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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Muon neutrino charged current single pion production on various targets in the MINERvA detector

Measurements of neutrino oscillation parameters at accelerator-based experiments require precise knowledge of neutrino interaction cross sections. A significant fraction of neutrino interactions observed in these experiments produce single charged pions. While single charged pion production has been measured on hydrocarbon and water, few precise measurements exist for heavier targets, and there are no high statistics measurements that directly compare pion production on different targets. This thesis measures differential cross sections of muon neutrino charged current single charged pion production with no other mesons in the final state in a neutrinobeam with a mean energy of ≈ 6 GeV. The pion production is studied on targets of scintillator, carbon, water, iron, and lead at MINERvA, a neutrino cross section experiment located in the NuMI beamline at Fermilab. These measured cross sections are differential in μ - and π + kinematics. A strong suppression of low Q 2 and an enhancement of low π are observed relative to commonly used neutrino interaction models in both the light and heavy nuclear targets. Incorporation of these observed effects in future neutrino oscillation experiments will improve their ability to measure energy of neutrino interactions, and therefore measure the parameters governing neutrino oscillations.

Bercellie, Aaron↗
DOE OSTI2022

DarkNews: a Python-based event generator for heavy neutral lepton production in neutrino-nucleus scattering

We introduce DarkNews, a lightweight Python-based Monte-Carlo generator for beyond-the-Standard-Model neutrino-nucleus scattering. The generator handles the production and decay of heavy neutral leptons via additional vector or scalar mediators, as well as through transition magnetic moments. DarkNews samples pre-computed neutrino-nucleus upscattering cross sections and heavy neutrino decay rates to produce dilepton and single-photon events in accelerator neutrino experiments. We present two case studies with differential distributions for models that can explain the MiniBooNE excess. The aim of this code is to aid the neutrino theory and experimental communities in performing searches and sensitivity studies for new particles produced in neutrino upscattering.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Physiochemical Machine Learning Models Predict Operational Lifetimes of CH3NH3PbI3 Perovskite Solar Cells

Halide perovskites are promising photovoltaic (PV) materials with the potential to lower the cost of electricity and greatly expand the penetration of PV if they can demonstrate long-term stability under illumination in the presence of moisture and oxygen. The solar cell service lifetime as quantified by the T80 (the time required for the power conversion efficiency to drop to 80% of its starting value) is a useful metric to assess stability. The T80 for utility, commercial, or residential PV systems needs to be several decades in order to yield low-cost electricity, and thus it is not practical to directly measure the T80. It would be useful if T80 could be predicted from the initial dynamics of a solar cell’s performance, but until now no models have been developed to forecast T80. In this work, we report the development of machine learning models to predict T80 of ITO/NiOx/CH3NH3PbI3/C60/BCP/Ag solar cells operating at maximum power point under 1-sun equivalent photon flux in air at varying temperatures and relative humidities. Efficiency losses are driven by short-circuit current and fill factor, indicating that chemical decomposition of the perovskite is a major contributor to degradation. Spatial patterns evident from in situ dark field optical microscopy suggest that the electric field gradient at device edges plays a significant role in perovskite decomposition, along with photochemical reactions with O2 and H2O. Models are trained using a menu of features from three distinct categories: (i) features based on measurements of the initial rates of change of device parameters, (ii) features based on the ambient conditions during operation (temperature, & partial pressure of H2O), and (iii) features based on underlying physics and chemistry. We show that a theory-based physiochemical feature derived from a model of the chemical reaction kinetics of the rate of degradation of the CH3NH3PbI3 is particularly valuable for prediction. This physiochemical feature was selected as the first or second most dominant feature in the best performing models. With a dataset consisting of 45 accelerated degradation experiments with T80 that range over a factor of 30, the model predicts T80 with an accuracy of about 40% (|predicted T80 - observed T80| / observed T80) on samples not used in training. This hybrid ML approach should be effective when applied to other compositions, device architectures, and advanced packaging schemes.

14 SOLAR ENERGY↗
DOE OSTI2022

Physiochemical Machine Learning Models Predict Operational Lifetimes of CH3NH3PbI3 Perovskite Solar Cells

Halide perovskites are promising photovoltaic (PV) materials with the potential to lower the cost of electricity and greatly expand the penetration of PV if they can demonstrate long-term stability under illumination in the presence of moisture and oxygen. The solar cell service lifetime as quantified by the T80 (the time required for the power conversion efficiency to drop to 80% of its starting value) is a useful metric to assess stability. The T80 for utility, commercial, or residential PV systems needs to be several decades in order to yield low-cost electricity, and thus it is not practical to directly measure the T80. It would be useful if T80 could be predicted from the initial dynamics of a solar cell’s performance, but until now no models have been developed to forecast T80. In this work, we report the development of machine learning models to predict T80 of ITO/NiOx/CH3NH3PbI3/C60/BCP/Ag solar cells operating at maximum power point under 1-sun equivalent photon flux in air at varying temperatures and relative humidities. Efficiency losses are driven by short-circuit current and fill factor, indicating that chemical decomposition of the perovskite is a major contributor to degradation. Spatial patterns evident from in situ dark field optical microscopy suggest that the electric field gradient at device edges plays a significant role in perovskite decomposition, along with photochemical reactions with O2 and H2O. Models are trained using a menu of features from three distinct categories: (i) features based on measurements of the initial rates of change of device parameters, (ii) features based on the ambient conditions during operation (temperature, & partial pressure of H2O), and (iii) features based on underlying physics and chemistry. We show that a theory-based physiochemical feature derived from a model of the chemical reaction kinetics of the rate of degradation of the CH3NH3PbI3 is particularly valuable for prediction. This physiochemical feature was selected as the first or second most dominant feature in the best performing models. With a dataset consisting of 45 accelerated degradation experiments with T80 that range over a factor of 30, the model predicts T80 with an accuracy of about 40% (|predicted T80 - observed T80| / observed T80) on samples not used in training. This hybrid ML approach should be effective when applied to other compositions, device architectures, and advanced packaging schemes.

14 SOLAR ENERGY↗
DOE OSTI2023

First Measurement of Inclusive Muon Neutrino Charged Current Triple Differential Cross Section on Argon

The field of accelerator neutrino experiments is entering an era of precision oscillation measurements where the remaining unknown neutrino measurements will be determined. The upcoming DUNE and Hyper-K experiments aim to determine the neutrino mass hierarchy and degree of Charge-Parity (CP) violation in the neutrino sector, providing potential insight on the matter-antimatter imbalance observed in the universe. However, these experiments require highly accurate measurements, and neutrino cross section modeling uncertainties may limit their capabilities. Cross section measurements at current- generation experiments can aid the development of neutrino interaction models to reduce these uncertainties. This is especially true for measurements of neutrino energy, as it drives neutrino oscillations and is of key importance to oscillation experiments. The MicroBooNE experiment uses a Liquid Argon Time Projection Chamber (LArTPC) to produce neutrino-argon cross sections as one of its physics goals. The MicroBooNE detector’s fully active volume, precision reconstruction, and calorimetry information are leveraged in the Wire-Cell analysis to produce a muon neutrino selection that is 92% pure while maintaining 68% efficiency. A reconstruction chain featuring a fully 3D charge reconstruction and a graph-based particle trajectory fit are used to produce accurate measurements of lepton kinematics as well as visible hadronic energy produced in a neutrino interaction. This thesis presents the first neutrino-argon triple-differential cross section measurement, targeting inclusive charged-current final states. Wiener SVD unfolding is used to produce a measurement over neutrino energy, muon momentum, and muon scattering angle. A series of constrained goodness of fit tests are used to demonstrate the validity of MicroBooNE’s model in describing the distribution of reconstructed kinematics seen in data to ensure the accuracy of unfolding. The validated unfolding to neutrino energy represents a step forward in the field of neutrino cross sections, and demonstrates the capabilities of the LArTPC detector.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Non-contact Real-time Target Health Monitor

Targets are an essential part of many accelerator-based experiments, yet their constant radiation exposure eventually affects their internal structure and, consequently, their properties. Current methods typically involve either direct contact with the target or complete removal of the system, which may not be the most efficient for assessing radiation damage. For this reason, a system has been proposed that will monitor a target s radiation damage without the need for direct contact or removal. This sensor will achieve this by measuring the reflectivity of S- and P-polarized waves, which are expected to change measurably due to radiation-induced alterations. As is commonly done, smaller-scale tests were performed to ensure that the necessary equipment was functioning correctly. Once all equipment is tested, the next step will be to perform reflectivity measurements using a tungsten sample, a material often used in targets. Longer-term work will involve scaling up the system and implementing higher-energy beams. This sensor will enable a more comprehensive study of radiation damage in materials and is being considered for projects such as Mu2e, Mu2e-II, LBNF, AMF, and muon colliders.

Agosto Reyes, Alanice↗
DOE OSTI2025

Revisiting Gauge Ambiguities for DUNE Precision

The de Forest prescription for handling off-shell initial states in the impulse approximation for lepton-nucleus scattering breaks gauge invariance. We discuss existing methods to address this problem and handle the form factor scale ambiguity. We demonstrate that the irreducible differences between the prescriptions are significant compared to the precision expected of next-generation accelerator neutrino experiments. A novel approach directly using the off-shell currents is proposed as a systematically improvable alternative.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Measurement of the muon neutrino charged-current mesonless cross section in the NOvA near detector

NOvA is a long-baseline accelerator neutrino experiment at Fermilab. Its physics goals include precision neutrino oscillation measurements, neutrino interaction cross-section measurements and beyond Standard Model explorations. We present a measurement of muon neutrino charged-current cross section with zero mesons in the final state at the NOvA near detector. This measurement is performed as a function of the kinematics of the final state muon. Our chosen interaction channel is especially sensitive to quasielastic and meson exchange current interactions and it provides handles for constraining the cross section systematic uncertainties in oscillation analyses in present and future experiments. For particle identification, we use a convolutional neural network (CNN) trained on individual particles simulated in the NOvA Near detector. This allows us to select the desired signal while reducing the potential bias from neutrino interaction modeling. We study strategies for constraining the remaining charged-pion background via Michel electron information in a template fitting approach. The main experimental result is a two-dimensional differential cross section as a function of final-state muon kinetic energy and polar angle. The parameters of this measurement, including binning and unfolding, were optimized to reduce the expected systematic uncertainty in the total cross section. The final result shows good agreement with the main GENIE-based simulation framework that was independently fine-tuned in NOvA. We finally propose improvements and subsequent steps that build on this analysis and further dissect the final states of neutrino interactions. This work has been supported by US DOE grant DE-SC0015684.

Sánchez Falero, Sebastián Jesús [Iowa State U.]↗
DOE OSTI2026

A Measurement of the Pion-Energy Dependence of Muon Neutrino Charged-Current Scattering to Final States With One Charged Pion in NOvA

The study of neutrino oscillations is a main priority for particle physics as the most immediately tractable lever on physics beyond the Standard Model. In particular, more insight into violation of the combined symmetry of charge-conjugation plus parity could yield clues to the origin of matter-antimatter asymmetry, and in some theoretical frameworks the neutrino mass could give insights into dark matter. NOvA is a long-baseline accelerator neutrino experiment with both a near and far detector that seeks to measure several of the parameters of the neutrino mixing matrix, as well as carry out a broad program of additional physics. NOvA has innovated and developed a variety of techniques in the space of neutrino physics, including expanding the use of machine learning techniques in reconstruction. NOvA has also set the stage for the next generation US-based long baseline experiment, DUNE. This dissertation details the creation of a new neutrino interaction vertex reconstruction package for NOvA, which offers enormous improvements in accuracy above the previous vertexer it replaces. This is accomplished using a Convolutional Visual Network trained on large datasets of simulated events. The vertexer is validated thoroughly against data. This dissertation also presents a cross-section measurement for $\nu_\mu + N \rightarrow \mu^- + 1\pi^\pm + X$ (where X does not include additional charged pions) binned in pion kinetic energy, a challenging measurement in general and for NOvA in particular. Measurements like this provide crucial inputs for neutrino interaction models utilized by neutrino oscillation experiments. This measurement in particular is important to the energy ranges relevant for DUNE in a band not well-covered by any other experiment.

Ewart, Erin [Indiana U., Bloomington (main)]↗
NASA NTRS1995

Quick Look Report of Acceleration Measurements on Mir Space Station During Mir-16

The NASA Microgravity Science and Applications Division (MSAD) sponsors the Space Acceleration Measurement System (SAMS) to support microgravity science experiments with microgravity acceleration measurements. In the past, SAMS was flown exclusively on the NASA Orbiters. MSAD is currently sponsoring science experiments participating in the Shuttle-Mir Science Program in cooperation with the Russians on the Mir space station. Included in the complement of MSAD experiments and equipment is a SAMS unit installed on the Mir space station. On 25 August 1994, the SAMS unit was launched on a Russia Progress vehicle to the Mir space station. The SAMS unit will support science experiments from the U.S. and Russia in a manner similar to the Orbiter missions by measuring the microgravity environments during the experiment operations. In October 1994, the SAMS unit recorded data on Mir for over fifty-three hours in seven different time periods to survey possible locations for future experiments. This report presents a quick look at the data and the microgravity environment during the time periods in which SAMS data were acquired. The Mir acceleration data were examined to ascertain gross attributes of the data. This report does not present an exhaustive examination of all possible activities due to the short time available to prepare this quick look report and due to the absence of complete timeline information during the SAMS recording time periods. Appendices A, B and C provide plots of the SAMS data for an overview of the microgravity environment at the times that data were recorded. Appendix D describes the procedures to access SAMS data by file transfer protocol (ftp) utilizing the internet. Appendix E contains a user comment sheet.

Delombard, Richard↗
DOE OSTI2023

A Review of the Mechanical Properties of Materials Used in Nb 3 Sn Magnets for Particle Accelerators

Superconducting magnets experience significant thermo-mechanical loads throughout their life cycle. These are introduced by the electro-magnetic forces during powering, but also by the prestress applied in many magnet designs. Further to this, the large thermal excursion that components of different materials experience can generate significant internal forces. The loads are also experienced by the superconducting coils, whose critical current can decrease as a consequence of the applied strain. It is then crucial to predict the overall mechanical behavior and conservatively design a magnet, avoiding failure of the mechanical components and of the superconducting coils. Finite Element Analysis (FEA) is generally used to perform these tasks, but its results rely heavily on the material properties and models used. This is in particular true for the coil composite, which is simplified to allow reasonable model sizes in full magnet models. Here we present the state-of-art knowledge of the mechanical properties of the materials mostly used in superconducting magnet construction. We review elastic and plastic properties at room and cryogenic temperature, thermal contraction, and summarize the state-of-art failure criteria for these materials. Finally, the paper summarizes the present understanding of the mechanical behavior and limits of Nb3Sn coils. For the first time, an orthotropic failure criteria is proposed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1972

Comparative changes in plasma protein concentration, hematocrit and plasma volume during exercise, bedrest and + Gz acceleration.

Discussion of experiments which indicate that under conditions of a constant red cell volume the proportional changes in hematocrit and plasma volume during exercise are never equal. On the basis of direct measurements and calculated changes of plasma volume it is concluded that during maximal exercise there is a small loss of protein from the plasma. It is clear that changes in content of blood constituents can only be evaluated correctly after determination of changes in plasma volume.

Van Beaumont, W.↗
DOE OSTI2024

Platform Of Optimal Experiment Management

The platform of optimal experiment management, POEM, powered with automated machine learning to accelerate the discovery of optimal solutions, and automatically guide the design of experiments to be evaluated. POEM currently supports 1) random model explorations for experiment design, 2) sparse grid model explorations with Gaussian Polynomial Chaos surrogate model to accelerate experiment design ,3) time-dependent model sensitivity and uncertainty analysis to identify the importance features for experiment design, 4) model calibrations via Bayesian inference to integrate experiments to improve model performance, and 5) Bayesian optimization for optimal experimental design. In addition, POEM aims to simplify the process of experimental design for users, enabling them to analyze the data with minimal human intervention, and improving the technological output from research activities.

Wang, Congjian [Idaho National Laboratory (INL), I↗
DOE OSTI2021

Rock Valley Accelerated Weight Drop Preliminary P-wave Tomographic Model

An active source experiment using an accelerated weight drop was conducted in Rock Valley, Nevada National Security Site, during the spring of 2021 in order to characterize the shallow seismic structure of the region. P-wave first arrival travel times picked from this experiment were used to construct a preliminary 3-D compressional wave speed model over an area that is roughly 4 km wide east-west and 8 km north-south to a depth of about 500-600 m below the surface, but with primary data concentration along the transects of the experimental lines. The preliminary model shows good correlation with basic geology and surface features, but geological interpretation is not the focus of this report. We describe the methods used in the tomographic inversion of the data and show results from this preliminary P-wave model.

42 ENGINEERING↗
NASA NTRS1977

Cancellation of residual spacecraft accelerations for zero-G space physics experiments

The Drop Dynamics Module houses an acoustic positioning system which counteracts the effects of small accelerations of a spacecraft and thus allows long-term study of free-floating materials such as liquid drops. The acoustic positioning system provides an acoustic 'well' in the center of the experiment chamber. Data collection is by cinematographic photography. The module subsystems are discussed.

Stephens, J. B.↗
DOE OSTI2023

The present and future status of heavy neutral leptons

Abstract The existence of nonzero neutrino masses points to the likely existence of multiple Standard Model neutral fermions. When such states are heavy enough that they cannot be produced in oscillations, they are referred to as heavy neutral leptons (HNLs). In this white paper, we discuss the present experimental status of HNLs including colliders, beta decay, accelerators, as well as astrophysical and cosmological impacts. We discuss the importance of continuing to search for HNLs, and its potential impact on our understanding of key fundamental questions, and additionally we outline the future prospects for next-generation future experiments or upcoming accelerator run scenarios.

Abdullahi, Asli M.↗
NASA NTRS1980

Generation and propagation of an electromagnetic pulse in the Trigger experiment and its possible role in electron acceleration

Instruments onboard the Trigger payload detected a large-amplitude, low-frequency, electric field pulse which was observed with a time delay consistent only with an electromagnetic wave. A model for this perturbation is constructed, and the associated field-aligned current is calculated as a function of altitude. This experiment may simulate the acceleration mechanism which results in the formation of auroral arcs, and possibly even other events in cosmic plasmas.

Kelley, M. C.↗