Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “statistical physics”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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

At least 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Uncertainties associated with GAN-generated datasets in high energy physics

Recently, Generative Adversarial Networks (GANs) trained on samples of traditionally simulated collider events have been proposed as a way of generating larger simulated datasets at a reduced computational cost. In this paper we point out that data generated by a GAN cannot statistically be better than the data it was trained on, and critically examine the applicability of GANs in various situations, including a) for replacing the entire Monte Carlo pipeline or parts of it, and b) to produce datasets for usage in highly sensitive analyses or sub-optimal ones. We present our arguments using information theoretic demonstrations, a toy example, as well as in the form of a formal statement, and identify some potential valid uses of GANs in collider simulations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Quantum and anharmonic effects in non-adiabatic transition state theory

Quantitative descriptions of non-adiabatic transition rates at intermediate temperatures are challenging due to the simultaneous importance of quantum and anharmonic effects. Here, in this paper, the interplay between quantum effects—for motion across or along the seam of crossing—and anharmonicity in the seam potential is considered within the weak coupling limit. The well-known expression for quantized 1-D motion across the seam (i.e., tunneling) in the linear terms approximation is derived in the thermal domain using the Lagrangian formalism, which is then applied to the case when tunneling is distributed along the seam of crossing (treating motion along the seam classically). For high-frequency quantum modes, a vibrationally adiabatic (VA) approach is developed that introduces to the non-adiabatic rate constant a factor associated with high-frequency wavefunction overlap; this approach treats the high-frequency motion along the seam quantum mechanically. To test these methodologies, the reaction N 2 O ↔ N 2 + O( 3 P) was chosen. CCSD(T)-F12b/cc-pVTZ-F12 explorations of the 3 A'- 1 A' seam of N 2 O revealed that seam anharmonicity has a strong effect on the rate constant (a factor of ~20 at 2000 K). Several quantum effects were found to be significant at intermediate/lower temperatures, including the quantum N–N vibration that was coupled with seam anharmonicity using the VA approach. Finally, a 1-D approximation to non-adiabatic instanton theory is presented to estimate the validity limit of the linear terms model at low temperatures (⁠~ 250 K for N 2 O). We recommend that the assumptions built into many statistical theories for non-adiabatic reactions—harmonic behavior, classical motion, linear terms, and weak coupling—should be verified on a case-by-case basis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Madden-Julian oscillation influences United States springtime tornado and hail frequency

The Madden–Julian Oscillation (MJO) is the dominant mode of intraseasonal variability in the tropics and has a documented influence on extratropical extreme weather through modulation of synoptic atmospheric conditions. MJO phase has been correlated with anomalous tornado and severe hail frequency in the United States (US). However, the robustness of this relationship is unsettled, and the variability of physical pathways to modulation is poorly understood, despite the socioeconomic impacts that tornadoes and hail evoke. We approached this problem using pentad MJO indices and practically perfect severe weather hindcasts. MJO lifecycles were cataloged and clustered to document variability and potential pathways to enhanced subseasonal tornado and hail predictability. Statistically significant increases in US tornado and hail probabilities were documented 3–4 weeks following the period of the strongest upper-level divergence for the 53 active MJO events that propagated past the Maritime continent, contrasting with the 47 MJO events that experienced the barrier effect, during boreal spring 1979–2019. The 53 MJO events that propagated past the Maritime continent revealed three prevailing MJO evolutions—each containing unique pathways and modulation of US tornado and hail frequency—advancing our knowledge and capability to anticipate these hazards at extended lead times.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Evaluating MPI resource usage summary statistics

The Message Passing Interface (MPI) remains the dominant programming model for scientific applications running on today’s high-performance computing (HPC) systems. This dominance stems from MPI’s powerful semantics for inter-process communication that has enabled scientists to write applications for simulating important physical phenomena. MPI does not, however, specify how messages and synchronization should be carried out. Those details are typically dependent on low-level architecture details and the message characteristics of the application. Therefore, analyzing an application’s MPI resource usage is critical to tuning MPI’s performance on a particular platform. The result of this analysis is typically a discussion of the mean message sizes, queue search lengths and message arrival times for a workload or set of workloads. While a discussion of the arithmetic mean in MPI resource usage might be the most intuitive summary statistic, it is not always the most accurate in terms of representing the underlying data. In this paper, we analyze MPI resource usage for a number of key MPI workloads using an existing MPI trace collector and discrete-event simulator. Our analysis demonstrates that the average, while easy and efficient to calculate, is a useful metric for characterizing latency and bandwidth measurements, but may not be a good representation of application message sizes, match list search depths, or MPI inter-operation times. Additionally, we show that the median and mode are superior choices in many cases. We also observe that the arithmetic mean is not the best representation of central tendency for data that are drawn from distributions that are multi-modal or have heavy tails. Furthermore, the results and analysis of our work provide valuable guidance on how we, as a community, should discuss and analyze MPI resource usage data for scientific applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Tempering stochastic density functional theory

Here, we introduce a tempering approach with stochastic density functional theory (sDFT), labeled t-sDFT, which reduces the statistical errors in the estimates of observable expectation values. This is achieved by rewriting the electronic density as a sum of a "warm" component complemented by "colder" correction(s). Since the warm component is larger in magnitude but faster to evaluate, we use many more stochastic orbitals for its evaluation than for the smaller-sized colder correction(s). This results in a significant reduction in the statistical fluctuations and systematic deviation compared to sDFT for the same computational effort. We demonstrate the method's performance on large hydrogen-passivated silicon nanocrystals, finding a reduction in the systematic deviation in the energy by more than an order of magnitude, while the systematic deviation in the forces is also quenched. Similarly, the statistical fluctuations are reduced by factors of ≈4-5 for the total energy and ≈1.5-2 for the forces on the atoms. Since the embedding in t-sDFT is fully stochastic, it is possible to combine t-sDFT with other variants of sDFT such as energy-window sDFT and embedded-fragmented sDFT.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Yield degradation due to laser drive asymmetry in D3He backlit proton radiography experiments at OMEGA

Mono-energetic proton radiography is a vital diagnostic for numerous high-energy-density-physics, inertial-confinement-fusion, and laboratory-astrophysics experiments at OMEGA. With a large number of campaigns executing hundreds of shots, general trends in D3He backlighter performance are statistically observed. Each experimental configuration uses a different number of beams and drive symmetry, causing the backlighter to perform differently. Here, we analyze the impact of these variables on the overall performance of the D3He backlighter for proton-radiography studies. This study finds that increasing laser drive asymmetry can degrade the performance of the D3He backlighter. The results of this study can be used to help experimental designs that use proton radiography.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Jet substructure from dark sector showers

We examine the robustness of collider phenomenology predictions for a dark sector scenario with QCD-like properties. Pair production of dark quarks at the LHC can result in a wide variety of signatures, depending on the details of the new physics model. A particularly challenging signal results when prompt production induces a parton shower that yields a high multiplicity of collimated dark hadrons with subsequent decays to Standard Model hadrons. The final states contain jets whose substructure encodes their non-QCD origin. This is a relatively subtle signature of strongly coupled beyond the Standard Model dynamics, and thus it is crucial that analyses incorporate systematic errors to account for the approximations that are being made when modeling the signal. We estimate theoretical uncertainties for a canonical substructure observable designed to be sensitive to the gauge structure of the underlying object, the two-point energy correlator $ {e}_2^{\left(\beta \right)} $ , by computing envelopes between resummed analytic distributions and numerical results from Pythia. We explore the separability against the QCD background as the confinement scale, number of colors, number of flavors, and dark quark masses are varied. Additionally, we investigate the uncertainties inherent to modeling dark sector hadronization. Simple estimates are provided that quantify one’s ability to distinguish these dark sector jets from the overwhelming QCD background. Such a search would benefit from theory advances to improve the predictions, and the increase in statistics using the data to be collected at the high luminosity LHC.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Direct CP violation and the ΔI=1/2 rule in K→ππ decay from the standard model

We present a lattice QCD calculation of the Δ I = 1 / 2 , K → π π decay amplitude A 0 and ϵ ' , the measure of direct C P violation in K → π π decay, improving our 2015 calculation [1] of these quantities. Both calculations were performed with physical kinematics on a 32 3 × 64 lattice with an inverse lattice spacing of a - 1 = 1.3784 ( 68 ) GeV . However, the current calculation includes nearly 4 times the statistics and numerous technical improvements allowing us to more reliably isolate the π π ground state and more accurately relate the lattice operators to those defined in the standard model. We find Re ( A 0 ) = 2.99 ( 0.32 ) ( 0.59 ) × 10 - 7 GeV and Im ( A 0 ) = - 6.98 ( 0.62 ) ( 1.44 ) × 10 - 11 GeV , where the errors are statistical and systematic, respectively. The former agrees well with the experimental result Re ( A 0 ) = 3.3201 ( 18 ) × 10 - 7 GeV . These results for A 0 can be combined with our earlier lattice calculation of A 2 [2] to obtain Re ( ϵ ' / ϵ ) = 21.7 ( 2.6 ) ( 6.2 ) ( 5.0 ) × 10 - 4 , where the third error represents omitted isospin breaking effects, and Re ( A 0 ) / Re ( A 2 ) = 19.9 ( 2.3 ) ( 4.4 ) . The first agrees well with the experimental result of Re ( ϵ ' / ϵ ) = 16.6 ( 2.3 ) × 10 - 4 . A comparison of the second with the observed ratio Re ( A 0 ) / Re ( A 2 ) = 22.45 ( 6 ) , demonstrates the standard model origin of this “ Δ I = 1 / 2 rule” enhancement.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Improvements to the macroscopic-microscopic approach of nuclear fission

The well-established macroscopic-microscopic (mac-mic) description of nuclear fission enables the prediction of fission-fragment yields for a broad range of fissioning systems. In this work, we present several key enhancements to this approach. We improve upon the microscopic sector of nuclear potential-energy surfaces by magnifying the resolution of the Lipkin-Nogami equations and strengthening the Strutinsky procedure, thus reducing spurious effects from the continuum. We further present a novel deterministic method for calculating fission dynamics under the assumption of strongly damped nucleonic motion. Our technique directly determines the evolution of the scissioned shape distribution according to the number of random-walk steps rather than the statistical accumulation of fission events. We show that our new technique is equivalent to the Metropolis random walk pioneered over the past decade by Randrup and colleagues. It further improves upon it because we remove the need for altering the nuclear landscape via a biased potential. With our final improvement, we calculate fission fragments mass and charge distributions using particle number projection, which affords the simultaneous calculation of both mass- and charge-yield distributions. Fission fragments are thus calculated from the quantum-mechanical A -body states of the potential-energy surface rather than from the collective mass asymmetry variable α g of the finite-range liquid-drop model used in past work. We highlight the success of our enhancements by predicting the odd-even staggering and the charge polarization for the neutron-induced fission of 233 U and 235 U .

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Bayesian model-data comparison incorporating theoretical uncertainties

Accurate comparisons between theoretical models and experimental data are critical for scientific progress. However, inferred physical model parameters can vary significantly with the chosen physics model, highlighting the importance of properly accounting for theoretical uncertainties. In this Letter, we present a Bayesian framework that explicitly quantifies these uncertainties by statistically modeling theory errors, guided by qualitative knowledge of a theory’s varying reliability across the input domain. We demonstrate the effectiveness of this approach using two systems: a simple ball drop experiment and multi-stage heavy-ion simulations. In both cases incorporating model discrepancy leads to improved parameter estimates, with systematic improvements observed as additional experimental observables are integrated.

Bayesian methods↗
DOE OSTI2024

Calibrating Bayesian generative machine learning for Bayesiamplification

Recently, combinations of generative and Bayesian deep learning have been introduced in particle physics for both fast detector simulation and inference tasks. These neural networks aim to quantify the uncertainty on the generated distribution originating from limited training statistics. The interpretation of a distribution-wide uncertainty however remains ill-defined. We show a clear scheme for quantifying the calibration of Bayesian generative machine learning models. For a Continuous Normalizing Flow applied to a low-dimensional toy example, we evaluate the calibration of Bayesian uncertainties from either a mean-field Gaussian weight posterior, or Monte Carlo sampling network weights, to gauge their behaviour on unsteady distribution edges. Well calibrated uncertainties can then be used to roughly estimate the number of uncorrelated truth samples that are equivalent to the generated sample and clearly indicate data amplification for smooth features of the distribution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Measurement of e + e − → η J / ψ cross section from s = 3.808 GeV to 4.951 GeV

Using data samples with an integrated luminosity of 22.42 fb − 1 collected by the BESIII detector operating at the BEPCII storage ring, we measure the cross sections of the e + e − → η J / ψ process at center-of-mass energies from 3.808 to 4.951 GeV. Three structures are observed in the line shape of the measured cross sections. A maximum-likelihood fit with ψ ( 4040 ) , two additional resonances, and a nonresonant component are performed. The mass and width of the first additional state are ( 4219.7 ± 2.5 ± 4.5 ) MeV / c 2 and ( 80.7 ± 4.4 ± 1.4 ) MeV , respectively, consistent with the ψ ( 4230 ) . For the second state, the mass and width are ( 4386 ± 13 ± 17 ) MeV / c 2 and ( 177 ± 32 ± 13 ) MeV , respectively, consistent with the ψ ( 4360 ) . The first uncertainties are statistical, and the second ones are systematic. The statistical significance of ψ ( 4040 ) is 8.0 σ and those for ψ ( 4230 ) and ψ ( 4360 ) are more than 10.0 σ . Published by the American Physical Society 2024

Ablikim, M.↗
DOE OSTI2022

Uncertainty Quantification for Dissimilar Material Joints Under Corrosion Environment

Abstract Self-Piercing Riveting (SPR) is one of the most commonly used methods for joining dissimilar materials in the automotive industry. These joints are popular due to their adaptability, high performance and short cycle time. However, since these joints involve two dissimilar materials, they are susceptible to galvanic corrosion in the presence of an electrolyte which is driven by the difference in the equilibrium potential of the metals. This can affect the safety and resilience of these joints. In this paper, we focus on galvanic corrosion in Al-Fe SPR joints. A Machine learning (ML) based surrogate model, which is based off of FE simulations, for statistical corrosion analysis is developed. This model enables the resilience and reliability analysis of SPR joints under corrosion environment. In this study, first a physics-based finite element (FE) corrosion model has been developed to simulate the galvanic corrosion between a Fe cathode and an Al anode of a SPR joint. This model takes into account the effect of the crystal microstructure of the Al anode and the precipitation of the corrosion product. Several geometric and environmental factors including crevice gap, roughness of anode, conductivity, pH and the temperature of the electrolyte that effect corrosion are investigated. A thorough Uncertainty Quantification (UQ) analysis is conducted for the overall corrosion behavior of the Fe-Al SPR joints using a novelistic Probabilistic Confidence-Based Adaptive Sampling (PCAS) technique. PCAS is used to train the surrogate model by identifying the critical sampling points and thus reducing the overall computational costs. It is found that the electrolyte temperature has the largest effects on the material loss and needs to be managed closely for better corrosion control. By understanding the corrosion performance and resultant uncertainty impact on SPR joints, the reliability and resilience of these joints can be improved.

36 MATERIALS SCIENCE↗
DOE OSTI2026

MINERvA s Open Data Product: A First for Neutrino Data Preservation

Access to information on neutrino nucleus interactions is critical to the success of all neutrino oscillation experiments. MINERvA's rich dataset covers a range of energies and nuclei unique amongst experiments, and as such is critical to the community in building the important shared knowledge needed to unravel the mysteries of the neutrino. In particular, its dataset provides the greatest statistical coverage in in the range of neutrino energies pertinent for DUNE until DUNE's near detector begins operation. Historically, such significant datasets in neutrino physics have been preserved primarily through their published results. While meaningful and useful, this limits the ability to explore the data to its fullest extent as new perspectives continue to form. MINERvA has undertaken a major effort to break this trend and preserve its data in a format to be as analyzable as possible from outside the collaboration. This has culminated in the officially-released MINERvA Open Data Product for the community to take advantage of and utilize. Maintaining direct access to the dataset in an analyzable form will allow new insights to continue to be extracted indefinitely. This talk will cover the contents of this product, the information included (and excluded), the tools provided to utilize the product effectively, the support MINERvA intends to provide in its use, and some lessons learned through the process.

Last, David [Rochester U.] (ORCID:0000000245147183↗
DOE OSTI2023

QUOTAS: A New Research Platform for the Data-driven Discovery of Black Holes

We present QUOTAS, a novel research platform for the data-driven investigation of supermassive black hole (SMBH) populations. While SMBH data—observations and simulations—have grown in complexity and abundance, our computational environments and tools have not matured commensurately to exhaust opportunities for discovery. To explore the BH, host galaxy, and parent dark matter halo connection—in this pilot version—we assemble and colocate the high-redshift, z > 3 quasar population alongside simulated data at the same cosmic epochs. As a first demonstration of the utility of QUOTAS, we investigate correlations between observed Sloan Digital Sky Survey (SDSS) quasars and their hosts with those derived from simulations. Leveraging machine-learning algorithms (ML), to expand simulation volumes, we show that halo properties extracted from smaller dark-matter-only simulation boxes successfully replicate halo populations in larger boxes. Next, using the Illustris-TNG300 simulation that includes baryonic physics as the training set, we populate the larger LEGACY Expanse dark-matter-only box with quasars, and show that observed SDSS quasar occupation statistics are accurately replicated. First science results from QUOTAS comparing colocated observational and ML-trained simulated data at z3 are presented. QUOTAS demonstrates the power of ML, in analyzing and exploring large data sets, while also offering a unique opportunity to interrogate theoretical assumptions that underpin accretion and feedback models. QUOTAS and all related materials are publicly available at the Google Kaggle platform. (The full data set—observational data and simulation data—are available at: https://www.kaggle.com/ and the codes are available at:https://www.kaggle.com/datasets/quotasplatform/quotas)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1980

Lightning return stroke models

We test the two most commonly used lightning return stroke models, Bruce-Golde and transmission line, against subsequent stroke electric and magnetic field wave forms measured simultaneously at near and distant stations and show that these models are inadequate to describe the experimental data. We then propose a new return stroke model that is physically plausible and that yields good approximations to the measured two-station fields. Using the new model, we derive return stroke charge and current statistics for about 100 subsequent strokes.

Lin, Y. T.↗
NASA NTRS1987

Simulation of charged particle transport on the MPP

Computations of cosmic ray transport based upon finite difference methods are afflicted by instabilities, inaccuracies, and artifacts. To avoid these problems, a Monte Carlo formulation was developed which is closely related not only to the finite difference formulation, but also to the underlying physics of transport phenomena. Implementations of this approach are currently running on the Massively Parallel Processor at Goddard, whose enormous computing power overwhelms the poor statistical accuracy that usually limits the use of stochastic methods. In a Monte Carlo simulation of rectilinear transport, the coherent and diffusive effects that appeared are in good quantitative agreement with both finite difference and analytical calculations.

Earl, James A.↗