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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

CUDO: closed-form universal dwell-time optimization for computer-controlled optical surfacing

Precision optical figuring demands fast and accurate dwell time optimization to reach nanometer- and sub-nanometer-level accuracy in next-generation optical systems. We introduce CUDO (closed-form universal dwell-time optimization), the first, to the best of our knowledge, unified closed-form analytical framework that supports both function-form and matrix-form dwell time models in computer-controlled optical surfacing (CCOS). In contrast to traditional methods, which rely on iterative optimization and hyperparameter tuning, our framework derives direct analytical solutions with no adjustable parameters. This approach unifies the solution principles of existing methods within a single mathematical model, delivering three key advantages: (1) accuracy on par with, or superior to, iterative solvers, (2) substantial reduction in computation time, and (3) numerical robustness. Comparative studies with prior art confirm that closed-form solutions achieve equivalent residual error while removing runtime bottlenecks. By simplifying the implementation and enabling real-time, scalable deployment, CUDO establishes a practical foundation for future deterministic fabrication of large-aperture and high-performance optics.

36 MATERIALS SCIENCE↗
DOE OSTI2018

A status review on DNB prediction using CASL baseline boiling model and possible suggestions regarding wall boiling closures

The main goal of FY18 THM’s focus task is to evaluate where the current CASL boiling model stands for DNB predictive performance, to identify which components should be improved or calibrated to enhance DNB performance. Over the past three year’s validation tests, Gen1A boiling model has presented an under-predictive behavior for DNB at the high pressure of interest for PWR application. With this in mind, this year’s task is to focus on 1) best practice guidelines on DNB detection criteria, 2) interfacial momentum transfer closure tests, and 3) wall boiling closure sensitivity on DNB. Best practice guidelines on DNB detection criteria are demonstrated by the following three monitoring variables: 1) max wall temperature, 2) K-value and 3) energy balance. Interfacial momentum transfer closure govern the bubble distribution, especially in lateral direction, as well as bubble mean diameter. A clear correlation between interfacial momentum closure and DNB prediction is not observed in the current tests. However, void distributions are changed with different interfacial momentum closure tests which requires further validation with corresponding experimental measurement. From a variety of wall boiling closure tests, bubble departure diameter seems the most sensitive for DNB performance while fulfilling numerical robustness in DNB simulation. Tolubinski’s bubble departure diameter model was calibrated to see if any improvement is observed in DNB performance. Notable DNB improvement was observed as the bubble departure diameter is reduced. However, reduced bubble departure diameter by calibrated Tolubinski’s model seemed to lead to relatively high wall superheat temperature prediction which requires further validation with associated experimental measurement It should be noted that lack of experimental measurement close to DNB condition hampers this boiling closure sensitivity study significantly. This situation directly reflects some of limitations of the CASL boiling model development. With this in mind, the implementation of improved boiling closure on 5x5 NMVG and MVG tests will be pursued in FY19, the associated DNB best practice guidelines and possible limitations will be addressed for industry DNB application.

42 ENGINEERING↗
DOE OSTI2018

A crystal plasticity framework for modeling the five-dimensional energy landscape of grain boundaries (Final Technical Report)

In this report, we describe our progress in modeling the co-evolution of grain boundaries and bulk dislocations which plays a crucial role in phenomena such as dynamic recovery, recrystallization, and grain growth in polycrystalline materials. The overarching goal of this work is to develop a robust numerical tool to predict microstructure evolution during severe plastic deformation. This work is associated with the project titled, “Computational Modeling and Design of Radiation Tolerant Materials in Fusion Environments” sponsored by the DOE under grant SC0012774.

36 MATERIALS SCIENCE↗
DOE OSTI2019

High-fidelity kinetic modeling of plasmas in Z-pinch and pulsed power configurations (18-ERD-048)

Plasma dynamics can be strongly influenced by fine-scale kinetic physics, which is not captured by standard fluid treatments, is challenging to simulate, and is poorly understood. The aim of this research was to investigate the fundamental fine-scale properties of collisionless plasmas in Z-pinch and pulsed power configurations by deploying novel noisefree high-accuracy computational algorithms. Significant advances were achieved through the development of robust numerical capabilities to exploit axisymmetry in kinetic simulations, the development of new methodologies to construct kinetic equilibria, and the theoretical and computational study of kinetic sheared-flow-driven transport in pulsed power systems. These new capabilities shed light on the anisotropies that can develop in Z-pinches and the transport processes that can lead to parasitic currents in pulsed power inertial confinement fusion experiments. The use of cutting-edge massively-parallel numerical algorithms to address outstanding scientific questions in plasma physics advances the mission of Lawrence Livermore National Laboratory in the areas of high energy density science and high performance computing. By bringing together kinetic theory, high-order numerical methods, high performance computing, and experimental applications, this research advances the state of the art in plasma physics modeling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Advanced Electronic Structure Theories for Strongly Correlated Ground and Excited States

The aim of this project was to create widely applicable, numerically robust, and systematically improvable multireference theories based on the Driven Similarity Renormalization Group (DSRG). The DSRG is a many-body formalism recently developed in our lab that maps a complex problem involving strongly and weakly interacting electrons to a simpler one in which a few electrons interact strongly via "renormalized" interactions. During this project, we focused our efforts on developing a multireference version of the DSRG (MR-DSRG) applicable to a wide range of problems in theoretical chemistry, including the computation of global ground and excited potential energy surfaces, spin-splittings in transition metal complexes and predicting the interaction of near-degenerate electronically excited states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Development of a Subchannel Capability for Liquid-Metal Fast Reactors in Pronghorn

This report details the development and demonstration of an entirely new capability in Pronghorn, namely the ability to model liquid-metal fast reactor (LMFR) flow conditions on the engineering scale. We developed two modeling approaches for LMFR that can be used separately or be combined into a hybrid simulation: (1) a modern subchannel capability called Pronghorn-Subchannel for square and hexagonal lattices, and (2) a porous flow capability for LMFR geometries. The report emphasizes the novel aspects of the developed subchannel capability and the interoperability of the subchannel capability, porous flow capability, and multiphysics tools within the multiphysics object oriented simulation environment (MOOSE). Here we demonstrate the ability to: (1) Accurately model subchannel flow in hexagonal lattices; (2) Couple the subchannel flow model to multidimensional finite-element method (FEM) or finite-volume method (FVM) heat conduction models; (3) Model LMFRs using Pronghorn’s porous media FVM approach; (4) Couple porous flow FVM and subchannel models in a single simulation; (5) Explicitly model inter-wrapper flows along with conjugate heat transfer from the intra-element flow; and (6) Demonstrate the numerical robustness of the subchannel algorithm by simulating intra-element flow recirculation in a high-buoyancy, low-flow fuel element.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Material Discovery and Design Principles of Perovskite Oxides for Reversible Solid Oxide Cells (R-SOC)

Reversible solid oxide cells (R-SOCs) are highly efficient devices for energy conversion and storage, capable of operating for both hydrogen utilization and production. In fuel cell mode, an R-SOC consumes hydrogen or natural gas to generate electricity, while in electrolysis mode, it produces hydrogen from steam. The discover of new materials with rapid oxygen surface exchange kinetics and enduring stability is crucial for the economically viable commercialization of R-SOCs. To facilitate this pursuit, we conducted extensive Density Functional Theory (DFT) calculations and developed Machine Learning (ML) models to predict critical catalytic properties essential for R-SOCs, such as oxygen surface exchange/diffusivity, and area-specific resistance (ASR). BaCoxFeyZrzO3-d(BFCZ)(x+y+z=1) emerged as a promising family of electrode materials with high activity and stability, validated through systematic experimental study. Moreover, a robust numerical multiphysics model was developed to optimize materials and microstructure parameters, providing the ability to predict the performance of functional R-SOCs.

Liu, Jian↗
DOE OSTI2024

A Low-Rank QTT-based Finite Element Method for Elasticity Problems

We present an efficient and robust numerical algorithm for solving the linear elasticity problem that combines the Quantized Tensor Train format and a domain partitioning strategy. This approach makes it possible to solve the linear elasticity problem on a computational domain that is more general than a square. By integrating Z-ordering and subdomain concatenation, our method substantially decreases memory usage and achieves a notable reduction in rank compared to established Finite Element implementations like the FEniCS platform. This efficiency is maintained while still guaranteeing exponential convergence with respect to the number of degrees of freedom. This performance gain, however, requires a fundamental rethinking of how core finite element operations are implemented. This includes changes to mesh discretization, node and degree of freedom ordering, stiffness matrix and internal nodal force assembly, and the execution of algebraic matrix-vector operations. In this work, we discuss all these aspects in detail and assess the method’s performance in the numerical approximation of three representative test cases.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Surrogate Model Integration with MOOSE XFEM for Creep Crack Growth

Ferritic-martensitic steels are key structural materials for advanced reactors but experience time-dependent deformation and damage under prolonged high temperature and irradiation, leading to creep-driven crack initiation and growth. High-fidelity models—crystal plasticity with irradiation mechanisms, phase-field for microstructural evolution, and continuum-damage viscoplasticity—capture the underlying physics but are too computationally intensive for broad design-space exploration and uncertainty quantification. This milestone advances a scalable alternative by integrating a microstructure-sensitive surrogate creep model into the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element framework and extending it to fracture via the extended finite element method (XFEM). The surrogate model, developed with collaborators at Sandia and Los Alamos National Laboratories, maps relevant microstructural descriptors to the viscoplastic response of HT9. We embed this surrogate within a coupled deformation-damage workflow in MOOSE/XFEM to simulate creep-driven crack initiation and propagation. Implementation enhancements include updates to the material interface, a plastic correction phase involving microstructure evolution, and fracture criteria to ensure numerical robustness and compatibility with the surrogate structure. Demonstrations on canonical creep benchmarks spanning uniaxial and multiaxial states show that the surrogate reproduces key trends of high-fidelity models while substantially reducing computational cost. The resulting capability bridges physics fidelity and performance, providing a practical path to a predictive, microstructure-aware assessment of creep and fracture in reactor materials.

36 - MATERIALS SCIENCE↗
DOE OSTI2026

Development of local hybrid density functionals to treat self-interaction error and many-electron effects

The goal of this project was to improve density functional theory (DFT) for systems where conventional semilocal approximations are limited by self-interaction error (SIE) and by near-degeneracy or strong many-electron effects. While DFT remains the only broadly practical first-principles framework for large-scale materials simulations, its predictive accuracy is often challenged in situations involving stretched bonds, charge transfer, transition-metal chemistry, magnetic couplings, band gaps, and correlated electronic states. This project addressed these limitations by developing physically grounded and numerically robust exchange–correlation functionals that retain the efficiency of modern DFT while extending its predictive scope.

36 MATERIALS SCIENCE↗
NASA NTRS1986

On realizations of least-squares estimation and Kalman filtering by systolic arrays

Least-squares (LS) estimation is a basic operation in many signal processing problems. Given y = Ax + v, where A is a m x n coefficient matrix, y is a m x 1 observation vector, and v is a m x 1 zero mean white noise vector, a simple least-squares solution is finding the estimated vector x which minimizes the norm of /Ax-y/. It is well known that for an ill-conditioned matrix A, solving least-squares problems by orthogonal triangular (QR) decomposition and back substitution has robust numerical properties under finite word length effect since 2-norm is preserved. Many fast algorithms have been proposed and applied to systolic arrays. Gentleman-Kung (1981) first presented the trianglular systolic array for a basic Givens reduction. McWhirter (1983) used this array structure to find the least-squares estimation errors. Then by geometric approach, several different systolic array realizations of the recursive least-squares estimation algorithms of Lee et al (1981) were derived by Kalson-Yao (1985). Basic QR decomposition algorithms are considered in this paper and it is found that under a one-row time updating situation, the Householder transformation degenerates to a simple Givens reduction. Next, an improved least-squares estimation algorithm is derived by considering a modified version of fast Givens reduction. From this approach, the basic relationship between Givens reduction and Modified-Gram-Schmidt transformation can easily be understood. This improved algorithm also has simpler computational and inter-cell connection complexities while compared with other known least-squares algorithms and is more realistic for systolic array implementation.

Chen, M. J.↗
NASA NTRS1989

Modeling and control system design and analysis tools for flexible structures

Described here are Boeing software tools used for the development of control laws of flexible structures. The Boeing Company has developed a software tool called Modern Control Software Package (MPAC). MPAC provides the environment necessary for linear model development, analysis, and controller design for large models of flexible structures. There are two features of MPAC which are particularly appropriate for use with large models: (1) numerical accuracy and (2) label-driven nature. With the first feature MPAC uses double precision arithmetic for all numerical operations and relies on EISPAC and LINPACK for the numerical foundation. With the second feature, all MPAC model inputs, outputs, and states are referenced by user-defined labels. This feature allows model modification while maintaining the same state, input, and output names. In addition, there is no need for the user to keep track of a model variable's matrix row and colunm locations. There is a wide range of model manipulation, analysis, and design features within the numerically robust and flexible environment provided by MPAC. Models can be built or modified using either state space or transfer function representations. Existing models can be combined via parallel, series, and feedback connections; and loops of a closed-loop model may be broken for analysis.

Anissipour, Amir A.↗
NASA NTRS1989

Improved vortex methods for three-dimensional flows

Robust numerical methods are developed for three-dimensional incompressible vortical flows, using Lagrangian vortex elements. A successful scheme must be able to handle regions of intense vortex stretching and vortex reconnection with reasonable accuracy (without diverging). Here, consideration is given to vortex particles, also commonly called vortons or vortex sticks. The following issues are discussed: (1) use of delta-function elements and weak solutions of the vorticity equation; (2) use of smoothed elements and the choice of the smoothing function; (3) representation of viscous effects and the redistribution of element strength; and (4) conservation laws (are they satisfied?). The various proposed schemes have been tested on flows involving a strong interaction between two vortex rings.

Winckelmans, G.↗
NASA NTRS1990

Development of UMARC (University of Maryland Advanced Rotorcraft Code)

The University of Maryland Advanced Rotorcraft Code (UMARC) is a user-friendly, FEM-based comprehensive helicopter rotor simulation code of high numerical robustness and computational efficiency. UMARC formulates the rotor-fuselage equations using Hamilton's principle, and are discretized using finite elements in space and time. The FEM formulation allows the code to analyze a wide variety of rotor designs. Dynamic inflow modeling is used for unsteady wake inflow computations. Predicted stability, response, and blade-load data are validated with experimental data for several configurations, including representative articulated, hingeless, and bearingless rotors.

Bir, Gunjit↗
NASA NTRS1991

A Newton algorithm for complex curve fitting

The problem of synthesizing transfer functions from frequency response measurements is considered. Given a complex vector representing the measured frequency response of a physical system, a transfer function of specified order is determined that minimizes the sum of the magnitude-squared of the frequency response errors. This nonlinear least squares minimization problem is solved by an iterative global descent algorithm of the Newton type which converges quadratically near the minimum. The unknown transfer function is expressed as a sum of second order rational polynomials, a parameterization that facilitates a numerically robust computer implementation. The algorithm is developed for single-input, single-output, causal, stable transfer functions.

Spanos, J. T.↗
NASA NTRS1992

Fluid/chemistry modeling for hypersonic flight analysis

Design studies are underway for a variety of hypersonic flight vehicles. The National Aero-Space Plane will provide a reusable, single-stage-to-orbit capability for routine access to low earth orbit. Flight-capable satellites will dip into the atmosphere to maneuver to new orbits, while planetary probes will decelerate at their destination by atmospheric aerobraking. To supplement limited experimental capabilities in the hypersonic regime, computational fluid dynamics is being used to analyze the flow about these configurations. The governing equations include fluid dynamic as well as chemical species equations, which are being solved with new, robust numerical algorithms. Examples of CFD applications to hypersonic vehicles suggest an important role this technology will play in the development of future aerospace systems. The computational resources needed to obtain solutions are large, but solution-adaptive grids, convergence acceleration, and parallel processing may make run times manageable.

Edwards, Thomas A.↗
NASA NTRS1992

Incorporation of spatial information in Bayesian image reconstruction - The maximum residual likelihood criterion

We have developed a new figure of merit, a 'maximum-residual-likelihood' (MRL) statistic, for the goodness of fit for Bayesian image restoration which explicitly incorporates spatial information. The MRL constraint provides a natural means of incorporating the prior knowledge that the residuals contain no spatial structure through the autocorrelation function of the residuals. We demonstrate that this statistic follows a Chi-square distribution and that forcing this statistic to have its most probable value leads to a restored image whose residuals are consistent with the noise model. Our numerical experiments suggest that image restoration using the MRL statistic alone is numerically robust and produces results which are independent of the initial guess for the restored image. However, we caution that using the MRL statistic without an image prior can result in overresolution in low SNR portions of the image.

Pina, R. K.↗