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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 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

STOP Analysis and Optimization of a Very-Low-Distortion Space Instrument: HST WFC3 Case Study

New generation optical instruments with very demanding stability requirements are being proposed and developed for space applications. STOP (Structural-Thermal-Optical Performance) analysis and optimization is crucial in meeting the very tight distortion budgets of these instruments. This presentation outlines STOP analysis and optimization approach in the context of WFC3 (Wide-Field Camera 3), which is a radial instrument designed to replace the Wide-Field Planetary Camera 2 (WFPC2) of the Hubble Space Telescope (HST). WFC3 houses two separate channels, UVIS and IR, and will have greater throughput and sensitivity than WFPC2. WFC3 line-of-sight alignment budget for the UVIS and IR channels are as small as 10 and 20 milli-arcsec, respectively. Its optical bench is the most critical subsystem effecting the optical stability of WFC3 hence our effort concentrates on the design and analysis of the bench and its interfaces. Structural analysis has accompanied the mechanical design of the bench since the initial concept study. A high fidelity structural Finite Element Model (FEM) of the bench has been developed and used for minimizing its thermally induced distortions as well as sizing it to meet the stiffness and strength requirements of a Shuttle launch. The bench is a composite honeycomb panel box structure with a very low planar Coefficient of Thermal Expansion (CTE) of approximately 0.1 ppm/C. Optic components are mounted to super-INVAR inserts bonded into the panels. The bench is kinematically supported on three HST latches via interface struts, which are tailored to exhibit negative CTE to cancel out the thermal motions of the latches. The interface struts also incorporate flexure elements to minimize the mechanical distortions coming into the bench from its enclosure. Bench FEM is coupled with the enclosure FEM to quantify these effects. Short term or on-orbit STOP analysis includes distortion due to the temperature variations of the bench, the struts, and the enclosure. Long term or ground-to-orbit STOP analysis includes distortional effects of gravity release, desorption, and assembly in addition to the ground-to-orbit temperature variations. A rigorous testing program has been implemented for verifying the material properties and the analysis predictions. STOP analysis results demonstrate that both the short-term and the long-term alignment budgets will be met. Presentation will cover design and analysis details that are critical to a successful implementation of the STOP analysis and optimization process.

Kunt, Cengiz↗
NASA NTRS2002

Efficient sensor/model based on-line collision detection for planetary manipulators

We present an algorithm that uses the Oriented Bounding Box (OBB) and a new primitive called the Oriented Bounding Prism (OBP) to detect potential self-collisions and collisions with terrain object sensed with the rover's on-board stereo camera; the algorithm thus has both model-based and sensor-based components.

rovers manipulation collision detection FIDO↗
DOE OSTI2018

Life-cycle analysis of integrated biorefineries with co-production of biofuels and bio-based chemicals: co-product handling methods and implications: Co-product handling methods and implications of life-cycle analysis of biofuel and bio-chemical co-producing biorefineries

New integrated biorefinery (IBR) concepts are being investigated to co-produce hydrocarbon fuels and high-value bio-based chemicals to improve the economic viability of IBRs, to enhance biomass resource utilization efficiencies, and to maximize potential greenhouse gas (GHG) emission reductions. Unlike fuel-only biorefineries, IBRs may co-produce a significant amount of bio-based chemicals, whose emission implications for specific biorefinery products and the biorefinery as a whole need to be evaluated. We discuss this in principle and apply three sets of co-product handling methods to conduct life-cycle analysis (LCA) of modeled IBRs with co-production of two bioproduct examples - succinic acid and adipic acid - alongside a renewable diesel blendstock fuel product. The LCA results for the specific co-product handling methods that were examined shed light on potential artifacts of product-specific LCA with selected co-product methods. We discuss the advantages and limitations of each method and conclude that (i) a system-level or 'black-box' LCA allocation method is too simplistic to reflect appropriately the GHG burdens of distinctly different processing trains for fuels and chemicals in the IBR context, and (ii) the displacement method is the only co-product handling method that accounts fully for the emission effects of both the fuel product and the non-fuel bio-based co-products in the IBRs within the context of the existing fuel-focused GHG regulatory framework. Alternatively, biorefinery system-level LCA combines benefits of individual products to offer a complete picture. This system-level LCA approach offers a holistic LCA without somewhat arbitrary decisions either on an allocation basis or by the selection of an evaluation metric based on specific products.

09 BIOMASS FUELS↗
DOE OSTI2024

Differentiable Multiphysics Codes: A Breakthrough Technology for Simulation and Computing

This document summarizes the findings of a strategic planning exercise commissioned by the Weapons Simulation and Computing, Computational Physics (WSC/CP) program at the Lawrence Livermore National Laboratory (LLNL) in FY24. During the year, the committee met with multiple stakeholder communities to gather input, opinions, suggestions and concerns which have been incorporated throughout this document. The key findings from this exercise are summarized: • The development of multiphysics modelling and simulation (mod/sim) codes and software technologies, their deployment on exascale compute platforms, and their broad adoption across the NNSA is a major success of the Advanced Simulation and Computing (ASC) program and the Exascale Computing Project (ECP). Sustained investment in these core technologies is essential. • Today’s state of the art involves running ensembles of O(100K) simulations to perform uncertainty quantification (UQ) and design studies using multiple statistical methods such as Bayesian optimization to understand sensitivities of our models and explore parameterized design spaces. Even with exascale computing, we are practically limited to O(10) parameters in these studies since the number of simulations required to sample the space scales exponentially with the number of design parameters. • The data from these simulation ensembles is increasingly being used to train machine learned (ML) surrogates (or reduced order models, ROMs) which can then be used for optimization or real time design exploration. However, the trained surrogates are still limited in the number of parameters they can represent due to the sampling limitations previously noted. • Augmenting our suite of integrated multiphysics simulation codes, both current and emerging, with the ability to compute gradients (solution derivatives) of arbitrary simulation outputs with respect to (some or all) simulation inputs would be a breakthrough technology, opening the door to a new era of efficient and automated inverse design based on verified and validated mod/sim capabilities. • This capability, which we refer to as differentiable multiphysics codes (DMCs), would revolutionize both UQ and optimization studies by breaking the curse of dimensionality that presently limits our “gradient-free” ensemble based computing approach. A similar breakthrough occurred in the AI/ML community once the ability to compute gradients of arbitrary loss functions using back-propagation became commonplace. Gradient information from the multiphysics codes can also be used to dramatically improve the efficiency and scale of training of ML/ROM surrogates for rapid assessments. • Achieving this in our suite of codes will be a grand challenge, similar to the amount of effort that was required to transition from CPU to GPU computing. It will require buy-in from the entire WSC/CP program and beyond, including all integrated codes, physics and engineering models, third-party library dependencies and performance portability abstractions. It will also require investment in research and development of numerical methods for computing adjoints of coupled physics across multiple adaptively refined moving meshes and of stochastic (Monte Carlo) and mesh free (SPH) methods. • New software and numerical techniques, largely pioneered by the AI/ML community, make this feasible. Chief among these is automatic differentiation (AD), the ability to employ AD at point-wise locations in a physics calculation (instead of traditional black-box approaches) and the ability to perform “back-propagation in time” (or reverse mode AD) for non-linear partial differential equations (PDEs). Fundamentally, the conclusion of this strategic planning exercise is that the time is right to undertake a large scale effort in WSC, centered on the existing integrated codes, to continue the natural evolution of mod/sim in the age of AI/ML. Instead of attempting to replace mod/sim with purely data driven AI/ML models, we believe the key to success is to integrate AI/ML by building on top of the decades of hard-won knowledge and the verified/validated multiphysics modelling capability that is the hallmark of the ASC program.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Barrier protective effects of withaferin A in HMGB1-induced inflammatory responses in both cellular and animal models

Withaferin A (WFA), an active compound from Withania somnifera, is widely researched for its anti-inflammatory, cardioactive and central nervous system effects. In this study, we first investigated the possible barrier protective effects of WFA against pro-inflammatory responses in human umbilical vein endothelial cells (HUVECs) and in mice induced by high mobility group box 1 protein (HMGB1) and the associated signaling pathways. The barrier protective activities of WFA were determined by measuring permeability, leukocytes adhesion and migration, and activation of pro-inflammatory proteins in HMGB1-activated HUVECs. We found that WFA inhibited lipopolysaccharide (LPS)-induced HMGB1 release and HMGB1-mediated barrier disruption, expression of cell adhesion molecules (CAMs) and adhesion/transendothelial migration of leukocytes to human endothelial cells. WFA also suppressed acetic acid-induced hyperpermeability and carboxymethylcellulose-induced leukocytes migration in vivo. Further studies revealed that WFA suppressed the production of interleukin 6, tumor necrosis factor-α (TNF-α) and activation of nuclear factor-κB (NF-κB) by HMGB1. Collectively, these results suggest that WFA protects vascular barrier integrity by inhibiting hyperpermeability, expression of CAMs, adhesion and migration of leukocytes, thereby endorsing its usefulness as a therapy for vascular inflammatory diseases. -- Highlights: ► Withaferin A inhibited LPS induced HMGB1 release. ► Withaferin A reduced HMGB1-mediated hyperpermeability. ► Withaferin A inhibited HMGB1-mediated adhesion and migration of leukocytes. ► Withaferin A inhibited HMGB1-mediated activation of NF-κB, IL-6 and TNF-α.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1977

Evaluation of subgrid-scale turbulence models using a fully simulated turbulent flow

An exact turbulent flow field was calculated on a three-dimensional grid with 64 points on a side. The flow simulates grid-generated turbulence from wind tunnel experiments. In this simulation, the grid spacing is small enough to include essentially all of the viscous energy dissipation, and the box is large enough to contain the largest eddy in the flow. The method is limited to low-turbulence Reynolds numbers, in our case R sub lambda = 36.6. To complete the calculation using a reasonable amount of computer time with reasonable accuracy, a third-order time-integration scheme was developed which runs at about the same speed as a simple first-order scheme. It obtains this accuracy by saving the velocity field and its first-time derivative at each time step. Fourth-order accurate space-differencing is used.

Clark, R. A.↗
DOE OSTI2023

Identifying common stored product insects using automated deep learning methods

Monitoring stored product insect pests is a common practice for post-harvest management of stored grain and grain-based commodities, which helps ensure product quality from harvest to final consumer. Current methods of sampling and monitoring can be time-consuming, labor-intensive, expensive and require expertise in insect identification. Therefore, this study aims to develop an image-based automated identification system for common stored product insect species using deep-learning methods. Top-down images of the common stored product adult insect species of Rhyzopertha dominica, Cryptolestes ferrugineus, Tribolium castaneum, Sitophilus oryzae, and Oryzaephilus surinamensis were acquired and analyzed. Deep learning-based, state-of-the-art Convolutional Neural Networks (CNN) models (ResNet-50, MobileNet-v2, DarkNet-53, and EfficientNet-b0) were fine-tuned with a transfer learning approach to classify the insect species. All models were able to correctly identify the insect species with at least 96% accuracy and with few misclassifications. One issue with trained CNNs is that they do not explain the reasoning for the classification and are often called a “black box”. Therefore, visualization methods called Gradient-weighted Class Activation Mapping (Grad-CAM) were implemented to explore the black box network. The Grad-CAM uses heat maps to highlight the major image features that the network focused on to make insect species predictions. The Grad-CAM verifies the network's prediction and also helps improve network performance. This study contributes to the overall goal of developing a camera-based system for monitoring stored grain insects. As a result, the developed system would empower warehouse, flour mills, and other food facilities with a tool to quickly and accurately identify insect species in stored product environments and could be implemented as part of a close to real-time monitoring system.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Explainable machine learning of the underlying physics of high-energy particle collisions

We present an implementation of an explainable and physics-aware machine learning model capable of inferring the underlying physics of high-energy particle collisions using the information encoded in the energy-momentum four-vectors of the final state particles. We demonstrate the proof-of-concept of our White Box AI approach using a Generative Adversarial Network (GAN) which learns from a DGLAP-based parton shower Monte Carlo event generator. The constrained generator network architecture mimics the structure of a parton shower exhibiting similarities with Recurrent Neural Networks (RNNs). We show, for the first time, that our approach leads to a network that is able to learn not only the final distribution of particles, but also the underlying parton branching mechanism, i.e. the Altarelli-Parisi splitting function, the ordering variable of the shower, and the scaling behavior. While the current work is focused on perturbative physics of the parton shower, we foresee a broad range of applications of our framework to areas that are currently difficult to address from first principles in QCD. Examples include nonperturbative and collective effects, factorization breaking and the modification of the parton shower in heavy-ion, and electron-nucleus collisions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

State-dependent motion of a genetically encoded fluorescent biosensor

Genetically encoded biosensors can measure biochemical properties such as small-molecule concentrations with single-cell resolution, even in vivo. Despite their utility, these sensors are “black boxes”: Very little is known about the structures of their low- and high-fluorescence states or what features are required to transition between them. We used LiLac, a lactate biosensor with a quantitative fluorescence-lifetime readout, as a model system to address these questions. X-ray crystal structures and engineered high-affinity metal bridges demonstrate that LiLac exhibits a large interdomain twist motion that pulls the fluorescent protein away from a “sealed,” high-lifetime state in the absence of lactate to a “cracked,” low-lifetime state in its presence. Understanding the structures and dynamics of LiLac will help to think about and engineer other fluorescent biosensors.

Rosen, Paul C. (ORCID:000000017414454X)↗
DOE OSTI2019

Reverse Monte Carlo modeling for low-dimensional systems

Reverse Monte Carlo (RMC) is one of the commonly used approaches for modeling total scattering data. However, to extend the capability of the RMC method for refining the structure of nanomaterials, the dimensionality and finite size need to be considered when calculating the pair distribution function (PDF). To achieve this, the simulation box must be set up to remove the periodic boundary condition in one, two or three of the dimensions. This then requires a correction to be applied for the difference in number density between the real system and the simulation box. In certain circumstances an analytical correction for the uncorrelated pairings of atoms is also applied. The validity and applicability of our methodology is demonstrated by applying the algorithms to simulate the PDF patterns of carbon systems with various dimensions, and also by using them to fit experimental data of CuO nanoparticles. This alternative approach for characterizing the local structure of nano-systems with the total scattering technique will be made available via the RMCProfile package. The theoretical formulation and detailed explanation of the analytical corrections for low-dimensional systems – 2D nanosheets, 1D nanowires and 0D nanoparticles – is also given.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Speeding up N -body simulations of modified gravity: chameleon screening models

We describe and demonstrate the potential of a new and very efficient method for simulating certain classes of modified gravity theories, such as the widely studied f ( R ) gravity models. High resolution simulations for such models are currently very slow due to the highly nonlinear partial differential equation that needs to be solved exactly to predict the modified gravitational force. This nonlinearity is partly inherent, but is also exacerbated by the specific numerical algorithm used, which employs a variable redefinition to prevent numerical instabilities. The standard Newton-Gauss-Seidel iterative method used to tackle this problem has a poor convergence rate. Our new method not only avoids this, but also allows the discretised equation to be written in a form that is analytically solvable. We show that this new method greatly improves the performance and efficiency of f ( R ) simulations. For example, a test simulation with 512{sup 3} particles in a box of size 512 Mpc/ h is now 5 times faster than before, while a Millennium-resolution simulation for f ( R ) gravity is estimated to be more than 20 times faster than with the old method. Our new implementation will be particularly useful for running very high resolution, large-sized simulations which, to date, are only possible for the standard model, and also makes it feasible to run large numbers of lower resolution simulations for covariance analyses. We hope that the method will bring us to a new era for precision cosmological tests of gravity.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Structural basis of TFIIIC-dependent RNA polymerase III transcription initiation

RNA polymerase III (Pol III) is responsible for transcribing 5S ribosomal RNA (5S rRNA), tRNAs, and other short non-coding RNAs. Its recruitment to the 5S rRNA promoter requires transcription factors TFIIIA, TFIIIC, and TFIIIB. Here, we use cryoelectron microscopy (cryo-EM) to visualize the S. cerevisiae complex of TFIIIA and TFIIIC bound to the promoter. Gene-specific factor TFIIIA interacts with DNA and acts as an adaptor for TFIIIC-promoter interactions. We also visualize DNA binding of TFIIIB subunits, Brf1 and TBP (TATA-box binding protein), which results in the full-length 5S rRNA gene wrapping around the complex. Our smFRET study reveals that the DNA within the complex undergoes both sharp bending and partial dissociation on a slow timescale, consistent with the model predicted from our cryo-EM results. Our findings provide new insights into the transcription initiation complex assembly on the 5S rRNA promoter and allow us to directly compare Pol III and Pol II transcription adaptations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

The role of correlation in the ground state energy of confined helium atom

We analyze the ground state energy of helium atom confined by spherical impenetrable walls, and the role of the correlation energy in the total energy. The confinement of an atom in a cavity is one way in which we can model the effect of the external pressure on an atom. The calculations of energy of the system are carried out by the variational method. We find that the correlation energy remains almost constant for a range values of size of the boxes analyzed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Spin Polarizations in a Covariant Angular-Momentum-Conserved Chiral Transport Model

Using a covariant and angular-momentum-conserved chiral transport model, which takes into account the spin-orbit interactions of chiral fermions in their scatterings via the side jumps, we study the quark spin polarization in quark matter. For a system of rotating and unpolarized massless quarks in an expanding box, we find that side jumps can dynamically polarize the quark spin and result in a final quark spin polarization consistent with that of thermally equilibrated massless quarks in a self-consistent vorticity field. Further, for the quark matter produced in noncentral relativistic heavy ion collisions, we find that in the medium rest frame both the quark local spin polarizations in the direction perpendicular to the reaction plane and along the longitudinal beam direction show an azimuthal angle dependence in the transverse plane similar to those observed in experiments for the Lambda hyperon.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Dust Polarization Maps from TIGRESS: E/B Power Asymmetry and TE Correlation

We present the first large set of all-sky synthetic dust polarization maps derived directly from a self-consistent magnetohydrodynamics simulation using the TIGRESS framework. Turbulence in this simulation is predominantly driven by supernova explosions, with rates that are self-consistently regulated by feedback loops. The simulation covers both the outer scale and inertial range of turbulence with uniformly high resolution. The shearing-box utilized in the simulation, in concert with resolved supernova-driven turbulence, enables the capturing of generation, growth, and saturation of both turbulent and mean magnetic fields. We construct polarization maps at 353 GHz, as seen by observers inside a model of the multiphase, turbulent, magnetized interstellar medium (ISM). To fully sample the simulated ISM state, we use 350 snapshots spanning over $\sim 350\,\mathrm{Myr}$ (more than six feedback loops) and nine representative observers. The synthetic skies show a prevalent E/B power asymmetry (${EE}\gt {BB}$) and positive TE correlation in broad agreement with observations by the Planck satellite. However, the ranges of ${EE}/{BB}\sim 1.4\mbox{-}1.7$ and ${TE}/{({TT}\cdot {EE})}^{1/2}\sim 0.2\mbox{-}0.3$ are generally lower than those measured by Planck. We find large fluctuations of E/B asymmetry and TE correlation depending on the observer's position and temporal fluctuations of ISM properties due to bursts of star formation. The synthetic maps are made publicly available to provide novel models of the microwave sky.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1985

Computational aspects of unsteady flows

The calculation of unsteady flows and the development of numerical methods for solving unsteady boundary layer equations and their application to the flows around important configurations such as oscillating airfoils are presented. A brief review of recent work is provided with emphasis on the need for numerical methods which can overcome possible problems associated with flow reversal and separation. The zig-zag and characteristic box schemes are described in this context, and when embodied in a method which permits interaction between solutions of inviscid and viscous equations, the characteristic box scheme is shown to avoid the singularity associated with boundary layer equations and prescribed pressure gradient. Calculations were performed for a cylinder started impulsively from rest and oscillating airfoils. The results are presented and discussed. It is conlcuded that turbulence models based on an algebraic specification of eddy viscosity can be adequate, that location of translation is important to the calculation of the location of flow separation and, therefore, to the overall lift of an oscillating airfoil.

Cebeci, T.↗
NASA NTRS1984

The spatial structure of terrain - A process signal in satellite digital images

Pattern recognition procedures applied to Landsat imagery carry an implicit assumption that the digital data are independently distributed. That assumption is incorrect over virtually any terrain. Deviations from independence occur because slopes follow a systematic pattern of variation arising from the slope-forming processes. That pattern can be identified using the stochastic process methodology of Box and Jenkins.Angles of adjacent slopes are autocorrelated and the bidirectional reflectance function transfers these systematic slope changes to the sensor. Imagery becomes autocorrelated through this transfer. Autocorrelation in the imagery can be removed through direct calculation from a digital elevation model or by use of stochastic process methodology. The latter has the advantage that the residuals are white noise; and it is applicable in any area, even where a D.E.M. is unavailable. The stochastic process signal can be used to study terrain processes.

Craig, R. G.↗
NASA NTRS1987

Gamma-ray burster counterparts - Infrared

The discovery of an IR counterpart to a gamma-ray burster (GRB) would be a big step forward in understanding this enigmatic phenomenon. A program of searching for IR emission from the smallest GRB source regions has been initiated. Seven boxes have been searched with ground-based telescopes at a wavelength of 2.2 microns and 23 with the IRAS data base at wavelengths of 12, 25, 60, and 100 microns. No convincing candidates were identified. The most constraining result are for two error boxes where the K-band magnitude are found to be fainter than 19.03. This observation is compared with the flux predicted from either a companion star or an accretion disk. The new IR observations pose serious difficulties for several GRB models.

Schaefer, Bradley E.↗