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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Search for electroweak production of charginos and neutralinos in proton-proton collisions at $$ \sqrt{s} $$ = 13 TeV

A direct search for electroweak production of charginos and neutralinos is presented. Events with three or four leptons, with up to two hadronically decaying $\tau$ leptons, or two same-sign light leptons are analyzed. The data sample consists of 137 fb$^{-1}$ of proton-proton collisions with a center of mass energy of 13 TeV, recorded with the CMS detector at the LHC. The results are interpreted in terms of several simplified models. These represent a broad range of production and decay scenarios for charginos and neutralinos. A parametric neural network is used to target several of the models with large backgrounds. In addition, results using orthogonal search regions are provided for all the models, simplifying alternative theoretical interpretations of the results. Depending on the model hypotheses, charginos and neutralinos with masses up to values between 300 and 1450 GeV are excluded at 95% confidence level.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Demonstrating the impact of ro-vibrationally excited H 2 on divertor detachment via population modelling

EDGE2D-EIRENE profiles characteristic for low recycling, high recycling and detached plasmas are postprocessed applying a vibrationally resolved collisional radiative (CR) model based on the Yacora solver to predict excited state densities and thus the molecular Lyman-, Werner- and Fulcher band emission intensities. These emission intensities are compared to predictions from the AMJUEL database standardly used in EIRENE. Lower Fulcher band and higher Lyman- and Werner band emission is predicted by the Yacora model in comparison to AMJUEL suggesting that inconsistent results from model based evaluation of measured spectra are expected depending on which model and molecular emission band is considered. The implications on detachment rate predictions are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Deep-learning-based workflow for boundary and small target segmentation in digital rock images using UNet++ and IK-EBM

We report three-dimensional (3D) X-ray micro-computed tomography (μCT) has been widely used in petroleum engineering because it can provide detailed pore structural information for a reservoir rock, which can be imported into a pore-scale numerical model to simulate the transport and distribution of multiple fluids in the pore space. The partial volume blurring (PVB) problem is a major challenge in segmenting raw μCT images of rock samples, which impacts boundaries and small targets near the resolution limit. We developed a deep-learning (DL)-based workflow for accurate and fast partial volume segmentation. The DL model's performance depends primarily on the training data quality and model architecture. This study employed the entropy-based-masking indicator kriging (IK-EBM) to segment 3D Berea sandstone images as training datasets. The comparison between IK-EBM and manual segmentation using a 3D synthetic sphere pack, which had a known ground truth, showed that IK-EBM had higher accuracy on partial volume segmentation. We then trained and tested the UNet++ model, a state-of-the-art supervised encoder-decoder model, for binary (i.e., void and solid) and four-class segmentation. We compared the UNet++ with the commonly used U-Net and wide U-Net models and showed that the UNet++ had the best performance in terms of pixel-wise and physics-based evaluation metrics. Specifically, boundary-scaled accuracy demonstrated that the UNet++ architecture outperformed the regular U-Net architecture in the segmentation of pixels near boundaries and small targets, which were subjected to the PVB effect. Feature map visualization illustrated that the UNet++ bridged the semantic gaps between the feature maps extracted at different depths of the network, thereby enabling faster convergence and more accurate extraction of fine-scale features. The developed workflow significantly enhances the performance of supervised encoder-decoder models in partial volume segmentation, which has extensive applications in fundamental studies of subsurface energy, water, and environmental systems.

02 PETROLEUM↗
DOE OSTI2020

ZND Verification Tests for Reactive Burn Models in FLAG

The ZND theory, named after Zeldovich, von Neumann, and Doering, provides a simple model for one-dimensional ideal steady-state detonation. It assumes that the detonation wave front starts with a shock that is a discontinuous jump and is followed by a finite-length reaction zone. Reactive burn (also called reactive flow) models are based on ZND theory, as they model the shock initiation and detonation process with a finite reaction rate. The ZND wave propagation test is essentially the only available test case where an analytic solution exists for verification of reactive burn models in numerical codes. However, there are extensions and variants of the ZND test that have been devised for verification of multidimensional flows. The objective of this work is to provide verification of the reactive burn models currently implemented in the Lagrangian hydrocode FLAG and investigate the influence of mesh resolution, artificial viscosity models, and the Arbitrary Lagrangian-Eulerian (ALE) Euler relaxer on the simulation results. The burn models of interest are the Wescott-Stewart-Davis (WSD) model, the Scaled Uniform Reactive Flow (SURF) model (specifically with the SURFplus model extension), and the Arrhenius shock temperature state dependent WSD (AWSD) model. Previously, Ralph Menikoff has used ZND tests for verification of the SURF and SURFplus models in the Eulerian hydrocode xRAGE. The ZND tests here are somewhat different than the approach by Menikoff. In particular, we use a piston-driven ZND detonation wave (via a prescribed constant velocity boundary condition) in a Lagrangian framework whereas Menikoff had a ZND wave followed by a invariant rarefaction wave. The xRAGE simulations were carried out on uniform grids and adaptive mesh refinement (AMR) grids. Although AMR was recently implemented in FLAG and now fully functional for 2D simulations, it will not be evaluated with ZND tests at this time. Some work has been done previously for validating the reactive burn models in FLAG. For example, the validation studies of SURF with shock-to-detonation (SDT) tests, cylinder tests, and gap-stick tests. Further validation of the AWSD, WSD, and SURF models is described in for SDT, multi-shock, cylinder, and corner-turning tests. Recently, a large parameter study with approximately twenty SDT tests was performed to validate the AWSD, WSD, SURF, and SURFplus models while also investigating mesh resolution and artificial viscosity settings. To the best of our knowledge, the current work represents the first documented verification of these burn models in FLAG. The reader should note that many of the tables and figures in this report use units of cm/g/µs, which are the default units for FLAG. However, some lengths and velocities are expressed in µm and mm/µs, respectively, which are typical units for detonation analyses.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2020

Position-dependent matter density probability distribution function

Here, we introduce the position-dependent probability distribution function (PDF) of the smoothed matter field as a cosmological observable. In comparison to the PDF itself, the spatial variation of the position-dependent PDF is simpler to model and has distinct dependence on cosmological parameters. We demonstrate that the position-dependent PDF is characterized by variations in the local mean density, and we compute the linear response of the PDF to the local density using separate universe N-body simulations. The linear response of the PDF to the local density field can be thought of as the linear bias of regions of the matter field selected based on density. We provide a model for the linear response, which accurately predicts our simulation measurements. We also validate our results and test the separate universe consistency relation for the local PDF using global universe simulations. We find excellent agreement between the two, and we demonstrate that the separate universe method gives a lower variance determination of the linear response.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Computational Approach for Rapidly Predicting Temperature–Dependent Polymer Solubilities Using Molecular–Scale Models

One promising approach to recycle multicomponent plastic waste (e. g., multilayer plastic films) is selective dissolution. Selective dissolution is a solvent-mediated process in which differences in polymer solubility in a carefully chosen solvent system are exploited to recover a target polymer. Here, a computational approach was developed that rapidly predicts temperature-dependent polymer solubilities to guide the design of solvent systems for solvent-mediated polymer recycling. Polymer conformations were obtained from molecular dynamics simulations by modeling the polymer as a short oligomer and then used as input to the conductor-like screening model for real solvents (COSMO-RS) for solubility predictions. Using polyethylene (PE) and ethylene vinyl alcohol (EVOH) as representative polymers, the effect of simulation parameters was systematically studied, and predicted solubilities were found to be in good agreement with experimental measurements. Furthermore, the applicability of the approach was demonstrated by identifying selective solvents for PE and EVOH dissolution from a library of 524 solvents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Modular machine learning-based elastoplasticity: Generalization in the context of limited data

The development of highly accurate constitutive models for materials that undergo path-dependent processes continues to be a complex challenge in computational solid mechanics. Challenges arise both in considering the appropriate model assumptions and from the viewpoint of data availability, verification, and validation. Recently, data-driven modeling approaches have been proposed that aim to establish stress-evolution laws that avoid user-chosen functional forms by relying on machine learning representations and algorithms. However, these approaches not only require a significant amount of data but also need data that probes the full stress space with a variety of complex loading paths. Furthermore, they rarely enforce all necessary thermodynamic principles as hard constraints. Hence, they are in particular not suitable for low-data or limited-data regimes, where the first arises from the cost of obtaining the data and the latter from the experimental limitations of obtaining labeled data, which is commonly the case in engineering applications. In this work, we discuss a hybrid framework that can work on a variable amount of data by relying on the modularity of the elastoplasticity formulation where each component of the model can be chosen to be either a classical phenomenological or a data-driven model depending on the amount of available information and the complexity of the response. The method is tested on synthetic uniaxial data coming from simulations as well as cyclic experimental data for structural materials. The discovered material models are found to not only interpolate well but also allow for accurate extrapolation in a thermodynamically consistent manner far outside the domain of the training data. This ability to extrapolate from limited data was the main reason for the early and continued success of phenomenological models and the main shortcoming in machine learning-enabled constitutive modeling approaches. Training aspects and details of the implementation of these models into Finite Element simulations are discussed and analyzed.

42 ENGINEERING↗
DOE OSTI2020

Helicity-dependent extension of the McLerran–Venugopalan model

We construct a generalization of the McLerran-Venugopalan (MV) model including helicity effects for a longitudinally polarized target (a proton or a large nucleus). The extended MV model can serve as the initial condition for the helicity generalization of the JIMWLK evolution equation constructed in our previous paper, as well as for calculation of helicity-dependent observables in the quasi-classical approximation to QCD.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Prevention of resistive wall tearing mode major disruptions with feedback

Resistive wall tearing modes (RWTMs) can cause major disruptions. A signature of RWTMs is that the rational surface is sufficiently close to the wall to interact with it. For (m,n) = (2,1) modes, a RWTM requires normalized minor radius of the rational surface ρ q2 ≥ 0.75, which can also be expressed as q 75 ≤ 2. Major disruptions can occur when the criterion is satisfied. This is confirmed in simulations and theory and in a DIII-D locked mode disruption database. The q 75 < 2 criterion is valid at high β as well as at low β. A very important feature of RWTMs is that they can be feedback stabilized. If the ρ q2 criterion is not satisfied, or if the wall is ideally conducting, then the mode does not produce a major disruption, although it can produce a minor disruption. Feedback, or rotation of the mode at the wall by complex feedback, can emulate an ideal wall, preventing major disruptions. The ρ q2 criterion depends weakly on the wall radius. A simple geometric model of its dependence on wall radius is given.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

DFT and microkinetic comparison of Pt, Pd and Rh-catalyzed ammonia oxidation

Ammonia oxidation is the heart of the Ostwald process and is important in emissions control. Catalytic behaviors are a function of conditions and are observed to vary across the platinum group metals (PGMs) Pt, Pd, Rh. Here, we combine density functional theory computations and microkinetic modeling to rationalize these dependencies. We compute reactions over model (2 1 1) and (1 1 1) surfaces of PGMs. Binding energies are similar on Pd and Pt and generally greater on Rh, while activation energies vary across all metals. Rates on (2 1 1) surfaces are greater than (1 1 1) surfaces. Additionally, the stepped Pt is most active and stepped Rh most selective to N 2 at ammonia slip conditions, while at Ostwald process conditions, stepped Pd is most active and stepped Pt most selective to NO. Degree of rate and selectivity control analysis provides insights into the reactions limiting performance of PGMs. Both activation barriers and surface coverages influence rates and selectivities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Evaluating the active site-substrate interplay between x-ray crystal structure and molecular dynamics in chorismate mutase

Designing realistic quantum mechanical (QM) models of enzymes is dependent on reliably discerning and modeling residues, solvents, and cofactors important in crafting the active site microenvironment. Interatomic van der Waals contacts have previously demonstrated usefulness toward designing QM-models, but their measured values (and subsequent residue importance rankings) are expected to be influenceable by subtle changes in protein structure. Using chorismate mutase as a case study, this work examines the differences in ligand-residue interatomic contacts between an x-ray crystal structure and structures from a molecular dynamics simulation. Select structures are further analyzed using symmetry adapted perturbation theory to compute ab initio ligand-residue interaction energies. The findings of this study show that ligand-residue interatomic contacts measured for an x-ray crystal structure are not predictive of active site contacts from a sampling of molecular dynamics frames. In addition, the variability in interatomic contacts among structures is not correlated with variability in interaction energies. However, the results spotlight using interaction energies to characterize and rank residue importance in future computational enzymology workflows.

Chemistry↗
DOE OSTI2023

Temperature-based reactive flow model for TATB plastic bonded explosives

A new reactive flow model is presented for TATB-based plastic bonded explosives, applicable to shock initiation and detonation problems of differing initial temperature. Temperature disequilibrium is assumed between unreacted explosive, material in the vicinity of compressed defects (called hot spots), and detonation products. The model incorporates temperature-dependent decomposition reaction rates. Arrhenius model parameters were derived from subscale quantum-based molecular dynamics simulations of shock-induced TATB decomposition. Further, a model of detonation carbon aggregation is incorporated, describing the late-time slow release of energy inherent to detonation in TATB-based materials. The predictive ability of the model in the shock initiation regime is tested against recent thin pulse experiments on PBX 9502. Here, the model is found to perform equally well in predicting the size effect curve of ambient, cold, and hot PBX 9502 rate sticks.

Chemistry - Chemical explosives↗
DOE OSTI2020

Traces of nonequilibrium effects, initial condition, bulk dynamics, and elementary collisions in the charm observables

Heavy quarks produced in relativistic heavy-ion collisions are known to be sensitive probes of the hot and dense QCD matter they traverse. In this paper we study how their dynamics is affected by the nature of the bulk evolution of the QCD matter, the initial condition of the system, and the treatment of elementary interactions between heavy quarks and the surrounding medium. For the same initial condition and the same quark-gluon plasma (QGP) expansion scenario we discuss the consequences of the assumption of a local equilibrium by comparing the consequences for the nuclear modification factor $R_{AA}$ and the elliptic flows of charm quarks, scrutinizing the different components of the final distribution of charm quarks. For this purpose we employ the parton-hadron-string dynamics (PHSD) model, which is an off-shell microscopic transport approach, as well as the linearized-Boltzmann (LB) scheme obtained by coarse graining the PHSD bulk and assuming local equilibrium for the interactions of the charm quarks with the bulk. The $R_{AA}$ of charm quarks stemming from the later LB approach is also compared to a genuine fluid dynamics evolution initiated by the coarse grained PHSD, which allows us to further assess the consequences of reducing the full $\textit{n}$-body dynamics. We then proceed to a systematic comparison of PHSD (in its LB approximation) with MC@HQ, another transport model for heavy flavors which also relies on the LB approach. In particular, we investigate the consequences for the nuclear modification factor of charm quarks if we vary separately the initial heavy quark distribution function in matter, the expansion dynamics of the QGP, and the elementary interactions of heavy quarks of these models. We find that the results for both models vary significantly depending on the details of the calculation. However, both models achieve very similar predictions for key heavy quark observables for certain combinations of initial condition, bulk evolution, and interactions. In this work, we conclude that this ambiguity limits our ability to determine the different properties of the system based on the current set of observables.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Solutions for Enhanced Legacy Probabilistic Risk Assessment Tools and Methodologies: Improving Efficiency of Model Development and Processing via Innovative Human Reliability Dependency Analysis

Probabilistic risk assessments (PRAs) are integral to nuclear power plant (NPP) operations, having tremendously benefitted the safety of the U.S. reactor fleet for decades. Insights obtained from the models have provided perspectives on a variety of applications, both at the plant and for the regulator. While these models are very useful, they are now being asked to represent and analyze aspects of the plant that were never envisioned by the initial PRA practitioners. Furthermore, heightened demands on the PRA models have led to increased computing power requirements. Additionally, as the complexity of the PRA models increased, the difficulty experienced by non-PRA experts in trying to understand these models, grasp the insights they provide, and effectively use that information has become problematic. The need for research to address key issues regarding PRA tools and methods has never been greater. Although the nuclear power industry has largely been well-served by these tools and methods, the underlying science is dated, remaining mostly unchanged for over two decades. Three areas were identified as most beneficial to address to maintain and improve the usefulness of the current practice legacy PRA tools: improved quantification speed, increased ability to efficiently model multi-hazard models, and improved modeling human action dependency in PRA. This report is focused on the third critical area, improvements in dependency analysis of human actions conducted as part of a typical human reliability assessment.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Multiscale Thermomechanical Damage Model with Internal State Variables for Ceramic Matrix Composites

A length scale-dependent matrix damage model has been developed to simulate the response of ceramic matrix composites (CMCs). This model captures damage initiation and propagation in the brittle matrix material by employing internal state variable (ISV) theory within a multiscale modeling framework to obtain damaged matrix stress-strain constitutive relationships at each length scale. Material degradation due to matrix cracking is captured by a damage variable determined using fracture mechanics and the self-consistent scheme. An additional state variable is introduced to capture the nucleation and growth of matrix porosity, a key mechanism contributing to matrix nonlinearity. Porosity occurs as a result of material diffusion around grain boundaries and the growth of the porosity state variable is related to the material entropy dissipation and the volumetric strain. The nonlinear predictive capabilities of the material model are demonstrated for monolithic silicon carbide, unidirectional (UD) carbon fiber/silicon carbide matrix (C/SiC) CMC, and five-harness satin (5HS) woven C/SiC CMC.

Skinner, Travis D.↗
DOE OSTI2024

A study on the scale dependence of mixing indices for Eulerian multiphase models

Abstract Mixing can vary based on the scale at which the system is observed, and a mixing index that can capture the features at different length scales is desirable. In this article, we analyze the scale dependence of the mixing indices developed for Eulerian multiphase models. Relevant length scales are distinguished by filtering solid fraction fields. The scale‐dependence study is first done on manufactured fields of solid fraction to assess the performance of the mixing indices. The study is extended to a two‐dimensional CFD simulation of the segregation of a bidisperse gas–solid mixture. The local mixing index performs well in capturing the spatial variation of mixing at different scales. The scale dependence of two global mixing indices is considered in the study, where the state of mixing is defined based on statistical measures. We demonstrate that the choice of measures influences the sensitivity of mixing indices to mixing at different scales.

Nagawkar, Barlev R.↗
DOE OSTI2023

Time-dependent SOLPS-ITER simulations of the tokamak plasma boundary for model predictive control using SINDy *

Abstract Time-dependent SOLPS-ITER simulations have been used to identify reduced models with the sparse identification of nonlinear dynamics (SINDy) method and develop model-predictive control of the boundary plasma state using main ion gas puff actuation. A series of gas actuation sequences are input into SOLPS-ITER to produce a dynamic response in upstream and divertor plasma quantities. The SINDy method is applied to identify reduced linear and nonlinear models for the electron density at the outboard midplane n e , s e p O M P and the electron temperature at the outer divertor T e , s e p d i v . Note that T e , s e p d i v is not necessarily the peak value of T e along the divertor. The identified reduced models are interpretable by construction (i.e. not black box), and have the form of coupled ordinary differential equations. Despite significant noise in T e , s e p d i v , the reduced models can be used to predict the response over a range of actuation levels to a maximum deviation of 0.5% in n e , s e p O M P and 5%–10% in T e , s e p d i v for the cases considered. Model retraining using time history data triggered by a preset error threshold is also demonstrated. A model predictive control strategy for nonlinear models is developed and used to perform feedback control of a SOLPS-ITER simulation to produce a setpoint trajectory in n e , s e p O M P using the integrated plasma simulator framework. The developed techniques are general and can be applied to time-dependent data from other boundary simulations or experimental data. Ongoing work is extending the approach to model identification and control for divertor detachment, which will present transient nonlinear behavior from impurity seeding, including realistic latency and synthetic diagnostic signals derived from the full SOLPS-ITER output.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗