DUNE: Validating Neutrino Simulation Performance
This abstract covers my work in data validation for the Near Detector Complex in DUNE under the 2026 SULI program.
Vershaw, Andre [Unlisted, US, IL; Fermilab] (ORCID↗
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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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Radio Links for the NASA ABTS
The closed loop prototype has operational bi-directional wireless links. The Wideband PCM-FSK receiver has been designed and characterized. Now that both links function, communication performance can be addressed. For example, noise problems with the received outlink signal that caused the PC program to lockup were just recently revealed and minimized by software "enhancements" to the Windows based PC program. A similar problem with inlink communication was uncovered several days before this report: A noise spike or dropout (expected events in the animal Habitat) caused an interrupt to the implant microcontroller which halted outlink transmission. Recovery of outlink transmission did not reliably occur. The problem has been defined and implant software is being modified to better recognize noise from data by changing the timing associated with valid data packet identification and by better utilizing the error flags generated by the microcontroller's SCI circuits. Excellent inlink performance will also require improvements in the implant's receiver. The biggest performance improvement can be provided by antenna design for the Habitat. The quarter wavelength whip antennas used with the demo prototype inlink leave much to be desired.
Jeutter, Dean C.↗
Ballistic Impact Response of Kevlar 49 and Zylon under Conditions Representing Jet Engine Fan Containment
A ballistic impact test program was conducted to provide validation data for the development of numerical models of blade out events in fabric containment systems. The impact response of two different fiber materials - Kevlar 49 (E.I. DuPont Nemours and Company) and Zylon AS (Toyobo Co., Ltd.) was studied by firing metal projectiles into dry woven fabric specimens using a gas gun. The shape, mass, orientation and velocity of the projectile were varied and recorded. In most cases the tests were designed such that the projectile would perforate the specimen, allowing measurement of the energy absorbed by the fabric. The results for both Zylon and Kevlar presented here represent a useful set of data for the purposes of establishing and validating numerical models for predicting the response of fabrics under conditions simulating those of a jet engine blade release situation. In addition some useful empirical observations were made regarding the effects of projectile orientation and the relative performance of the different materials.
Pereira, J. Michael↗
FAA Development of Reliable Modeling Methodologies for Fan Blade Out Containment Analysis: Ballistic Impact Testing - Part 2
This report summarizes the ballistic impact testing that was conducted to provide validation data for the development of numerical models of blade out events in fabric containment systems. The ballistic impact response of two different fiber materials - Kevlar 49 (E.I. DuPont Nemours and Company) and Zylon AS (Toyobo Co., Ltd.) was studied by firing metal projectiles into dry woven fabric specimens using a gas gun. The shape, mass, orientation and velocity of the projectile were varied and recorded. In most cases the tests were designed such that the projectile would perforate the specimen, allowing measurement of the energy absorbed by the fabric. The results for both Zylon and Kevlar presented here represent a useful set of data for the purposes of establishing and validating numerical models for predicting the response of fabrics under conditions simulating those of a jet engine blade release situations. In addition some useful empirical observations were made regarding the effects of projectile orientation and the relative performance of the different materials.
Revilock, Duane M.↗
Explicit Finite Element Modeling of Multilayer Composite Fabric for Gas Turbine Engine Containment Systems, Phase II: Ballistic Impact Testing - Part 2
This report summarizes the ballistic impact testing that was conducted to provide validation data for the development of numerical models of blade-out events in fabric containment systems. The ballistic impact response of two different fiber materials - Kevlar(TradeName) 49 and Zylon(TradeName) AS (as spun) was studied by firing metal projectiles into dry woven fabric specimens using a gas gun. The shape, mass, orientation, and velocity of the projectile were varied and recorded. In most cases, the tests were designed so the projectile would perforate the specimen, allowing measurement of the energy absorbed by the fabric. The results for both Zylon and Kevlar presented here represent a useful set of data for the purposes of establishing and validating numerical models to predict the response of fabrics under conditions that simulate those of a jet engine blade-release situation. In addition, some useful empirical observations were made regarding the effects of projectile orientation and the relative performance of the different fabric materials.
Zylon↗
Utilizing 3D-DIC on Mars 2020 Rover Wheel Assembly: Test-Analysis Correlation
Following the successful implementation of full-field photogrammetry, more specifically three-dimensional Digital Image Correlation (3D-DIC), on the Mars 2020 Heat Shield Structural Failure Review assessment, 3D-DIC was selected as one of the primary measurement techniques for the Mars 2020 Rover wheel assembly qualification test at the NASA Jet Propulsion Laboratory (JPL). To validate the Rover wheel landing loads simulations, it was extremely important to have high confidence in the wheel models. Due to the large deformations and strains that the wheel would be subject to during landing, traditional instrumentation such as linear variable displacement transducers (LVDTs), electrical-resistance strain gages and string potentiometers, would not be sufficient on their own to provide all the necessary validation data. Therefore, the NASA Engineering and Safety Center (NESC) provided the 3D-DIC expertise and support to measure the high deformation and strain in the wheel flexures and qualify the overall structural response of the Mars 2020 rover wheel assembly. There were two key objectives for the photogrammetry technique: (1) monitor the wheel response in real-time, guarding against anomalous behavior and failure, and (2) provide test data for test-analysis correlation to validate and/or improve the high-fidelity computational model. The contents of this paper will focus on the challenges of applying 3D-DIC to the Mars 2020 Rover wheel assembly and how these challenges were overcome. Examples of test-analysis correlation during the stiffness characterization and structural qualification will be presented and discussed in detail. Experimental results were compared with the analysis and showed excellent agreement between the predicted behavior and helped validate the high-fidelity models.
Mars 2020 Rover Wheel↗
Hourly PM 2.5 Estimates across California from 2018 to 2023
This study presents a new data set of hourly PM 2.5 concentrations across California from 2018 to 2023 at a three-kilometer resolution. This data set was developed by assimilating observations from PurpleAir and the U.S. EPA Air Quality System monitors into wildfire smoke forecasts from the High-Resolution Rapid Refresh Smoke (HRRR-Smoke) model using the Gridpoint Statistical Interpolation (GSI) three-dimensional variational data assimilation framework. Archived forecasts of modeled wildfire smoke PM 2.5 from HRRR-Smoke create the background field for assimilation, which is then corrected using surface observations of total PM 2.5 . The resulting reanalysis from GSI provides an estimate of total PM 2.5 that minimizes error from both the observational and the model data. Validation results indicate strong performance, with monthly R 2 values ranging from 0.73 to 0.91 across the six-year data set, comparable to other PM 2.5 data sets. Case studies are presented for three major fire events, the 2018 Camp Fire, 2019 Kincade Fire, and 2020 Lightning Complex Fires to demonstrate the data set’s fidelity in resolving plume dynamics and local exposure patterns. Root-mean-squared error averaged over each month scales with average PM 2.5 concentrations, resulting in a low error under typical conditions but higher absolute errors during extreme smoke events. This is the first long-term, hourly PM 2.5 data set of its kind for California and enables the generation of subdaily exposure metrics, such as peak hourly concentrations, exceedance durations, and time-of-day exposure peaks. The novelty and strong validation of this data set make it a compelling resource for future studies on the impact and significance of subdaily PM 2.5 exposure.
PM2.5↗
Initial tests of large format sensors for the ATLAS ITk strip tracker
For the construction of the Inner Tracker (ITk) as part of the phase-II upgrade programme of the ATLAS detector for the High-Luminosity (HL) LHC, batches of Long Strip (LS) and Short Strip (SS) n + -in-p type micro-strip sensors have been produced by Hamamatsu Photonics and Infineon. The full size sensors measure approximately 98 × 98 mm 2 and are designed and engineered for tolerance against the 9.7 × 10 14 1 MeV n eq /cm 2 fluence expected at the HL-LHC, including a safety factor of 1.5. Each sensor has 2 or 4 columns of 1280 individual channels arranged at 75.5 μ m horizontal pitch. To ensure the sensors comply with their specifications, a Quality Control (QC) procedure has been implemented, comprising measurements on every individual sensor as well as on a sample basis. Every sensor is subjected to an initial visual inspection, after which the full surface of the sensor is captured with very high resolution by an automated camera setup. Non-contact metrology is performed to obtain the sensor surface profile. Electrical measurements establishing the reverse bias leakage current and depletion voltage are then conducted automatically. Sample sensors from every batch are subjected to 40 h of leakage stability checks in controlled atmosphere, and tests on every channel measuring leakage current, coupling capacitance and bias resistance are done. The recorded results are uploaded to a production database following data quality checks. In this paper, QC test validation data and the compiled results for the first batches of production grade sensors are presented. The QC protocol was validated, and the first production sensors were confirmed to be within specification. The results are compared to those from the previous generation of prototype sensors.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Gamma-ray Measurements from Neutron Pulsed Die-Away Experiments
Pulsed-neutron die-away experiments are a promising experimental method that complement criticality benchmarks for nuclear data validation. The experiments have several advantages that include compatibility with non-fissile material, low benchmark uncertainties, and high sensitivity to absorption and scattering cross sections. When validating thermal neutron scattering laws, small targets are desirable for their large sensitivity to the scattering cross section and angular distribution. Unfortunately, room return or scattering from a shielding box limits the use of the very small targets needed to maximize sensitivity to thermal scattering laws. To address this problem, we propose changing the observable of the experiment from leaked thermal neutrons to γ-rays produced by (n, γ) reactions in the target. If feasible, this change allows removal of the shielding box, achieving higher sensitivity to thermal neutron scattering laws. This study focuses on replicating benchmark pulsed-neutron die-away experiments with γ-rays. We compare the integral parameters with γ-rays to those obtained with neutrons. We also discuss experimental design choices such as detector placement, shielding, and the presence of Cd. The results show the integral parameter with γ-rays is sensitive to detector location with respect to the target when Cd shielding is present. In addition, while Pb shielding around the γ-ray detectors do not seem to affect the integral parameter, the presence of Cd shielding does and adds background γ-rays to the die-away curves making it difficult to calculate the integral parameter.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Temperature Data Assimilation with Salinity Corrections: Validation for the NSIPP Ocean Data Assimilation System in the Tropical Pacific Ocean, 1993-1998
The NASA Seasonal-to-Interannual Prediction Project (NSIPP) has developed an Ocean data assimilation system to initialize the quasi-isopycnal ocean model used in our experimental coupled-model forecast system. Initial tests of the system have focused on the assimilation of temperature profiles in an optimal interpolation framework. It is now recognized that correction of temperature only often introduces spurious water masses. The resulting density distribution can be statically unstable and also have a detrimental impact on the velocity distribution. Several simple schemes have been developed to try to correct these deficiencies. Here the salinity field is corrected by using a scheme which assumes that the temperature-salinity relationship of the model background is preserved during the assimilation. The scheme was first introduced for a zlevel model by Troccoli and Haines (1999). A large set of subsurface observations of salinity and temperature is used to cross-validate two data assimilation experiments run for the 6-year period 1993-1998. In these two experiments only subsurface temperature observations are used, but in one case the salinity field is also updated whenever temperature observations are available.
Troccoli, Alberto↗
Energy dependence of prompt fissions neutron multiplicity in the 239 Pu(n, ƒ) reaction
Accurate multiplicities of prompt fission neutrons emitted in neutron-induced fission on a large energy range are essential for fundamental and applied nuclear physics. Measuring them to high precision for radioactive fissioning nuclides remains, however, an experimental challenge. In this work, the average prompt-neutron multiplicity emitted in the 239 Pu(n, ƒ) reaction was extracted as a function of the incident-neutron energy, over the range 1-700 MeV, with a novel technique, which allowed to minimize and correct for the main sources of bias and thus achieve unprecedented precision. At low energies, our data validate for the first time the ENDF/B-VIII.0 nuclear data evaluation with an independent measurement and reduce the evaluated uncertainty by up to 60%. This work opens up the possibility of precisely measuring prompt fission neutron multiplicities on highly radioactive nuclei relevant for an essential component of energy production world-wide.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
iButton snow-ground interface temperature measurements in Los Alamos, New Mexico from 2023-2024
Snow/ground interface temperature measurements were collected at two sites in Los Alamos, New Mexico. Data were collected from November 29, 2023 to April 8, 2024 using iButton Link DS1921G-F5# Thermochron miniature temperature sensors (https://www.ibuttonlink.com/products/ds1921g). These sensors are a cost-efficient way to collect snowpack temperatures at a higher spatial resolution than what is normally achieved. iButton data were collected every 3 hours from a total of 19 iButtons. iButtons were placed in pairs, with one iButton placed at the ground surface and another buried 1 - 5 cm below the ground surface. One buried iButton did not successfully collect data, and therefore was excluded from this dataset. Data were collected throughout the snow cover season so that snowpack characteristics could be derived using the temperature data. Specifically, this dataset was used as a validation source for a novel machine learning approach to estimating snow depth (see related publication). Sensors were placed in areas with bare ground or minimal grass coverage, located away from any large vegetation. At Site A (TA51), manual snow depths were collected as validation data. These measurements were taken next to iButtons periodically throughout the winter, and notes on other precipitation types were also recorded. At Site B (TA6 Meteorological Station), a nearby sensor collected snow depths throughout the winter. This dataset contains one *.csv file of snow/ground interface temperatures at two sites, one *.csv file of manually collected snow depths, and one *.kml file of sensor locations. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).
54 ENVIRONMENTAL SCIENCES↗
Adjoint Waveform Tomography for Crustal and Upper Mantle Structure the Middle East and Southwest Asia for Improved Waveform Simulations Using Openly Available Broadband Data
We present a new model of radially anisotropic seismic wavespeeds for the crust and upper mantle of a broad region of the Middle East and Southwest Asia (MESWA) derived from adjoint waveform tomography. We inverted waveforms from 192 Global Centroid Moment Tensor earthquakes (MW 5.5-7.0) recorded by over 1000 openly available broadband seismic stations from permanent and temporary networks in the region. Spatial coverage of the available data is highly uneven due to earthquakes clustered along plate boundaries and sparse coverage of open seismic networks in the region. We considered three possible starting models: the SPiRaL global model (Simmons et al., 2021); MEC-1 (Kaviani et al., 2020); and CSEM2.0 (Noe et al., 2023). Because the SPiRaL model provides good fits to the observed waveforms measured by the time-bandwidth product of selected windows in several period bands, provides all the necessary parameters and covers the entire domain we used it for the starting model with the period band 50-100 seconds. Inversion iterations proceeded using time-frequency phase misfits in six stages and 54 total iterations reducing the minimum period to 30 seconds. Our final model, MESWA, provides improved waveform fits compared to the starting model for both the data used in the inversion and an independent validation data set of 66 events. Two metrics of waveform fit (the time-frequency phase misfit used in the optimization and normalized L2 misfit) were both reduced by nearly 60% for both data sets and MESWA provides significantly larger misfit reductions relative to the SPiRaL model than the MEC-1 or CSEM models. We also find that MESWA provides a larger time-bandwidth product of selected windows indicating that more information content of the observed waveforms is explained by MESWA than the other models. Our new model reveals tectonic features imaged by other studies and methods but in a new holistic model of shear and compressional wavespeeds (v S and v P , respectively) with anisotropy covering the crust and uppermost mantle of a larger domain. MESWA has smaller scale-length features and tends to sharpen some features relative to the SPiRaL starting model. Examples include: low crustal v S in the TurkishIranian Plateau, Zagros Mountains, Afghan Central Blocks and Sulaiman Fold Belt; low mantle vSfollowing divergent (Gulf of Aden, Red Sea) and transform (Dead Sea Fault) margins of the Arabian Plate; low and high v S in the mantle beneath the Arabian Shield and Platform, respectively. Low vS is imaged below Cenozoic volcanic centers of the Arabian Peninsula, the so-called Mecca-Madina-Nafud (MMN) Line. Positive anisotropy (v SH > v SV ) is inferred for asthenospheric depths across the region except where up/downwelling may influence fabric alignment (e.g. Afar, Red Sea, Arabian Shield). Elevated vS tracks Makran subduction under southeast Iran. MESWA resembles the SPiRaL model in its long-wavelength structure, but enhances shorter wavelengths features on the order of 200 km and smaller. The resulting model could be used for as a starting model for further improvements, say using waveforms from in-country seismic networks that are not openly available or smaller-scale studies targeting shorter period waveforms. The model also could be used for source characterization and moment tensor inversion to improve earthquake hazard studies and nuclear explosion monitoring.
58 GEOSCIENCES↗
Soil organic matter and plant carbon allocated to nitrogen acquisition simulated by the FUN-BioCROP model
This data package contains the model input, results, and validation data from Juice et al (citation below). The FUN-BioCROP model (Fixation and Uptake of Nitrogen- Bioenergy Carbon, Rhizosphere, Organisms, and Protection) advances the field of bioenergy modeling by integrating new empirical paradigms of the role of belowground processes in shaping coupled carbon (C) and nitrogen (N) cycles. It was developed by modifying the FUN-CORPSE model (Fixation and Uptake of Nitrogen- Carbon, Organisms, Rhizosphere, and Protection in the Soil Environment, Sulman et al. 2017 Ecology Letters) for use in bioenergy systems by including mechanistic tillage, organic matter addition, nitrogen fertilization, harvest, and feedstock-specific parameters, and to be driven by DayCent plant productivity and biomass data.
biofuel sustainability↗
Analysis of Particle Image Velocimetry (PIV) Data for Application to Subsonic Jet Noise Studies
Global velocimetry measurements were taken using Particle Image Velocimetry (PIV) in the subsonic flow exiting a 1 inch circular nozzle in an attempt to better understand the turbulence characteristics of its shear layer region. This report presents the results of the PIV analysis and data reduction portions of the test and details the processing that was done. Custom data analysis and data validation algorithms were developed and applied to a data ensemble consisting of over 750 PIV 70 mm photographs taken in the 0.85 mach flow facility. Results are presented detailing spatial characteristics of the flow including ensemble mean and standard deviation, turbulence intensities and Reynold's stress levels, and 2-point spatial correlations.
Blackshire, James L.↗
Fuzzy Logic Enhanced Digital PIV Processing Software
Digital Particle Image Velocimetry (DPIV) is an instantaneous, planar velocity measurement technique that is ideally suited for studying transient flow phenomena in high speed turbomachinery. DPIV is being actively used at the NASA Glenn Research Center to study both stable and unstable operating conditions in a high speed centrifugal compressor. Commercial PIV systems are readily available which provide near real time feedback of the PIV image data quality. These commercial systems are well designed to facilitate the expedient acquisition of PIV image data. However, as with any general purpose system, these commercial PIV systems do not meet all of the data processing needs required for PIV image data reduction in our compressor research program. An in-house PIV PROCessing (PIVPROC) code has been developed for reducing PIV data. The PIVPROC software incorporates fuzzy logic data validation for maximum information recovery from PIV image data. PIVPROC enables combined cross-correlation/particle tracking wherein the highest possible spatial resolution velocity measurements are obtained.
Wernet, Mark P.↗
AI Curation Methods for NASA Scientific Data
The NASA Open Science Data Repository (OSDR) serves as a central hub for sharing and accessing NASA's vast collection of scientific data, supporting researchers across diverse fields. To enhance the efficiency, accuracy, and accessibility of this data, we are leveraging advanced artificial intelligence (AI) techniques as part of the AI for Curation project. By integrating large language models (LLMs) into our data curation workflow, we aim to streamline the entire process—from data submission to user interaction. This initiative focuses on improving key areas, including data ingestion, curation, and user engagement with curated datasets, impacting multiple domains and a wide user base. First, we are developing tools that can automatically parse data in various formats, using LLMs to convert unstructured data into structured, standardized formats. This reduces the manual effort required for curation, allowing curators to focus on more critical scientific analyses. Additionally, AI and machine learning (ML) models are being implemented to automate data validation and verification, ensuring the highest standards of data quality and reliability. Finally, we are creating a conversational AI agent to interact with the curated scientific studies in OSDR, helping users easily navigate the repository and access relevant data. By enhancing data discoverability and accessibility, these advancements will foster new research opportunities and promote the principles of open science.
Walter Alvarado↗
Development of process model of CESAR1 solvent system and validation with large pilot data
Presented at the 16th International Conference on Greenhouse Gas Control Technologie in Lyons, France.
Morgan, Joshua↗