SEARCH · Engineering Papers

Results for “functional modeling”

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.

SourceResearch connectionFrom yearThrough year

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

At least 811 records · Page 45

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Design of a Scavenging Pyrrole Additive for High Voltage Lithium-Ion Batteries

We report 1-(dimethylamino) pyrrole (PyDMA) as an electrolyte additive for high voltage lithium-ion batteries based on LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC622)//Graphite with an upper cutoff voltage of 4.4 V. Density Functional Theory (DFT) modeling indicates that the unique structure of PyDMA could be effective in preventing the hydrolysis of LiPF 6 in a carbonate electrolyte, mitigating issues related to HF formation. The calculations also indicated that the additive would oxidize at lower potentials than typical electrolyte solvents, which could lead to protective films at the cathode surface. These expectations were tested using Nuclear Magnetic Resonance (NMR) and extensive electrochemical characterization. NMR studies confirmed the superb dehydrating capability of PyDMA, which successfully prevents HF formation even at high water content. Addition of 0.5 wt% PyDMA resulted in improved capacity retention in full-cells, and also in lower levels of transition metal dissolution from the cathode. Incremental capacity (dQ/dV) analysis indicates that benefits of PyDMA at low concentration (0.5–1 wt%) are associated with decreased rates of Li + -trapping reactions, and that higher concentrations of the additive can lead to isolation of cathode domains. Furthermore, our study indicates that PyDMA could be a promising electrolyte additive for high voltage lithium-ion batteries at a low concentration.

25 ENERGY STORAGE↗

DOE OSTI2021

Keras CT Segmentation v.1

SAND2020-14119 O A Tensorflow and Keras-backed framework for learned segmentation methods of 3D CT scan volumes. Supported functionality includes training models, running inference and quantifying uncertainty. The main underlying model architecture is V-Net. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Ganter, Tyler↗

DOE OSTI2024

Multiplayer Engineering

INL engineers developed a special purpose software framework designed to establish real-time connections between multiple running Unity instances. The framework is developed in Unity, a game engine development platform. This framework programmatically attaches functions to engineering models, enabling users to interact with, observe, and make changes to virtual models. These interactions are broadcasted through websocket connections, and received by other engineers in real-time.

Woodruff, Nathan↗

DOE OSTI2024

LTAU-FF: Loss Trajectory Analysis for Uncertainty in atomistic Force Fields

LTAU (Loss Trajectory Analysis for Uncertainty) is a technique for estimating the uncertainty in a model's predictions for any regression task by approximating the cumulative distribution function (CDF) of the model's errors over the course of training. The approximated CDF, combined with a similarity search algorithm in the model's descriptor space, can then be used to estimate the likelihood that the model's predictions on any given test point will fall below a chosen threshold. LTAU-FF (LTAU in atomistic Force Fields) is the application of LTAU specifically for use with atomistic force fields.

Vita, JoshuaA↗

DOE OSTI2024

LATTE: Los Alamos TravelTime package based on Eikonal equation

This Fortran code focuses on traveltime computation and tomography based on eikonal equation. Specifically, the package provides three major functionalities: (1) forward modeling of traveltime from single-point or ensemble source based on factorized eikonal equation, (2) adjoint-state first-arrival traveltime tomography based on picked first arrival traveltime using steepest descent, conjugate gradient, or limited-memory BFGS inversion scheme, and (3) adjoint-state joint transmission-reflection tomography based on picked first-arrival and reflection traveltimes. The package applies to forward modeling and tomography based on traveltime in 2D and 3D isotropic regular-grid models. We name this package LATTE – Los Alamos TravelTime package based on Eikonal equation. * The code is for accompanying a journal paper under preparation. The paper will be submitted via LA-UR separately later.

Gao, Kai↗

DOE OSTI2025

blastforge

BlastForge is a python module meant to aid reinforcement learning research for geometry optimization research projects. The code is built to use PyTorch as a backend and will contain several model architectures and reinforcement learning training loops as well as helper python functions to evaluate a model’s performance during and after training. BlastForge is meant to be a small, focused python project to study moderate-complexity geometry optimization problems

Hickmann, Kyle [Los Alamos National Laboratory]↗

DOE OSTI2021

Powder Diffraction Crystallography : 98 Years as Plan B?

A historical essay written in 2014 to accompany a talk in the Transactions Symposium "100 Years of Crystallography" at the 2014 American Crystallographic Association Annual Meeting (talk at https://history.amercrystalassn.org/h-brian-toby-videos). Abstract: Powder diffraction patterns were used for structure solution almost contemporaneously with the Bragg’s initial single-crystal determinations. Structures have continued to be determined from powders, in the subsequent century. There has been a nearly explosive growth in this technique since the 1970’s. This was initially driven by neutron diffraction, which prompted the invention of Rietveld analysis, but synchrotrons have gone on to have at least as large an impact. There is no apparent upper limit to the scale of systems that can be structurally studied with powder diffraction; novel protein structures have been determined. When short-range ordering or disordered regions of a material are of interest, the Fourier transform of a powder diffraction pattern, the pair distribution function can be modeled.

Toby, Brian H.↗

DOE OSTI2023

Autonomous Fracture Conductivity Using Expandable Proppants in Enhanced Geothermal Systems

Summary Early thermal breakthrough in enhanced geothermal systems (EGS) due to the presence of preferential flow channels is a major challenge that endangers efficient and economic heat extraction in such systems. Previous studies mainly focused on adjusting circulation rates of the working fluid, which still leaves significant amounts of untapped heat behind. Currently, there is a lack of technologies for altering flow distribution within the fracture network to achieve uniform heat sweeping in the reservoir. This work presents a novel concept for making proppants to autonomously control fracture conductivity based on the surrounding temperature. Here, proppants with negative thermal expansion coefficients have demonstrated the capability for appropriate fracture conductivity adjustment as a function of temperature to achieve uniform flow across the fracture network. Particle-particle interactions governing such functions are explicitly modeled, and then the Lattice Boltzmann methods (LBM) is used to determine the potential impact of closure stress and temperature changes on the permeability of the proposed proppant packs. Microscale analyses are further used to determine the required material properties to achieve a certain improvement in the permeability of the proppant pack. Our analyses show an enhancement in permeability and the associated fracture conductivity by half of their initial values. Field-scale analysis further confirms the effectiveness of the proposed concept as 31.4% more heat can be extracted from EGS over 50 years of production when the proposed proppants are used. Such novel proppants may effectively delay thermal breakthrough, sweep heat from larger rock volumes, and elongate the life span of the EGS project.

Engineering↗

DOE OSTI2023

New machine learning techniques for simulation-based inference: InferoStatic nets, kernel score estimation, and kernel likelihood ratio estimation

We propose an intuitive, machine-learning approach to multiparameter inference, dubbed the InferoStatic Networks (ISN) method, to model the score and likelihood ratio estimators in cases when the probability density can be sampled but not computed directly. The ISN uses a backend neural network that models a scalar function called the inferostatic potential \varphi φ . In addition, we introduce new strategies, respectively called Kernel Score Estimation (KSE) and Kernel Likelihood Ratio Estimation (KLRE), to learn the score and the likelihood ratio functions from simulated data. We illustrate the new techniques with some toy examples and compare to existing approaches in the literature. We mention en passant some new loss functions that optimally incorporate latent information from simulations into the training procedure.

Kong, Kyoungchul↗

DOE OSTI2023

Codebase release 0.1 for infstat

Kong, Kyoungchul↗

DOE OSTI2020

Final Technical Report for project entitled Highly Active, Durable, and Ultra-Low PGM NSTF Thin Film ORR Catalysts and Support

In this project, the objective was to develop new oxygen reduction reaction (ORR) electrocatalysts for proton exchange membrane fuel cells (PEMFCs) which could exceed all of the Department of Energy (DOE) 2020 targets listed in DE-FOA-0001224, Subtopic 1b, Table I. The expected outcome was development of one or more electrocatalysts which are substantially improved over the current state-of-the-art in terms of overall activity, durability, and cost, and are suitable for automotive traction and stationary fuel cell applications. This report summarizes this project’s progress towards meeting the stated objectives and includes a summary of key findings and conclusions. The development activities towards new highly active and durable thin film electrocatalysts has led to the discovery of several electrocatalysts which approached or exceeded several DOE 2020 targets for activity, durability, and performance in proton exchange membrane fuel cell (membrane electrode assemblies (MEAs). In this project, electrocatalyst development focused on systematic physical and electrochemical characterization of electrocatalyst activity, durability, and performance in MEAs as a function of electrocatalyst fabrication, compositional and structural variables. The project approach was to develop relationships between the catalyst functional responses (activity, durability and performance) with catalyst physical properties and catalyst fabrication methods. Additionally, the thin film catalysts were integrated onto the unique and durable 3M Nanostructured Thin Film (NSTF) support, consisting of arrays of self-assembled organic crystalline whiskers. The catalysts were evaluated against the project targets via extensive electrochemical characterization in MEA format at 3M, advanced structural and compositional microscopy at Oak Ridge National Laboratory (ORNL), and atomic structure analysis via XAFS at Argonne National Laboratory (ANL). The extensive electrochemical and physical characterization resulted in development of several trends which correlate the catalysts’ electrochemical properties to their physical properties, including composition, structure, and method of fabrication. The development was guided by density functional theory (DFT) modeling at Purdue University and kinetic Monte Carlo (kMC) modeling at Johns Hopkins University. The catalyst simulations provided key insights into the observed experimental activity and durability trends, and additionally were utilized to assess new electrocatalyst concepts prior to or coincident with physical catalyst development. This development has led to several electrocatalyst candidates with activity and durability which approach or exceed DOE targets. One class of catalysts, based on nm-scale thin layers of Pt on Ir, met or exceeded 6 of the 6 DOE targets the project addressed.

08 HYDROGEN↗

DOE OSTI2022

Designing linear lattices for round beam in electron storage rings using the solution by linear matrices analysis

For some synchrotron light source beamline applications, a round beam is preferable to a flat one. A conventional method of obtaining round beam in an electron storage ring is to shift its tune close to a linear difference resonance. The linearly coupled beam dynamics is analyzed with perturbation theories, which have certain limitations. In this paper, we adopt the Solution by LInear Matrices (SLIM) analysis to calculate exact beam sizes to design round beam lattices. The SLIM analysis can deal with a generally linearly coupled accelerator lattice. The effects of various coupling sources on beam emittances and sizes can be studied within a self-consistent frame. Both the on- and off-resonance schemes to obtain round beams are explained with examples. The SLIM formalism for two widely used magnet models: combined-function bending magnets, and planar wigglers and undulators, is also derived.

43 PARTICLE ACCELERATORS↗

DOE OSTI2022

Permutation-adapted complete and independent basis for atomic cluster expansion descriptors

In many recent applications, particularly in the field of atom-centered descriptors for interatomic potentials, tensor products of spherical harmonics have been used to characterize complex atomic environments. When coupled with a radial basis, the atomic cluster expansion (ACE) basis is obtained. However, symmetrization with respect to both rotation and permutation results in an overcomplete set of ACE descriptors with linear dependencies occurring within blocks of functions corresponding to particular generalized Wigner symbols. All practical applications of ACE employ semi-numerical constructions to generate a complete, fully independent basis. While computationally tractable, the resultant basis cannot be expressed analytically, is susceptible to numerical instability, and thus has limited reproducibility. Here we present a procedure for generating explicit analytic expressions for a complete and independent set of ACE descriptors. The procedure uses a coupling scheme that is maximally symmetric w.r.t. permutation of the atoms, exposing the permutational symmetries of the generalized Wigner symbols, and yields a permutation-adapted rotationally and permutationally invariant basis (PA-RPI ACE). Theoretical support for the approach is presented, as well as numerical evidence of completeness and independence. A summary of explicit enumeration of PA-RPI functions up to rank 6 and polynomial degree 32 is provided. The PA-RPI blocks corresponding to particular generalized Wigner symbols may be either larger or smaller than the corresponding blocks in the simpler rotationally invariant basis. Finally, we demonstrate that basis functions of high polynomial degree persist under strong regularization, indicating the importance of not restricting the maximum degree of basis functions in ACE models a priori.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2022

High Performance Circuit Pastes for Solid Oxide Fuel Cell Applications: Final Technical Report

Using a combination of in-plane electrical conductivity measurements, electrical contact resistance measurements, tensile fracture tests, double shear lap fracture tests, rapid thermal cycling adhesion tests, in situ wetting angle measurements, 3D X-ray tomography, reduction-oxidation (RedOx) cycling, scanning electron microscopy (SEM), energy dispersive x-ray spectroscopy (EDAX), Density Functional Theory (DFT) modeling, Molecular Dynamics (MD) modeling, and Phase Field modeling, this project determined that a new brazing technique developed by the PIs (specifically the use of nickel particles to direct the wetting and spreading of molten silver) could be used to produce well-adhered, >97% dense, electrically-conductive circuits, current collectors, and/or electrical contacts on a variety of ceramic and ceramic-coated substrates (specifically lanthanum strontium manganite, yttria stabilized zirconia, sapphire, Cr2O3-passivated stainless steel, and Al2O3-passivated stainless steel). Compared to other silver-based alternatives, Ag:Ni led to less manufacturing defects and was more tolerant of the extreme environments (isothermal high-temperature aging) and occasional abuse (rapid thermal cycling and RedOx cycling) encountered during Solid Oxide Fuel Cell and/or Solid Oxide Electrolysis Cell operation. Further, in some situations (such as when to produce Ag:Ni electrical contacts to Al2O3-protected stainless steel) the Ni particles also improved operation by acting as chemical getters that removed electrically-insulating, surface-segregating substrate impurities (i.e. by lowering the contact resistance with the underlying substrate).

36 MATERIALS SCIENCE↗

DOE OSTI2024

Air-coupled tsunamis generated from impacts and airbursts: Our understanding before Hunga-Tonga Hunga-Ha'apai

The effort to prevent or mitigate the effects of an impact on Earth is known as planetary defense. A significant component of planetary defense research involves risk assessment. Much of our understanding of the risk from near-Earth objects comes from the geologic record in the form of impact craters, but not all asteroid impacts are crater-forming events. Small asteroids explode before reaching the surface, generating an airburst, and most impacts into the ocean do not penetrate the water to form a crater in the sea floor. The risk from these non-crater-forming ocean impacts and airbursts is difficult to quantify and represents a significant uncertainty in our assessment of the overall threat. We are currently working to better understand impact scenarios that can generate dangerous tsunamis. One of the suggested mechanisms for the production of asteroid–generated tsunamis is by direct coupling of the pressure wave to the water, analogous to the means by which a moving weather front can generate a meteotsunami. To test this hypothesis, we ran a series of airburst simulations and provided time-resolved pressure and wind profiles to use as source functions for tsunami models. We used the CTH hydrocode to model the various airburst scenarios to compare to the results of other simulations and provide time dependent boundary conditions as input to shallow-water wave propagation codes. The strongest and most destructive meteotsunamis are generated by atmospheric pressure oscillations with amplitudes of only a few hPa1 (mbar), corresponding to changes in sea level of a few cm. The resulting wave is strongest when there is a resonance between the ocean and the atmospheric forcing. A Proudman resonance takes place when the atmospheric disturbance’s translational speed (U) equals the longwave phase speed $\sqrt{gh}$ of shallow water wave. Coupling is strongest when the Froude number (Fr=U/c) is unity. A weather front propagates much slower than the speed of sound, so meteotsunamis are most common and dangerous in shallow bodies of water such as the Mediterranean Sea or Lake Michigan. By contrast, the blast wave from an airburst or crater-forming impact propagates at a speed faster than a tsunami in the deepest ocean, and a Proudman resonance cannot be achieved even though the overpressures are orders of magnitude greater. However, blast wave profiles are N-waves in which a sharp shock wave leading to overpressure is followed by a more gradual rarefaction to a much longer-duration underpressure phase. Even though the blast outruns the water wave it is forcing, the tsunami should continue to be driven by the out-of-resonance gradient associated with the suction phase, which may depend strongly on the details of the airburst or impact scenario. The open question is whether there are any conditions under which such an airburst-driven tsunami can be dangerous enough to contribute to the overall impact risk. We have also identified other potential mechanisms for airburst-generated tsunamis: 1) reaction force at the surface from the plume ejected into space, which carries significant momentum, 2) expanding toroidal vortices at the surface, which travel more slowly than the shock wave and can generate a Proudman resonance in relatively shallow ocean (such as continental shelf), and 3) steam explosion from seawater ablation by a “Type II” (Libyan Desert Glass-type) airburst in which the hot vapor jet descends to the surface. On January 15, 2022, the Hunga-Tonga Hunga-Ha’apai volcano, located approximately 60 km north of Tongatapu, the main island of Tonga, violently erupted with a powerful explosion, culminating the period of volcanic activity that started in December of 2021. This event and resulting tsunamis provided an existence proof for the air pressure wave coupling mechanism we proposed. It also suggests that it can be stronger and more significant over much greater distances than we contemplated, leading to global tsunamis associated with impact events on land as well as in the water. Large atmospheric explosions generate global Lamb waves with larger amplitudes, longer periods, and slower speeds than the local and regional blast waves we modeled prior to that event. This paper reviews our analysis and modeling of airburst-driven tsunamis prior to the 2022 Hunga-Tonga Hunga-Ha’apai tsunami, which was the subject of two presentations at the 2023 Planetary Defense Conference and is the subject of another paper currently in preparation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Modeling Ni Coarsening and Migration in the Hydrogen Electrode of Solid oxide Cells under Operating Conditions

Ni coarsening and migration is the most important degradation in the hydrogen electrode of solid oxide cells. This presentation reviews our works on Ni coarsening and migration in NETL over the past years. We used simulation techniques including phase-field modeling and density function theory to investigate possible mechanisms of Ni coarsening and migration, including self-diffusion of Ni, diffusion of gaseous Ni(OH)2, surface diffusion of Ni(OH)x and Ni-YSZ wettability change, and examined the effect of operating conditions on these mechanisms. So far, none of the mechanisms can fully explain the experiments. Remaining questions and possible paths forward are summarized and discussed.

Lei, Yinkai↗

DOE OSTI2024

Machine Learned Force Field Modeling of Metal Organic Frameworks for CO2 Direct Air Capture

Metal organic frameworks (MOFs) are a large class of porous materials and have garnered significant interest due to their large surface areas and their tunable physical and chemical properties. Numerous prior studies have been performed to screen large databases of this material class for promising DAC sorbent materials. These studies have often relied on classical model potentials. While density functional theory (DFT) calculations have been shown to be very accurate for modeling the interaction of CO2 with MOFs, such calculations are too computationally demanding for statistically significant adsorption predictions. To overcome this barrier, we developed methods for training models to achieve DFT-level accuracy for the forces and energies associated with MOF flexibility and CO2 adsorption using machine learned force fields (MLFFs). These methods were parametrized based on DFT calculations of CO2 in a flexible MOF and used to predict MOF structural properties as well as CO2 adsorption in several MOFs.

Findley, John↗

DOE OSTI2024

Model-form Error Correction using Universal Differential Equations for an Agent-Based Model of Infectious Disease

This report demonstrates universal differential equations (UDEs) as an approach to bridge the gap between ordinary differential equations (ODE) models and agent-based models (ABMs). Using UDE models as surrogates for ABMs allows us to preserve the foundational ODE that represents global disease dynamics while coupling it with a neural network model to approximate functions for the local behaviors of the ABM.

59 BASIC BIOLOGICAL SCIENCES↗