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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 1,765 records · Page 98
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Neutrino Interactions observed with Large Area Picosecond Photodetectors in ANNIE

The Accelerator Neutrino Neutron Interaction Experiment (ANNIE) is a 26-ton water-based neutrino detector located at Fermilab, approximately 110 m downstream of the Booster Neutrino Beam (BNB). ANNIE utilizes both photomultiplier tubes (PMTs) and advanced photodetectors, specifically Large Area Picosecond Photodetectors (LAPPDs), to detect Cherenkov light emitted by leptons produced in neutrino interactions within ANNIE. LAPPDs are a novel technology designed to detect photons with picosecond-level temporal resolution and sub-millimetre spatial precision. Multiple LAPPDs have been deployed in the ANNIE detector. This is the first use of this technology in a running particle physics experiment and has yielded the first detection of light from neutrino interactions in water with LAPPDs. In this poster, I will showcase the operational performance and functionality of LAPPDs in the ANNIE experiment. Neutrino beam data from the BNB is used to evaluate the timing precision, hit reconstruction performance, and beam response of deployed LAPPDs, demonstrating how this novel picosecond-resolution technology performs in a running neutrino water Cherenkov detector. This work highlights the successful integration of LAPPDs in ANNIE and provides quantitative benchmarks that inform their application in future neutrino experiments requiring high-resolution photon detection.

Aman, Mohammad Adil [Florida State U.] (ORCID:0009↗
NASA NTRS1982

Evaluation of inelastic constitutive models for nonlinear structural analysis

The influence of inelastic material models on computed stress-strain states, and therefore predicted lives, was studied for thermomechanically loaded structures. Nonlinear structural analyses were performed on a fatigue specimen which had been subjected to thermal cycling in fluidized beds and on a mechanically load cycled benchmark notch specimen. Four incremental plasticity creep models (isotropic, kinematic, combined isotropic kinematic, combined plus transient creep) were exercised using the MARC program. Of the plasticity models, kinematic hardening gave results most consistent with experimental observations. Life predictions using the computed strain histories at the critical location with a strainrange partitioning approach considerably overpredicted the crack initiation life of the thermal fatigue specimen.

Kaufman, A.↗
NASA NTRS1993

Benchmark radar targets for the validation of computational electromagnetics programs

Results are presented of a set of computational electromagnetics validation measurements referring to three-dimensional perfectly conducting smooth targets, performed for the Electromagnetic Code Consortium. Plots are presented for both the low- and high-frequency measurements of the NASA almond, an ogive, a double ogive, a cone-sphere, and a cone-sphere with a gap.

Woo, Alex C.↗
NASA NTRS1999

Application of the RNS3D Code to a Circular-Rectangular Transition Duct With and Without Inlet Swirl and Comparison with Experiments

Circular-rectangular transition ducts are used between engine exhausts and nozzles with rectangular cross sections that are designed for high performance aircraft. NASA Glenn Research Center has made experimental investigations of a series of circular-rectangular transition ducts to provide benchmark flow data for comparison with numerical calculations. These ducts are all designed with superellipse cross sections to facilitate grid generation. In response to this challenge, the three-dimensional RNS3D code has been applied to one of these transition ducts. This particular duct has a length-to-inlet diameter ratio of 1.5 and an exit-plane aspect ratio of 3.0. The inlet Mach number is 0.35. Two GRC experiments and the code were run for this duct without inlet swirl. One GRC experiment and the code were also run with inlet swirl. With no inlet swirl the code was successful in predicting pressures and secondary flow conditions, including a pair of counter-rotating vortices at both sidewalls of the exit plane. All these phenomena have been reported from the two GRC experiments. However, these vortices were suppressed in the one experiment when inlet swirl was used; whereas the RNS3D code still predicted them. The experiment was unable to provide data near the sidewalls, the very region where the vortices were predicted.

Cavicchi, Richard H.↗
NASA NTRS2006

Dielectronic Recombination In Active Galactic Nuclei

XMM-Newton and Chandra observations of active galactic nuclei (AGN) show rich spectra of X-ray absorption lines. These observations have detected a broad unresolved transition array (UTA) between approx. 15-17 A. This is attributed to inner-shell photoexcitation of M-shell iron ions. Modeling these UTA features is currently limited by uncertainties in the low-temperature dielectronic recombination (DR) data for M-shell iron. In order to resolve this issue, and to provide reliable iron M-shell DR data for plasma modeling, we are carrying out a series of laboratory measurements using the heavy-ion Test Storage Ring (TSR) at the Max-Plank-Institute for Nuclear Physics in Heidelberg, Germany. Currently, laboratory measurements of low temperature DR can only be performed at storage rings. We use the DR data obtained at TSR, to calculate rate coefficients for plasma modeling and to benchmark theoretical DR calculations. Here we report our recent experimental results for DR of Fe XIV forming Fe XIII.

Lukic, D. V.↗
NASA NTRS2012

I/O Performance Characterization of Lustre and NASA Applications on Pleiades

In this paper we study the performance of the Lustre file system using five scientific and engineering applications representative of NASA workload on large-scale supercomputing systems such as NASA s Pleiades. In order to facilitate the collection of Lustre performance metrics, we have developed a software tool that exports a wide variety of client and server-side metrics using SGI's Performance Co-Pilot (PCP), and generates a human readable report on key metrics at the end of a batch job. These performance metrics are (a) amount of data read and written, (b) number of files opened and closed, and (c) remote procedure call (RPC) size distribution (4 KB to 1024 KB, in powers of 2) for I/O operations. RPC size distribution measures the efficiency of the Lustre client and can pinpoint problems such as small write sizes, disk fragmentation, etc. These extracted statistics are useful in determining the I/O pattern of the application and can assist in identifying possible improvements for users applications. Information on the number of file operations enables a scientist to optimize the I/O performance of their applications. Amount of I/O data helps users choose the optimal stripe size and stripe count to enhance I/O performance. In this paper, we demonstrate the usefulness of this tool on Pleiades for five production quality NASA scientific and engineering applications. We compare the latency of read and write operations under Lustre to that with NFS by tracing system calls and signals. We also investigate the read and write policies and study the effect of page cache size on I/O operations. We examine the performance impact of Lustre stripe size and stripe count along with performance evaluation of file per process and single shared file accessed by all the processes for NASA workload using parameterized IOR benchmark.

Saini, Subhash↗
NASA NTRS2019

Feature Learning for Multispectral Satellite Imagery Classification Using Neural Architecture Search

Automated classification of remote sensing data is an integral tool for earth scientists, and deep learning has proven very successful at solving such problems. However, building deep learning models to process the data requires expert knowledge of machine learning. We introduce DELTA, a software toolkit to bridge this technical gap and make deep learning easily accessible to earth scientists. Visual feature engineering is a critical part of the machine learning lifecycle, and hence is a key area that will be automated by DELTA. Hand-engineered features can perform well, but require a cross functional team with expertise in both machine learning and the specific problem domain, which is costly in both researcher time and labor. The problem is more acute with multispectral satellite imagery, which requires considerable computational resources to process. In order to automate the feature learning process, a neural architecture search samples the space of asymmetric and symmetric autoencoders using evolutionary algorithms. Since denoising autoencoders have been shown to perform well for feature learning, the autoencoders are trained on various levels of noise and the features generated by the best performing autoencoders evaluated according to their performance on image classification tasks. The resulting features are demonstrated to be effective for Landsat-8 flood mapping, as well as benchmark datasets CIFAR10 and SVHN.

Robert Campbell↗
DOE OSTI2020

2019 ASHRAE Handbook: HVAC Applications - Chapter 37 - Energy Use and Management

Handbook is a highly-regarded engineers reference book for heating, ventilating, air conditioning, and energy engineers. Building energy and water use metrics were developed for 53 commercial and residential building types. Supporting narrative was drafted and provided along with multiple tables of building performance metrics for publication in this ASHRAE handbook. ORNL (T. Sharp) developed the building performance metrics in Tables 2, 3, and 4 and authored the narrative about them. T. Sharp also authored the section on "Benchmarking Water Use" and developed building water use metrics published in Table 5.

Sharp, Terry↗
DOE OSTI2023

Characterizing Quantum Classifier Utility in Natural Language Processing Workflows

Quantum Natural Language Processing (QNLP) develops natural language processing (NLP) models for deployment on quantum computers. We explore feature and data prototype selection techniques to address challenges posed by encoding high dimensional features. Our study builds quantum circuit classifiers that includes classical feature pre-processing, quantum embedding and quantum model training. The quantum models are built on 4 or 6 qubits and the quantum neural network (QNN) uses the established bricklayer design. We compare the dependence of model performance (in terms of accuracy and F1 scores) on feature length, embedding gates and parameterized unitary design. We compare the performance of quantum machine learning models to classical convolution neural network model (CNN) on binary and multi-class classification tasks using two datasets of synthetic features and labels. The first is the ECP-CANDLE P3B3 dataset a corpus of synthetically generated cancer pathology reports. The second dataset is extracted from well-known benchmark dataset (MADELON) - features are generated with a combination of informative, repeated and uninformative features. Both datasets are used for binary classification and multi-class classification with 3 classes. We observe robust, accurate performance from all models on the binary classification tasks, but multiclass classification is a challenge for the quantum models-there is a notable decrease in accuracy when using 3 classes. Overall the performance is comparable in terms of recall and accuracy between QNNs and CNNs, even with large datasets. These results provide a point of comparison between quantum and classical models on real-world datasets.

Hamilton, Kathleen↗
DOE OSTI2026

Revealing the Full Potential of Glycolated Mixed Ionic-Electronic Semiconductors – Symmetric Monomer Polymerization to Boost Electrochemical Transistor Performance

Organic electrochemical transistors (OECTs) enable the transduction of ionic signals into electronic outputs, positioning them as ideal candidates for next-generation sensing and (bio)signal processing applications. Recent years have witnessed the development of various OECT channel materials, affording insights into structural fine-tuning to achieve optimal performance and/or stability. However, homocouplings, commonly present in alternating conjugated polymers, have largely been overlooked. This study investigates the effect of homocoupling on OECT materials by employing two synthesis methods – standard Stille polymerization and an alternative symmetric approach – to create the p-type enhancement-mode benchmark polymer pgBTTT. The impact of homocoupling, and its absence, is studied by comparing the bulk properties of the two polymers and evaluating their respective OECT metrics. The new, homocoupling-free polymer exhibits a notably improved OECT performance ( μC *), mainly due to an average 3-fold increase in electronic mobility (μ).

defects↗
DOE OSTI2024

SRBench++: Principled Benchmarking of Symbolic Regression With Domain-Expert Interpretation

Symbolic regression searches for analytic expressions that accurately describe studied phenomena. The main promise of this approach is that it may return an interpretable model that can be insightful to users, while maintaining high accuracy. The current standard for benchmarking these algorithms is SRBench, which evaluates methods on hundreds of datasets that are a mix of real-world and simulated processes spanning multiple domains. At present, the ability of SRBench to evaluate interpretability is limited to measuring the size of expressions on real-world data, and the exactness of model forms on synthetic data. In practice, model size is only one of many factors used by subject experts to determine how interpretable a model truly is. Furthermore, SRBench does not characterize algorithm performance on specific, challenging sub-tasks of regression such as feature selection and evasion of local minima. In this work, we propose and evaluate an approach to benchmarking SR algorithms that addresses these limitations of SRBench by 1) incorporating expert evaluations of interpretability on a domain-specific task, and 2) evaluating algorithms over distinct properties of data science tasks. We evaluate 12 modern symbolic regression algorithms on these benchmarks and present an in-depth analysis of the results, discuss current challenges of symbolic regression algorithms and highlight possible improvements for the benchmark itself.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Performance-Aligned LLMs for Generating Fast HPC Code

Optimizing scientific software is a difficult task because codebases are often large and complex, and performance can depend upon several factors including the algorithm, its implementation, and hardware among others. Causes of poor performance can originate from disparate sources and be difficult to diagnose. Recent years have seen a multitude of work that use large language models (LLMs) to assist in software development tasks. However, these tools are trained to model the distribution of code as text, and are not specifically designed to understand performance aspects of code. In this work, we introduce a reinforcement learning based methodology to align the outputs of code LLMs with performance. This allows us to build upon the current code modeling capabilities of LLMs and extend them to generate better performing code. Here, we demonstrate that our fine-tuned model improves the expected speedup of generated code over base models for a set of benchmark tasks from 0.9 to 1.6 for serial code and 1.9 to 4.5 for OpenMP parallel code.

Computer science↗
DOE OSTI2020

Foams in Hohlraums

Foam materials are starting to find application in laser-heated hohlraums used to drive inertial confinement fusion (ICF) implosions. The disparate scales of the solid foam elements (nm) compared to the typical problem scale (mm) make it expensive to resolve the individual foam elements in hydrodynamic calculations. In this project we developed two new models for treating foam materials – a 3D hydrodynamic model that treats the foam as bits of pre-expanded solid material separated by voids, and a subgrid model that captures the essential physics of laser-heated foams without requiring resolution of the individual solid elements. We also explored the microphysics of the transition from interpenetrating kinetic behavior to fully-collisional fluid-like behavior during the early time heating and expansion of foam elements through a combination of single-fluid and multi-fluid hydrodynamics calculations and particle-in-cell calculations. The model was benchmarked against these calculations and against experimental data on laser-heated chemical and additive-manufactured (AM) foams. Since there was no existing data on laser-heated AM foams, we performed the first experiments on such foams at the Jupiter Laser Facility. Samples of three different types of printed AM foams were heated using a single 0.5 micron laser. The foam densities ranged from 10 to 100 mg/cc (supercritical for 0.5 micron light). We measured the backscattered light (power and spectrum), the transmitted light, and the time-integrated temperature of the foam samples. This benchmarked subgrid foam model is a new capability that should allow routine calculation of ICF designs using foam elements, potentially opening up a new design space.

36 MATERIALS SCIENCE↗
NASA NTRS2016

Bumper 3 Update for IADC Protection Manual

The Bumper code has been the standard in use by NASA and contractors to perform meteoroid/debris risk assessments since 1990. It has undergone extensive revisions and updates [NASA JSC HITF website; Christiansen et al., 1992, 1997]. NASA Johnson Space Center (JSC) has applied BUMPER to risk assessments for Space Station, Shuttle, Mir, Extravehicular Mobility Units (EMU) space suits, and other spacecraft (e.g., LDEF, Iridium, TDRS, and Hubble Space Telescope). Bumper continues to be updated with changes in the ballistic limit equations describing failure threshold of various spacecraft components, as well as changes in the meteoroid and debris environment models. Significant efforts are expended to validate Bumper and benchmark it to other meteoroid/debris risk assessment codes. Bumper 3 is a refactored version of Bumper II. The structure of the code was extensively modified to improve maintenance, performance and flexibility. The architecture was changed to separate the frequently updated ballistic limit equations from the relatively stable common core functions of the program. These updates allow NASA to produce specific editions of the Bumper 3 that are tailored for specific customer requirements. The core consists of common code necessary to process the Micrometeoroid and Orbital Debris (MMOD) environment models, assess shadowing and calculate MMOD risk. The library of target response subroutines includes a board range of different types of MMOD shield ballistic limit equations as well as equations describing damage to various spacecraft subsystems or hardware (thermal protection materials, windows, radiators, solar arrays, cables, etc.). The core and library of ballistic response subroutines are maintained under configuration control. A change in the core will affect all editions of the code, whereas a change in one or more of the response subroutines will affect all editions of the code that contain the particular response subroutines which are modified. Note that the Bumper II program is no longer maintained or distributed by NASA.

Christiansen, Eric L.↗
NASA NTRS1990

A system performance throughput model applicable to advanced manned telescience systems

As automated space systems become more complex, autonomous, and opaque to the flight crew, it becomes increasingly difficult to determine whether the total system is performing as it should. Some of the complex and interrelated human performance measurement issues are addressed that are related to total system validation. An evaluative throughput model is presented which can be used to generate a human operator-related benchmark or figure of merit for a given system which involves humans at the input and output ends as well as other automated intelligent agents. The concept of sustained and accurate command/control data information transfer is introduced. The first two input parameters of the model involve nominal and off-nominal predicted events. The first of these calls for a detailed task analysis while the second is for a contingency event assessment. The last two required input parameters involving actual (measured) events, namely human performance and continuous semi-automated system performance. An expression combining these four parameters was found using digital simulations and identical, representative, random data to yield the smallest variance.

Haines, Richard F.↗
DOE OSTI2021

Critical and Californium Source-Driven Noise Analysis Subcritical Measurements with an Unreflected Cylindrical Tank of Mixed Uranium-Plutonium Nitrate Solution

The reported experiments were performed by Oak Ridge National Laboratory (ORNL) at the Battelle Northwest Laboratory’s (now Pacific Northwest National Laboratory) critical experiments facility at Hanford, Washington in 1981 and used 16 days of critical facility time, not including 10 days for setup and removal of ORNL equipment. These measurements were to assess the capability of the Cf source-driven noise analysis (CSDNA) method to measure the subcriticality (keff) of mixed U-Pu nitrate solutions. In addition to the CSNDA measurements, measurements were also performed near delayed criticality where CSDNA measurements cannot be performed. This report documents the experiments that were not reported at that time by presenting the ORNL experimental results and any online analysis performed during and shortly after the measurements. The mixed nitrate solution had a U concentration at 188 grams per liter (g/L), a Pu concentration of 280 g/L, free acid normality of 2.80, H ion molarity of 5.9 and a specific gravity of 1.754 g/cm 3 , a 240 Pu isotopic content of 7.981 wt. %, and a 235 U isotopic content of 0.724 wt. %. The stainless-steel tank for the solution had an inside diameter of 35.38 cm, an outside diameter of 35.53 cm, a height of 56.72 cm, and bottom thickness of 0.9525 cm. A Zircaloy pipe with a 3.1496 cm outside diameter, a 2.7788 cm inside diameter, and bottom thickness of 0.635 cm was available for insertion of the Cf source in the center of the fissile solution. The Cf source was also located at the outside surface of the tank (solution height varied from 10 to 53 cm) and in the center of the solution (solution height varied from 10 to 60.7 cm). The CSDNA measurements were not analyzed online to determine the subcritical neutron multiplication factors. At all subcritical states, the break frequency noise analysis data was fitted to obtain the prompt neutron decay constant. The neutron multiplication factors were determined for the two configurations of the measurements near delayed criticality. The subcritical neutron multiplication factors from the CNSDA measurements can be obtained with further analysis. However, the near delayed critical configuration, the prompt neutron decay constants, the count rates, and the measured cross and auto power spectral densities can be calculated directly for benchmarking. Much of data presented in this report are from ORNL notes—not in the ORNL logbooks. For the final benchmark analysis, the data from the Battelle Northwest Laboratory (which operated the critical facility in 1981) critical facility logbook should be consulted and be incorporated where appropriate. The purpose of this report is to document the experimental information for the measurements performed so that at a later date researchers could perform the required uncertainty and calculational analyses and documentation to use these data for an International Criticality Safety Benchmark Program (ICSBEP) or Nuclear Energy Agency benchmark. The data from these measurements are available from the ORNL Records Management Services Department, and the logbook is available from ICSBEP at Idaho National Laboratory. Preparation of the present report is part of a larger cooperative effort between Idaho National Laboratory (INL) and Oak Ridge National Laboratory (ORNL) to document more than 15 undocumented critical and subcritical experiments enumerated in ORNL/TM-2019/18 and performed by ORNL at ORCEF and other USDOE critical experiments facilities using more than 500 operational days of critical facility time.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2017

Trade Study: Storing NASA HDF5/netCDF-4 Data in the Amazon Cloud and Retrieving Data Via Hyrax Server Data Server

This study explored three candidate architectures with different types of objects and access paths for serving NASA Earth Science HDF5 data via Hyrax running on Amazon Web Services (AWS). We studied the cost and performance for each architecture using several representative Use-Cases. The objectives of the study were: Conduct a trade study to identify one or more high performance integrated solutions for storing and retrieving NASA HDF5 and netCDF4 data in a cloud (web object store) environment. The target environment is Amazon Web Services (AWS) Simple Storage Service (S3). Conduct needed level of software development to properly evaluate solutions in the trade study and to obtain required benchmarking metrics for input into government decision of potential follow-on prototyping. Develop a cloud cost model for the preferred data storage solution (or solutions) that accounts for different granulation and aggregation schemes as well as cost and performance trades.We will describe the three architectures and the use cases along with performance results and recommendations for further work.

AWS cost↗
NASA NTRS2016

Performance Assessment of Different Pulse Reconstruction Algorithms for the ATHENA X-Ray Integral Field Unit

The X-ray Integral Field Unit (X-IFU) microcalorimeter, on-board Athena, with its focal plane comprising 3840 Transition Edge Sensors (TESs) operating at 90 mK, will provide unprecedented spectral-imaging capability in the 0.2-12 keV energy range. It will rely on the on-board digital processing of current pulses induced by the heat deposited in the TES absorber, as to recover the energy of each individual events. Assessing the capabilities of the pulse reconstruction is required to understand the overall scientific performance of the X-IFU, notably in terms of energy resolution degradation with both increasing energies and count rates. Using synthetic data streams generated by the X-IFU End-to-End simulator, we present here a comprehensive benchmark of various pulse reconstruction techniques, ranging from standard optimal filtering to more advanced algorithms based on noise covariance matrices. Beside deriving the spectral resolution achieved by the different algorithms, a first assessment of the computing power and ground calibration needs is presented. Overall, all methods show similar performances, with the reconstruction based on noise covariance matrices showing the best improvement with respect to the standard optimal filtering technique. Due to prohibitive calibration needs, this method might however not be applicable to the X-IFU and the best compromise currently appears to be the so-called resistance space analysis which also features very promising high count rate capabilities.

microcalorimeters↗