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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Physics-based modeling and data analytics [Slides]

This presentation contains a summary of ongoing work within the physics-based modeling and data analytics work package within the Nuclear Materials Discovery and Qualification initiative (NMDQi). Topics include work on MOOSE-based crystal plasticity, molecular dynamics modeling of recombination in metals and alloys, the MOOSE Stochastic Tools Module, and machine learning and atomistic modeling to predict thermo-kinetic properties of nuclear structural materials.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Shock to detonation transition of pentaerythritol tetranitrate (PETN) initially pressed to 1.65 g/cm 3

A novel set of experiments and reactive flow modeling of pentaerythritol tetranitrate (PETN) is presented. In this work, the specific phenomenon of shock to detonation transition is examined, where an initial, relatively weak shock is propagated into pressed PETN powder at 1.65 g/cm 3 and the subsequent buildup to detonation is observed experimentally. These experiments, in conjunction with reactant and products’ equations of state, are utilized for building reactive flow models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Transient Coupled Chemical-Thermal-Fluid Field Simulation for Sealed Aluminum-clad Spent Nuclear Fuel Storage Canister

As the first step toward developing three-dimensional (3D) multi-physics computational fluid dynamics (CFD) model for unsealed and vented canister storage system, a 3D CFD model coupled with bulk gas radiolysis reactions was developed first for sealed DOE standard canisters filled with inert gas and trace amount of air and water. The workflow for constructing canister-scale 3D CFD models and coupling with gas phase radiolysis reactions were established, which can be readily extended to unsealed, vented canister storage system. This interim milestone report documents the theory of the model, workflow to establish radiolysis reaction network, and initial simulations of the evolutions of thermal fields and hydrogen gas concentrations within sealed DOE standard canisters over long period of time. In addition, a mesh refinement test was done to show that increasing the models mesh refinement had negligible impact upon the temperature profiles.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Refined Outgassing Model for the LiH/LiOH System

Previous models for H 2 and H 2 O outgassing from moisture exposed LiH specimens were based on temperature programmed desorption/decomposition (TPD) experiments and analyses that yielded kinetic descriptions which were specific to defined sets of initial conditions. Subsequently the inputs to the kinetic models were refined to correlate with infrared spectra of the adsorbed species. In this current enhancement, better agreement between prediction and experiment was obtained through: 1) refining the reaction mechanisms for some of the decomposition reactions; 2) developing the potential range of kinetic parameters by simultaneous fitting of all the TPD outgassing curves obtained at different heating rates; and, 3) limiting the scope of possible kinetic parameters to an optimized subset by matching the outgassing prediction curves at 3 different temperatures to the outcomes from the accurate but cumbersome, non-intuitive, and effort demanding isoconversional analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Seismic Monitoring at the Farnsworth CO2-EOR Field Using Time-Lapse Elastic-Waveform Inversion of 3D-3C VSP Data

During the Development Phase of the U.S. Southwest Regional Partnership on Carbon Sequestration, supercritical CO2 was continuously injected into the deep oil-bearing Morrow B formation of the Farnsworth Unit in Texas for Enhanced Oil Recovery (EOR). The project injected approximately 94 kilotons of CO2 to study geologic carbon storage during CO2-EOR. A three-dimensional (3D) surface seismic dataset was acquired in 2013 to characterize the subsurface structures of the Farnsworth site. Following this data acquisition, the baseline and three time-lapse three-dimensional three-component (3D-3C) vertical seismic profiling (VSP) data were acquired at a narrower surface area surrounding the CO2 injection and oil/gas production wells between 2014 and 2017 for monitoring CO2 injection and migration. With these VSP datasets, we inverted for subsurface velocity models to quantitatively monitor the CO2 plume within the Morrow B formation. We first built 1D initial P-wave (Vp) and S-wave (Vs) velocity models by upscaling the sonic logs. We improved the deep region of the Vp and Vs models by incorporating the deep part of a migration velocity model derived from the 3D surface seismic data. We improved the shallow region of 3D Vp and Vs models using 3D traveltime tomography of first arrivals of VSP downgoing waves. We further improved the 3D baseline velocity models using elastic-waveform inversion (EWI) of the 3D baseline VSP upgoing data. Our advanced EWI method employs alternative tomographic and conventional gradients and total-variation-based regularization to ensure the high-fidelity updates of the 3D baseline Vp and Vs models. We then sequentially applied our 3D EWI method to the three time-lapse datasets to invert for spatiotemporal changes of Vp and Vs in the reservoir. Our inversion results reveal the volumetric changes of the time-lapse Vp and Vs models and show the evolution of the CO2 plume from the CO2 injection well to the oil/gas production wells.

42 ENGINEERING↗
DOE OSTI2024

Revealing the unusual rate-dependent mechanical behaviors of nematic liquid crystal elastomers

Liquid crystal elastomers (LCEs) exhibit unique mechanical properties of soft elasticity and enhanced energy dissipation with rate dependency. They are potentially transformative materials for applications in mechanical impact mitigation and vibration isolation. However, previous studies have primarily focused on the mechanics of LCEs under equilibrium and quasistatic loading conditions. Critical knowledge gaps exist in understanding their rate-dependent behaviors, which are a complex mixture of traditional network viscoelasticity and the soft elastic behaviors with changes in the mesogen orientation and order parameter. Together, these inelastic mechanisms lead to unusual rate-dependent energy absorption responses of LCEs. In this work, we developed a viscoelastic constitutive theory for monodomain nematic LCEs to investigate how multiple underlying sources of inelasticity manifest in the rate-dependent and dissipative behaviors of monodomain LCEs. Here, the theoretical modeling framework combines the neo-classical network theory with evolution rules for the mesogen orientation and order parameter with conventional viscoelasticity. The model is calibrated with uniaxial tension and compression data spanning six decades of strain rates. The established 3D constitutive model enables general loading predictions taking the initial mesogen orientation and order parameter as inputs. Additionally, parametric studies were performed to further understand the rate dependence of monodomain LCEs in relation to their energy absorption characteristics. Based on the parametric studies, particularly loading scenarios are identified as conditions where LCEs outperform conventional elastomers regarding energy absorption.

42 ENGINEERING↗
DOE OSTI2023

Lessons learned in coupling atmospheric models across scales for onshore and offshore wind energy

Abstract. The Mesoscale to Microscale Coupling team, part of the U.S. Department of Energy Atmosphere to Electrons (A2e) initiative, has studied various important challenges related to coupling mesoscale models to microscale models for the use case of wind energy development and operation. Several coupling methods and techniques for generating turbulence at the microscale that is subgrid to the mesoscale have been evaluated for a variety of cases. Case studies included flat-terrain, complex-terrain, and offshore environments. Methods were developed to bridge the terra incognita, which scales from about 100 m through the depth of the boundary layer. The team used wind-relevant metrics and archived code, case information, and assessment tools and is making those widely available. Lessons learned and discerned best practices are described in the context of the cases studied for the purpose of enabling further deployment of wind energy.

17 WIND ENERGY↗
DOE OSTI2021

A predictive modeling tool for damage analysis and design of hydrogen storage composite pressure vessels

In this study, a predictive modeling tool is developed for damage analysis and design of hydrogen (H 2 ) storage composite pressure vessels. It integrates micromechanics of matrix cracking into a continuum damage mechanics (CDM) description for damage evolution, and three-dimensional (3D) finite element (FE) modeling of the vessel structural response. At the scale of the composite layer (mesoscale), the temperature-dependent stiffness reduction law in terms of the damage variable for transverse matrix cracking is computed using an Eshelby-Mori-Tanaka approach for the initial composite thermoelastic properties and a self-consistent model for the stiffness reduction as a function of the damage variable. While transverse matrix cracking obeying a damage evolution relation can progressively evolve from an initiation to a saturation state, fiber failure is predicted by a micromechanical fiber rupture criterion that accounts for the fiber strength and matrix stress. The implementation of this integrated multiscale modeling model into a 3D FE formulation enables damage analysis and design of H 2 storage composite pressure vessels. The developed tool is illustrated through 3D damage analyses of a cryogenically compressed H 2 storage vessel model subjected to thermomechanical loadings to investigate effects of the helical layer fiber orientation and loading scenario on damage development, vessel integrity and burst pressure.

08 HYDROGEN↗
DOE OSTI2024

Anomaly detection with flow-based fast calorimeter simulators

Recently, several normalizing flow-based deep generative models have been proposed to accelerate the simulation of calorimeter showers. Using caloflow as an example, we show that these models can simultaneously perform unsupervised anomaly detection with no additional training cost. As a demonstration, we consider electromagnetic showers initiated by one (background) or multiple (signal) photons. The caloflow model is designed to generate single-photon showers, but it also provides access to the shower likelihood. We use this likelihood as an anomaly score and study the showers tagged as being unlikely. As expected, the tagger struggles when the signal photons are nearly collinear but is otherwise effective. This approach is complementary to a supervised classifier trained on only specific signal models using the same low-level calorimeter inputs. While the supervised classifier is also highly effective at unseen signal models, the unsupervised method is more sensitive in certain regions, and, thus, we expect that the ultimate performance will require a combination of these approaches.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Steady Laminar Flame for 1-Step Thermal Decomposition Model of PBX 9501

We have recently developed a new 1-step thermal decomposition model of PBX 9501 high explosive. In this report, we examine the behavior of the model in 1-D steady laminar flame calculations. In particular, the dependencies of the steady laminar flame velocity on initial pressure, thermal conductivies and parameters of the thermal decomposition model are investigated. The results of our numerical calculations are compared to available experimental data.

42 ENGINEERING↗
DOE OSTI2022

Verification of MOOSE/Bison's Heat Conduction Solver Using Combined Spatiotemporal Convergence Analysis

Bison is a computational physics code that uses the finite element method to model the thermo-mechanical response of nuclear fuel. Since Bison is used to inform high-consequence decisions, it is important that its computational results are reliable and predictive. One important step in assessing the reliability and predictive capabilities of a simulation tool is the verification process, which quantifies numerical errors in a discrete solution relative to the exact solution of the mathematical model. One step in the verification process—called code verification—ensures that the implemented numerical algorithm is a faithful representation of the underlying mathematical model, including partial differential or integral equations, initial and boundary conditions, and auxiliary relationships. In this paper, the code verification process is applied to spatiotemporal heat conduction problems in Bison. Simultaneous refinement of the discretization in space and time is employed to reveal any potential mistakes in the numerical algorithms for the interactions between the spatial and temporal components of the solution. For each verification problem, the correct spatial and temporal order of accuracy is demonstrated for both first- and second-order accurate finite elements and a variety of time-integration schemes. Furthermore, these results provide strong evidence that the Bison numerical algorithm for solving spatiotemporal problems reliably represents the underlying mathematical model in MOOSE. The selected test problems can also be used in other simulation tools that numerically solve for conduction or diffusion.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

GNET2: an R package for constructing gene regulatory networks from transcriptomic data

Abstract Motivation The Gene Network Estimation Tool (GNET) is designed to build gene regulatory networks (GRNs) from transcriptomic gene expression data with a probabilistic graphical model. The data preprocessing, model construction and visualization modules of the original GNET software were developed on different programming platforms, which were inconvenient for users to deploy and use. Results Here, we present GNET2, an improved implementation of GNET as an integrated R package. GNET2 provides more flexibility for parameter initialization and regulatory module construction based on the core iterative modeling process of the original algorithm. The data exchange interface of GNET2 is handled within an R session automatically. Given the growing demand for regulatory network reconstruction from transcriptomic data, GNET2 offers a convenient option for GRN inference on large datasets. Availability and implementation The source code of GNET2 is available at https://github.com/jianlin-cheng/GNET2. Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Characterizing IHE Response to Multiple Shock Loading

The response of high explosives to shock loading is traditionally measured with a steady loading pressure. In many accident scenarios involving fragment impact, however, a loading duration that is shorter than the build up to detonation may occur. Fragments passing through multiple materials before reaching a high explosive charge may produce loading that is comprised of more than one shock wave. Additionally, the build up to detonation in high explosive corner turning loads the explosive a short duration pressure pulse, since rarefactions can often rapidly overtake the reactive wave. For these reasons, we have studied the response of the insensitive high explosive (IHE) materials PBX 9502 and LX-17 to complex loadings of varied intensity and duration. We refer to a single loading of limited duration as a “thin pulse”, whereas more complex scenarios were studied with an impactor that produces a double shock in the explosive. The following report presents experimental data and analyses of thin pulse shock initiation and double shock experiments designed to guide development of models of Insensitive High Explosives (IHEs) under controlled one-dimensional conditions relevant to accident scenarios and corner turning. Thin pulse shock initiation data on PBX 9502 and LX-17 were obtained under varied pulse duration, pressed density, and temperature conditions in order to probe various parameters essential for the development of a physics-based Cheetah reactive flow hotspot model. In situ pressure gauges provide insight into the degree of reaction in the explosive that are not obtainable with optical PDV measurements or distance measurements such as run to detonation. Double shock data was obtained to inform a Composition Aware Cheetah model which can be applied to any TATB-based IHEs. This model supports efforts to find a new IHE formulation and potentially incorporate new binders into IHE formulations. Simulations of each experiment are included to demonstrate the utility of these focused experiments to developing models of HE behavior. One-dimensional gas gun experiments are essential for characterizing shocked HE behavior and informing HE models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

A comprehensive modeling procedure for estimating statistical properties of forced ignition

In this work, a comprehensive modeling procedure for estimating the probability of ignition with application to high altitude relights of aircraft combustors is developed. In these configurations, an ignitor is used to introduce high-enthalpy discharge into a fuel-laden but stratified flow. Because of the inherent variabilities inflow conditions, kernel discharge process, and the chaotic turbulent flow, ignition cannot be described deterministically, but only as a probabilistic measure. The proposed modeling framework consists of three components. The turbulent flow is represented using the large eddy simulation (LES) framework. The ignition process is modeled using a manifold approach, where the initial kernel evolution is represented using a homogeneous reactor while the latter part of the evolution is represented as a competition between diffusion and chemical reactions using a flamelet-type mapping. A combined lookup table that can track the evolution of the kernel through these two distinct reaction stages is developed. The table lookup variables are solved within the LES framework. The resulting simulation tool is then embedded within an uncertainty quantification approach, where variations in the turbulent flow, as well as operating and kernel properties, are simulated using a Monte-Carlo-based sampling approach. Techniques to reduce computational cost are used to obtain a robust, numerically accurate, and physically representative model for engine relight. The method is validated using experimental data for ignition of methane/air mixtures. Due to the comprehensive nature of the modeling procedure, it is found that the simulation tool reproduces experimentally observed ignition probabilities over a wide range of operating conditions.

42 ENGINEERING↗
DOE OSTI2023

Statistical chronometry of Meteorites: II. Initial abundances and homogeneity of short-lived radionuclides

Astrophysical models of planet formation require accurate radiometric dating of meteoritic components by short-lived (Al-Mg, Mn-Cr, Hf-W) and long-lived (U-Pb) chronometers, to develop a timeline of such events in the solar nebula as formation of Ca-rich, Al-rich Inclusions (CAIs), chondrules, planetesimals, etc. CAIs formed mostly around a time (“t=0”) when the short-lived radionuclide 26 Al (t 1/2 = 0.72 Myr) was present and presumably homogeneously distributed at a known level we define as ( 26 Al/ 27 Al) SS = 5.23 × 10 -5 . The time of formation after t=0 of another object can be found by determining its initial ( 26 Al/ 27 Al) 0 ratio and comparing it to ( 26 Al/ 27 Al) SS . Dating of meteoritic objects using the Mn-Cr or Hf-W systems is hindered because the abundances ( 53 Mn/ 55 Mn) SS and ( 182 Hf/ 180 Hf) SS at t=0 are not known precisely. To constrain these quantities, we compile literature Al-Mg, Mn-Cr, Hf-W and Pb-Pb data for 13 achondrites and use novel statistical techniques to minimize the discrepancies between their times of formation across these systems. We find that for ( 53 Mn/ 55 Mn) SS = (7.80±0.36)×10 -6 , ( 182 Hf/ 180 Hf) SS = (10.41 ± 0.12) × 10-5, t SS = 4568.65 ± 0.10 Myr, and a 53 Mn half-life of 3.98 ± 0.22 Myr, these four free parameters make concordant 18 formation times recorded by the different systems in all six known volcanic achondrites (the quenched angrites D’Orbigny, Sahara 99555, Northwest Africa 1670; the psuedo-eucrites Asuka 881394 and Ibitira; and the basaltic achondrite Northwest Africa 7325). These parameters also make concordant the ages derived for chondrules from CB/CH achondrites, formed simultaneously in an impact. The other seven achondrites are not quite concordant, but are plutonic angrites or ‘carbonaceous achondrites’ for which simultaneous closure of the isotopic systems might not be expected. Our findings provide very strong support for homogeneity of 26 Al, 53 Mn, and 182 Hf in the solar nebula, and our approach offers a path for more precise chronometry

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Development of phenomena identification and ranking table for Westinghouse lead fast reactor’s safety

The Westinghouse Lead-cooled Fast Reactor (LFR) is a medium-size, passively safe, economic, Gen-IV nuclear reactor. An important effort within the Westinghouse LFR program is the development of the safety analysis methodology, which comprises computer code development, model development, and experimental testing. A key initial task associated with the development of the safety analysis methodology is the identification of processes and phenomena that affect the plant's capability to meet selected safety performance indicators. This is accomplished through the development of a Phenomena Identification and Ranking Table (PIRT) for selected accident scenarios which, for this specific PIRT effort, included selected postulated design basis accidents and hypothetical beyond design basis accidents in LFRs. This paper describes the role of PIRT in the development of the Westinghouse LFR safety analysis methodology and the process used in the PIRT development. Specifically, the Westinghouse LFR PIRT assessed importance of pertinent phenomena and identified gaps in their knowledge-base by evaluating current modeling capabilities and data available for validation. The ultimate goal was to provide guidance on computer code development and validation efforts and to prioritize testing to support LFR design and licensing. The key phenomena and processes that are deemed highly important for the safety performance indicators, but for which the state of knowledge is low, are presented. The testing program and analyses development are planned to address significant phenomena in the PIRT.

Lead fast reactor↗
DOE OSTI2026

Deflagration to Detonation Transition Update: XDDT Code Modularization

A legacy FORTRAN 77 implementation of the Baer–Nunziato two-phase mixture theory for deflagration-to-detonation transition (DDT) in reactive granular materials—hereafter the XDDT (eXplosive DDT) code—has been modularized to Fortran 90 with modular structure, external input files, and adaptive mesh capability. During validation, two code defects were identified and corrected: an inconsistency in the nodal solid pressure evaluation and a nonphysical burn-front tracking criterion. The ignition criterion was also corrected to use the granular surface temperature from the interface heat transfer model, matching the original Baer implementation. An initial attempt to validate against Figure 3 of the original Baer and Nunziato (1986) paper revealed that the code’s detonation velocity on a 201-node mesh (5.5 km/s) was approximately 21% below the expected Chapman–Jouguet value for 70% TMD HMX (∼7 km/s). Validation was redirected to the piston-driven DDT experiments of McAfee et al. (1989), Shot B-9036, for which well-characterized ionization-pin data are available. With the compaction-burn coefficient calibrated to 𝐶 𝛼 = 75, the XDDT code reproduces the DDT transition time to within 0.4% and produces a steady-state detonation velocity within 4% of the McAfee experimental value of 6.36 km/s. The burn model was generalized to support pressure-dependent exponents, enabling application to nitrocellulose-based ball propellants (TS3659) with a cube-root pressure dependence. Validation against the Sandusky/Baer PDC82 piston-impact experiment yielded a reactive wave velocity of 2.3–2.8 km/s, in good agreement with the experimental value of ∼2.2 km/s, and wave coalescence within 5% of the experimental timing. The mathematical model, input parameter requirements, and a roadmap for extending XDDT to PETN with an autocatalytic burn model are presented.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

Machine Learning Emulation of Spatial Deposition from a Multi-Physics Ensemble of Weather and Atmospheric Transport Models

In the event of an accidental or intentional hazardous material release in the atmosphere, researchers often run physics-based atmospheric transport and dispersion models to predict the extent and variation of the contaminant spread. These predictions are imperfect due to propagated uncertainty from atmospheric model physics (or parameterizations) and weather data initial conditions. Ensembles of simulations can be used to estimate uncertainty, but running large ensembles is often very time consuming and resource intensive, even using large supercomputers. In this paper, we present a machine-learning-based method which can be used to quickly emulate spatial deposition patterns from a multi-physics ensemble of dispersion simulations. We use a hybrid linear and logistic regression method that can predict deposition in more than 100,000 grid cells with as few as fifty training examples. Logistic regression provides probabilistic predictions of the presence or absence of hazardous materials, while linear regression predicts the quantity of hazardous materials. The coefficients of the linear regressions also open avenues of exploration regarding interpretability—the presented model can be used to find which physics schemes are most important over different spatial areas. A single regression prediction is on the order of 10,000 times faster than running a weather and dispersion simulation. However, considering the number of weather and dispersion simulations needed to train the regressions, the speed-up achieved when considering the whole ensemble is about 24 times. Ultimately, this work will allow atmospheric researchers to produce potential contamination scenarios with uncertainty estimates faster than previously possible, aiding public servants and first responders.

97 MATHEMATICS AND COMPUTING↗