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Results for “field validation results”

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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NASA NTRS2000

Aeroelastic Response of Swept Aircraft Wings in a Compressible Flow Field

The present study addresses the subcritical aeroelastic response of swept wings, in various flight speed regimes, to arbitrary time-dependent external excitations. The methodology based on the concept of indicial functions is carried out in time and frequency domains. As a result of this approach, the proper unsteady aerodynamic loads necessary to study the subcritical aeroelastic response of the open/closed loop aeroelastic systems, and of flutter instability, respectively are obtained. Validation of the aeroelastic model is provided, and applications to subcritical aeroelastic response to blast pressure signatures are illustrated. In this context, an original representation of the aeroelastic response in the phase-space is displayed, and pertinent conclusions on the implications of a number of selected parameters of the system are outlined.

Marzocca, Piergiovanni↗

DOE OSTI2022

Focusing ions at atmospheric pressure using nonlinear DC voltage sequences applied to a stacked ring ion guide

Many modern ion mobility (IM) and mass spectrometers (MS) operate under low pressure (= 10 Torr) and employ high voltage radiofrequencies (RF) to provide ion confinement. Unfortunately, RF effectiveness drastically decreases as pressure increases, and few techniques for focusing ions at elevated pressures exist. Here we demonstrate a new approach for focusing ions at atmospheric pressure (AP) by applying nonlinear DC voltage sequences following quadratic and power (exponential) functions to a stacked ring ion guide. In this work, we used ion trajectory simulations to rigorously explore how ions react to nonlinear electric fields and validate the simulations with a set of ion current measurements performed at AP. Ion trajectory simulations show that ions initially defocus near the entrance of the device but then become intensely focused as they travel through the device. Contour plots for both nonlinear voltage sequences show electric field lines that increasingly curve inwards as a function of distance, resulting in spatial ion focusing. Experimental ion current and spot size measurements were performed at AP using a 10-cm stacked ring ion guide and a segmented Faraday cup detector. Quadratic sequences produced ~5% smaller spot sizes (~22.8 mm) and ~25% higher ion current compared to a linear voltage sequence (~24.0 mm). Alternatively, power sequences produced ~64% smaller spot sizes (~8.7 mm), albeit with ~10x lower ion current. However, both nonlinear voltage sequences produced similar ion currents at the center of the Faraday cup detector, indicating that higher ion densities are achieved when using nonlinear voltage gradients. These results demonstrate a new way to focus ions at AP, and the capabilities demonstrated here provide fundamental insights on how to keep ions inside analytical devices at elevated pressures without RF.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Modeling Framework to Predict Melting Dynamics at Microstructural Defects in TNT-HMX High Explosive Composites

Many high explosive (HE) formulations are composite materials whose microstructure is understood to impact functional characteristics. Interfaces are known to mediate the formation of hot spots that control their safety and initiation. Here, to study such processes at molecular scales, we developed all-atom force fields (FFs) for Octol, a prototypical HE formulation comprised of TNT (2,4,6-trinitrotoluene) and HMX (octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine). We extended a FF for TNT and recasted it in a form that can be readily combined with a well-established FF for HMX. The resulting FF was extensively validated against experimental results and density functional theory calculations. We applied the new combined TNT-HMX FF to predict and rank surface and interface energies, which indicate that there is an energetic driver for coarsening of microstructural grains in TNT-HMX composites. Finally, we assess the impact of several microstructural environments on the dynamic melting of TNT crystal under ultrafast thermal loading. We find that both free surfaces and planar material interfaces are effective nucleation points for TNT melting. However, MD simulations show that TNT crystal is prone to superheating by at least 50 K on subnanosecond time scales and that the degree of superheating is inversely correlated with surface and interface energy. The modeling framework presented here will enable future studies on hot spot formation processes in accident scenarios that are governed by strong coupling between microstructural interfaces, material mechanics, momentum and energy transport, phase transitions, and chemistry.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Spatiotemporal dynamics of fast electron heating in solid-density matter via XFEL

Abstract High-intensity, short-pulse lasers are crucial for generating energetic electrons that produce high-energy-density (HED) states in matter, offering potential applications in igniting dense fusion fuels for fast ignition laser fusion. High-density targets heated by these electrons exhibit spatially non-uniform and highly transient conditions, which have been challenging to characterize due to limitations in diagnostics that provide simultaneous high spatial and temporal resolution. Here, we employ an X-ray Free Electron Laser (XFEL) to achieve spatiotemporally resolved measurements at sub-micron and femtosecond scales on a solid-density copper foil heated by laser-driven fast electrons. Our X-ray transmission imaging reveals the formation of a solid-density hot plasma localized to the laser spot size, surrounded by Fermi degenerate, warm dense matter within a picosecond, and the energy relaxation occurring within the hot plasma over tens of picoseconds. These results validate 2D particle-in-cell simulations incorporating atomic processes and provide insights into the energy transfer mechanisms beyond current simulation capabilities. This work significantly advances our understanding of rapid fast electron heating and energy relaxation in solid-density matter, serving as a key stepping stone towards efficient high-density plasma heating and furthering the fields of HED science and inertial fusion energy research using intense, short-pulse lasers.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Interior soft x-ray tomography with sparse global sampling

To investigate the feasibility of interior imaging reconstruction in soft X-ray tomography for higher-resolution cellular imaging, including whole-cell imaging, we develop an alignment and reconstruction algorithm that combines a small number of sparse whole-cell images with a high-resolution local interior scan. Based on numerical simulations, we demonstrate that combined reconstructions mitigate the depth-of-field limitation in high-resolution scans, enable radiation dose optimization, and yield quantitative X-ray absorption values with sparse sampling. We further validate our numerical approach using experimental data from two different cell types and show that the combined reconstruction reliably provides high spatial resolution within an interior region of interest of a whole cell. The resulting sparse reconstruction framework offers robust, faithful visualization of cellular organelles in soft X-ray tomography. This mesoscale imaging strategy allows one to ‘scout’ and zoom into selected subcellular volumes of interest, enabling increased spatial resolution without sacrificing larger-volume imaging and providing information on the relative positions of all organelles within a cell.

3D imaging↗

DOE OSTI2022

Focusing Ions at Atmospheric Pressure using Nonlinear DC Voltage Sequences Applied to a Stacked Ring Ion Guide

Many modern ion mobility (IM) and mass spectrometers (MS) operate under low pressure (= 10 Torr) and employ high voltage radiofrequencies (RF) to provide ion confinement. Unfortunately, RF effectiveness drastically decreases as pressure increases, and few techniques for focusing ions at elevated pressures exist. Here we demonstrate a new approach for focusing ions at atmospheric pressure (AP) by applying nonlinear DC voltage sequences following quadratic and power (exponential) functions to a stacked ring ion guide. We used ion trajectory simulations to rigorously explore how ions react to nonlinear electric fields and validate the simulations with a set of ion current measurements performed at AP. Ion trajectory simulations show that ions initially defocus near the entrance of the device but then become intensely focused as they travel through the device. Contour plots for both nonlinear voltage sequences show electric field lines that increasingly curve inwards as a function of distance, resulting in spatial ion focusing. Experimental ion current and spot size measurements were performed at AP using a 10-cm stacked ring ion guide and a segmented Faraday cup detector. Quadratic sequences produced ~5% smaller spot sizes (~22.8 mm) and ~25% higher ion current compared to a linear voltage sequence (~24.0 mm). Alternatively, power sequences produced ~64% smaller spot sizes (~8.7 mm), albeit with ~10x lower ion current. However, both nonlinear voltage sequences produced similar ion currents at the center of the Faraday cup detector, indicating that higher ion densities are achieved when using nonlinear voltage gradients. These results demonstrate a new way to focus ions at AP, and the capabilities demonstrated here provide fundamental insights on how to keep ions inside analytical devices at elevated pressures without RF.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Predicting cutoff L-shells of solar protons using the GPPSn particle dataset

Solar energetic protons (SEPs) arriving at the Earth trigger severe radiation storms in the near-Earth space, directly impacting space missions operating at various altitudes. Therefore, monitoring SEP events and predicting the penetration depths of solar protons are critical for aerospace sectors. Building on previous efforts, here we demonstrate the feasibility of using proton measurements from the Global Prompt Proton Sensor network (GPPSn), enabled by Los Alamos National Laboratory developed combined X-ray dosimeters aboard GPS satellites, to characterize and predict the penetration of solar protons into the geomagnetic field. The inclined medium-Earth-orbits (MEOs) of the global GPS constellation offer a unique advantage of allowing simultaneous measurements of penetrating solar protons inside both open- and closed-field line regions. Therefore, the L-profiles of ∼10s–100 MeV solar protons and their associated cutoff L-shells can be determined from the GPPSn dataset, using predefined threshold proton flux values rather than traditional flux ratios. After examining a list of SEP event intervals across solar cycles 23, 24 and 25—including the 2024 Mother’s Day superstorm, we showcase how the latest GPPSn proton dataset (release v1.10), reprocessed and calibrated, can not only be used to monitor solar proton distributions inside the dynamic geomagnetic field for individual events, but also to derive a new empirical model linking cutoff L-shells with several key space weather parameters. This newly developed SEPCL-MEO model demonstrates high predictive performance; for example, predictions for > 30 MeV solar protons yield a correlation coefficient of 0.85 and performance efficiency of 0.67 when validated against GPPSn observations. Results from this pilot study underscores the scientific and operational value of the GPPSn dataset, and this dataset—when paired with machine-learning techniques—can play a critical role in observing and predicting the effects of future incoming SEP events, including extreme ones.

58 GEOSCIENCES↗

DOE OSTI2024

Statistical Validation of Multiple Related Data Sets—Case Study Using Interstellar Boundary Explorer Satellite Data

Abstract Space scientists often face the question of whether data collected by different instruments are measurements of the same source population. This paper proposes a statistical validation method for evaluating the agreement between such related data sets. It offers a detailed case study focused on validating a new data set from the Interstellar Boundary Explorer (IBEX) mission, which serves as a practical how-to guide for similar analyses. Since 2008, the IBEX satellite has been gathering data on heliospheric energetic neutral atoms (ENAs) while being exposed to various sources of background noise, such as cosmic rays and solar energetic particles. The IBEX mission initially released only a qualified triple-coincidence (qABC) data product, which was designed to provide observations of ENAs free of background contamination. Further measurements revealed that the qABC data were in fact susceptible to contamination, having relatively low ENA counts and high background rates. To mitigate this issue, the mission team recently considered releasing a certain qualified double-coincidence (qBC) data product, which has roughly twice the detection rate of the qABC data product. This paper presents a simulation-based validation of the new qBC data product against the already-released qABC data product. The results show that the qBCs can plausibly be said to be measuring the same source population as the qABCs up to an average absolute deviation of 3.6%. Visual diagnostics provide additional confirmation of source rate coherence across data products. The framework introduced here is general and can be applied to other validation problems both within and outside the field of space physics.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1981

Synchrotron emissivity from mildly relativistic particles

A simple approximate method for the evaluation of the spectrum and directivity of the synchrotron radiation from an ensemble of particles in a given magnetic field is considered, taking into account the results of this method for the total emissivity at high harmonics. The general formula is presented along with the details of the derivation of the emissivity for an arbitrary energy spectrum and pitch angle distribution of particles. The emissivities for some commonly encountered particle distributions are provided and some empirical formulae valid for a large range of the parameters are given. The results from the analytic expressions are compared with those obtained by detailed numerical calculations. For isotropic pitch angle distributions, spectra from the simple analytic expressions agree with the numerical results to a high degree of accuracy even at lower harmonics.

Petrosian, V.↗

NASA NTRS1987

Exact-image method for Gaussian-beam problems involving a planar interface

The exact-image method, recently introduced for the solution of electromagnetic field problems involving sources above a planar interface between two homogeneous media, is shown to be valid also for sources located in complex space, which makes its application possible for Gaussian-beam analysis. It is demonstrated that the Goos-Hanchen shift and the angular shift of a TE-polarized beam are correctly given as asymptotic results by the exact-reflection-image theory. Also, the apparent-image location giving the correct Gaussian beam transmitted through the interface is obtained as another asymptotic check. The theory described here makes it possible to calculate the exact coupling from the Gaussian beam to the reflected and refracted beams as well as to the surface wave.

Lindell, Ismo V.↗

NASA NTRS1961

Calculation of Flow Fields from Bow-Wave Profiles for the Downstream Region of Blunt-Nosed Circular Cylinders in Axial Hypersonic Flight

A method by which known bow-wave profiles may be analyzed to give the flow fields around blunt-nosed cylinders in axial hypersonic flow is presented. In the method, the assumption is made that the pressure distribution curve in a transverse plane is similar to that given by blast- wave theory. Numerical analysis based on the one-dimensional energy and continuity equations then leads to distributions of all the flow variables in the cross section, for either a perfect gas or a real gas. The entire flow field need not be solved. Attention can be confined to any desired station. The critical question is the validity of the above assumption. It is tested for the case of a hemisphere cylinder in flight at 20,000 ft/sec. The flow is analyzed for three stations along the cylindrical afterbody, and found to compare very closely with the results of an exact (inviscid) solution. The assumed form of the pressure distribution occurs at stations as close as 1.2 diameters to the body nose. However, it is suggested that the assumption may not apply this far forward in general, particularly when bodies of nonsmooth contour are considered.

Seiff, Alvin↗

NASA NTRS2011

Applications of the BIOPHYS Algorithm for Physically-Based Retrieval of Biophysical, Structural and Forest Disturbance Information

Canopy reflectance model inversion using look-up table approaches provides powerful and flexible options for deriving improved forest biophysical structural information (BSI) compared with traditional statistical empirical methods. The BIOPHYS algorithm is an improved, physically-based inversion approach for deriving BSI for independent use and validation and for monitoring, inventory and quantifying forest disturbance as well as input to ecosystem, climate and carbon models. Based on the multiple-forward mode (MFM) inversion approach, BIOPHYS results were summarized from different studies (Minnesota/NASA COVER; Virginia/LEDAPS; Saskatchewan/BOREAS), sensors (airborne MMR; Landsat; MODIS) and models (GeoSail; GOMS). Applications output included forest density, height, crown dimension, branch and green leaf area, canopy cover, disturbance estimates based on multi-temporal chronosequences, and structural change following recovery from forest fires over the last century. Good correspondences with validation field data were obtained. Integrated analyses of multiple solar and view angle imagery further improved retrievals compared with single pass data. Quantifying ecosystem dynamics such as the area and percent of forest disturbance, early regrowth and succession provide essential inputs to process-driven models of carbon flux. BIOPHYS is well suited for large-area, multi-temporal applications involving multiple image sets and mosaics for assessing vegetation disturbance and quantifying biophysical structural dynamics and change. It is also suitable for integration with forest inventory, monitoring, updating, and other programs.

Peddle, Derek R.↗

NASA NTRS2017

Jet Noise Prediction Using Hybrid RANS/LES with Structured Overset Grids

Hybrid RANS/LES simulations using the structured overset grid approach and a low dissipation finite-difference method within the Launch Ascent and Vehicle Aerodynamics (LAVA) solver framework are presented for jet noise prediction. The simulations are part of a validation effort to demonstrate jet noise prediction capability, to assess noise characteristics of next generation quiet supersonic commercial jets. Results are compared with experimental data acquired in the Small Hot Jet Acoustic Rig in the Aeroacoustic Propulsion Laboratory at NASA Glenn Research Center. Details of the structured overset grids, numerical discretization, and turbulence model are provided. Near-field comparisons to PIV data and far-field comparisons to microphone data are discussed. Excellent agreement of time-averaged mean quantities along the jet center-line and lip-line are obtained. Good agreement with root-mean-squared (RMS) quantities along the jet center-line are also obtained. An over prediction of lip-line RMS at the nozzle exit is observed leading to a small over-prediction of side-line far-field noise (less than 2 dB). Good agreement with far-field noise in the Mach wave radiation directions is achieved.

Housman, Jeffrey A.↗

NASA NTRS2021

MOBSTER - IV. Detection of a new magnetic B-type star from follow-up spectropolarimetric observations of photometrically selected candidates

In this paper, we present results from the spectropolarimetric follow-up of photometrically selected candidate magnetic B stars from the MOBSTER project. Out of four observed targets, one (HD 38170) is found to host a detectable surface magnetic field, with a maximum longitudinal field measurement of 105±14 G. This star is chemically peculiar and classified as a^2 CVn variable. Its detection validates the use of TESS to perform a photometric selection of magnetic candidates. Furthermore, upper limits on the strength of a putative dipolar magnetic field are derived for the remaining three stars, and we report the discovery of a previously unknown spectroscopic binary system, HD 25709. Finally, we use our non-detections as case studies to further inform the criteria to be used for the selection of a larger sample of stars to be followed up using high-resolution spectropolarimetry.

A David-Uraz↗

DOE OSTI2022

Technical and Economic Evaluation of the First Ever Polymer Flood Field Pilot to Enhance the Recovery of Heavy Oils on Alaska's North Slope via Machine Assisted History Matching

Polymer flooding has become globally established as a potential enhanced oil recovery method for heavy oils. To determine whether this technology may be useful in developing the substantial heavy oil resources on the Alaska North Slope, a polymer flood field pilot commenced at the Milne Point Unit in August 2018. This study seeks to evaluate the results of the field pilot on a technical and economic basis. A reservoir simulation model is constructed and calibrated to predict the oil recovery performance of the pilot through machine-assisted reservoir simulation techniques. To replicate the early water breakthrough observed during waterflooding, transmissibility contrasts are introduced into the simulation model, forcing viscous fingering effects. In the ensuing polymer flood, these transmissibility contrasts are reduced to replicate the restoration of injection conformance during polymer flooding. Transmissibility contrasts are later reinstated to replicate fracture overextension interpreted in one of the producing wells. The calibrated simulation models produced at each stage of the history matching process are used to forecast oil recovery. These forecasts are used as input for economic analysis, incremental to waterflooding expectations. The simulation forecasts indicate that polymer flooding significantly increases the heavy oil production for this field pilot compared to waterflooding alone, yielding attractive project economics. However, meaningful variations between simulation scenarios demonstrate that a simulation model is only valid for prediction if flow behavior in the reservoir remains consistent with that observed during the history matched period. Critically, this means that a simulation model calibrated for waterflooding may not fully capture the technical and economic benefits of an enhanced oil recovery process such as polymer flooding. Subsequently, the simulation model and economic model are used in conjunction to conduct a sensitivity analysis for polymer flood design parameters, from which recommendations are provided for both the continued operation of the current field pilot and future polymer flood designs. The results demonstrate that a higher polymer concentration can be injected due to the development of fractures in the reservoir. The throughput rate should remain high without exceeding operating constraints. A calculated point-forward polymer utilization parameter demonstrates the decreasing efficiency of the polymer flood at later times in the pattern life. Future projects will benefit from starting polymer injection earlier in the pattern life. A pattern with tighter horizontal well spacing will observe a greater incremental benefit from polymer flooding.

Keith, Cody↗

DOE OSTI2022

Approaching PetaVolts per Meter Plasmonics Using Structured Semiconductors

A newly uncovered class of plasmons in the strongly excited limit opens access to unprecedented Petavolts per meter electromagnetic fields with wide-ranging, transformative impact. Unlike conventional plasmons, such plasmons are constituted by non-perturbative, large-amplitude oscillations of the ultradense, delocalized free electron Fermi gas inherent in conductive media. Here structured semiconductors doped to have an appropriate conduction electron density are introduced to tune the properties of the Fermi gas for matched excitation of large-amplitude plasmons using readily available electron beams which enables immediate experimental validation. Specifically, an electrostatic, surface “crunch-in” plasmon is collisionlessly excited by the beam launched inside a tube. Strong excitation due to matching results in relativistic oscillations of the electron gas and unravels unique phenomena. Relativistically induced ballistic electron transport comes about due to relativistic multifold increase in the mean free path and also leads to unconventional heat deposition beyond Ohm’s law. This explains the absence of observed damage or solid-plasma formation in past experiments on conductive samples interacting with electron bunches shorter than 10-13 seconds. Furthermore, relativistic momentum leads to copious tunneling of electron gas across the surface, which then crunches inside the tube. Relativistic effects along with large, localized electron density variations underlying these modes necessitate kinetic approach to theoretical and computational modeling. Kinetic model presented here demonstrates experimental viability of observing tens of gigavolts per meter plasmonic fields excited by matching readily available electron beams to plasmons in semiconductors with 1018cm-3 free electron density, and paves the way for Petavolts per meter plasmonics.

42 ENGINEERING↗

DOE OSTI2021

Measurement of charged-current $\nu_{\mu}$ and $\nu_e$ interactions with wire-cell in MicroBooNE towards a search for low-energy $\nu_e$ excess

This technote summarizes the existing work in searching for $\nu_e$ low-energy excess (eLEE) in MicroBooNE Booster Neutrino Beam (BNB) data stream based on the Wire-Cell event reconstruction paradigm. The charged-current $\nu_{\mu}$ and $\nu_e$ events are selected from the 5.3e19 POT data from the BNB beam and 2.06e20 POT data from Neutrinos at the Main Injector (NuMI) beam. The charged-current $\nu_e$ selection results from the BNB data that are sensitive to the eLEE search are not included. Various comparisons between data and Monte Carlo predictions are performed to validate the overall model and demonstrate the power of the analysis techniques.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

A Data-Agnostic, Continuous Machine Learning Framework for Application in High Energy Physics and Beyond: Phase 1 Final Scientific/Technical Report

This Phase 1 effort has focused on the development of continual learning frameworks for use in machine learning, specifically in the applied context of High Energy Physics (HEP). Machine learning (ML) is a transformative technology by which computers, typically through the use of neural networks, are able to perform tasks with proficiency that rivals or surpasses that of human users. Model Degradation & Catastrophic Forgetting are two undesired phenomena which can occur in ML where the performance of a model degrades when either deployed on novel data streams, or trained on novel data which are sufficiently different than the data the models were initially trained on. A natural example where these sorts of effects can be observed is in the performance of detectors in harsh environments, where the detector signature may change over the lifetime of the detector as it ages and deteriorates — precisely what occurs in the experiments conducted in HEP. Real world HEP data is therefore an excellent test-ground and use-case for Continual Learning paradigms, which are techniques used in ML to counteract these problems. Ensemble learning is one such technique, where multiple smaller models are trained on subsets of the overall data and are ensembled together during inference. The intuition behind this technique is that, although there are shifts in the distributions which govern the incoming data streams, these shifts are not expected to be homogeneous or global. If a sufficient diversity in solutions within the various sub-models has been achieved, then at least one sub-model is expected to retain its performance within the overall ensemble. One further strength of this approach is that the architectures of the various models do not need to be identical, and in fact even different modalities of data can naturally be combined in this way. This work focused on applying ensemble learning techniques to derive results using two main datasets, anomaly detection in HEP data & time-series forecasting in semiconductor manufacturing data. Semiconductor manufacturing involves data with surprising similarity to that of HEP (e.g. wafer maps look very similar to digi-occupancy maps) and Cerium Lab’s prominence within the semiconductor industry makes semiconductor manufacturing a natural opportunity for commercialization of this work. Our efforts have led to two strong results. The first is that we evaluated the proposed ensembling techniques using previously proposed machine learning architectures for use in anomaly detection, namely AutoEncoder based models and their derivatives. We also developed new architectures which have not been evaluated in this context before. In fact, this work marks the first use of Vision Transformers for anomaly detection in HEP. Second, we demonstrated that ensemble learning significantly improves model performance in scenarios prone to degradation, validating its effectiveness across both HEP and semiconductor datasets. These results further support ensemble learning as a powerful strategy for mitigating catastrophic forgetting and maintaining robust performance in evolving data environments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗