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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Understanding the influence of defects and surface chemistry on ferroelectric switching: a ReaxFF investigation of BaTiO 3

Ferroelectric materials such as barium titanate (BaTiO 3 ) have a wide range of applications in nano scale electronic devices due to their outstanding properties. In this study, we developed an easily extendable atomistic ReaxFF reactive force field for BaTiO 3 that can capture both its field- and temperature-induced ferroelectric hysteresis and corresponding changes due to surface chemistry and bulk defects. Using our force field, we were able to reproduce and explain a number of experimental observations: (1) the existence of a critical thickness of 4.8 nm below which ferroelectricity vanishes in BaTiO 3 ; (2) migration and clustering of oxygen vacancies (OVs) in BaTiO 3 and a reduction in the polarization and the Curie temperature due to the OVs; (3) domain wall interaction with the surface chemistry to influence the ferroelectric switching and polarization magnitude. This new computational tool opens up a wide range of possibilities for making predictions for realistic ferroelectric interfaces in energy-conversion, electronic and neuromorphic systems.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A Novel Partitioned Approach for Reduced Order Model—Finite Element Model (ROM-FEM) and ROM-ROM Coupling

Partitioned methods allow one to build a simulation capability for coupled problems by reusing existing single-component codes. In so doing, partitioned methods can shorten code development and validation times for multiphysics and multiscale applications. In this work, we consider a scenario in which one or more of the “codes” being coupled are projection-based reduced order models (ROMs), introduced to lower the computational cost associated with a particular component. We simulate this scenario by considering a model interface problem that is discretized independently on two non-overlapping subdomains. Here we then formulate a partitioned scheme for this problem that allows the coupling between a ROM “code” for one of the subdomains with a finite element model (FEM) or ROM “code” for the other subdomain. The ROM “codes” are constructed by performing proper orthogonal decomposition (POD) on a snapshot ensemble to obtain a low-dimensional reduced order basis, followed by a Galerkin projection onto this basis. The ROM and/or FEM “codes” on each subdomain are then coupled using a Lagrange multiplier representing the interface flux. To partition the resulting monolithic problem, we first eliminate the flux through a dual Schur complement. Application of an explicit time integration scheme to the transformed monolithic problem decouples the subdomain equations, allowing their independent solution for the next time step. We show numerical results that demonstrate the proposed method’s efficacy in achieving both ROM-FEM and ROM-ROM coupling.

de Castro, Amy↗
DOE OSTI2022

Interleukin-2 superkines by computational design

Significance While computational engineering of therapeutic proteins is a desirable goal, in practice the optimization of protein–protein interactions requires substantial experimental intervention. We present here a computational approach that focuses on stabilizing core protein structures rather than engineering the protein–protein interface. Using this approach, we designed thermostabilized interleukin-2 (IL-2) variants that bind tightly to their receptor without experimental optimization, mimicking the properties of the yeast-display engineered IL-2 variant “super-2.” Our results suggest that structure-guided stabilization may be a general method for in silico affinity maturation of protein–protein interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Interfacial engineering of phthalocyanine molecules on graphitic and metal substrates

Metal porphyrin and phthalocyanine have found variety of applications in catalysis, electronic and spintronic devices and photovoltaic cells, many of which rely on accurate position of the molecules and alignment of their electronic levels with respect to the substrate. The substrate and local environment affect significantly the electronic properties of these macrocyclic molecules. Computational simulations provide valuable insights for engineering the molecule–metal, molecule–molecule and molecule–ligand interfaces. In this review, we focus on adsorption of metal phthalocyanine, particularly iron phthalocyanine, on graphite, epitaxial graphene, and metal substrates. Furthermore, these systems show varied interfacial binding strength and chameleon-like molecular electronic structures. Spin of the molecules can be controlled by small ligands, and the ground state can be tuned between S = 1, S = 1/2 and S = 0. Inclusion of van der Waals interaction in the first-principles calculations is shown to be essential for accurate description of the interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Preserving Command Line Workflow for a Package Management System using ASCII DAG Visualization

Package managers provide ease of access to applications by removing the time-consuming and sometimes completely prohibitive barrier of successfully building, installing, and maintaining the software for a system. A package dependency contains dependencies between all packages required to build and run the target software. Package management system developers, package maintainers, and users may consult the dependency graph when a simple listing is insufficient for their analyses. However, users working in a remote command line environment must disrupt their workflow to visualize dependency graphs in graphical programs, possibly needing to move files between devices or incur forwarding lag. Such is the case for users of Spack, an open source package management system originally developed to ease the complex builds required by supercomputing environments. To preserve the command line workflow of Spack, we develop an interactive ASCII visualization for its dependency graphs. Through interviews with Spack maintainers, we identify user goals and corresponding visual tasks for dependency graphs. We evaluate the use of our visualization through a command line-centered study, comparing it to the system's two existing approaches. We observe that despite the limitations of the ASCII representation, our visualization is preferred by participants when approached from a command line interface workflow.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Microstructural examination of interactions between chromia-based refractory and nuclear glass in a melter

This study shows the effects of nuclear waste glass production on Monofrax K-3 refractory corrosion. A continuously fed research-scale melter containing an Fe- and Ni-rich simulated nuclear waste feed with borosilicate glass-forming chemicals was cyclically melted at 1150°C and idled at 1050°C for a total of 11 weeks. Chemical maps using scanning electron microscopy show the interactions between the quenched melt and the refractory. Nanoscale X-ray-computed tomography was used for a three-dimensional visualization of certain parts of the interface. Unreacted K-3 consists of primarily corundum (Al,Cr) 2 O 3 and spinel (Fe 2+ ,Mg)(Al,Cr) 2 O 4 interlocking crystalline phases. Some of the Cr from the refractory interacts with the Ni and Fe from the melt to form a reaction layer comprising (Ni,Fe 2+ )(Cr,Fe 3+ ) 2 O 4 spinel crystals. Simultaneously, melt components (Na,Si) infiltrate into the refractory. This interaction proceeds at the expense of the integrity of the refractory structure. Intact refractory grains (e.g., (Al,Cr) 2 O 3 ) as well as the reaction layer itself can lose mechanical integrity and spall off into the melt, especially near the top of the melter. As the reaction layer can be a protective boundary for the refractory against further melt infiltration, a reduction in the reaction layer thickness allows an increase in refractory corrosion.

36 MATERIALS SCIENCE↗
DOE OSTI2016

SENSMG: First-Order Sensitivities of Neutron Reaction Rates, Reaction-Rate Ratios, Leakage, k eff , and α Using PARTISN

SENSMG is a tool for computing first-order sensitivities of neutron reaction rates, reaction-rate ratios, leakage, k eff , and α using the PARTISN multigroup discrete-ordinates code. SENSMG computes sensitivities to all of the transport cross sections and data (total, fission, nu, chi, and all scattering moments), two edit cross sections (absorption and capture), and the density for every isotope and energy group. It also computes sensitivities to the mass density for every material and derivatives with respect to all interface locations. The tool can be used for one-dimensional spherical (r) and two-dimensional cylindrical (r-z) geometries. The tool can be used for fixed-source and eigenvalue problems. The tool implements Generalized Perturbation Theory (GPT) as discussed by Williams and Stacey. Section II of this report describes the theory behind adjoint-based sensitivities, gives the equations that SENSMG solves, and defines the sensitivities that are output. Section III describes the user interface, including the input file and command line options. Section IV describes the output. Section V gives some notes about the coding that may be of interest. Section VI discusses verification, which is ongoing. Section VII lists needs and ideas for future work. Appendix A lists all of the input files whose results are presented in Sec. VI.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

(U) SENSMG: First-Order Sensitivities of Neutron Reaction Rates, Reaction-Rate Ratios, Leakage, k eff , α, and Subcritical Multiplication Using PARTISN

SENSMG is a tool for computing first-order sensitivities of neutron reaction rates, reaction-rate ratios, leakage, keff, α, and subcritical multiplication using the PARTISN multigroup discrete-ordinates code.1 SENSMG computes sensitivities to all of the transport cross sections and data (total, fission,a nu, chi, and all scattering moments), four edit cross sections (absorption, capture, elastic scattering, and inelastic scattering), and the density for every isotope and energy group. It also computes sensitivities to the mass density for every material and derivatives with respect to all interface locations and outer boundaries. The tool can be used for one-dimensional spherical and slab (r) and two-dimensional cylindrical (r-z) geometries.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

G2PDeep-v2: A Web-Based Deep-Learning Framework for Phenotype Prediction and Biomarker Discovery for All Organisms Using Multi-Omics Data

Multi-omics data offers rich insights into complex traits across organisms, yet integrating and analyzing these datasets for phenotype prediction and marker discovery remains challenging. Researchers need accessible tools that combine deep learning, hyperparameter optimization, visualization, and downstream analysis in a unified web platform. To address this, we developed G2PDeep-v2, a web-based platform powered by deep learning for phenotype prediction and marker discovery from multi-omics data across a wide range of organisms, including humans and plants. The server provides multiple services for researchers to create deep-learning models through an interactive interface and train these models using an automated hyperparameter tuning algorithm on high-performance computing resources. Users can visualize the results of phenotype and markers predictions and perform Gene Set Enrichment Analysis for the significant markers to provide insights into the molecular mechanisms underlying complex diseases, conditions and other biological phenotypes being studied.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Machine Learning Methods for Connection RTT and Loss Rate Estimation Using MPI Measurements Under Random Losses

Scientific computations are expected to be increasingly distributed across wide-area networks, and Message Passing Interface (MPI) has been shown to scale to support their communications over long distances. Application-level measurements of MPI operations reflect the connection Round-Trip Time (RTT) and loss rate, and machine learningmethods have been previously developed to estimate them under deterministic periodic losses. In this paper, we consider more complex, random losses with uniform, Poisson and Gaussian distributions. We study five disparate machine leaning methods, with linear and non-linear, and smooth and non-smooth properties, to estimate RTT and loss rate over 10 Gbps connections with 0–366 ms RTT. The diversity and complexity of these estimators combined with the randomness of losses and TCP’s non-linear response together rule out the selection of a single best among them; instead, we fuse them to retain their design diversity. Overall, the results show that accurate estimates can be generated at low loss ratesbut become inaccurate at loss rates 10% and higher, thereby illustrating both their strengths and limitations.

Rao, Nageswara S.↗
DOE OSTI2018

A New Safeguards Technique for Spent Fuel Verification in Dry Storage by Using He-4 Detectors - 18262

It is demanded to find key issues and critical paths for verifying and monitoring a spent nuclear fuel cask or storage with a purpose of non-proliferation of nuclear weapon. However, unfortunately there are no reliable methods to verify the containment in a spent nuclear fuel cask or storage. Therefore, research and development (R and D) has been continuously required to develop new and alternative technologies for searching and verifying undeclared nuclear materials, activities, and facilities. Therefore, the present authors have developed a new safeguards technique of passively scanning a spent fuel cask or storage using pressurized He-4 scintillation neutron detectors. A new approach is to quickly verify content in a spent nuclear fuel cask or presence of all special nuclear materials in unknown packages by comparing experimental and computational results. For that, the present authors have developed a new algorithm and user-interface coupled ORIGEN-ARP and MCNP codes, and the prototype safeguards apparatus employing the array of He-4 fast neutron detectors has been designed, built, and tested. The feasibility test of this new apparatus has been performed with Cf-252 neutron sources and the laboratory scale model cask, minimized by a factor of ten compared to the actual dimension of a KN-21 cask. This technique has several advantages over current methods based on neutron and gamma detection; (1) incident neutron energy information is preserved, (2) disturbance of gamma-ray is excellently rejected (discriminated), and (3) much higher neutron counts and operational cost and space-effectiveness are expected since no moderator is required for fast neutrons. The final goal of this study will (1) conduct a prototype instrument and employ it to monitor a nuclear spent fuel cask or storage at a commercial nuclear power reactor facilities, (2) use spectral-specific measurement data to show proof of concept for measurable data successfully converted to quantifiable signatures, such as diversion/removal of fuel, and maintenance of fuel and cask integrity of fuel, and (3) develop a cask imaging capability. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Network traffic control for multi-homed end-hosts via SDN

Software-defined networking (SDN) is an emerging technology of efficiently controlling and managing computer networks, such as in data centres, wide-area networks, as well as in ubiquitous communication. In this study, the authors explore the idea of embedding the SDN components, represented by SDN controller and virtual switch, in end-hosts to improve network performance. In particular, the authors consider load balancing across multiple network interfaces on end-hosts with different link capacity scenarios. The authors have explored and implemented different SDN-based load-balancing approaches based on OpenFlow software switches, and have demonstrated the feasibility and the potential of this approach. The proposed system has been evaluated with MultiPath transmission control protocol (MPTCP). Furthermore, the proposed results demonstrated the potential of applying the SDN concepts on multi-homed devices resulting in an increase in achieved throughput of 55% compared to the legacy single network approach and 10% compared to the MPTCP.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Sensitivity analysis of the technical and economic feasibility of converter-interfaced CHP System

The adoption of small-to-medium sized (1MW~20MW) combined heat and power (CHP) system is lagging, especially in industrial and commercial applications. Our prior research has proved that interfacing CHP with grid-ready converters can increase its economic value and technical benefits; this paper is focused on investigating the critical parameters impacting profitability of converter-interfaced CHP, including CHP sizing scenario, energy price, generator cost, converter cost, voltage support price, converter to engine size ratio and interconnection delay. An automatic toolkit for evaluating CHP return on investment (ROI) is developed to enhance the computation capability and efficiency. Based on varying the value of critical parameters, 975 use cases are analyzed. Results show that the profitability of converter-interfaced CHP over directly-coupled CHP is more sensitive to energy price, delays in interconnection process, converter cost and much less to generator cost or voltage support price.

converter, CHP, ROI, economic feasibility, sensiti↗
DOE OSTI2023

Normality of I-V Measurements Using ML

There is an increased interest in instrument-computing ecosystems (ICEs) that support science workflows empowered by AI-automated experiments and computations in diverse areas. In particular, electrochemistry ICEs are promising for accelerating the design and discovery of electrochemical systems for energy storage and conversion, by automating significant parts of workflows that combine synthesis and characterization experiments with computations. They require the integration of flow controllers, solvent containers, pumps, fraction collectors, and potentiostats, all connected to an electrochemical cell, as illustrated in Fig. 1. These are specialized instruments with custom software that is not originally designed for network integration. We developed network and software solutions for electrochemical workflows that adapt system and instrument settings in real-time for multiple rounds of experiments. In particular, we developed Python wrappers for Application Programming Interfaces (APIs) of instrument commands and Pyro client-server modules that enable them to be executed from remote computers. The entire workflow is orchestrated by a Jupyter notebook running on a remote computer.

Al Najjar, Anees↗
DOE OSTI2016

Tracking interface and common curve dynamics for two-fluid flow in porous media

Pore-scale studies of multiphase flow in porous medium systems can be used to understand transport mechanisms and quantitatively determine closure relations that better incorporate microscale physics into macroscale models. Multiphase flow simulators constructed using the lattice Boltzmann method provide a means to conduct such studies, including both the equilibrium and dynamic aspects. Moving, storing, and analyzing the large state space presents a computational challenge when highly-resolved models are applied. We present an approach to simulate multiphase flow processes in which in-situ analysis is applied to track multiphase flow dynamics at high temporal resolution. We compute a comprehensive set of measures of the phase distributions and the system dynamics, which can be used to aid fundamental understanding and inform closure relations for macroscale models. The measures computed include microscale point representations and macroscale averages of fluid saturations, the pressure and velocity of the fluid phases, interfacial areas, interfacial curvatures, interface and common curve velocities, interfacial orientation tensors, phase velocities and the contact angle between the fluid-fluid interface and the solid surface. Test cases are studied to validate the approach and illustrate how measures of system state can be obtained and used to inform macroscopic theory.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Multiphysics Degradation Modeling of Energy Storage Materials via RKPM with a Neural Network-Enhancement

In energy storage materials, strong electrochemical-mechanical coupling and highly anisotropic material properties contribute to the formation and propagation of micro-cracking during charge/discharge cycling, resulting in reduced performance and service life. A coupled electro-chemo-mechanical reproducing kernel particle method (RKPM) formulation is developed, and a patch-test is formulated to certify optimal convergence of the proposed RKPM method for the coupled physics system. With microstructural images supplied by the National Renewable Energy Laboratory (NREL), pixel-based model construction by RKPM is then used to represent the complex material microstructures for modeling the coupled physics of these systems. Further, a neural network-enhanced reproducing kernel particle method (NN-RKPM) [1, 2] is introduced to effectively model damage and crack propagation in the material microstructures; the location, orientation, and solution transition near a localization are automatically captured by superimposed block-level NN optimizations. This NN enrichment approach allows for effective modeling of localizations via a fixed background discretization, relieving tedious efforts for adaptive refinement in traditional mesh-based methods. Applications to the heterogeneous microstructures of Li-ion battery cathodes will be presented to demonstrate the effectiveness of the proposed methods. Reference: [1] Baek, J., Chen, J. S., Susuki, K., "Neural Network enhanced Reproducing Kernel Particle Method for Modeling Localizations," International Journal for Numerical Methods in Engineering, Vol. 123, pp 4422-4454, https://doi.org/10.1002/nme.7040, 2022. [2] Baek, J., Chen, J. S., "A Neural Network-Based Enrichment of Reproducing Kernel Approximation for Modeling Brittle Fracture", Computer Methods in Applied Mechanics and Engineering Vol. 410, 116590, 2024.

electro-chemo-mechanical coupling↗
DOE OSTI2018

Updated status of the ART neutronic fast reactor tools integration to the NEAMS Workbench

The Workbench initiative was launched in FY-2017 within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) Integration Product Line to facilitate the transition from conventional tools to high-fidelity tools. The Workbench provides a common user interface for model creation, real-time validation, execution, output processing, and visualization for integrated codes. The integration of the Argonne Reactor Computation (ARC) suite of codes into the NEAMS Workbench was initiated in FY-2017. The ARC codes contain both legacy codes like DIF3D and REBUS-3 that were developed with over 30 years of experience, and newer NEAMS additions like MC 2 -3 and PERSENT. The ARC integration into the NEAMS Workbench interface relies on the PyARC module which handles the pre- and post-processing of the native ARC codes input, and the runtime environment. The PyARC module together with the NEAMS Workbench interface are both released under Open Source Software licenses. This report describes the ARC capabilities available with the Workbench at the end of FY-2018, and a tutorial is provided together with the automatically-generated code documentation. Integrating the ARC codes into the Workbench benefits directly the Advanced Reactor Technology (ART) Campaign by providing a set of controlled, maintained and validated scripts to generate ARC inputs, which promotes best practices, reduces the learning curve, and facilitates project collaboration. The second benefit from this project is to improve the user experience with the ARC codes: the Workbench interface provides assistance for building an input through auto-completion, real-time validation, access to templates, and visualization. Finally, the ARC integration into the NEAMS Workbench enables new modeling capabilities, those will be extremely useful for advanced reactor design and analyses. The PyARC module facilitates and automatizes complex calculations and workflows for reactor analysis enabling geometrical perturbations, cross-section update through depletion, etc. The Dakota/PyARC coupling in the Workbench was also demonstrated to enable mathematical optimization and sensitivity analysis/uncertainty quantification (SA/UQ) techniques with ARC neutronic simulations. For demonstration purposes, the ARC codes were used through the Workbench for solving the Sodium-cooled Fast Reactor Uncertainty Analysis in Modelling (SFR-UAM) benchmark problems. The ARC codes are currently used at ANL through the Workbench by nuclear engineers for SFR core design analyses. Future efforts will focus on continuously adding modeling capabilities available with the ARC codes, training new users to continue building some experience, and on integrating high-fidelity codes such as PROTEUS into the Workbench.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗