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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 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Invertible Temper Modeling using Normalizing Flows and the Effects of Structure Preserving Loss

Advanced manufacturing research and development is typically small-scale, owing to costly experiments associated with these novel processes. Deep learning techniques could help accelerate this development cycle but frequently struggle in small-data regimes like the advanced manufacturing space. While prior work has applied deep learning to modeling visually plausible advanced manufacturing microstructures, little work has been done on data-driven modeling of how microstructures are affected by heat treatment, or assessing the degree to which synthetic microstructures are able to support existing workflows. We propose to address this gap by using invertible neural networks (normalizing flows) to model the effects of heat treatment, e.g., tempering. The model is developed using scanning electron microscope imagery from samples produced using shear-assisted processing and extrusion (ShAPE) manufacturing. This approach not only produces visually and topologically plausible samples, but also captures information related to a sample’s material properties or experimental process parameters. We also demonstrate that topological data analysis, used in prior work to characterize microstructures, can also be used to stabilize model training, preserve structure, and improve downstream results. We assess directions for future work and identify our approach as an important step towards end-to-end deep learning system for accelerating advanced manufacturing research and development.

Howland, Sylvia↗
DOE OSTI2021

A temperature profile diagnostic for radiation waves on OMEGA-60

Predicting and matching radiation wave propagation with computational models has proven difficult. Information provided by experiments studying radiation flow has been limited when only radiation breakout is measured. We have developed the COAX (co-axial) diagnostic platform to provide spatial temperature profiles of a radiation wave through low density foams as a more detailed constraint for simulations. COAX uses a standard, laser-driven OMEGA-60 halfraum to drive radiation down a titanium-laden silicon oxide foam. Point-projection X-ray absorption spectroscopy perpendicular to the radiation flow measures the spatial profile of titanium ionization. The spectroscopic measurement utilizes a broadband capsule backlighter. Imaging and streak spectroscopy are used to characterize the size and spectrum of this source. Radiography provides an additional constraint by capturing the developing shock as the radiation flow becomes subsonic. The DANTE diagnostic is used to measure the halfraum temperature. Here, we provide a spectroscopic analysis of COAX data to determine temperature, and we describe experimental sources of uncertainty. The temperature is obtained by comparison to multi-temperature synthetic spectra post-processed from radiation-hydrodynamics simulations. Quantitative comparison between data and synthetic spectra generated from temperature profiles at relevant simulation times enable determination of a peak temperature of 114 ± 8 eV at 265 ± 22.4 μm from the halfraum. This represents an improvement over the temperature uncertainties of previous radiation flow experiments. Further refinements to the spectroscopic analysis could achieve ±4 eV. The combination between space-resolved spectroscopy and radiography enables us to determine the distance from the halfraum of both the radiation front and the shock front at the time of measurement. For the example shown in this paper the radiation front position is 600–630 μm at 3.43 ± 0.16 ns and the shock front position is 633 μm at 3.3 ± 0.24 ns.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Fluorescence Correlation Spectroscopy with Photobleaching Correction in Slowly Diffusing Systems

Fluorescence correlation spectroscopy (FCS) is a powerful tool to quantitatively study the diffusion of fluorescently labeled molecules. It allows in principle important questions of macromolecular transport and supramolecular aggregation in living cells to be addressed. However, the crowded environment inside the cells slows diffusion and limits the reservoir of labeled molecules, causing artifacts that arise especially from photobleaching and limit the utility of FCS in these applications. We present a method to compute the time correlation function from weighted photon arrival times, which compensates computationally during the data analysis for the effect of photobleaching. We demonstrate the performance of this method using numerical simulations and experimental data from model solutions. Using this technique, we obtain correlation functions in which the effect of photobleaching has been removed and in turn recover quantitatively accurate mean-square displacements of the fluorophores, especially when deviations from an ideal Gaussian excitation volume are accounted for by using a reference calibration correlation function. This allows quantitative FCS studies of transport processes in challenging environments with substantial photobleaching like in living cells in the future.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Holistic Measurement Driven Resilience: Combining Operational Fault and Failure Measurements and Fault Injection for Quantifying Fault Detection, Propagation and Impact. Final report

For HPC systems to date, application resilience to faults and failures has been accomplished by the brute- force method of checkpoint/restart, which allows an application to make forward progress in the face of system and application faults, errors, and failures independent of root cause or end result. It has remained the primary resilience mechanism because we lack a way to identify faults and anticipate consequences early enough to take meaningful mitigating action. However, checkpoint/restart implementations put a tremendous burden on system resources and on the applications themselves and is becoming less feasible at scale. Because we have not yet operated at scales at which checkpoint/restart fails to provide forward progress, despite increasing costs, vendors have had little motivation to provide the instrumentation necessary for early identification of faults and failures. However, as we move from petascale to exascale, component mean time to failure (MTTF) will render the existing techniques ineffectual and/or too expensive. Furthermore, fault recovery mechanisms such as failover and/or error correction introduce performance inconsistency. Instrumentation allowing early indication of problems and tools to enable use of such information by systems, operating systems, and applications offer an alternative, more scalable and less costly solution. In the HMDR project, we built on our experience and expertise developed and accumulated over years of research on design, monitoring, measurement, and assessment of resilient computing systems. Analysis of field data on the current and past generations of extreme-scale systems revealed several challenges that, if not addressed in increasingly larger and more complex systems, may hinder the effectiveness of future exascale computing systems. Specifically, i) file systems and interconnects in current-generation large-scale systems already operate at the margins of resiliency, including consistent performance, and may not scale to larger deployments; ii) automated, software-based failover mechanisms are frequently inadequate and can introduce wider failures, such that failures during recovery may lead to system/application failures, including system-wide outages; and iii) silent data corruption represents a critical fault mode and will require efficient detection mechanisms if next-generation applications are to take full advantage of exascale hardware. To address the above challenges, we assembled a team of world-renowned experts in resilient extreme- scale computing from the University of Illinois (Electrical and Computer Engineering, Computer Science, and NCSA), SNL, LANL, NERSC, and Cray. Our team includes representatives from centers that house many of the largest HPC resources in the world, both today and over the coming years. The team has a unique track record of research in i) system and application failure characterization based on the analysis of field data, ii) data-driven design of fault/error detection mechanisms, and iii) experimental characterization of system/application resiliency. The team includes system owners/operators who provide continuous data collection and access and ensure installation of appropriate analysis tools.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Detector Instrumentation, Energy Reconstruction and Data Analysis in the DUNE and NOvA Neutrino Experiments

Neutrino oscillations are so far the only experimental observation beyond the standard model since its development four decades ago. The remaining fundamental questions that can be answered by long-baseline neutrino oscillations are (1) the CP violation (whether neutrinos and antineutrinos behave the same way in oscillation), and (2) the mass hierarchy ($m_3>m_{1,2}$ or $m_{1,2}>m_3$), and (3) the octant of $\theta_{23}$ ($\theta_{23}>45^\circ, =45^\circ$ or $<45^\circ$). The PI's group at UCI focuses on long-baseline neutrino experiments DUNE and NOvA, key components of DOE's Intensity Frontier program. NOvA is the current major U.S.-based long-baseline neutrino experiment aiming to solve the mass hierarchy and $\theta_{23}$ octant. It is taking $\nu$ and $\bar{\nu}$ data from the NuMI beam at Fermilab. DUNE is the next-generation flagship neutrino experiment in the U.S. which is designed to decisively determine neutrino CP violation, mass hierarchy and $\theta_{23}$ octant. DUNE is Fermilab's first priority, and has been established as an international collaboration. During the period covered by the report, the PI's group has been exceptionally productive, with leading contributions to DUNE argon-purity monitoring detectors, NOvA/DUNE deep-learning reconstruction, and NOvA oscillation and near detector (ND) analyses. The group also is actively involved in DUNE/NOvA detector operation, data production, calibration, software upgrade and maintenance, and ProtoDUNE cold electronic QA/QC. Specifically, we have made accomplishments in the following four research projects: 1) Purity monitor R\&D and data analysis for DUNE, 2) Deep-learning-based energy reconstruction at NOvA and DUNE, 3) Oscillation analysis at NOvA, and 4) $\nu$-e elastic scattering analysis at NOvA.

47 OTHER INSTRUMENTATION↗
NASA NTRS1992

Theoretical and experimental study of a fiber optic microphone

Modifications to condenser microphone theory yield new expressions for the membrane deflections at its center, which provide the basic theory for the fiber optic microphone. The theoretical analysis for the membrane amplitude and the phase response of the fiber optic microphone is given in detail in terms of its basic geometrical quantities. A relevant extension to the original concepts of the optical microphone includes the addition of a backplate with holes similar in design to present condenser microphone technology. This approach generates improved damping characteristics and extended frequency response that were not previously considered. The construction and testing of the improved optical fiber microphone provide experimental data that are in good agreement with the theoretical analysis.

Hu, Andong↗
NASA NTRS1994

Computational Analysis of Forebody Tangential Slot Blowing on the F/A-18

An overview of the computational effort to analyze forebody tangential slot blowing for use on the F/A-18 aircraft is presented. Tangential slot blowing generates side force and yawing moment which may be used to control the aircraft flying at high angle of attack. Computations using the isolated forebody are obtained at full-scale wind tunnel test conditions for direct comparison with available experimental data. The effects of jet exit conditions, jet length, and jet location are also studied using the isolated forebody. In addition, these computations are used to predict the effect of slot blowing at transonic maneuvering flight conditions. The effects of over- and under-blowing on force and moment production are analyzed. Non-time-accurate solutions are obtained to determine the steady-state side force and yawing moments generated by tangential slot blowing. Time-accurate solutions are obtained to study the force onset time lag of tangential slot blowing. The effect of blowing on the burst point location are then analyzed by obtaining computations using the aircraft geometry, which includes the wing, empennage, and faired-over inlets. The effect of blowing on the buffet loads on the vertical tails are analyzed using time-accurate computations. Comparison with available experimental data from full-scale wind tunnel and sub-scale wind tunnel tests are made. This computational analysis compliments the experimental results and provides a detailed understanding of the effects of tangential slot blowing on the flow field about the F/A-18.

Gee, Ken↗
NASA NTRS1972

Neutron die-away experiment for remote analysis of the surface of the moon and the planets, phase 3

Continuing work on the two die-away measurements proposed to be made in the combined pulsed neutron experiment (CPNE) for analysis of lunar and planetary surfaces is described. This report documents research done during Phase 3. A general exposition of data analysis by the least-squares method and the related problem of the prediction of variance is given. A data analysis procedure for epithermal die-away data has been formulated. In order to facilitate the analysis, the number of independent material variables has been reduced to two: the hydrogen density and an effective oxygen density, the latter being determined uniquely from the nonhydrogeneous elemental composition. Justification for this reduction in the number of variables is based on a set of 27 new theoretical calculations. Work is described related to experimental calibration of the epithermal die-away measurement. An interim data analysis technique based solely on theoretical calculations seems to be adequate and will be used for future CPNE field tests.

Mills, W. R.↗
NASA NTRS2007

Virtual Diagnostics Interface: Real Time Comparison of Experimental Data and CFD Predictions for a NASA Ares I-Like Vehicle

Virtual Diagnostics Interface technology, or ViDI, is a suite of techniques utilizing image processing, data handling and three-dimensional computer graphics. These techniques aid in the design, implementation, and analysis of complex aerospace experiments. LiveView3D is a software application component of ViDI used to display experimental wind tunnel data in real-time within an interactive, three-dimensional virtual environment. The LiveView3D software application was under development at NASA Langley Research Center (LaRC) for nearly three years. LiveView3D recently was upgraded to perform real-time (as well as post-test) comparisons of experimental data with pre-computed Computational Fluid Dynamics (CFD) predictions. This capability was utilized to compare experimental measurements with CFD predictions of the surface pressure distribution of the NASA Ares I Crew Launch Vehicle (CLV) - like vehicle when tested in the NASA LaRC Unitary Plan Wind Tunnel (UPWT) in December 2006 - January 2007 timeframe. The wind tunnel tests were conducted to develop a database of experimentally-measured aerodynamic performance of the CLV-like configuration for validation of CFD predictive codes.

Schwartz, Richard J.↗
NASA NTRS2007

Virtual Diagnostics Interface: Real Time Comparison of Experimental Data and CFD Predictions for a NASA Ares I-Like Vehicle

Virtual Diagnostics Interface technology, or ViDI, is a suite of techniques utilizing image processing, data handling and three-dimensional computer graphics. These techniques aid in the design, implementation, and analysis of complex aerospace experiments. LiveView3D is a software application component of ViDI used to display experimental wind tunnel data in real-time within an interactive, three-dimensional virtual environment. The LiveView3D software application was under development at NASA Langley Research Center (LaRC) for nearly three years. LiveView3D recently was upgraded to perform real-time (as well as post-test) comparisons of experimental data with pre-computed Computational Fluid Dynamics (CFD) predictions. This capability was utilized to compare experimental measurements with CFD predictions of the surface pressure distribution of the NASA Ares I Crew Launch Vehicle (CLV) - like vehicle when tested in the NASA LaRC Unitary Plan Wind Tunnel (UPWT) in December 2006 - January 2007 timeframe. The wind tunnel tests were conducted to develop a database of experimentally-measured aerodynamic performance of the CLV-like configuration for validation of CFD predictive codes.

Schwartz, Richard J.↗
DOE OSTI2023

Experimental Observations of the Topology of Convolutional Neural Network Activations

Topological data analysis (TDA) is a branch of computational mathematics, bridging algebraic topology and data science, that provides compact, noise-robust representations of complex structures. Deep neural networks (DNNs) learn millions of parameters associated with a series of transformations defined by the model architecture resulting in high-dimensional, difficult to interpret internal representations of input data. As DNNs become more ubiquitous across multiple sectors of our society, there is increasing recognition that mathematical methods are needed to aid analysts, researchers, and practitioners in understanding and interpreting how these models' internal representations relate to the final classification. In this paper we apply cutting edge techniques from TDA with the goal of gaining insight towards interpretability of convolutional neural networks used for image classification. We use two common TDA approaches to explore several methods for modeling hidden layer activations as high-dimensional point clouds, and provide experimental evidence that these point clouds capture valuable structural information about the model's process. First, we demonstrate that a distance metric based on persistent homology can be used to quantify meaningful differences between layers and discuss these distances in the broader context of existing representational similarity metrics for neural network interpretability. Second, we show that a mapper graph can provide semantic insight as to how these models organize hierarchical class knowledge at each layer. These observations demonstrate that TDA is a useful tool to help deep learning practitioners unlock the hidden structures of their models.

topological data analysis, deep learning↗
NASA NTRS1983

Application of a full potential method for predicting supersonic flow fields and aerodynamic characteristics

A nonlinear aerodynamic prediction technique which solves the conservative full potential equation has been applied to the analysis of three waverider configurations. This technique was selected based on its capability to analyze the off-design characteristics of the waveriders. Very good correlations were achieved with surface pressure data for both the Mach 4 elliptic cone waverider and the Mach 6 caret-wing derivative. Off-design Mach number and angle-of-attack pressure correlations were very good for the elliptic cone waverider. The range of correlation with data exceeded that expected based on the theory limitations. A surface pressure integration routine was demonstrated and agreement between predicted aerodynamic forces and experimental force data for the Mach 4 waverider was excellent. Analysis of a nonconical waverider configuration was initiated where a discrete input option is used to achieve the computational gridding. Preliminary analysis of this configuration indicates the correct shock location will be predicted.

Jones, K. M.↗
NASA NTRS1998

Buckling and Damage Resistance of Transversely-Loaded Composite Shells

Experimental and numerical work was conducted to better understand composite shell response to transverse loadings which simulate damage-causing impact events. The quasi-static, centered, transverse loading response of laminated graphite/epoxy shells in a [+/-45(sub n)/O(sub n)](sub s) layup having geometric characteristics of a commercial fuselage are studied. The singly-curved composite shell structures are hinged along the straight circumferential edges and are either free or simply supported along the curved axial edges. Key components of the shell response are response instabilities due to limit-point and/or bifurcation buckling. Experimentally, deflection-controlled shell response is characterized via load-deflection data, deformation-shape evolutions, and the resulting damage state. Finite element models are used to study the kinematically nonlinear shell response, including bifurcation, limit-points, and postbuckling. A novel technique is developed for evaluating bifurcation from nonlinear prebuckling states utilizing asymmetric spatial discretization to introduce numerical perturbations. Advantages of the asymmetric meshing technique (AMT) over traditional techniques include efficiency, robustness, ease of application, and solution of the actual (not modified) problems. The AMT is validated by comparison to traditional numerical analysis of a benchmark problem and verified by comparison to experimental data. Applying the technique, bifurcation in a benchmark shell-buckling problem is correctly identified. Excellent agreement between the numerical and experimental results are obtained for a number of composite shells although predictive capability decreases for stiffer (thicker) specimens which is attributed to compliance of the test fixture. Restraining the axial edge (simple support) has the effect of creating a more complex response which involves unstable bifurcation, limit-point buckling, and dynamic collapse. Such shells were noted to bifurcate into asymmetric deformation modes but were undamaged during testing. Shells in this study which were damaged were not observed to bifurcate. Thus, a direct link between bifurcation and atypical damage could not be established although the mechanism (bifurcation) was identified. Recommendations for further work in these related areas are provided and include extensions of the AMT to other shell geometries and structural problems.

Wardle, Brian L.↗
NASA NTRS2023

A Guide to Forced Oscillation Data Processing and Analysis

The NASA Langley Research Center Flight Dynamics Branch has a long history of experimental testing of aircraft and spacecraft flight dynamics. One of the frequently used wind tunnel test methods is forced oscillation testing. This method involves a model mounted on a specialized dynamic test rig in a tunnel and oscillated about a body axis, typically at a fixed sinusoidal frequency and amplitude. This report provides the derivation of two commonly used data reduction methods and introduces one new method to extract the linear dynamic derivatives from forced oscillation wind tunnel data.

Flight Dynamics↗
DOE OSTI2025

Oklo Sponsored Testing using PELICAN: System, Subchannel, and High-Fidelity Software Validation (Final CRADA Report)

Argonne National Laboratory (the Contractor), located in Lemont IL, and Oklo, Inc., (the Participant), headquartered in Santa Clara, CA, propose to enter into a Cooperative Research and Development Agreement (CRADA) to perform a gap analysis of thermal hydraulic data, perform prototypical fuel assembly pressure drop and cavitation model validation, generate the experimental data as well as the corresponding uncertainties for this matrix and, finally, develop the validation models with the Argonne system level code SAS4A/SASSYS-1, the Argonne subchannel analysis code DASSH, the Argonne high fidelity code Nek5000, and/or the Idaho National Laboratory code Pronghorn Subchannel. The work outlined below will significantly improve the experimental and validation database currently available for liquid metal fast reactors, thus making it a viable part of a comprehensive reactor design and licensing suite to be used by the participant.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1984

Biogeochemical cycling and remote sensing

The present investigation is concerned with the role of remote sensing in the analysis of biochemical cycling. A general review is provided of the interest of NASA in biochemical cycling, taking into account an assessment of the state and dynamics of the pools and fluxes of four major elements (carbon, nitrogen, phosphorus, sulfur), an understanding of the coupling and interaction of the biosphere and the atmosphere, and an understanding of the biosphere and the oceans. Attention is given to biogeochemical cycling science issues, the potential remote sensing role, the vegetation type, aspects of vegetation structure, the leaf area index, the canopy height, functional relationships, environmental and soil variables, questions of experimental design, sampling sites and ground data, and radiometric data and analysis.

Peterson, D. L.↗
DOE OSTI2025

Discovering CO Adsorption and Desorption Pathways from Chemical Reaction Neural Network Modeling of Transient Kinetics Spectroscopy

Here, we demonstrate a data-driven approach to interpreting surface reactions by combining time-resolved gas pulsing infrared spectroscopy with chemical reaction neural networks (CRNNs). Using CO adsorption and desorption on Pd(111) at 460–490 K as a model system, we show how transient kinetic data can reveal detailed reaction mechanisms. Starting with a simple one-species model, we systematically evaluate increasingly complex mechanisms involving hollow and bridge site adsorption. Despite the similar goodness of fit to the same experimental absorbance data, our models predict distinct coverage dynamics for different adsorption sites. Through analysis of spectral peak stability and predicted dynamics, we identify a mechanism in which CO primarily adsorbs on bridge sites followed by rapid conversion to hollow sites as being the most physically consistent with experimental observations. This work provides a framework for extracting mechanistic insights from limited experimental data, demonstrating how machine learning can bridge the gap between transient kinetic measurements and a molecular-level understanding of surface reactions.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Lead tungstate calorimeters at Jefferson Lab and perspectives for the Electron–Ion Collider

Electromagnetic calorimeters based on PbWO4 scintillating crystals have a widespread applica- tion in experiments at different accelerator facilities such as CERN, FNAL, GSI, and Jefferson Lab. The unique properties of PbWO4 crystals, including a small radiation length and Molire radius, make them ideal for building high-granularity, radiation-hard detectors. This enables excellent spa- tial separation and energy resolution of reconstructed electromagnetic showers, making PbWO4 crystals the material of choice for numerous experiments. Lead tungstate calorimeters have been successfully used in several experiments at Jefferson Lab. Two large-scale detectors have been re- cently fabricated for future experiments : the Neutral Particle Spectrometer and the lead tungstate calorimeter of the GlueX detector. The future application of PbWO4 crystals in the ElectronIon Collider further highlights their ongoing importance in advancing experimental capabilities. In planning new experiments, the development of calorimeter instrumentation technologies becomes paramount. The integration of modern photodetectors, such as Silicon photomultipliers that are capable of operating in strong magnetic fields, and the implementation of streaming readout data acquisition systems, sophisticated shower reconstruction algorithms, and real-time data analysis are some examples of the continuously growing requirements of experimental setups. I will give an overview of the lead tungstate scintillating calorimeters and discuss some recent advancement in the calorimeter instrumentation.

Somov, Alexander↗