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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Mass extinctions: Persistent problems and new directions

Few contest that mass extinctions have punctuated the history of life, or that those events were so pervasive environmentally, taxonomically, and geographically that physical forcing factors were probably involved. However, consensus remains elusive on the nature of those factors, and on how a given perturbation - impact, volcanism, sea-level change, or ocean anoxic event - could actually generate the observed intensity and selectivity of biotic losses. At least two basic problems underlie these long-standing disagreements: difficulties in resolving the fine details of taxon ranges and abundances immediately prior to and after an extinction boundary and the scarcity of simple, unitary cause-and-effect relations in complex biological systems.

Jablonski, D.↗
DOE OSTI2026

D$e^+e^-$ffusion: Capturing the Beam-Beam Physics of $e^+e^-$ Collisions with Diffusion Models

Beam-induced backgrounds at high-luminosity $e^+e^-$ colliders, such as the FCC-ee, are dominated by incoherent pair creation (IPC), and require computationally expensive simulations with dedicated Monte Carlo (MC) event generators. Reliable detector and machine-detector interface studies necessitate event samples that are several orders of magnitude larger than what is practically attainable with existing MC. To alleviate this bottleneck, we present D$e^+e^-$ffusion, a denoising diffusion probabilistic model that operates as a permutation-equivariant, set-valued surrogate for fast IPC simulation. Trained on a small GuineaPig++ sample, D$e^+e^-$ffusion faithfully reproduces the marginal and joint kinematic, angular, and positional distributions of all three IPC production processes. In addition, we assess the fidelity at the detector level by propagating both Geant4 and D$e^+e^-$ffusion events through a Geant4 simulation of the CLD vertex detector and by training a transformer-based two-sample classifier; the classifier achieves an area under the ROC curve of $0.553 \pm 0.016$. The trained model generates events nearly four orders of magnitude faster than Geant4, paving the way for a fast-simulation surrogate for FCC-ee design studies.

Chahine, Antonio [Imperial Coll., London]↗
DOE OSTI2020

Finding wombling boundaries in LHC data with Voronoi and Delaunay tessellations

We address the problem of finding a wombling boundary in point data generated by a general Poisson point process, a specific example of which is an LHC event sample distributed in the phase space of a final state signature, with the wombling boundary created by some new physics. We discuss the use of Voronoi and Delaunay tessellations of the point data for estimating the local gradients and investigate methods for sharpening the boundaries by reducing the statistical noise. The outcome from traditional wombling algorithms is a set of boundary cell candidates with relatively large gradients, whose spatial properties must then be scrutinized in order to construct the boundary and evaluate its significance. Here we propose an alternative approach where we simultaneously form and evaluate the significance of all possible boundaries in terms of the total gradient flux. We illustrate our method with several toy examples of both straight and curved boundaries with varying amounts of signal present in the data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1982

The evolution of the mesoscale environment of severe local storms Preliminary modeling results

A mesoscale model is employed for predicting two severe weather events observed during thy 1979 SESAME field programs. Particular attention is given to the development and decay of a low-level jet, to the formation of a mesoscale convective complex (MCC) and its modification of lower- and upper-level circulation, to the formation of mesoscale regions of heavy precipitation, the intensification of surface warm and cold fronts, the formation of drylines, dynamic coupling of upper- and low-level jets, the formation of a mountain wave, and the formation and maintenance of capping inversions. A summary of the physics and parameters of a tornado outbreak and a heavy precipitation event are given for a simple bulk-PBL formulation with no heating. A ten-layer model was demonstrated to be sufficient for generating and maintaining distinct vertical gradients of temperature, moisture, and wind across low-level inversions.

Anthes, R. A.↗
DOE OSTI2022

Electrons for Neutrinos

The ability of current and next generation accelerator based neutrino oscillation measurementsto reach their desired sensitivity requires a high level of understanding of the neutrino-nucleus interactions. This includes precise estimation of the relevant cross sections for the incident neutrino energy from the measured final state particles. Incomplete understanding of these interactions can skew the reconstructed neutrino spectrum and thereby bias the extraction of fundamental oscillation parameters and searches for new physics. In this talk, I will present new results of wide phase-space electron scattering data, collected with the CLAS spectrometer at the Thomas Jefferson National Accelerator Facility (JLab), where the reconstruction of the incoming lepton energy from the measured final state is being tested. Disagreements with current event generators, used in the analysis of neutrino oscillation measurements, are observed which indicate underestimation of nuclear effects.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Deep convolutional neural networks for multi-scale time-series classification and application to disruption prediction in fusion devices

The multi-scale, mutli-physics nature of fusion plasmas makes predicting plasma events challenging. Recent advances in deep convolutional neural network architectures (CNN) utilizing dilated convolutions enable accurate predictions on sequences which have long-range, multi-scale characteristics, such as the time-series generated by diagnostic instruments observing fusion plasmas. Here we apply this neural network architecture to the popular problem of disruption prediction in fusion tokamaks, utilizing raw data from a single diagnostic, the Electron Cyclotron Emission imaging (ECEi) diagnostic from the DIII-D tokamak. ECEi measures a fundamental plasma quantity (electron temperature) with high temporal resolution over the entire plasma discharge, making it sensitive to a number of potential pre-disruptions markers with different temporal and spatial scales. Promising, initial disruption prediction results are obtained training a deep CNN with large receptive field ({$\sim$}30k), achieving an $F_1$-score of {$\sim$}91\% on individual time-slices using only the ECEi data.

convolutional neural networks↗
NASA NTRS2005

Health Management Applications for International Space Station

Traditional mission and vehicle management involves teams of highly trained specialists monitoring vehicle status and crew activities, responding rapidly to any anomalies encountered during operations. These teams work from the Mission Control Center and have access to engineering support teams with specialized expertise in International Space Station (ISS) subsystems. Integrated System Health Management (ISHM) applications can significantly augment these capabilities by providing enhanced monitoring, prognostic and diagnostic tools for critical decision support and mission management. The Intelligent Systems Division of NASA Ames Research Center is developing many prototype applications using model-based reasoning, data mining and simulation, working with Mission Control through the ISHM Testbed and Prototypes Project. This paper will briefly describe information technology that supports current mission management practice, and will extend this to a vision for future mission control workflow incorporating new ISHM applications. It will describe ISHM applications currently under development at NASA and will define technical approaches for implementing our vision of future human exploration mission management incorporating artificial intelligence and distributed web service architectures using specific examples. Several prototypes are under development, each highlighting a different computational approach. The ISStrider application allows in-depth analysis of Caution and Warning (C&W) events by correlating real-time telemetry with the logical fault trees used to define off-nominal events. The application uses live telemetry data and the Livingstone diagnostic inference engine to display the specific parameters and fault trees that generated the C&W event, allowing a flight controller to identify the root cause of the event from thousands of possibilities by simply navigating animated fault tree models on their workstation. SimStation models the functional power flow for the ISS Electrical Power System and can predict power balance for nominal and off-nominal conditions. SimStation uses realtime telemetry data to keep detailed computational physics models synchronized with actual ISS power system state. In the event of failure, the application can then rapidly diagnose root cause, predict future resource levels and even correlate technical documents relevant to the specific failure. These advanced computational models will allow better insight and more precise control of ISS subsystems, increasing safety margins by speeding up anomaly resolution and reducing,engineering team effort and cost. This technology will make operating ISS more efficient and is directly applicable to next-generation exploration missions and Crew Exploration Vehicles.

Alena, Richard↗
DOE OSTI2020

Dynamic PRA Methods to Evaluate the Impact on Accident Progression of Accident Tolerant Fuels

Accident tolerant fuels (ATFs) are new nuclear fuels developed in response to the accident at the Fukushima power station in March 2011. The goal of ATFs is to withstand accident scenarios through better performance compared to currently employed fuels (e.g., small-scale hydrogen generation). This paper targets a method for evaluating and comparing ATF performance from a probabilistic risk assessment (PRA) perspective by employing a newly developed combination of event trees and dynamic PRA methods. Compared to classical PRA methods based on event trees and fault trees, dynamic PRA can evaluate with higher resolution the safety impacts of physics dynamics and the timing/sequencing of events on the accident progression without the need to introduce overly conservative modeling assumptions and success criteria. In this paper, we analyze the impact on the accident progression of three different cladding configurations for two initiating events [a large break loss-of-coolant accident (LB-LOCA) and a station blackout (SBO)] by employing dynamic PRA methods. The goal is to compare the safety performance of ATFs (FeCrAl and Cr-coated cladding) and the currently employed Zr-based clad fuel. We employ two different strategies. The first focuses on the identification of success criteria discrepancies between the accident sequences generated by the classical PRA model and the set of simulation runs generated by dynamic PRA using ATF. The second one, on the other hand, directly uses dynamic PRA to evaluate the impact of timing of events (e.g., recovery actions) on accident progression. In conclusion, by applying these methods to the LB-LOCA and SBO initiating events, we show how dynamic PRA methods can provide analysts with detailed and quantitative information on the safety impact of ATFs.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Shock wave formation in the thermosphere by an earthgrazing fireball: Empirical evidence for volatile-enhanced hydrodynamic shielding

Hydrodynamic shielding is a theoretically well-established but observationally elusive and experimentally difficult-to-replicate phenomenon with implications that extend far beyond meteor physics. Rare earthgrazing meteoroids with infrasound signatures that penetrate to the ground can be used to probe hydrodynamic shielding that leads to strong shock formation at high altitude. Here, we report the first coordinated optical and multi-station infrasound observations of a centimeter-scale earthgrazing fireball that generated sustained cylindrical line shock at thermospheric altitudes near 92 km. The event was recorded by numerous optical stations and three infrasound arrays, allowing trajectory reconstruction, ablation behavior, acoustic source localization, and shock characteristics. Optical observations indicate early mechanical erosion and ablation/evaporation at exceptionally low dynamic pressure, consistent with a cometary or a porous, volatile-bearing CM chondritic object. Independent infrasound detections localize shock generation to multiple points along a 164 km trajectory segment near perigee. Weak-shock modeling yields a consistent blast radius of ∼30 m, implying an acoustic-equivalent source size far exceeding the physical dimensions of the ∼45 g nucleus. We demonstrate that classical gas dynamics and ablation-driven hydrodynamic shielding alone cannot account for these observations under ambient thermospheric conditions. We show that volatile release provides the additional flow-field density enhancement required to amplify hydrodynamic shielding, reduce the effective local Knudsen number, and sustain a shock envelope capable of radiating detectable infrasound. Furthermore, these results demonstrate that small, volatile-rich meteoroids can transiently establish continuum-like flow in rarefied environments.

Astrometry↗
DOE OSTI2023

Application of Quantum Machine Learning to High Energy Physics Analysis at LHC using IBM Quantum Computer Simulators and IBM Quantum Computer Hardware

Our group pioneers the use of Quantum Machine Learning (QML) on High Energy Physics analysis at LHC. We have successfully employed several QML classification algorithms in the ttH (Higgs production in association with a top quark pair) and Higgs to two muons (Higgs coupling to second generation fermions), two recent LHC flagship physics analysis, on gate-model quantum computer simulators and hardware. The simulation studies have been performed with the IBM Quantum Framework, Google Tensorflow Quantum Framework, and Amazon Braket Framework, and we have achieved good classification performance that is similar to the performances of the classical machine learning methods currently used in LHC physics analyses, classical SVM, classical BDT, and classical deep neural network for example. We have also performed our studies using IBM superconducting quantum computer hardware and the performance is promising and is approaching the performance from IBM quantum simulators. Moreover, we extend our studies to other QML areas such as quantum anomaly detection and quantum generative adversarial, and some preliminary results have been obtained. Also, we have overcome the challenges of intensive computing resources in the cases of large qubits (25 qubits or more) and large numbers of events using NVIDIA cuQuantum with NERSC Perlmutter HPC. Our studies give an example that Quantum Machine Learning performs as well as its classical counterpart for realistic High Energy Physics analysis datasets. Furthermore, our result on noisy quantum hardware provides important validation for the result on noiseless quantum simulators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

SNEWPY: A Data Pipeline from Supernova Simulations to Neutrino Signals

Current neutrino detectors will observe hundreds to thousands of neutrinos from Galactic supernovae, and future detectors will increase this yield by an order of magnitude or more. With such a data set comes the potential for a huge increase in our understanding of the explosions of massive stars, nuclear physics under extreme conditions, and the properties of the neutrino. However, there is currently a large gap between supernova simulations and the corresponding signals in neutrino detectors, which will make any comparison between theory and observation very difficult. SNEWPY is an open-source software package that bridges this gap. The SNEWPY code can interface with supernova simulation data to generate from the model either a time series of neutrino spectral fluences at Earth, or the total time-integrated spectral fluence. Data from several hundred simulations of core-collapse, thermonuclear, and pair-instability supernovae is included in the package. This output may then be used by an event generator such as sntools or an event rate calculator such as the SuperNova Observatories with General Long Baseline Experiment Simulator (SNOwGLoBES). Additional routines in the SNEWPY package automate the processing of the generated data through the SNOwGLoBES software and collate its output into the observable channels of each detector. In this paper we describe the contents of the package, the physics behind SNEWPY, the organization of the code, and provide examples of how to make use of its capabilities.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Gamma-Ray Bursts and Kilonovae from the Accretion-induced Collapse of White Dwarfs

Abstract We present the first seconds-long 2D general relativistic neutrino magnetohydrodynamic simulations of accretion-induced collapse (AIC) in rapidly rotating, strongly magnetized white dwarfs (WDs), which might originate as remnants of double-WD mergers. This study examines extreme combinations of magnetic fields and rotation rates, motivated both by the need to address the limitations of 2D axisymmetric simulations and to explore the physics of AIC under rare conditions that, while yet to be observationally confirmed, may be consistent with current theoretical models and account for unusual events. Under these assumptions, our results demonstrate that, if realizable, such systems can generate relativistic jets and neutron-rich outflows with properties consistent with long gamma-ray bursts (LGRBs) accompanied by kilonovae, such as GRB 211211A and GRB 230307A. These findings highlight the potential role of AIC in heavy r -process element production and offer a framework for understanding rare LGRBs associated with kilonova emission. Longer-duration 3D simulations are needed to fully capture magnetic field amplification, resolve instabilities, and determine the fate of the energy retained by the magnetar at the end of the simulations.

Cheong 張, Patrick Chi-Kit 志杰 (ORCID:00000003144933↗
NASA NTRS2002

Flexible substrata for the detection of cellular traction forces

By modulating adhesion signaling and cytoskeletal organization, mechanical forces play an important role in various cellular functions, from propelling cell migration to mediating communication between cells. Recent developments have resulted in several new approaches for the detection, analysis and visualization of mechanical forces generated by cultured cells. Combining these methods with other approaches, such as green-fluorescent protein (GFP) imaging and gene manipulation, proves to be particularly powerful for analyzing the interplay between extracellular physical forces and intracellular chemical events.

Review, Tutorial↗
DOE OSTI2025

Fuel Property Effects on Stochastic Preignition Events During Engine Load Transitions

Stochastic preignition (SPI) is an abnormal combustion phenomenon that can cause catastrophic engine damage. There have been several proposed mechanisms of SPI, where a uniform source is still not certain, however, SPI tendencies have been shown to be influenced by engine operating conditions, oil composition, engine age, and fuel chemical and physical properties. Laboratory research and testing for SPI propensity is challenging given the stochastic nature of events, as well as the potential for significant degradation of the engine platform and measuring equipment over time. Thus, SPI specific experiments are generally conducted under either sustained or cyclic patterning of steady-state operating conditions to avoid the influence of transient engine boundary conditions on test parameters of interest (e.g. oil additive package, fuel properties, engine speed/load, etc.). In this work a cyclically varying SPI test sequence involves a 5 min engine warmup period at a low engine load of around 4 bar gross indicated mean effective pressure (IMEPg), followed by a transition to high load (~20 bar IMEPg) at a constant 2000 rev/min engine speed for a total of 25 min. This individual test sequence load schedule is then sequentially repeated 10 times to generate significant statistical data for analysis. This work examines the influence of fuel chemical and physical properties on SPI tendency during the unsteady portion of the 10-cycle sequence (the first 5 min of the high load operation in each sequence of the loading cycle) which has been discarded from previous analyses due to the uncertainty in engine operating and thermal boundary conditions. Results from this analysis suggest an increasing trend in the ratio of SPI events during the unsteady test period relative to the steady test period with increasing fuel Reid Vapor Pressure (RVP), implying differences in uncontrolled ignition source terms, possibly from, fuel wall interactions and retention during the load transition phase of the test.

Splitter, Derek [ORNL] (ORCID:0000000174044047)↗
DOE OSTI2026

Search for New Physics via EFT in collisions containing a top quark and a boosted Z or Higgs boson

We present a generator-level sensitivity study of physics beyond the Standard Model within the framework of Effective Field Theory (EFT). The targeted signal processes are single top quark production in association with a Lorentz-boosted Higgs or Z boson (tHq and tZq) in proton-proton collisions at a center-of-mass energy of 13.6 TeV. Event selection requires one electron or muon, a high-transverse-momentum, large-radius (AK8) jet reconstructing hadronic H → b̄b or Z → b̄b decays, at least two distinct, non-overlapping small-radius (AK4) jets with one originating from a b quark, and a missing transverse energy greater than 30 GeV. Signal and background samples are generated via Monte Carlo simulation using MadGraph with MadJax to perform EFT matrix-element calculations. Deviations from the Standard Model are parametrized through dimension-six EFT operators that probe modified top quark interactions. This generator-level study identifies kinematic observables with enhanced sensitivity to EFT operators and motivates future reconstruction-level analyses of tHq and tZq channels.

Meshramkar, Daniel [Baylor U., Waco]↗
DOE OSTI2026

Search for New Physics via EFT in collisions containing a top quark and a boosted Z or Higgs boson

We present a generator-level sensitivity study of physics beyond the Standard Model within the framework of Effective Field Theory (EFT). The targeted signal processes are single top quark production in association with a Lorentz-boosted Higgs or Z boson (tHq and tZq) in proton-proton collisions at a center-of-mass energy of 13.6 TeV. Event selection requires one electron or muon, a high-transverse-momentum, large-radius (AK8) jet reconstructing hadronic H → b̄b or Z → b̄b decays, at least two distinct, non-overlapping small-radius (AK4) jets with one originating from a b quark, and a missing transverse energy greater than 30 GeV. Signal and background samples are generated via Monte Carlo simulation using MadGraph with MadJax to perform EFT matrix-element calculations. Deviations from the Standard Model are parametrized through dimension-six EFT operators that probe modified top quark interactions. This generator-level study identifies kinematic observables with enhanced sensitivity to EFT operators and motivates future reconstruction-level analyses of tHq and tZq channels.

Meshramkar, Daniel [Baylor U., Waco]↗