the load introduction system. Fourth, the architecture is designed to allow cooperative monitoring and control of the test progression from multiple stations both remote and local to the test system. To illustrate the architecture, a preliminary implementation is described monitoring the Stitched Composite Wing recently tested at LaRC.

Doggett, William↗
NASA NTRS1994

Linear Algorithms for Worst Case Identification in H infinity with Applications to Flexible Structures

This paper is concerned with linear algorithms for identification in which have been studied in [9]. It is shown that the two different linear algorithms in [9] can be unified into a single one which can be further extended to nonuniformly spaced frequency response samples with exponential convergence for the noise free case. Improved upper bounds for the corresponding identification errors are derived. Applications to the identification of lightly damped systems such as flexible structures are also considered.

linear↗
DOE OSTI2022

Symmetry relation database and its application to ferroelectric materials discovery

To investigate the displacive phase transition at the atomic scale, we have implemented a numerical algorithm to automate the detection of the symmetry relations between any two candidate crystal structures. Using this algorithm, here we systematically screen all possible polar–nonpolar structure pairs from the Materials Project database and establish a library of ~4500 pairs that can be connected through a continuous phase transition with small atomic displacements. From this database, we identify several new ferroelectric materials. In addition, the database may also be used in other areas, such as material structure prediction and new materials discovery.

36 MATERIALS SCIENCE↗
DOE OSTI2014

sp3-hybridized framework structure of group-14 elements discovered by genetic algorithm

Group-14 elements, including C, Si, Ge, and Sn, can form various stable and metastable structures. Finding new metastable structures of group-14 elements with desirable physical properties for new technological applications has attracted a lot of interest. Using a genetic algorithm, we discovered a new low-energy metastable distorted sp3-hybridized framework structure of the group-14 elements. It has P42/mnm symmetry with 12 atoms per unit cell. The void volume of this structure is as large as 139.7Å3 for Si P42/mnm, and it can be used for gas or metal-atom encapsulation. Band-structure calculations show that P42/mnm structures of Si and Ge are semiconducting with energy band gaps close to the optimal values for optoelectronic or photovoltaic applications. With metal-atom encapsulation, the P42/mnm structure would also be a candidate for rattling-mediated superconducting or used as thermoelectric materials.

36 MATERIALS SCIENCE↗