Search NASA⌕ Search

SEARCH · Search NASA

Results for “test configuration”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Protons in the NOvA Test Beam

The NOvA (NuMI Off-Axis electron neutrino Appearance) Experiment is a long-baseline neutrino oscillation experiment composed of two functionally identical detectors, a 300 ton Near Detector, and a 14 kton Far Detector separated by 809 km and placed 14 mrad off the axis of the NuMI neutrino beam created at Fermilab. This configuration enables NOvA's rich neutrino physics program, which includes measuring neutrino mixing parameters, determining the neutrino mass hierarchy, and probing CP violation in the leptonic sector. The NOvA Test Beam experiment deployed at Fermilab between 2018 and 2022 used a scaled-down 30 ton detector to analyse tagged beamline particles. The beamline selected and identified electrons, muons, pions, kaons, and protons with momenta ranging from 0.4 to 1.8 GeV/c, as understanding how the detector responds to these particles found in the final state of neutrino interactions is crucial. This poster shows preliminary results from studies of proton response in the NOvA Test Beam detector.

Bannister, Emerson [Sussex U.] (ORCID:000000027535↗
DOE OSTI2024

Neural networks for estimation of divertor conditions in DIII-D using C III imaging

Deep learning approaches have been applied to images of C III emission in the lower divertor of DIII-D to develop models for estimating the level of detachment and magnetic configuration (X-point location and strike point radial location). The poloidal distance from the target to the C III emission front is used to represent the level of detachment. The models perform well on a test dataset not used in training, achieving $F_1$ scores as high as 0.99 for detachment state classification and root mean squared error (RMSE) as low as 2cm for front location regression. Predictions for shots with intermittent reattachment are studied, with class activation mapping used to aid in interpretation of the model predictions. Based on the success of these models, a third model was trained to predict the X-point location and strike point radial position from C III images. Though the dataset covers only a small range of possible magnetic configurations, the model shows promising results, achieving RMSE around 1cm for the test data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

High-Speed and High-Quality Field Welding Repair Based on Advanced Non-Destructive Evaluation and Numerical Modeling

Creep strength-enhanced ferritic (CSEF) steels such as Grade 91 (9Cr-1Mo-V) and Grade 92 (Fe-9Cr-2W-0.5Mo) steels are widely used in the fossil-fuel-fired and nuclear power plants. The weld integrity of these steels is crucial for power plants' safe and reliable operations. Due to harsh service conditions, the steel weld can become susceptible to environmental degradation. Field welding repair is used to restore the degraded weld’s performance where a controlled temper-bead welding technique is commonly used to temper the freshly formed martensite during welding. However, knowledge of weld repairability is limited and experimental trial and error optimization to achieve desired microstructure and joint properties is expensive and time-consuming. Many existing computational models, e.g., finite element models, are limited to solving heat conduction equation and ignoring convective heat transfer due to molten metal flow. These models can result in over-prediction of peak temperatures of weld pool and heat-affected zone (HAZ), which in turn can affect the accuracy of tempering prediction. Moreover, these finite element models require an input of the deposit profiles in advance and thus limits the usability of these models. Here, a molten pool-based, multi-pass multi-layer model has been developed based on computational fluid dynamics (CFD) approach with the Volume of Fluid (VOF) method. The model calculates the bead formation, thereby eliminating the need for pre-determined bead profiles required by finite element models. For computational efficiency, a coordinate system attached to the moving heat source is utilized. A subroutine is developed to convert the temperature profiles in the reference frame stationary to the heat source to that stationary to the workpiece. The converted thermal cycles are then imported into a microstructure model to compute the tempering kinetics and resultant hardness using a Johnson-Mehl-Avrami-Kolmogorov (JMAK), and modified Grange-Baughman parameter. The modeling approach is first developed and validated on single- and multi-pass deposition of stainless steel filler metal onto a SA-533 high strength steel substrate. The models are then applied to a multi-pass V-groove repair weld of Grade 91 steel plate as well as directed energy deposition of Grade 92 steel. Non-destructive characterization of microstructures was performed on Grade 91 and 92 steel welds. Two welding processes, cold metal transfer (CMT) and flux-cored arc welding (FCAW), were investigated for the Grade 91 steel weld samples. For the Grade 92 weld samples, three different heat inputs (low, medium, and high) of gas tungsten arc welding (GTAW) were utilized to replicate traditional field welding processes. The non-destructive evaluation (NDE) method used for this research was immersion ultrasonic testing (UT) using a micro-resolution ultrasonic imaging methodology specifically designed to operate in the through-transmission configuration operating at 20 MHz of frequency. The system used a focused ultrasonic beam spot size diameter between 250-300 μm, and a 6 μm laser vibrometer spot size for detection, to produce highly defined images with longitudinal and mode-converted shear waves. From the micro-resolution ultrasonic C-scan images, three microstructural regions, i.e., weld metal (WM), HAZ, and base metal (BM), were clearly identifiable. Various levels of ultrasonic amplitudes distributed over the three regions were correlated with electron beam backscattered diffraction (EBSD) images using grain size, grain boundaries, and dislocation densities. The results showed that areas with relatively higher ultrasonic amplitude levels were associated with smaller grains and higher dislocation densities, while areas with lower amplitude levels were associated with larger grains and lower dislocation densities. In addition, ultrasonic velocity data obtained across the three different weld microstructural regions of Grade 91 test samples were correlated with optical metallographic images and hardness measurements. The results showed distinctive decreases in ultrasonic velocity and hardness over the HAZ region, where weld failures often occur during service.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Fracture toughness measurement of ceramics with fuel pellet geometry

The crack initiation of nuclear fuel pellets, driven by extreme temperature gradients, is a critical factor impacting reactor performance. Although this fact is widely acknowledged, there is limited fracture toughness data for specimens with representative geometry and fabricated using relevant processing methods. Here, to address this, a new chevron-notched short-rod specimen configuration with diameter and length both equal to 10 mm, representative of a conventional fuel pellet and tested in tension, was developed in an attempt to validly measure Mode I fracture toughness, K Ic . Test calibration was carried out by testing polycrystalline ZrO 2 , SiC, and Si 3 N 4 ceramics fabricated with conventional fuel pellet geometry and known fracture toughnesses. The results suggest that the method described in this paper produces valid K Ic measurements using conventional ceramic fuel pellets.

Ceramics↗
DOE OSTI2025

Understanding the Competition between Alcohol Formation and Dimerization during Electrochemical Reduction of Aromatic Carbonyl Compounds

The electrochemical reductive dimerization of small aromatic carbonyl compounds derived from lignocellulosic biomass is a crucial C−C coupling reaction for upgrading small molecules to longchain hydrocarbons, particularly in the synthesis of drop-in sustainable aviation fuels. Although other electrochemical reduction reactions of these reactants (i.e., hydrogenation and hydrogenolysis) have undergone extensive mechanistic investigation, the understanding of dimerization remains relatively underdeveloped. Most importantly, there is a lack of understanding of the selectivity-determining step between dimerization and monomer reduction and critical factors that can affect this step. In this study, we provide a comprehensive mechanistic model to explain the competition between dimerization and monomer reduction of benzaldehyde under various conditions. Our model proposes that the selectivity between dimerization and monomer reduction depends on the competition between desorption of a ketyl radical from the electrode, necessary for dimerization, and further reduction of the ketyl radical to an alcohol on the electrode by proton-coupled electron transfer (PCET). Computationally comparing the adsorption/desorption energy and PCET activation barrier energy is challenging because conventional DFT calculations substantially underestimate the PCET kinetic barriers. In this study, we employed constrained DFTbased configuration interaction (CDFT-CI) to obtain a reliable comparison of these energies. Our mechanistic model was tested and supported by experimental results obtained with four electrodes (Cu, Pb, Bi, graphite), three pH conditions (acidic, neutral, basic), and three potentials. Our study offers a coherent mechanistic foundation that can explain how each of these conditions impacts the desorption and PCET processes and the selectivities for dimerization and alcohol production.

09 BIOMASS FUELS↗
DOE OSTI2024

Toward Automated Detection of Portability Bugs in Kokkos Parallel Programs

Performance-portable programming frameworks provide abstractions for parallel execution to allow easily porting an application to multiple backend programming models, such as CUDA, HIP, and OpenMP. However, programs may still have portability bugs that manifest only on specific backends. Traditional testing is ineffective in discovering these bugs, as it would require concrete execution on all supported hardware configurations for a potentially infinite set of inputs. To mitigate this issue, we focused on a specific programming framework, Kokkos, and identified several categories of common portability bugs. We then developed Klokkos, a static analysis approach based on symbolic execution that can run on commodity hardware, before execution on supercomputers. As a proof-of-concept, we ran Klokkos on examples encoding the identified bugs. Our results show that Klokkos is effective, efficient, and precise: it detected all the considered bugs, quickly, and without any false positives. Although preliminary, our results motivate further research and development in this direction.

Kale, Vivek↗
DOE OSTI2026

Quantum correlation imaging via X-ray parametric down-conversion

Quantum imaging leverages correlations between pairs of photons and has the potential to obtain image information beyond what classical sources provide. Extending this approach to the X-ray regime has been limited by low photon-pair generation rates and the lack of suitable detectors. Here, we demonstrate X-ray coincidence imaging using spontaneous parametric down-conversion (SPDC) and a pixelated area detector with time- and energy-resolved capabilities. This configuration enables simultaneous detection of correlated X-ray photon pairs and coincidence-based imaging of test objects, including a biological specimen. The increased coincidence rate and spatially resolved detection establish a basis for future quantum-enhanced and low-dose X-ray imaging.

Goodrich, Justin C. [Brookhaven National Laborator↗
DOE OSTI2024

Structure Formation Through Magnetohydrodynamical Instabilities in Primordial Disks

The shear flow instabilities under the presence of magnetic fields in the primordial disk can greatly facilitate the formation of density structures that serve as seeds prior to the onset of the gravitational Jeans instability. We evaluate the effects of the Parker, magnetorotational and kinematic dynamo instabilities by comparing the properties of these instabilities. We calculate the mass spectra of coagulated density structures by the above mechanism in the radial direction for an axisymmetric magnetohydrodynamic (MHD) torus equilibrium and power density profile models. Our local three-dimensional MHD simulation indicates that the coupling of the Parker and magnetorotational instability creates spiral arms and gas blobs in an accretion disk, reinforcing the theory and model. Such a mechanism for the early structure formation may be tested in a laboratory. The recent progress in experiments involving shear flows in rotating tokamak, field reversed configuration (FRC) and laser plasmas may become a key element to advance in nonlinear studies.

Noguchi, Koichi↗
DOE OSTI2025

Machine Learning for LBNF Beam Diagnostics

This paper focuses on developing a machine learning model for predicting initial beam parameters for the Long Baseline Neutrino Facility (LBNF) beamline using downstream muon monitor data. Parameters such as proton beam position on target, sigma on target, focusing horn current, and focusing horn tilt are parameters we anticipate to be predictable based on the muon monitors. Uncertainty in initial beam condition measurements are a major contributor to uncertainty in downstream flux, and over operation time beam misalignment can occur [1]. A machine learning model has promise to detect anomalies along the beamline based on discrepancies between predicted configurations and measured configurations, and thus can expedite error detection and handling. A PyTorch neural network is defined, trained, and tested. The developed model currently does not provide reliable predictions, with the lowest loss being 0.09.. Further steps to improve the model’s accuracy are discussed, as well as future plans to detect anomalous beam conditions using a digital twin.

O'Brien, Bridget [Fermilab]↗
DOE OSTI2025

Isomers and hindrances in No254: A touchstone for theories of superheavy nuclei

We report on a new spectroscopic study of the decay of high-K isomers in No152102254, a touchstone nucleus for testing models to understand the structure of superheavy nuclei. The experiment, performed using the Argonne gas-filled analyzer (AGFA), was geared toward resolving long-standing ambiguities in spin-parity and configuration assignments for the two- and four-quasiparticle (qp) intrinsic excitations identified in this nucleus. The isomer decay schemes are firmly established with the help of the highest-statistics γ-γ coincidence data collected to date, providing anchor points for competing theories. A newly measured half-life in the nanosecond range establishes a second 2-qp isomer in No254. The preferred decay pathways for the 2- and 4-qp isomers are discussed, providing new insights into the underlying hindrance mechanisms at play in these heavy nuclei. With firm configuration assignments, the intrinsic excitations in this deformed mass region provide stringent constraints and challenge the different theoretical approaches at play in understanding the structure of superheavy nuclei.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

An atomic cluster expansion potential for twisted multilayer graphene

Twisted multilayer graphene, characterized by its moiré patterns arising from inter-layer rotational misalignment, serves as a rich platform for exploring quantum phenomena. Machine learning interatomic potentials (MLIPs) are a promising approach to model such systems. Our work develops a method to generate training and test datasets for fitting MLIPs that capture all possible misalignments but remain small-scale to facilitate efficient data generation and parameter estimation. To achieve this, we generate configurations with periodic boundary conditions suitable for density functional theory calculations, and then introduce an internal twist and shift within those supercell structures. Using this technique, supplemented with an active learning workflow, we fit an Atomic Cluster Expansion potential for simulating twisted multilayer graphene and test it for accuracy and robustness on a range of simulation tasks.

2D materials↗
DOE OSTI2026

On High-Temperature Dynamometer Test Stand Development

RePED is a novel prototype alternator that has been designed and built to operate at 35 kW under 250 degrees C ambient temperature conditions. The operating efficiency will be measured using a 225-kW motor to drive the machine in a back-to-back configuration. The goal is to determine if the RePED alternator can deliver 35 kW at a rotational speed of 1,000 rpm while operating in 250 degrees C ambient temperature and have a minimum efficiency of 60%. Dynamometer testing of a high-temperature alternator for geothermal drilling presents several unique challenges, especially around maintaining and managing the various sources and types of energy passing through the system without impacting data quality. The objectives of this report are to (1) describe the test stand in detail, the relative orientation of each major component, and the data acquisition system and (2) discuss the behavior of the test stand components such that this report can serve as a reference document for future projects.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

ADRIANO2 Calorimeter Performance from 2022 Test Beams

A novel high-granularity dual-readout calorimetric technique was developed as part of the T1604 collaboration. The ADRIANO2 Calorimeter Prototype consists of a pair of optically isolated, small sized tiles made of scintillating plastic and lead glass. Čerenkov light from the lead glass are exploited to for high resolution timing measurements, while high granularity from scintillating plastic can be used to probe the spatial component of the particle shower. This setup works for excellent energy resolution and particle detection for REDTOP as it is crucial for a calorimeter to detect the decay products of eta/eta-prime mesons. Measurements were collected on ADRIANO2 between February to December 2022 to evaluate the detector performance at Fermilab’s Test Beam Facility. The key metrics extracted from my analysis are the detector’s efficiency for various tile configuration and light-yield which will then be used as parameters for an upgraded REDTOP monte-carlo simulation campaign. An in-depth analysis of ADRIANO2 performance are detailed in this presentation.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Validation of Exploding Wire Tests Using Alegra-NG

Exploding wire tests are used to characterize materials undergoing high voltage loading and to validate computational models in a simple configuration. In this report, the materials emphasized are gold, aluminum, copper and nickel wires. Model validation is presented using the nominal model (no uncertainty) in the form of heat maps (per material) that show model bias across scalar quantities and initial voltage. Mesh convergence and uncertainty quantification is also presented.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Representing lateral groundwater flow from land to river in Earth system models

Lateral groundwater flow (LGF) is an important hydrologic process in controlling water table dynamics. Due to the relatively coarse spatial resolutions of land surface models, the representation of this process is often overlooked or overly simplified. In this study, we developed a hillslope-based lateral groundwater flow model. Specifically, we first developed a hillslope definition model based on an existing watershed delineation model to represent the subgrid spatial variability in topography. Building upon this hillslope definition, we then developed a physical-based lateral groundwater flow using Darcy’s equation. This model explicitly considers the relationships between the groundwater table along the hillslope and the river water table levels. We coupled this intra-grid model to the land component (E3SM Land Model: ELM) and river component (MOdel for Scale Adaptive River Transport: MOSART) of the Energy Exascale Earth System Model (E3SM). We tested both the hillslope definition model and the lateral groundwater flow model and performed sensitivity experiments using different configurations. Simulations for a single grid cell at 0.5°×0.5° within the Amazon basin show that the definition of hillslope is the key to modeling lateral flow processes and the runoff partition between surface and subsurface can be dramatically changed using the hillslope approach. Although our method provides a pathway to improve the lateral flow process, future improvements are needed to better capture the subgrid structure to account for the spatial variability in hillslopes within the simulated grid of land surface models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

IOTA Experiment for Proton Pulse Compression at Extreme Space-Charge

The longitudinal compression of high-intensity, space-charge-dominated proton bunches is a critical requirement for future proton-driven muon colliders. We propose a proton bunch compression experiment at the Integrable Optics Test Accelerator (IOTA) storage ring at Fermilab to investigate optimal radio-frequency (RF) cavity parameters and lattice configurations. IOTA is a compact, fixed-energy storage ring dedicated to beam physics Research and Development and capable of circulating a 2.5 MeV proton beam under extreme space-charge conditions. Using the ImpactX code with its 3D space-charge solver, simulations indicate that the bunch length can be rapidly reduced by at least a factor of two without appreciable degradation of transverse beam quality--even in the strong space-charge regime. However, longitudinal defocusing due to the space-charge remains a significant challenge in short-pulsed intense proton bunches, and the optimization of compression under these conditions is discussed.

Simons, B. D. [Northern Illinois U.]↗
DOE OSTI2025

A Reductively Stable Electrolyte Realizes Deep Cycling Behavior in Anode‐free Sodium Batteries

For anode‐free sodium batteries to achieve practical consideration, highly reversible chemistries require exceptional ≥99.95% coulombic efficiencies that maintain over prolonged cycling periods. To do so, consumption of this severely limited sodium inventory must be restricted while metal nucleation processes that comprise the in situ formed metal anode are improved. Herein, we describe a fluorine‐free carborane electrolyte that satisfies these criteria by emphasizing reductive stability and weakly coordinating anion behavior as design principles. We find this approach promotes the development of a thin, robust SEI chemistry rich in both organic speciation and boron. The electrolyte described herein exhibits ideal metal nucleation behavior on one‐micron thin carbonaceous current collector surfaces and achieves a metal deposition/stripping efficiency near parity for 400 cycles. This novel anode chemistry is introduced to anode‐free full cell configurations where 87% of the initial discharge capacity is retained after 1000 cycles at 2.0 C. In conclusion, post‐test characterization of deep‐cycled anode‐free cells reveals suppressed capacity fade in these systems is attributed to the chemical stability of the carborane anion.

anode-free↗
DOE OSTI2025

Butterfly valve performance factors using the multiphysics object oriented simulation environment

Butterfly valves are typically used in nuclear reactors to control incompressible fluid flow with high inlet velocities. Performance factors for butterfly valves include the pressure drop across the valve and the loss coefficient from which hydrodynamic torque and flow coefficients can be computed. This work explores a computational fluid dynamics approach for butterfly valve performance factors using the open-source Multiphysics Object Oriented Simulation Environment (MOOSE) framework. While MOOSE is often used in the nuclear energy modeling and simulation community for simulations ranging from fuel characterization to heat pipe simulation, this work employs the MOOSE open-source Navier–Stokes solver capability for simulating butterfly valve performance factors and compares those to experimentally measured results from the Advanced Test Reactor at Idaho National Laboratory at Reynolds numbers in the order of 10 6 for the partially opened configuration. The MOOSE framework results are compared against experimentally measured butterfly valve performance factors across five valve opening angles using meshes with order 10 4 – 10 5 elements. This validation serves to enable MOOSE-based multiphysics simulations incorporating the open-source Navier–Stokes module.

97 - MATHEMATICS AND COMPUTING↗