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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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DOE OSTI2014

The use of discrete harmonics in direct multi-scale embedding of polycrystal plasticity

In this work, we describe an approach for directly embedding polycrystal plasticity models in component scale calculations, with an emphasis on computational tractability. Previously, we have employed adaptive sampling to mitigate the computational cost of direct embedding, achieving two or more orders of magnitude in wall-clock speedup compared to more traditional approaches. However, in our previous work the crystal orientation distribution function (crystallographic texture) was not allowed to evolve significantly. Here we discuss an approach that allows for evolving texture by employing discrete harmonics, effectively decoupling considerations related to accuracy of integrals in the homogenization from those related to adequate representation of the evolving texture. We discuss the basic behaviors and convergence of the new polycrystal plasticity framework. Specific applications focus on the deformation of titanium, including the effects of twinning. Overall, the discrete harmonic based framework offers an attractive path forward for computationally efficient multi-scale embedding of polycrystal plasticity.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Pressure and fluid-driven fracture propagation in porous media using an adaptive finite element phase field model

This work presents phase field fracture modeling in heterogeneous porous media. We develop robust and efficient numerical algorithms for pressure-driven and fluid-driven settings in which the focus relies on mesh adaptivity in order to save computational cost for large-scale 3D applications. In the fluid-driven framework, we solve for three unknowns pressure, displacements and phase field that are treated with a fixed-stress iteration in which the pressure and the displacement–phase-field system are decoupled. The latter subsystem is solved with a combined Newton approach employing a primal–dual active set method in order to account for crack irreversibility. Numerical examples for pressurized fractures and fluid filled fracture propagation in heterogeneous porous media demonstrate our developments. Finally in particular, mesh refinement allows us to perform systematic studies with respect to the spatial discretization parameter.

42 ENGINEERING↗

DOE OSTI2019

A Monte Carlo Rectangle Packing Algorithm for Identifying Likely Spatial Distributions of Final Closure Cap Subsidence in the E-Area Low-Level Waste Facility

A Monte Carlo rectangle packing algorithm, summarized in Figure ES-1, has been developed to provide insights into the likely spatial distribution of subsided areas or holes in the final closure cap for the E-Area Low-Level Waste Facility (ELLWF) resulting from the placement of non-crushable waste containers within slit and engineered trench disposal units. Using historical records provided by Solid Waste Management as an indicator of future waste streams, a probability distribution of unique waste containers was constructed, and Monte Carlo sampling was used to sequentially select waste containers for placement in a rectangular region bounded by the disposal unit footprint. Within this Monte Carlo approach, the probability of any container type being selected is weighted by the fractional abundance relative to all other container types. For each Monte Carlo realization, the frequency of non-crushable waste containers appearing at each location on a spatially discretized mesh is updated. After many realizations, the location(s) with the highest frequencies of non-crushable waste containers are regarded as the most likely locations to experience subsidence (i.e., for a hole to form). Utilizing this approach has enabled the down-selection of a computationally intractable set of subsidence hole combinations to be explored in three-dimensional finite element groundwater flow and contaminant transport models. Such an approach can be applied to a number of different packaging problems.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS2021

Simulation of Solar-Induced Chlorophyll Fluorescence from 3D Canopies with the Dart Model

The potential of solar-induced chlorophyll fluorescence (SIF) to monitor photosynthesis and plant stress has attracted considerable interest in SIF remote sensing (RS). However, canopy SIF and RS observations are impacted by topography, vegetation three dimension (3D) structure, leaf orientation, non foliar elements (e.g., tree woody skeleton), ... Physically based downscaling of canopy SIF RS data to leaf-level (i.e., to leaf photosynthesis) requires 3D radiative transfer (RT) models simulating canopy SIF and its observation. These models are necessary to better exploit the potential of SIF, by linking leaf SIF and SIF in RS observations as a function of canopy 3D architecture and experimental configurations (sun and viewing directions, etc.). The Discrete Anisotropic Radiative Transfer (DART) model is a comprehensive 3D radiative transfer (RT) model for urban and natural landscapes. This paper presents its SIF modeling for vegetation simulated with facets, its validation with the SCOPE/mSCOPE 1D models, and its recent extension to SIF modelling for landscapes simulated with 3D turbid medium.

radiative transfer↗

NASA NTRS2021

Simulation of Solar-Induced Chlorophyll Fluorescence from 3D Canopies with the Dart Model

Radiative transfer↗

DOE OSTI2017

Numerical Simulation and Experimental Study of the Gas–Solid Flow Behavior Inside a Full-Loop Circulating Fluidized Bed: Evaluation of Different Drag Models

Both experimental and computational studies of the fluidization of high-density polyethylene (HDPE) particles in a small-scale full-loop circulating fluidized bed (CFB) are conducted. Experimental measurements of pressure drop are taken at various locations along the bed. The solids circulation rate is measured with an advanced particle image velocimetry (PIV) technique. Bed height of the quasi-static region in the standpipe is also measured. Comparative numerical simulations are performed with a computational fluid dynamics solver utilizing a discrete element method (CFD-DEM). Here, this paper examines the effect of different drag laws used in the CFD simulations through a detailed and direct comparison with experimental data from a small-scale, full-loop circulating fluidized bed. The Hill–Koch–Ladd drag correlation was shown to have good agreement with respect to system component pressure drop and inventory height in the standpipe.

42 ENGINEERING↗

DOE OSTI2026

Instabilities and phase transitions in architected metamaterials: a gradient-enhanced continuum approach

Architected metamaterials such as foams and lattices exhibit a wide range of properties governed by microstructural instabilities and emerging phase transitions. Their macroscopic response–including energy dissipation during impact, large recoverable deformations, morphing between configurations, and auxetic behavior–remains difficult to capture with conventional continuum models, which often rely on discrete approaches that limit scalability. In this work, we propose a nonlocal continuum formulation that captures both stable and unstable responses of elastic architected metamaterials. The framework extends anisotropic hyperelasticity by introducing nonlocal variables and internal length scales reflective of microstructural features. Local polyconvex free-energy models are systematically augmented with two families of non-(poly)convex energies, enabling both metastable and bistable responses. Implementation in a finite element framework enables solution using a hybrid monolithic–staggered strategy. Simulations capture densification fronts, forward and reverse transitions, hysteresis loops, imperfection sensitivity, and globally coordinated auxetic modes. Overall, this framework provides a robust foundation for accelerated modeling of instability-driven phenomena in architected metamaterials, while enabling extensions to anisotropic, dissipative, and active systems as well as integration with data-driven and machine learning approaches.

42 ENGINEERING↗

NASA NTRS2013

Launch and Assembly Reliability Analysis for Mars Human Space Exploration Missions

NASA s long-range goal is focused upon human exploration of Mars. Missions to Mars will require campaigns of multiple launches to assemble Mars Transfer Vehicles in Earth orbit. Launch campaigns are subject to delays, launch vehicles can fail to place their payloads into the required orbit, and spacecraft may fail during the assembly process or while loitering prior to the Trans-Mars Injection (TMI) burn. Additionally, missions to Mars have constrained departure windows lasting approximately sixty days that repeat approximately every two years. Ensuring high reliability of launching and assembling all required elements in time to support the TMI window will be a key enabler to mission success. This paper describes an integrated methodology for analyzing and improving the reliability of the launch and assembly campaign phase. A discrete event simulation involves several pertinent risk factors including, but not limited to: manufacturing completion; transportation; ground processing; launch countdown; ascent; rendezvous and docking, assembly, and orbital operations leading up to TMI. The model accommodates varying numbers of launches, including the potential for spare launches. Having a spare launch capability provides significant improvement to mission success.

Cates, Grant R.↗

DOE OSTI2024

Kaon mixing beyond the standard model with physical masses

We present nonperturbative results for beyond the standard model kaon mixing matrix elements in the isospin symmetric limit ( m u = m d ) of QCD, including a complete estimate of all dominant sources of systematic error. Our results are obtained from numerical simulations of lattice QCD with N f = 2 + 1 flavors of dynamical domain wall fermions. For the first time, these quantities are simulated directly at the physical pion mass m π ∼ 139 MeV for two different lattice spacings. We include data at three lattice spacings in the range a = 0.11 – 0.07 fm and with pion masses ranging from the physical value up to 450 MeV. Compared to our earlier work, we have added both direct calculations at physical quark masses and a third lattice spacing making the removal of discretization effects significantly more precise and eliminating the need for any significant mass extrapolation beyond the range of simulated data. We renormalize the lattice operators nonperturbatively using RI-SMOM off-shell schemes. These schemes eliminate the need to model and subtract nonperturbative pion poles that arises in the RI-MOM scheme and, since the calculations are performed with domain wall fermions, the unphysical mixing between chirality sectors is suppressed. Our results for the bag parameters in the MS ¯ scheme at 3 GeV are B K ≡ B 1 = 0.5240 ( 17 ) ( 54 ) , B 2 = 0.4794 ( 25 ) ( 35 ) , B 3 = 0.746 ( 13 ) ( 17 ) , B 4 = 0.897 ( 02 ) ( 10 ) and B 5 = 0.6882 ( 78 ) ( 94 ) , where the first error is from lattice uncertainties and the second is the uncertainty due to the perturbative matching to MS ¯ . Published by the American Physical Society 2024

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2014

Two-phase flow with mass density contrast: Stable schemes for a thermodynamic consistent and frame-indifferent diffuse-interface model

In this paper, we present a numerical scheme for the diffuse-interface model in [3] for two-phase flow of immiscible, incompressible fluids. As that model is in particular consistent with thermodynamics, energy estimates are expected to carry over to the discrete setting. By a subtle discretization of the convective coupling with the flux of the phase-field in the momentum equation, we prove discrete consistency with thermodynamics. Numerical experiments in two spatial dimensions – ranging from Rayleigh–Taylor instability to a comparison with previous modeling approaches – indicate the full practicality of our scheme and enable a first validation of the new modeling approach in [3].

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2018

A high-order multiscale finite-element method for time-domain acoustic-wave modeling

Accurate and efficient wave equation modeling is vital for many applications in such as acoustics, electromagnetics, and seismology. However, solving the wave equation in large-scale and highly heterogeneous models is usually computationally expensive because the computational cost is directly proportional to the number of grids in the model. We develop a novel high-order multiscale finite-element method to reduce the computational cost of time-domain acoustic-wave equation numerical modeling by solving the wave equation on a coarse mesh based on the multiscale finite-element theory. In contrast to existing multiscale finite-element methods that use only first-order multiscale basis functions, our new method constructs high-order multiscale basis functions from local elliptic problems which are closely related to the Gauss–Lobatto–Legendre quadrature points in a coarse element. Essentially, these basis functions are not only determined by the order of Legendre polynomials, but also by local medium properties, and therefore can effectively convey the fine-scale information to the coarse-scale solution with high-order accuracy. Numerical tests show that our method can significantly reduce the computation time while maintain high accuracy for wave equation modeling in highly heterogeneous media by solving the corresponding discrete system only on the coarse mesh with the new high-order multiscale basis functions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Mixed-Integer Linear Programming Formulation with Embedded Machine Learning Surrogates for the Design of Chemical Process Families

In previous work, we introduced process family design. The main idea is to design a platform of common elements, and, allowing us to capture additional cost savings, simultaneously design a family of processes, and reducing both engineering and deployment timelines. We formulate this as an optimization problem, specifically a nonlinear generalized disjunctive program (GDP). We have proposed two approaches for reformulating and solving this problem: one based on full-discretization of the design space and one that uses Machine Learning (ML) surrogates to replace the nonlinear process models. Using ML surrogates to predict required system costs and performance indicators allows us to reformulate the nonlinearities in the GDP generate an efficient MILP formulation. In this work, we apply the ML surrogate approach to two case studies. One case study involves designing a family of carbon capture systems to cover a set of different flue gas flow rates and inlet CO 2 concentrations, where we consider the absorber and stripper as common unit module types. The second case study focuses on a water-desalination process, where we design a family of these processes for a variety of salt concentrations and flow rates. In both of these case studies, we demonstrate a scalable optimization approach that enables the design of multiple processes simultaneously, reducing the time-to-market and overall costs by maximizing the cost savings due to both economies of scale and economies of numbers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

A soft departure from jamming: the compaction of deformable granular matter under high pressures

Here, the high-pressure compaction of three-dimensional granular packings is simulated using a bonded particle model (BPM) to capture linear elastic deformation. In the model, grains are represented by a collection of point particles connected by bonds. A simple multibody interaction is introduced to control Poisson's ratio and the arrangement of particles on the surface of a grain is varied to model both high- and low-frictional grains. At low pressures, the growth in packing fraction and coordination number follows the expected behavior near jamming and exhibit friction dependence. As the pressure increases, deviations from the low-pressure power-law scaling emerge after the packing fraction grows by approximately 0.1 and results from simulations with different friction coefficients converge. These results are compared to predictions from traditional discrete element method simulations which, depending on the definition of packing fraction and coordination number, may only differ by a factor of two. As grains deform under compaction, the average volumetric strain and asphericity, a measure of the change in the shape of grains, are found to grow as power laws and depend heavily on the Poisson's ratio of the constituent solid. Larger Poisson's ratios are associated with less volumetric strain and more asphericity and the apparent power-law exponent of the asphericity may vary. The elastic properties of the packed grains are also calculated as a function of packing fraction. In particular, we find the Poisson's ratio near jamming is 1/2 but decreases to around 1/4 before rising again as systems densify.

36 MATERIALS SCIENCE↗

DOE OSTI2015

Freely cooling granular gases with short-ranged attractive potentials

We treat the case of an undriven gas of inelastic hard-spheres with short-ranged attractive potentials via an extension of the pseudo-Liouville operator formalism. New evolution equations for the granular temperature and coordination number are obtained. The granular temperature exhibits deviation from both Haff’s law and the case of long-ranged potentials. We verify this departure using soft-sphere discrete element method simulations. Excellent agreement is found for the duration of the simulation even beyond where exclusively binary collisions are expected. Simulations show the emergence of strong spatial-velocity correlations on the length scale of the last peak in the pair-correlation function but do not show strong correlations beyond this length scale. We argue that molecular chaos may remain an adequate approximation if the system is modelled as a Smoluchowski type equation with aggregation and break-up processes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2019

Electromagnetic wave propagation based upon spectral-element methodology in dispersive and attenuating media

SUMMARY We build on mathematical equivalences between Maxwell’s wave equations for an electromagnetic medium and elastic seismic wave equations. This allows us to readily model Maxwell’s wave propagation in the spectral-element codes SPECFEM2D and SPECFEM3D, written for acoustic, viscoelastic and poroelastic seismic wave propagation, providing the ability to handle complex geometries, inherent to finite-element methods and retaining the strength of exponential convergence and accuracy due to the use of high-degree polynomials to interpolate field functions on the elements, characteristic to spectral-element methods (SEMs). Attenuation and dispersion processes related to the frequency dependence of dielectric permittivity and conductivity are also included using a Zener model, similar to shear attenuation in viscoelastic media or viscous diffusion in poroelastic media, and a Kelvin–Voigt model, respectively. Ability to account for anisotropic media is also discussed. Here, we limit ourselves to certain dielectric permittivity tensor geometries, in order to conserve a diagonal mass matrix after discretization of the system of equations. Doing so, simulation of Maxwell’s wave equations in the radar frequency range based on SEM can be solved using explicit time integration schemes well suited for parallel computation. We validate our formulation with analytical solutions. In 2-D, our implementation allows for the modelling of both a transverse magnetic (TM) mode, suitable for surface based reflection ground penetration radar type of applications, and a transverse electric (TE) mode more suitable for crosshole and vertical radar profiling setups. Two 2-D examples are designed to demonstrated the use of the TM and TE modes. A 3-D example is also presented, which allows for the full TEM solution, different antenna orientations, and out-of-plane variations in material properties.

58 GEOSCIENCES↗

NASA NTRS1986

Gust response of hingeless rotors

The gust response of a coupled hingeless rotor-fuselage system is studied in both hover and forward flight. Each rotor blade undergoes flap bending, lag bending, and torsional deflections. The blades are discretized into beam elements, each with fifteen nodal degrees of freedom. The fuselage is permitted three translational (vertical, longitudinal, and lateral) and two rotational (pitch and roll) degrees of freedom. The formulation considers a three-dimensional gust field wherein each gust velocity component can have an arbitrary variation in space and time. Aerodynamic loads are obtained using quasisteady strip theory. Wake-induced effects are introduced through dynamic inflow modeling. Dynamic stall and reverse flow effects are also included. Equations governing the rotor-fuselage gust response are linearized about the vehicle propulsive trim state and the blade steady-state defected positions, and solved by time integration. The effects of several parameters on the helicopter gust response are illustrated, including dynamic inflow, lag stiffness, forward speed, gust profile, gust penetration rate, and gust velocity direction.

Bir, G. S.↗

NASA NTRS1989

Control of the errors of discretization and idealization in finite element analysis

Understanding of the basic principles which control errors of discretization in finite element analysis has increased very substantially since 1980. The main milestones were: (1) development of the theoretical basis of p-extensions (1981); (2) understanding of the proper interplay between mesh design and assignment of polynomial degree to elements. Practical realization of exponential convergence rates, independently of the smoothness of the exact solution (1984); and (3) industrial experience with the new finite element technology known as the p- or hp-version of the finite element method: General Dynamics reported thirty- to forty-fold savings in terms of human time and large savings in computer time (1986). Lockheed reported favorably on their evaluation of error estimation and quality control capabilities of the p-version in industrial settings (1987). The gains in our understanding of how to control the errors of discretization represent only half of the control necessary to ensure that a numerical model is in fact an accurate representation of the corresponding physical system. Control of the errors of idealization is equally important. A brief overview of the main ideas of how to ensure the quality and reliability of mathematical models of structural systems is presented.

Szabo, Barna A.↗

NASA NTRS2006

Accuracy Quantification of the Loci-CHEM Code for Chamber Wall Heat Transfer in a GO2/GH2 Single Element Injector Model Problem

A robust rocket engine combustor design and development process must include tools which can accurately predict the multi-dimensional thermal environments imposed on solid surfaces by the hot combustion products. Currently, empirical methods used in the design process are typically one dimensional and do not adequately account for the heat flux rise rate in the near-injector region of the chamber. Computational Fluid Dynamics holds promise to meet the design tool requirement, but requires accuracy quantification, or validation, before it can be confidently applied in the design process. This effort presents the beginning of such a validation process for the Loci-CHEM CFD code. The model problem examined here is a gaseous oxygen (GO2)/gaseous hydrogen (GH2) shear coaxial single element injector operating at a chamber pressure of 5.42 MPa. The GO2/GH2 propellant combination in this geometry represents one the simplest rocket model problems and is thus foundational to subsequent validation efforts for more complex injectors. Multiple steady state solutions have been produced with Loci-CHEM employing different hybrid grids and two-equation turbulence models. Iterative convergence for each solution is demonstrated via mass conservation, flow variable monitoring at discrete flow field locations as a function of solution iteration and overall residual performance. A baseline hybrid was used and then locally refined to demonstrate grid convergence. Solutions were obtained with three variations of the k-omega turbulence model.

West, Jeff↗