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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Influence of capillary end effects on steady-state relative permeability estimates from direct pore-scale simulations

In this study, we investigate and characterize the influence of capillary end effects on steady-state relative permeabilities obtained in pore-scale numerical simulations of two-phase flows. Our study is motivated by the observation that capillary end effects documented in two-phase laboratory-scale experiments can significantly influence permeability estimates. While numerical simulations of two-phase flows in reconstructed pore-spaces are increasingly employed to characterize relative permeabilities, a phenomenon which is akin to capillary end effects can also arise in such analyses due to the constraints applied at the boundaries of the computational domain. We profile the relative strength of these capillary end effects on the calculation of steady-state relative permeabilities obtained within randomly generated porous micro-structures using a finite volume-based two-phase flow solver. Finally, we suggest a procedure to estimate the extent of the regions influenced by these capillary end effects, which in turn allows for the alleviation of bias in the estimation of relative permeabilities.

42 ENGINEERING↗
DOE OSTI2023

A complementarity-based vapor-liquid equilibrium formulation for equation-oriented simulation and optimization

Vapor-Liquid Equilibrium (VLE) is a cornerstone of computer aided process engineering (CAPE). Embedded within process system models, VLE calculations are inherently procedural with non-smooth behavior that frequently require discrete decisions. Traditionally, these features resist the incorporation of VLE within efficient, large-scale equation-oriented (EO) process simulation and optimization strategies. On the other hand, recent reformulation of VLE models through the incorporation of complementarity constraints has broadened its scope to deal seamlessly with phase transitions and even supercritical excursions in process simulation and optimization. In this study, we extend these VLE complementarity models to EO frameworks where procedural thermodynamic property libraries are still required. Here, we develop an efficient, non-intrusive, and intuitive “square-flash” equation system that has been implemented within the IDAES Integrated Platform (IDAES-IP). Further, the effectiveness of this modular approach is demonstrated on case studies for non-ideal flash calculations and distillation optimization with disappearing phases and supercritical transitions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Reduced‐cost sparsity‐exploiting algorithm for solving coupled‐cluster equations

We present an algorithm for reducing the computational work involved in coupled‐cluster (CC) calculations by sparsifying the amplitude correction within a CC amplitude update procedure. We provide a theoretical justification for this approach, which is based on the convergence theory of inexact Newton iterations. We demonstrate by numerical examples that, in the simplest case of the CCD equations, we can sparsify the amplitude correction by setting, on average, roughly 90% nonzero elements to zeros without a major effect on the convergence of the inexact Newton iterations.

Brabec, Jiri↗
DOE OSTI2016

Variational projection methods for gradient crystal plasticity using Lie algebras

Summary A computational method is developed for evaluating the plastic strain gradient hardening term within a crystal plasticity formulation. While such gradient terms reproduce the size effects exhibited in experiments, incorporating derivatives of the plastic strain yields a nonlocal constitutive model. Rather than applying mixed methods, we propose an alternative method whereby the plastic deformation gradient is variationally projected from the elemental integration points onto a smoothed nodal field. Crucially, the projection utilizes the mapping between Lie groups and algebras in order to preserve essential physical properties, such as orthogonality of the plastic rotation tensor. Following the projection, the plastic strain field is directly differentiated to yield the Nye tensor. Additionally, an augmentation scheme is introduced within the global Newton iteration loop such that the computed Nye tensor field is fed back into the stress update procedure. Effectively, this method results in a fully implicit evolution of the constitutive model within a traditional displacement‐based formulation. An elemental projection method with explicit time integration of the plastic rotation tensor is compared as a reference. A series of numerical tests are performed for several element types in order to assess the robustness of the method, with emphasis placed upon polycrystalline domains and multi‐axis loading. Copyright © 2016 John Wiley & Sons, Ltd.

Truster, Timothy J.↗
DOE OSTI2024

Design and testing of ultrasound probe adapters for a robotic imaging platform

Medical imaging-based triage is a critical tool for emergency medicine in both civilian and military settings. Ultrasound imaging can be used to rapidly identify free fluid in abdominal and thoracic cavities which could necessitate immediate surgical intervention. However, proper ultrasound image capture requires a skilled ultrasonography technician who is likely unavailable at the point of injury where resources are limited. Instead, robotics and computer vision technology can simplify image acquisition. As a first step towards this larger goal, here, we focus on the development of prototypes for ultrasound probe securement using a robotics platform. The ability of four probe adapter technologies to precisely capture images at anatomical locations, repeatedly, and with different ultrasound transducer types were evaluated across more than five scoring criteria. Testing demonstrated two of the adapters outperformed the traditional robot gripper and manual image capture, with a compact, rotating design compatible with wireless imaging technology being most suitable for use at the point of injury. Next steps will integrate the robotic platform with computer vision and deep learning image interpretation models to automate image capture and diagnosis. This will lower the skill threshold needed for medical imaging-based triage, enabling this procedure to be available at or near the point of injury.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

SIERRA Low Mach Module: Fuego Verification Manual (V. 4.40)

The verification process is intended to demonstrate that a code is solving the governing equations correctly. Verification problems consist of analytical solutions to the mathematical model equations, derived analytical solutions based on an equivalent source term generation procedure (i.e., manufactured solutions), and established numerical bench mark solutions.

42 ENGINEERING↗
DOE OSTI2016

Spin density and orbital optimization in open shell systems: A rational and computationally efficient proposal

The present work describes a new method to compute accurate spin densities for open shell systems. The proposed approach follows two steps: first, it provides molecular orbitals which correctly take into account the spin delocalization; second, a proper CI treatment allows to account for the spin polarization effect while keeping a restricted formalism and avoiding spin contamination. The main idea of the optimization procedure is based on the orbital relaxation of the various charge transfer determinants responsible for the spin delocalization. The algorithm is tested and compared to other existing methods on a series of organic and inorganic open shell systems. The results reported here show that the new approach (almost black-box) provides accurate spin densities at a reasonable computational cost making it suitable for a systematic study of open shell systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Approximating the near-edge mass absorption coefficients for Ni using an ultra-thin bimetal foil

In an effort to improve the characteristics of a fluorescing metal-foil-based beam position monitor, a new bimetal ultra-thin (0.98/0.67 µm) Ti–Ni foil was introduced to replace an existing single-element ultra-thin 0.5 µm thick Cr foil. During characterization it was determined that absorption measurements on the bimetal foil could be used to fit the Ni mass absorption coefficients accurately in the vicinity of the Ni K edge. Comparison with experimental results from the literature demonstrated that the fitting procedure produced coefficients with uncertainties of the order of ±1%. Once determined, these fit coefficients allowed the thickness of an independently mounted 8 µm thick Ni foil to be computed from absorption measurements instead of relying on a tool-based measurement of the foil thickness. Using the 8 µm thick foil, a continuous map of Ni mass absorption coefficients was produced at 1 eV resolution throughout the near-edge region. Lastly, this high-resolution map marks a significant improvement over the existing NIST XCOM or FFAST database mass absorption coefficients, which have estimated errors of 10–20% for the near-edge region.

36 MATERIALS SCIENCE↗
DOE OSTI2024

tobac v1.5: introducing fast 3D tracking, splits and mergers, and other enhancements for identifying and analysing meteorological phenomena

There is a continuously increasing need for reliable feature detection and tracking tools based on objective analysis principles for use with meteorological data. Many tools have been developed over the previous 2 decades that attempt to address this need but most have limitations on the type of data they can be used with, feature computational and/or memory expenses that make them unwieldy with larger datasets, or require some form of data reduction prior to use that limits the tool's utility. The Tracking and Object-Based Analysis of Clouds (tobac) Python package is a modular, open-source tool that improves on the overall generality and utility of past tools. A number of scientific improvements (three spatial dimensions, splits and mergers of features, an internal spectral filtering tool) and procedural enhancements (increased computational efficiency, internal regridding of data, and treatments for periodic boundary conditions) have been included in tobac as a part of the tobac v1.5 update. These improvements have made tobac one of the most robust, powerful, and flexible identification and tracking tools in our field to date and expand its potential use in other fields. Future plans for tobac v2 are also discussed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Dynamic Species Reduction for Multi-Cycle CFD Simulations (Final Technical Report)

This project primarily sought to address some of the computational cost concerns of detailed simulations by developing improved methods of handling species transport, and chemical kinetics evaluation in a commercial 3D Computational Fluid Dynamics (CFD) environment. Secondary goals were to apply these techniques to fuels and conditions of interest to better understand the key species and reactions required to adequately capture cycle to cycle coupling. Improved modeling will lead to better understanding of these combustion modes and their dependence on fuel composition, which can then enable more clean and efficient engines, ultimately benefiting the consumer as well as the general public. Two approaches were used to address the computational cost. A “Dynamic Species Reduction” (DSR) procedure was developed to remove chemical species from the simulation during periods when chemical reactions were not expected to be important, particularly during gas exchange when temperatures are low and little fuel remains. This modelling procedure automatically detects relevant species to retain in the simulation domain based on their local concentration, removes species below a specified concentration threshold, and then adjusts the remaining species mass to conserve not only the number of H, C, and O atoms in each cell, but also the relative proportions between species and the heating value of the mixture in every cell. The second procedure was a “Product Directed Remapping” (PDR) updates the algorithm used to group individual computational cells for chemical kinetics evaluation to account for non-uniform temperature distributions and the CO to CO 2 ratio in the cells. The model techniques developed in this work successfully demonstrated computational performance improvements for a range of conditions relevant for Highly Dilute SI and HCCI engine operation. Runtime reductions of 10% were observed for small mechanisms, with further reductions of up to 36% observed for larger mechanisms. Improvements were primarily related to reducing the number of chemical species tracked during the gas exchange process using the Dynamic Species Reduction method. With smaller benefits observed from changes to the kinetics binning and evaluation strategy in the post combustion region using the PDR method. The results of this work show the potential for improved computational runtime for complicated simulations. They can and should be extended to additional conditions and new bio-derived and renewable fuels as they are developed and new kinetic mechanisms become available.

10 SYNTHETIC FUELS↗
DOE OSTI2025

Statistical evaluation of microscale stress conditions leading to void nucleation in the weak shock regime

Here, we investigate the heterogeneity of the stress state driven by anisotropic deformation response at the single crystal level through five statistical volume element (SVE) calculations of polycrystalline BCC tantalum. This work focuses on grain boundaries as a prominent material defect type prone to void nucleation based upon experimental observations of predominantly intergranular void nucleation in this material. The SVEs are constructed to be statistically representative of larger volumes of material and are meshed such that mean and standard deviation of grain size and orientation information is reconstructed. The computational meshes feature hexahedral (brick) elements and smooth conformal grain boundaries where significant stress concentration is known to occur, a tail effect of interest in the extreme events process of dynamic ductile damage. An existing micromechanical crystallographic plasticity model shown to capture the single crystal behavior of BCC tantalum well is used to perform the polycrystal calculations. The model includes representation of the non-Schmid effect of non-planar screw dislocation kinetics in tantalum. A three-dimensional stress state time profile predicted by damage modeling of a flyer plate impact experiment is applied as boundary conditions to each SVE. Resulting grain boundary stress state statistics are strongly non-Gaussian. Significant structural evolution is observed within the compressive hold before unloading into tension in the stress profile. Strong angular dependence of grain boundary traction magnitude with shock direction is observed. Non-Schmid effects continue to suggest their influence on propensity of microstructural defect types to nucleate voids. A general void nucleation criterion is proposed using probability theory. The general framework is specified to polycrystalline BCC tantalum in the weak shock regime to include the SVE calculations and literature molecular dynamics calculations of grain boundary void nucleation strength. Probability density functions (PDFs) are used to describe the interaction between the local stress state heterogeneity and the distributed grain boundary void nucleation strength state. A causation entropy maximization procedure removes the requirement for ad hoc selection of a PDF functional form and provides a rigorous procedure for data-based PDF determination. The resulting physically informed PDF describes the spatial appearance frequency of nucleated voids as a function of applied macroscale pressure. Lower length scale physics are thus packaged in a precise and computationally efficient way to provide computational plasticity insight to macroscale dynamic ductile damage models.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Multiscale simulations for multi-continuum Richards equations

In this paper, we study a multiscale method for simulating a dual-continuum unsaturated flow problem within complex heterogeneous fractured porous media. Mathematically, each of the dual continua is modeled by a multiscale Richards equation (for pressure head), and these equations are coupled to one another by transfer terms. On its own, Richards equation is already a nonlinear partial differential equation, and it is exceedingly difficult to solve numerically due to the extra nonlinear dependencies involving the soil water. To deal with multiple scales, our strategy is that starting from a microscopic scale, we upscale the coupled system of dual-continuum Richards equations via homogenization by the two-scale asymptotic expansion, to obtain a homogenized system, at an intermediate scale (level). Based on a hierarchical approach, the homogenization’s effective coefficients are computed through solving the arising cell problems. Furthermore, to tackle the nonlinearity, after time discretization, we use Picard iteration procedure for linearization of the homogenized Richards equations. At each Picard iteration, some degree of multiscale still remains from the intermediate level, so we utilize the generalized multiscale finite element method (GMsFEM) combining with a multi-continuum approach, to upscale the homogenized system to a macroscopic (coarse-grid) level. This scheme involves building uncoupled and coupled multiscale basis functions, which are used not only to construct coarse-grid solution approximation with high accuracy but also (with the coupled multiscale basis) to capture the interactions among continua. These prospects and convergence are demonstrated by several numerical results for the proposed method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Conservative discontinuous Galerkin schemes for nonlinear Dougherty–Fokker–Planck collision operators

Here, we present a novel discontinuous Galerkin algorithm for the solution of a class of Fokker–Planck collision operators. These operators arise in many fields of physics, and our particular application is for kinetic plasma simulations. In particular, we focus on an operator often known as the ‘Lenard–Bernstein’ or ‘Dougherty’ operator. Several novel algorithmic innovations, based on the concept of weak equality, are reported. These weak equalities are used to define weak operators that compute primitive moments, and are also used to determine a reconstruction procedure that allows an efficient and accurate discretization of the diffusion term. We show that when two integrations by parts are used to construct the discrete weak form, and finite velocity-space extents are accounted for, a scheme that conserves density, momentum and energy exactly is obtained. One novel feature is that the requirements of momentum and energy conservation lead to unique formulas to compute primitive moments. Careful definition of discretized moments also ensure that energy is conserved in the piecewise linear case, even though the kinetic-energy term, $v^2$ is not included in the basis set used in the discretization. A series of benchmark problems is presented and shows that the scheme conserves momentum and energy to machine precision. Empirical evidence also indicates that entropy is a non-decreasing function. The collision terms are combined with the Vlasov equation to study collisional Landau damping and plasma heating via magnetic pumping.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Local electric dipole moments for periodic systems via density functional theory embedding

We describe a novel approach for the calculation of local electric dipole moments for periodic systems. Since the position operator is ill-defined in periodic systems, maximally localized Wannier functions based on the Berry-phase approach are usually employed for the evaluation of local contributions to the total electric dipole moment of the system. We propose an alternative approach: within a subsystem-density functional theory based embedding scheme, subset electric dipole moments are derived without any additional localization procedure, both for hybrid and non-hybrid exchange–correlation functionals. This opens the way to a computationally efficient evaluation of local electric dipole moments in (molecular) periodic systems as well as their rigorous splitting into atomic electric dipole moments. As examples, Infrared spectra of liquid ethylene carbonate and dimethyl carbonate are presented, which are commonly employed as solvents in Lithium ion batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Control of simulation of a particle accelerator as a spatially distributed system

The work deals with the construction of strategy for finding optimal control of systems for spatially distributed systems on an example of problems in physics beams. The suggested approach is based on use of exact and approximate invariants as a controlling mechanism for control of modelling process of beam lines. The classical problem of optimal control of similar systems as an optimal control problem is formulated in a functional space. This approach is based on algebraic methods Lie and the corresponding matrix formalism that allows you to build not only the formal procedures for finding optimal solutions, but also provide the necessary constructive computational procedures.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Netload Range Cost Curves for Coordinated Transmission-Distribution Planning Under DER Growth Uncertainty

The increasing penetration of distributed energy resources (DERs) requires better coordination between transmission and distribution (T&D) planning to ensure system security and cost efficiency. However, misaligned planning horizons, computational burdens, and privacy concerns hinder effective coordination, leading to either underutilized resources caused by overinvestments or reliability risks due to underinvestment. To address this challenge, we introduce netload range cost curves (NRCCs), a novel approach for managing long-term DER growth uncertainty through T&D coordination, while preserving existing data-sharing and regulatory structures. NRCCs provide pairs of (i) peak substation netload guarantees and (ii) corresponding distribution upgrade options and costs, enabling their seamless integration into transmission planning workflows. To compute NRCCs efficiently, we develop a transmission-aware distribution network planning (TADNP), which is subsequently integrated to an iterative computation procedure. These NRCCs are then embedded into an NRCC-informed transmission planning model to enable resource-efficient coordination. We illustrate our proposed approach with a case study based on realistic distribution and transmission systems in the San Francisco Bay Area, California. Our results indicate the possibility of dramatic savings in transmission investments by incorporating the proposed NRCC-integrated T&D coordination framework.

Li, Yujia↗
DOE OSTI2015

An Integrated Tool for Functional Requirements Analysis, Function Allocation and Task Analysis

The software application is called "HFE-Trace". This is an integrated method and tool for the management of Human Factors Engineering analyses and related data. Its primary purpose is to support the coherent and consistent application of the nuclear industry's best practices for human factors engineering work. The software is a custom Microsoft® Access® application. The application is used (in conjunction with other tools such as spreadsheets, checklists and normal documents where necessary) to collect data on the design of a new nuclear power plant from subject matter experts and other sources. This information is then used to identify potential system and functional breakdowns of the intended power plant design. This information is expanded by developing extensive descriptions of all functions, as well as system performance parameters, operating limits and constraints, and operational conditions. Once these have been verified, the human factors elements are added to each function, including intended operator role, function allocation considerations, prohibited actions, primary task categories, and primary work station. In addition, the application includes a computational method to assess a number of factors such as system and process complexity, workload, environmental conditions, procedures, regulations, etc.) that may shape operator performance. This is a unique methodology based upon principles described in NUREG/CR-3331 ("A methodology for allocating nuclear power plant control functions to human or automatic control") and it results in a semi-quantified allocation of functions to three or more levels of automation for a conceptual automation system. The aggregate of all this information is then linked to the Task Analysis section of the application where the existing information on all operator functions is transformed into task information and ultimately into design requirements for Human-System Interfaces and Control Rooms. This final step includes assessment of methods to prevent potential operator errors.

Hugo, Jacques↗
DOE OSTI2022

Artificial Intelligence for Accelerating Nuclear Applications, Science, and Technology

Artificial intelligence (AI) and machine learning (ML) methods have had significant impacts in science and technology in recent years. These methods for generating models from datasets or logic-based algorithms that emulate aspects of human performance can similarly accelerate the fields of nuclear applications, science, and technology toward the IAEA goals of contributing to peace, health, and prosperity. In order to accomplish advances with AI in general and ML in particular across these fields, IAEA can play a significant role by establishing, hosting and curating centralised resources, including databases, adhering to FAIR (findable, accessible, interoperable and reusable) principles and Open Science best practices, providing stewardship of data sharing, supporting training efforts and development of relevant workforces, as well as enabling connections among the scientific, technology, mathematics, AI and ethics communities. Many areas can benefit from the use of AI in the realm of nuclear applications. In human health, these areas include clinical research, epidemiology, nutrition, medical imaging, radiotherapy and education of health professionals. AI-based tools are also being used to facilitate different clinical tasks in imaging, computer-assisted diagnosis in mammography and lung cancer screening programmes, and dose prediction in nuclear medicine procedures. ML methods in particular may also increase the efficiency and accuracy of the analysis of computerised tomography and dual-energy absorptiometry scans for body composition and bone analysis. The application of AI methods to nuclear and related technologies in food and agriculture can lead to significant advances and improved efficiency in the optimisation of agricultural production, food product development, management of supply chains, food safety and food authenticity control. In the water and environmental sector, AI can help inform policies to mitigate the world’s water problems. The application of AI techniques to hydrology and environmental sciences is expected to improve patterns identification and enable model predictions under a changing climate.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗