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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Modal Interpolation Program, L 215 (INTERP): Supplemental System Design and Maintenance Document - Volume 2

The design, structure, and usage of the modal interpolation program L215 are presented. The program uses modal data sets of arrays containing interpolation coefficients. The interpolation arrays are used to determine displacements at various aerodynamic control points. The displacements consist of translations normal to the aerodynamic surface and surface slopes that are parallel and perpendicular to the free stream direction. Five different interpolation methods are available.

Hirayama, M. Y.↗
NASA NTRS1982

Opportunities for composites in commercial transport structures

Manufacturers are developing composite versions of structural components on existing aircraft. Development involves testing of various material options before selecting one and then extensive testing to develop an adequate data base of material strength and stiffness properties. Design options are narrowed through analysis and a varied spectrum of development tests on small and large subcomponents. In parallel with this, a suitable production process including economical ply preparation and cure at high temperature and pressure is evolved, tools are designed and fabricated, and full scale components are then manufactured for ground qualification tests, flight tests, and airline service. The various tests include many that are required by the FAA for flight certification, which must precede airline service. Inspection and repair methods to insure adequate maintenance in service are also developed.

Herman L. Bohon↗
NASA NTRS1997

Hypersonic Flow Computations on Unstructured Meshes

A method for computing inviscid hypersonic flow over complex configurations using unstructured meshes is presented. The unstructured grid solver uses an edge{based finite{volume formulation. Fluxes are computed using a flux vector splitting scheme that is capable of representing constant enthalpy solutions. Second{order accuracy in smooth flow regions is obtained by linearly reconstructing the solution, and stability near discontinuities is maintained by locally forcing the scheme to reduce to first-order accuracy. The implementation of the algorithm to parallel computers is described. Computations using the proposed method are presented for a sphere-cone configuration at Mach numbers of 5.25 and 10.6, and a complex hypersonic re-entry vehicle at Mach numbers of 4.5 and 9.8. Results are compared to experimental data and computations made with established structured grid methods. The use of the solver as a screening tool for rapid aerodynamic assessment of proposed vehicles is described.

Bibb, K. L.↗
DOE OSTI2022

Mesoflow: An Open-Source Reacting Flow Solver for Catalysis at Mesoscale

We present the capabilities and software performance metrics of our open-source continuum solver for catalysis, Mesoflow, developed specifically for modeling transport and chemistry at the mesoscale. Our solver utilizes Cartesian block-structured adaptive mesh refinement to resolve complex catalyst surface morphologies directly obtained from X-ray tomography data. An immersed boundary based formulation enables rapid representation of complex geometries prevalent in most mesoporous catalyst interfaces. The solver is developed on top of open-source performance portable library, AMReX, providing parallel execution capabilities on current and upcoming high-performance-computing (HPC) architectures. Our flexible software framework enables integration of complex chemical mechanisms at heterogenous interfaces and time-split algorithms for circumventing highly disparate reaction and flow time-scales. Our current studies indicate a ten-fold performance gain by using graphics-processing-units (GPUs) compared to a single processor for representative problem sizes (2 million cell mesh). We will also present a brief introduction on how to build and use this software for application problems pertaining to catalytic upgrading and gas transport within porous catalyst particles.

adaptive meshing↗
DOE OSTI2025

Spotlight: efficient automated global optimization in rietveld analysis of diffraction data

Performing reliable Rietveld analysis on tens or hundreds of powder diffraction datasets from parametric or time-resolved experiments often poses a bottleneck in extracting meaningful results from the data. While automated analysis of data has recently been demonstrated, high temperature annealing studies, during which phase transformations occur and lattice parameters may change due to repartitioning of elements, are prime examples where automation by a simple phase identification from a database of room temperature structures or automation by sequential refinements is likely to fail. To enable reliable, efficient, automated Rietveld analysis, we present a Python package named Spotlight , building on established Rietveld packages such as MAUD, GSAS , or GSAS-II , which extends the refinement of best fit parameters to a global optimization using an ensemble of optimizers leveraging hierarchical parallel execution on high-performance computing clusters. Spotlight further enables the efficient design of refinement plans through the iterative automated machine-learning of a surrogate for the refinement on which the global optimizations are performed until results from the surrogate converge to the response surface data. We demonstrate Spotlight with the analysis of uranium molybdenum and Ti–6Al–4V datasets, as well as in two open-source tutorials analyzing aluminium oxide and lead sulphate.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Nuclear Resonance Vibrational Spectroscopy Definition of O 2 Intermediates in an Extradiol Dioxygenase: Correlation to Crystallography and Reactivity

The extradiol dioxygenases are a large subclass of mononuclear nonheme Fe enzymes that catalyze the oxidative cleavage of catechols distal to their OH groups. These enzymes are important in bioremediation, and there has been significant interest in understanding how they activate O 2 . The extradiol dioxygenase homoprotocatechuate 2,3-dioxygenase (HPCD) provides an opportunity to study this process, as two O 2 intermediates have been trapped and crystallographically defined using the slow substrate 4-nitrocatechol (4NC): a side-on Fe–O 2 –4NC species and a Fe–O 2 –4NC peroxy bridged species. Also with 4NC, two solution intermediates have been trapped in the H200N variant, where H200 provides a second-sphere hydrogen bond in the wild-type enzyme. While the electronic structure of these solution intermediates has been defined previously as Fe III -superoxo-catecholate and Fe III -peroxy-semiquinone, their geometric structures are unknown. Nuclear resonance vibrational spectroscopy (NRVS) is an important tool for structural definition of nonheme Fe–O 2 intermediates, as all normal modes with Fe displacement have intensity in the NRVS spectrum. In this study, NRVS is used to define the geometric structure of the H200N–4NC solution intermediates in HPCD as an end-on Fe III -superoxo-catecholate and an end-on Fe III -hydroperoxo-semiquinone. Parallel calculations are performed to define the electronic structures and protonation states of the crystallographically defined wild-type HPCD–4NC intermediates, where the side-on intermediate is found to be a Fe III -hydroperoxo-semiquinone. The assignment of this crystallographic intermediate is validated by correlation to the NRVS data through computational removal of H200. While the side-on hydroperoxo semiquinone intermediate is computationally found to be nonreactive in peroxide bridge formation, it is isoenergetic with a superoxo catecholate species that is competent in performing this reaction. In conclusion, this study provides insight into the relative reactivities of Fe III -superoxo and Fe III -hydroperoxo intermediates in nonheme Fe enzymes and into the role H200 plays in facilitating extradiol catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Structural and functional consequences of the STAT5B N642H driver mutation

Hyper-activated STAT5B variants are high value oncology targets for pharmacologic intervention. STAT5B N642H , a frequently-occurring oncogenic driver mutation, promotes aggressive T-cell leukemia/lymphoma in patient carriers, although the molecular origins remain unclear. Herein, we emphasize the aggressive nature of STAT5B N642H in driving T-cell neoplasia upon hematopoietic expression in transgenic mice, revealing evidence of multiple T-cell subset organ infiltration. Notably, we demonstrate STAT5B N642H -driven transformation of γδ T-cells in in vivo syngeneic transplant models, comparable to STAT5B N642H patient γδ T-cell entities. Importantly, we present human STAT5B and STAT5B N642H crystal structures, which propose alternative mutation-mediated SH2 domain conformations. Our biophysical data suggests STAT5B N642H can adopt a hyper-activated and hyper-inactivated state with resistance to dephosphorylation. MD simulations support sustained interchain cross-domain interactions in STAT5B N642H , conferring kinetic stability to the mutant anti-parallel dimer. This study provides a molecular explanation for the STAT5B N642H activating potential, and insights into pre-clinical models for targeted intervention of hyper-activated STAT5B.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1984

Acoustooptic linear algebra processors - Architectures, algorithms, and applications

Architectures, algorithms, and applications for systolic processors are described with attention to the realization of parallel algorithms on various optical systolic array processors. Systolic processors for matrices with special structure and matrices of general structure, and the realization of matrix-vector, matrix-matrix, and triple-matrix products and such architectures are described. Parallel algorithms for direct and indirect solutions to systems of linear algebraic equations and their implementation on optical systolic processors are detailed with attention to the pipelining and flow of data and operations. Parallel algorithms and their optical realization for LU and QR matrix decomposition are specifically detailed. These represent the fundamental operations necessary in the implementation of least squares, eigenvalue, and SVD solutions. Specific applications (e.g., the solution of partial differential equations, adaptive noise cancellation, and optimal control) are described to typify the use of matrix processors in modern advanced signal processing.

Casasent, D.↗
DOE OSTI2023

Thermal Scattering Law Data Development for Paraffin Wax

Paraffin wax is often used as a nuclear moderator to slow down the fast neutrons in experimental critical assemblies [1]. It is a colorless and soft solid material that consists primarily of straight-chain alkanes (n-alkanes), which are hydrocarbons with the general formula CnH2n+2 [2-3]. The length of the hydrocarbon chain ranges from C20 to C30 and higher [2]. It is distinguished by its solid state at room temperature and begins to melt above approximately 310 K [4]. Paraffin wax is a commonly employed substance in the manufacture of shielding. One of its noteworthy characteristics is its ability to effectively absorb the neutrons. Also, it possesses a high macroscopic cross section, which enables it to efficiently moderate neutrons. As a result, paraffin wax is extensively utilized in various applications where moderation and shielding of neutrons are needed. For simulations, it is necessary to evaluate its thermal scattering law (TSL) and cross sections. Computationally, classical molecular dynamics (CMD) simulations provide the capability of simulating atomic details. For example, several unary, binary, and few multi component mixtures have been investigated of the paraffin model by using molecular dynamics simulations [5-12]. An assessment of thermal neutron scattering in a heavy paraffinic oil treated both as a solid and a viscous fluid containing 25% linear branched paraffin (C30H62), 35% one ring cycloalkane (C30H60), 15% two rings cycloalkane (C30H58), and 25% aromatic (C30H60) chains has been studied using CMD simulations for producing TSL data [13]. Nevertheless, there is lack of TSL and cross section data for paraffin wax as most of the reported analyses focus on the unary and binary mixture of n-alkanes, which is not consistent with actual paraffin wax [2]. In this work, we applied the equilibrium CMD simulations technique to explore the structure and dynamical properties of wax, which are fundamental input to calculate the TSL. A paraffin wax system was modeled using the CMD code LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator) [14-15] with the semi-empirical COMPASS [16] force field. The density of state (DOS) was calculated from the normalized velocity autocorrelation function (VACF), which is the Fourier transform of the normalized VACF. The DOS was used for the calculation of the TSL and thermal scattering cross sections. The paraffin wax atomic system was constructed by using the MedeA material design platform [17], and was benchmarked using available properties (i.e., density, bond lengths, angles, diffusivity, and viscosity).

Nuclear Criticality Safety Program (NCSP)↗
DOE OSTI2020

Crystal structure of an Escherichia coli Hfq Core (residues 2–69)–DNA complex reveals multifunctional nucleic acid binding sites

Hfq regulates bacterial gene expression post-transcriptionally by binding small RNAs and their target mRNAs, facilitating sRNA-mRNA annealing, typically resulting in translation inhibition and RNA turnover. Hfq is also found in the nucleoid and binds double-stranded (ds) DNA with a slight preference for A-tracts. Here, we present the crystal structure of the Escherichia coli Hfq Core bound to a 30 bp DNA, containing three 6 bp A-tracts. Although previously postulated to bind to the ‘distal’ face, three statistically disordered double stranded DNA molecules bind across the proximal face of the Hfq hexamer as parallel, straight rods with B-DNA like conformational properties. One DNA duplex spans the diameter of the hexamer and passes over the uridine-binding proximal-face pore, whereas the remaining DNA duplexes interact with the rims and serve as bridges between adjacent hexamers. Binding is sequence-independent with residues N13, R16, R17 and Q41 interacting exclusively with the DNA backbone. Atomic force microscopy data support the sequence-independent nature of the Hfq-DNA interaction and a role for Hfq in DNA compaction and nucleoid architecture. Our structure and nucleic acid-binding studies also provide insight into the mechanism of sequence-independent binding of Hfq to dsRNA stems, a function that is critical for proper riboregulation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Cabana: A Performance Portable Library for Particle-Based Simulations

Particle-based simulations are ubiquitous throughout many fields of computational science and engineering, spanning the atomistic level with molecular dynamics (MD), to mesoscale particle-in-cell (PIC) simulations for solid mechanics, device-scale modeling with PIC methods for plasma physics, and massive N-body cosmology simulations of galaxy structures, with many other methods in between (Hockney & Eastwood, 1989). While these methods use particles to represent significantly different entities with completely different physical models, many low-level details are shared including performant algorithms for short- and/or long-range particle interactions, multi-node particle communication patterns, and other data management tasks such as particle sorting and neighbor list construction. Cabana is a performance portable library for particle-based simulations, developed as part of the Co-Design Center for Particle Applications (CoPA) within the Exascale Computing Project (ECP) (Alexander et al., 2020). The CoPA project and its full development scope, including ECP partner applications, algorithm development, and similar software libraries for quantum MD, is described in (Mniszewski et al., 2021). Cabana uses the Kokkos library for on-node parallelism (Edwards et al., 2014; Trott et al., 2022), enabling simulation on multi-core CPU and GPU architectures, and MPI for GPU-aware, multi-node communication. Cabana provides particle simulation capabilities on almost all current Kokkos backends, including serial execution, OpenMP (including OpenMP-Target for GPUs), CUDA (NVIDIA GPUs), HIP (AMD GPUs), and SYCL (Intel GPUs), providing a clear path for the coming generation of accelerator-based exascale hardware. Cabana builds on Kokkos by providing new particle data structures and particle algorithms resulting in a similar execution policy-based, node-level programming model that is intended to be used in addition to the core Kokkos library within an application. Cabana is designed as an application and physics agnostic, but particle-specific toolkit which can either be used to generate a new application, or to be used as needed in existing applications at various levels of invasiveness including through interfaces that wrap user memory in existing data structures.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

NICS (NASA Instrument Capabilities Study) Instrument Schedule and Cost Study

This paper summarizes work performed on the Flight Projects Directorate Planetary Science Projects Division (PSPD, Code 430) NICS (NASA Instrument Capabilities study) instrument schedule and cost study. Included are a short summary of the original NICS (NASA, 2008), and the design and approach, data collection, analysis, preliminary findings and recommendations from select areas of the current study. The NICS (2008) was chartered by then NASA Chief Engineer Michael Ryschkewitsch and chaired by Goddard Space Flight Center (GSFC) engineer, John Leon. The focus was to identify problem areas in instrument development and, if possible, to offer solutions. In the area of instrument developments, the NICS (2008) identified a lack of resources and authority to successfully manage to instrument cost and schedule requirements; and a lack of critical skills, expertise, and leadership to successfully implement unique (one-of-a-kind) high technology developments (NASA, 2008, pp. 51, 52). Additionally, the NICS (2008) found problems in requirements formulation, reviews and management; unrealistic caps and overly optimistic estimates; and externally directed changes which increased the likelihood of overrunning cost and schedule (NASA, 2008, pp.53, 54). It is noteworthy that NICS findings are consistent with previous studies at the mission level (Robbins, Schmidt & White, 2020). Five years later in 2013, the Instrument Projects Division (IPD) was established to implement and manage instrument projects greater than $20M. The IPD was known as Code 490. Its structure incorporated several of the NICS (2008) recommendations. To see if these incorporated recommendations made a difference, and to identify other potential challenges in instrument developments, two parallel studies were initiated. Originally led by the IPD, now led by the PSPD, and the Instrument and Payload Systems Engineering Branch (IPSE, Code 592), respectively, the instrument schedule and cost study and the instrument technical complexity study began in 2017. Data collection was initiated in 2020 and is on-going. This paper is limited to the IPD/PSPD study. Among other findings, preliminary data indicate IPD/PSPD project management support positively influenced instrument development as related to providing a dedicated level of support staff, including a deputy Instrument Project Manager (dIPM), reducing IPM leadership changes, and providing other project support. Next steps include continued data collection and analysis, and mapping to technical complexity data.

NICS implementation↗
DOE OSTI2020

Simultaneous 10 kHz three-dimensional CH 2 O and tomographic PIV measurements in a lifted partially-premixed jet flame

High-speed, three-dimensional (3D) scalar-velocity field measurements are demonstrated in a lifted partially-premixed dimethyl-ether/air jet flame using simultaneous laser-induced fluorescence (LIF) of formaldehyde (CH 2 O) and tomographic particle image velocimetry (TPIV). The 3D LIF measurements are performed by raster scanning the laser beam from a 100 kHz pulse-burst laser across the probe volume using an acousto-optic deflector. The volumetric reconstruction of the LIF signal from ten parallel planes provides quasi-instantaneous 3D LIF measurements that are synchronized with 10 kHz TPIV measurements. Here, the temporally resolved CH 2 O-LIF and velocity field data are used to analyze Lagrangian particle trajectories and displacement speeds at the base of the lifted flame. The particle trajectories reveal flow structures that are difficult to observe in an Eulerian reference frame. Positive and negative displacement speeds are observed at the CH 2 O-LIF surfaces at the inner and outer regions of the jet flame with a maximum displacement speed of approximately eight times the laminar flame speed of a stoichiometric dimethyl-ether/air mixture. The observations in present study support formation of lean premixed flames near the flame base whose role in flame stabilization should be investigated in more detail.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Transferring predictions of formation energy across lattices of increasing size*

In this study, we show the transferability of graph convolutional neural network (GCNN) predictions of the formation energy of the nickel-platinum solid solution alloy across atomic structures of increasing sizes. The original dataset was generated with the large-scale atomic/molecular massively parallel simulator using the second nearest-neighbor modified embedded-atom method empirical interatomic potential. Geometry optimization was performed on the initially randomly generated face centered cubic crystal structures and the formation energy has been calculated at each step of the geometry optimization, with configurations spanning the whole compositional range. Using data from various steps of the geometry optimization, we first trained our open-source, scalable implementation of GCNN called HydraGNN on a lattice of 256 atoms, which accounts well for the short-range interactions. Using this data, we predicted the formation energy for lattices of 864 atoms and 2048 atoms, which resulted in lower-than-expected accuracy due to the long-range interactions present in these larger lattices. We accounted for the long-range interactions by including a small amount of training data representative for those two larger sizes, whereupon the predictions of HydraGNN scaled linearly with the size of the lattice. Therefore, our strategy ensured scalability while reducing significantly the computational cost of training on larger lattice sizes.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Scalable Computation of Topological Abstractions for Scalar Data

Topological data analysis has become an important tool for large scale scalar data analysis and visualization, efficiently extracting the inherent structure and features of interest of the data. However, with growing dataset sizes and complexity, it is increasingly becoming infeasible to compute topological abstractions of interest in serial and on single machines. This paper presents the state of the art in the scalable computation of topological abstractions on scalar data, in shared memory parallel on single machines, and in distributed memory parallel on multiple machines. We highlight results for set‐based, graph‐based and complex‐based abstractions and organize the state of the art based on this taxonomy. The paper identifies parallelization and distribution techniques common in topological algorithms and highlights further areas of interest with underdeveloped efforts.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2019

Analysis Ready Data in Analytics Optimized Data Stores for Analysis of Big Earth Data in the Cloud

Cloud computing offers the possibility of making the analysis of Big Data approachable for a wider community due to affordable access to computing power, an ecosystem of usable tools for parallel processing, and migration of many large datasets to archives in the cloud, allowing data-proximal computing. Generally, data analysis acceleration in the cloud comes from running multiple nodes in a split-combine-apply strategy. Data systems such as the Earth Observing System Data and Information System are in a position to "pre-split" the data by storing them in a data store that is optimized for data parallel computing, i.e., an Analytics-Optimized Data Store (AODS). A variety of approaches to AODS are possible, from highly scalable databases to scalable filesystems to data formats optimized for cloud access (e.g., zarr and cloud-optimized datasets), with the optimal choice dependent on both the types of analysis and the geospatial structure of the data. A key question is how much preprocessing of the data to do, both before splitting and as the first part of the apply step. Again, the geospatial structure of the data and the analysis type influence the decision, with the added complexity of the user type. Trans-disciplinary users who are not well-versed in the nuances of quality-filtering and georeferencing of remote sensing orbit/swath/scene data tend to ask for more highly processed data, relying on the data provider to make sensible decisions on preprocessing parameters. (This accounts for the popularity of "Level 3" gridded data, despite the lower spatial resolution it provides.) In this case, data can be preprocessed before the split, resulting in higher performance in the rest of the "apply" step, which can be transformative for use cases such as interactive data exploration at scale. Discipline researchers who are experienced with remote sensing data often prefer more flexibility in customizing the preprocessing data into Analysis Ready Data, resulting in more need for on-the-fly preprocessing.

Lynnes, Christopher↗
DOE OSTI2024

Investigation of Benchmark $k$ eff Sensitivity and Uncertainty for 239 Pu fission in Specific Energy Ranges

Nuclear data at intermediate energies (from 1 to 100s of keV) are evaluated based on scarce differential data and theory unable to capture physics’ expected structure. There is also a lack of integral data. This is a known deficiency and is challenging to address. Calculated effective multiplication factor, k eff , values for intermediate energy experiments are ~25× further from experiment than for fast energies and are often well outside the experimental uncertainties. The goal of the PARADIGM (PARallel Approach of Differential and InteGral Measurements) project is to significantly re duce the uncertainties of intermediate energy nuclear data for 239 Pu. To this end, PARADIGM simultaneously optimizes experiments at both the Los Alamos Neutron Science Center (LANSCE) and National Criticality Experiments Research Center (NCERC). The combined set of data will inform new intermediate-energy nuclear data. By execution of differential and integral experiments, establishment of new theory, and undertaking nuclear data evaluation in parallel, the timeline to deliver improved nuclear data to users will be reduced significantly that is to three years. For the PARADIGM project, it was decided to optimize an integral experiment for two neutron energy ranges, within the full intermediate energy range. The low energy range goes from 1 to 30 keV, while the higher energy range goes from 30 to 600 keV. This work focuses on nuclear data sensitivities and uncertainties for 239 Pu fission for existing experiments in the International Criticality Safety Benchmark Evaluation Project (ICSBEP). When designing new experiments, it is important to understand what benchmarks currently exist. For a more traditional experiment design (in which a specific application model(s) exists), comparisons would be made between the application model(s) and existing benchmarks. For PARADIGM, there is no specific application model, but instead the specific nuclear data reaction and energy ranges of interest can be explored for existing benchmarks.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1993

Chocolate tablet aspects of cytherean Meshkenet Tessera

Meshkenet Tessera structures were mapped from Magellan data and several resemblances to chocolate tablet boudinage were found. The complex fault sets display polyphase tectonic sequences of a few main deformation phases. Shear and tension have contributed to the areal deformation. Main faults cut the 1600-km long Meshkenet Tessera highland into bar-like blocks which have ridge and groove pattern oriented along or at high angles to the faults. The first approach to the surface block deformation is an assumption of initial parallel shear faulting followed by a chocolate tablet boudinage. Major faults which cut Meshkenet Tessera into rectangular blocks have been active repetitively while two progressive or superposed boudinage set formations have taken place at high angles during the relaxational or flattening type deformation of the area. Chocolate tablet boudinage is caused by a layer-parallel two-dimensional extension resulting in fracturing of the competent layer. Such structures, defined by two sets of boudin neck lines at right angles to each other, have been described by a number of authors. They develop in a flattening type of bulk deformation or during superposed deformation where the rock is elongated in two dimensions parallel to the surface. This is an attempt to describe and understand the formation and development of structures of Meshkenet Tessera which has complicated fault structures.

Raitala, J.↗