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At least 1,729 records · Page 96
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

PyApprox: A software package for sensitivity analysis, Bayesian inference, optimal experimental design, and multi-fidelity uncertainty quantification and surrogate modeling

PyApprox is a Python-based one-stop-shop for probabilistic analysis of numerical models such as those used in the earth, environmental and engineering sciences. Easy to use and extendable tools are provided for constructing surrogates, sensitivity analysis, Bayesian inference, experimental design, and forward uncertainty quantification. The algorithms implemented represent a wide range of methods for model analysis developed over the past two decades, including recent advances in multi-fidelity approaches that use multiple model discretizations and/or simplified physics to significantly reduce the computational cost of various types of analyses. An extensive set of Benchmarks from the literature is also provided to facilitate the easy comparison of new or existing algorithms for a wide range of model analyses. Here, this paper introduces PyApprox and its various features, and presents results demonstrating the utility of PyApprox on a benchmark problem modeling the advection of a tracer in groundwater.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Electron-beam-ion-source (EBIS) modeling progress at FAR-TECH, Inc

FAR-TECH, Inc. has been developing a numerical modeling tool for Electron-Beam-Ion-Sources (EBISs). The tool consists of two codes. One is the Particle-Beam-Gun-Simulation (PBGUNS) code to simulate a steady state electron beam and the other is the EBIS-Particle-In-Cell (EBIS-PIC) code to simulate ion charge breeding with the electron beam. PBGUNS, a 2D (r,z) electron gun and ion source simulation code, has been extended for efficient modeling of EBISs and the work was presented previously. EBIS-PIC is a space charge self-consistent PIC code and is written to simulate charge breeding in an axisymmetric 2D (r,z) device allowing for full three-dimensional ion dynamics. This 2D code has been successfully benchmarked with Test-EBIS measurements at Brookhaven National Laboratory. For long timescale (< tens of ms) ion charge breeding, the 2D EBIS-PIC simulations take a long computational time making the simulation less practical. Most of the EBIS charge breeding, however, may be modeled in 1D (r) as the axial dependence of the ion dynamics may be ignored in the trap. Where 1D approximations are valid, simulations of charge breeding in an EBIS over long time scales become possible, using EBIS-PIC together with PBGUNS. Initial 1D results are presented. The significance of the magnetic field to ion dynamics, ion cooling effects due to collisions with neutral gas, and the role of Coulomb collisions are presented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Reviews and syntheses: Four decades of modeling methane cycling in terrestrial ecosystems

Abstract. Over the past 4 decades, a number of numerical models have been developed to quantify the magnitude, investigate the spatial and temporal variations, and understand the underlying mechanisms and environmental controls of methane (CH4) fluxes within terrestrial ecosystems. These CH4 models are also used for integrating multi-scale CH4 data, such as laboratory-based incubation and molecular analysis, field observational experiments, remote sensing, and aircraft-based measurements across a variety of terrestrial ecosystems. Here we summarize 40 terrestrial CH4 models to characterize their strengths and weaknesses and to suggest a roadmap for future model improvement and application. Our key findings are that (1) the focus of CH4 models has shifted from theoretical to site- and regional-level applications over the past 4 decades, (2) large discrepancies exist among models in terms of representing CH4 processes and their environmental controls, and (3) significant data–model and model–model mismatches are partially attributed to different representations of landscape characterization and inundation dynamics. Three areas for future improvements and applications of terrestrial CH4 models are that (1) CH4 models should more explicitly represent the mechanisms underlying land–atmosphere CH4 exchange, with an emphasis on improving and validating individual CH4 processes over depth and horizontal space, (2) models should be developed that are capable of simulating CH4 emissions across highly heterogeneous spatial and temporal scales, particularly hot moments and hotspots, and (3) efforts should be invested to develop model benchmarking frameworks that can easily be used for model improvement, evaluation, and integration with data from molecular to global scales. These improvements in CH4 models would be beneficial for the Earth system models and further simulation of climate–carbon cycle feedbacks.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1994

Self-consistent steady state model of the low-latitude boundary layer

Results are presented from a steady state numerical model of the low-latitude boundary layer (LLBL) on closed field lines and its coupling to the dayside auroral ionosphere. In the model the boundary layer approximation is used, the result being that inertial forces are taken into account only in the main flow direction (-x) where they are balanced by pressure forces, j x B forces, and viscous forces. Motion in the transverse directions (y and z) is treated kinematically, the force balances in these two directions being purely static. Computationally, the model is two dimensional, describing the motion of plasma and frozen-in magnetic field in the equatorial (xy) plane but allowing for lowest-order polynomial variation of some quantities with the coordinate (z) perpendicular to that plane. The plasma expands and compresses isentropically; the magnetic field is calculated self-consistently, which leads to approximately parabolic field line shape in planes parallel to the magnetopause (the xz plane), with maximum field curvature near the magnetopause edge of the LLBL. Coupling to the ionosphere via region 1 field-aligned currents is included. The effects of the ionosphere are represented by two parallel resistive plates at fixed height above and below the equatorial plane. The model can be used to investigate the influence of various physical parameters, for example, viscous and magnetic Reynolds numbers, and of boundary conditions at the magnetopause and in the magnetosphere on the LLBL development in the -x direction. Special attention is given to viscous effects which, under suitable circumstances, lead to a region 1 current that first increases and then reduces with increasing longitude away from local noon. Asymptotic matching of the antisunward motion of the cool LLBL plasma to sunward convection of hot plasma in the magnetosphere is illustrated along with the entrainment of magnetospheric plasma by the antisunward LLBL flow.

Drakou, E.↗
DOE OSTI2025

Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data

The Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) satellite developed by the European Space Agency (ESA) and the Japan Aerospace Exploration Agency (JAXA) launched in May 2024 carries a novel 94 GHz cloud profiling radar (CPR) with Doppler capability. This work describes the open-source instrument simulator Orbital-Radar, which transforms high-resolution radar data from field observations or forward simulations of numerical models to CPR primary measurements and uncertainties. The transformation accounts for sampling geometry and surface effects. We demonstrate Orbital-Radar's ability to provide realistic CPR views of typical cloud and precipitation scenes. The presented case studies show small-scale convection, marine stratus clouds, and Arctic mixed-phase cloud cases. These results provide valuable insights into the capabilities and challenges of the EarthCARE CPR mission and its advantages over the CloudSat CPR. Finally, Orbital-Radar allows for evaluating kilometre-scale numerical weather prediction models with EarthCARE CPR observations. So, Orbital-Radar can generate calibration and validation (Cal/Val) data sets already pre-launch. Nevertheless, an evaluation of synthetic CPR output data to accurate EarthCARE CPR data is missing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Numerical and Analytical Modeling of the Effect of Cracks on the Self-Inductance of a COTS YJ-41003-TC Toroid

COTS inductors and transformers often contain partial cracks whose effect on inductance, a key performance parameter, have not been carefully studied. In this report, the effects of both partial and complete cracks on the self-inductance of a 100 turn square cross section COTS YJ-41003-TC toroid comprised of J Material was comprehensively investigated using both analytically derived closed form expressions and 3D computational techniques employing commercial codes. Both partial (half-penny) and complete (air gap) cracks of 10 and 25 μm were investigated. The crack is defined as the physical distance between two faces of the toroid's magnetic core, such that the surface normal of either face is along the Φ-direction, in alignment with the B-field. For the purposes of validation, two different approaches were incorporated for both the analytical and numerical models. The two analytical methods are comprised of a first principles approach based on the physics of electromagnetics, as well as linear circuit theory. The former directly utilizes the integral form of Maxwell's equations while the latter exploits the interchangeable relationship between electric and magnetic circuits. Validation within the computational scheme is realized through a code-to-code comparison between commercial solvers, COMSOL Multiphysics and CST, with the former employing the Finite Element Method (FEM) and the latter the Finite Difference Time Domain (FDTD) technique. Sound agreement between all four methods (ie., two analytical and two numerical) is observed, with results indicating that only a perturbation in self-inductance occurs for the half-penny cracks, while a substantial reduction takes place for the case of complete cracks. It is important to note that even though a static μ r is applied, representing the linear region of the BH curve (based on manufacturer specifications), the complete crack results still place a lower conservative bound on the inductance. This follows from the fact that even in the case of a half-penny crack, if the magnetic core portion of the crack approaches saturation, the crack begins to behave like an air gap, or complete crack. When an air gap is introduced into a magnetic core, a substantial reduction in inductance can occur due to the significant difference in permeabilities between the two mediums (ie., μ core >> μ air ). The once intact bulk magnetic core of the toroid essentially begins to behave like an air core.

36 MATERIALS SCIENCE↗
NASA NTRS1977

Experience with a vectorized general circulation weather model on Star-100

A version of an atmospheric general circulation model was vectorized to run on a CDC STAR 100. The numerical model was coded and run in two different vector languages, CDC and LRLTRAN. A factor of 10 speed improvement over an IBM 360/95 was realized. Efficient use of the STAR machine required some redesigning of algorithms and logic. This precludes the application of vectorizing compilers on the original scalar code to achieve the same results. Vector languages permit a more natural and efficient formulation for such numerical codes.

Soll, D. B.↗
NASA NTRS2022

Can Machine Learning Reveal Precursors of Reversals of the Geomagnetic Axial Dipole Field?

It is well known that the axial dipole part of Earth’s magnetic field reverses polarity, so that the magnetic North Pole becomes the South Pole and vice versa. The timing of reversals is well documented for the past 160 Myr, but the conditions that lead to a reversal are still not well understood. It is not known if there are reliable ‘precursors’ of reversals (events that indicate that a reversal is upcoming) or what they might be. We investigate if machine learning (ML) techniques can reliably identify precursors of reversals based on time-series of the axial magnetic dipole field. The basic idea is to train a classifier using segments of time-series of the axial magnetic dipole. This training step requires modification of standard ML techniques to account for the fact that we are interested in rare events—a reversal is unusual, while a non-reversing field is the norm. Without our tweak, the ML classifiers lead to useless predictions. Perhaps even more importantly, the usable observational record is limited to 0–2 Ma and contains only five reversals, necessitating that we determine if the data are even sufficient to reliably train and validate an ML algorithm. To answer these questions we use several ML classifiers (linear/non-linear support vector machines and long short-term memory networks), invoke a hierarchy of numerical models (from simplified models to 3-D geodynamo simulations), and two palaeomagnetic reconstructions (PADM2M and Sint-2000). The performance of the ML classifiers varies across the models and the observational record and we provide evidence that this is not an artefact of the numerics, but rather reflects how ‘predictable’ a model or observational record is. Studying models of Earth’s magnetic field via ML classifiers thus can help with identifying shortcomings or advantages of the various models. For Earth’s magnetic field, we conclude that the ability of ML to identify precursors of reversals is limited, largely due to the small amount and low frequency resolution of data, which makes training and subsequent validation nearly impossible. Put simply: the ML techniques we tried are not currently capable of reliably identifying an axial dipole moment (ADM) precursor for geomagnetic reversals. This does not necessarily imply that such a precursor does not exist, and improvements in temporal resolution and length of ADM records may well offer better prospects in the future.

Kyle Gwirtz↗
NASA NTRS2003

A Numerical Climate Observing Network Design Study

This project was concerned with three related questions of an optimal design of a climate observing system: 1. The spatial sampling characteristics required from an ARGO system. 2. The degree to which surface observations from ARGO can be used to calibrate and test satellite remote sensing observations of sea surface salinity (SSS) as it is anticipated now. 3. The more general design of an climate observing system as it is required in the near future for CLIVAR in the Atlantic. An important question in implementing an observing system is that of the sampling density required to observe climate-related variations in the ocean. For that purpose this project was concerned with the sampling requirements for the ARGO float system, but investigated also other elements of a climate observing system. As part of this project we studied the horizontal and vertical sampling characteristics of a global ARGO system which is required to make it fully complementary to altimeter data with the goal to capture climate related variations on large spatial scales (less thanAttachment: 1000 km). We addressed this question in the framework of a numerical model study in the North Atlantic with an 1/6 horizontal resolution. The advantage of a numerical design study is the knowledge of the full model state. Sampled by a synthetic float array, model results will therefore allow to test and improve existing deployment strategies with the goal to make the system as optimal and cost-efficient as possible. Attachment: "Optimal observations for variational data assimilation".

Stammer, Detlef↗
DOE OSTI2024

Continuous integration data-driven platform of industrial-scale subsurface storage for real-time analytics

This project helped address the growing need for efficient and scalable models to support geological carbon and energy storage, which are crucial for achieving net-zero emissions. Traditionally accurate high-fidelity numerical models have been used to simulate relevant storage processes under a handful of processes, however such models are computationally demanding, making uncertainty quantification impractical. Consequently, we first developed a machine learning framework, based on Graph Neural Operators (GNOs), to improving the accuracy of model predictions for a fixed computational budget. We then developed an Ensemble of Improved Neural Operators (ENO), which uses bagging and Monte Carlo dropout techniques, to further improve prediction accuracy. Lastly, we developed the way to explain progressive transfer learning methods to reduce the amount of training data and computational cost of training (i.e., reduce trainable parameters) when using our models for multiple storage sites. Our numerical investigation, which used real-world case studies, demonstrated that our framework can significantly improve the safety and efficiency of geological storage operations, with potential applications in other domains such as geothermal reservoirs and climate modeling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Using Hydrodynamic Similarity as a Verification Method for Impact Cratering Simulations in the FLAG Hydrocode

Hydrodynamic codes (hydrocodes) are common tools for modeling hypervelocity impacts to provide insight into the physical phenomenon. Hydrocodes can simulate impacts from micrometer to kilometer spatial scales and reach impact velocities difficult to achieve in experimental settings. However, numerical models are approximations, and demonstrating that a numerical method is capable of providing physical results for these models is essential. In this work, we employ a hydrocode verification technique that leverages hydrodynamic similarity, a mathematical property of the conservation equations of fluid mechanics that form the basis for hydrocode models. Using the FLAG hydrocode, we simulate aluminum (Al) and basalt projectiles and targets at spatial scales spanning 7 orders of magnitude (hundreds of micrometers to kilometers). These materials were chosen because Al-6061 is a common material in spacecraft and satellites and basalt is a useful approximation of rocky astronomical bodies. Our results show that hydrodynamic similarity holds for each material model used and across spatial scales. We show that under certain conditions hydrodynamic similarity can apply in the presence of gravity and that similarity does not hold in the presence of strength models. We conclude that the FLAG hydrocode preserves important mathematical properties of fluid dynamics in hypervelocity impacts of Al-6061 and basalt.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1994

Analysis of the early spectra and light curve of SN 1987A

Numerical modeling of supernova spectra, light curves, and hydrodynamics requires physical inputs, numerical techniques, approximations, and assumptions which must be thoroughly understood in order to study the details of supernova explosions. Here, we discuss some of these in the context of the early evolution of supernova 1987A. Gray radiation-hydrodynamics is used to calculate the bolometric light curve and the hydrodynamic evolution of the supernova. Synthetic spectra are then obtained for the resulting density and velocity structure. The spectrum calculations are performed using a special-relativistic treatment of the radiative transfer equation in the comoving frame, line blanketing by about 10(exp 5) spectral lines, and departures from local thermodynamic equilibrium (LTE) for H I, He I, Mg II, and Ca II. We find that we are able to simultaneously fit the early light curve and spectra reasonably well, using a progenitor model from Arnett (1991a), without fine-tuning the free parameters. Temperature structures and radiative equilibrium, non-LTE effects, homologous expansion, and mean opacities are discussed.

Hauschildt, Peter H.↗
DOE OSTI2017

In situ frustum indentation of nanoporous copper thin films

Mechanical properties of thin films are often obtained solely from nanoindentation. At the same time, such measurements are characterized by a substantial amount of uncertainty, especially when mean pressure or hardness are used to infer uniaxial yield stress. In this paper we demonstrate that indentation with a pyramidal flat tip (frustum) indenter near the free edge of a sample can provide a significantly better estimate of the uniaxial yield strength compared to frequently used Berkovich indenter. This is first demonstrated using a numerical model for a material with an isotropic pressure sensitive yield criterion. Numerical simulations confirm that the indenter geometry provides a clear distinction of the mean pressure at which a material transitions to inelastic behavior. The mean critical pressure is highly dependent on the plastic Poisson ratio ν p so that at the 1% offset of normalized indent depth, the critical pressure p m c normalized to the uniaxial yield strength σ 0 is 1 < p m c /σ 0 < 1.3 for materials with 0 < ν p < 0.5. Choice of a frustum over Berkovich indenter reduces uncertainty in hardness by a factor of 3. These results are used to interpret frustum indentation experiments on nanoporous (NP) Copper with struts of typical diameter of 45 nm. An estimate of the yield strength of NP Copper is obtained 230 MPa < σ 0 < 300 MPa. Edge indentation further allows one to obtain in-plane strain maps near the critical pressure. Finally, comparison of the experimentally obtained in-plane strain maps of NP Cu during deformation and the strain field for different plastic Poisson ratios suggest that this material has a plastic Poisson ratio of the order of 0.2–0.3. However, existing constitutive models may not adequately capture post-yield behavior of NP metals.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Simulating bubble dynamics in a buoyant system

Summary Multiphase flows are critical components of many physical systems; however, numerical models of multiphase flows with large parameter gradients can be challenging. Here, two different numerical methods, volume of fluid (VOF) and smoothed particle hydrodynamics (SPH), are used to model the buoyant rise of isolated gas bubbles through quiescent fluids for a range of Bond and Reynolds numbers. The VOF is an Eulerian grid–based method, whereas the SPH is Lagrangian and mesh free. Each method has unique strengths and weaknesses, and a comparison of the two approaches as applied to multiphase phenomena has not previously been performed. The VOF and SPH simulations are compared, verified, and validated. Results using two‐dimensional VOF and SPH simulations are similar to each other and are able to reproduce numerical benchmarks and experimental results for sufficiently large Morton and Reynolds numbers. It is also shown that at low Reynolds numbers, the two methods, SPH and VOF, diverge in the transient regime of the bubble rise. Regimes that require simulations capable of representing three‐dimensional drag are identified as well as regimes in which results from VOF and SPH diverge.

Arai, Erin↗
DOE OSTI2023

Multiscale Electrothermal Design of a Modular Multilevel Converter for Medium-Voltage Grid-Tied Applications

As a key feature of modular multilevel converters (MMCs), a large number of semiconductor devices are employed in the converter and distributed over a stack of submodules. Each submodule has a strict temperature limit that imposes constraints on the operating range of the converter. Different loading conditions/losses in the submodules lead to unavoidable temperature variations inside the MMC, which consequently affect the system-level performance and reliability. This paper is focused on the electrothermal analysis and design of a medium-voltage silicon carbide (SiC)-based MMC system, from submodule power semiconductors to the overall MMC system integration of multiple submodules, for grid-connected applications. Loss calculations are performed to estimate the cooling requirements and aid thermal design at different levels. The performance of a forced-air cooling approach is analyzed within a numerical modeling framework. Maximum temperature of the SiC power modules is predicted using numerical tools. Thermal design of the MMC cabinet with various arrangements of air inlet(s) and outlet(s) is investigated and compared from a cooling performance perspective. A fully resolved model of the arrangement that yields optimal results is developed to accurately predict the temperature profile of the essential components in the submodules.

computational fluid dynamics↗
DOE OSTI2018

Evolution of planar fractures in limestone: The role of flow rate, mineral heterogeneity and local transport processes

In this study, the processes that affect the evolution of fracture geometry and reactive transport in limestone fractures were evaluated using an integrated experimental and modeling approach. Flow-through experiments were performed to investigate the alteration of three artificially made planar limestone fractures, which were exposed to HCl-acidified water flow (pH 3.8 ± 0.1) at three different rates. Reactive infiltration instability developed in the fractures because of small fracture aperture variations and naturally occurring heterogeneity in the rock, i.e., the presence of clay spots of higher porosity. The dissolution regime changed from conical to dominant and ramified wormhole with increasing flow rate, i.e., Péclet number. Maps of fracture aperture obtained from X-ray micro-tomography imaging, together with measurements of permeability and analyses of fluid chemistry, provided experimental constraints for modeling. Numerical simulations were performed using a 2.5D continuum reactive transport model to examine the development of flow patterns and the reactivity and permeability evolution over time, and to interrogate the impacts of fluid reactivity, mineral heterogeneity and diffusive boundary layer. The modeling results showed that fracture alteration is very sensitive to initial fluid reactivity and mineralogical heterogeneity, in addition to flow rate. Finally, the changes of local transport processes during fracture opening also affected the reactivity of the fractured samples.

58 GEOSCIENCES↗
DOE OSTI2021

On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks

Physics-informed neural networks (PINNs) are demonstrating remarkable promise in integrating physical models with gappy and noisy observational data, but they still struggle in cases where the target functions to be approximated exhibit high-frequency or multi-scale features. Here in this work we investigate this limitation through the lens of Neural Tangent Kernel (NTK) theory and elucidate how PINNs are biased towards learning functions along the dominant eigen-directions of their limiting NTK. Using this observation, we construct novel architectures that employ spatio-temporal and multi-scale random Fourier features, and justify how such coordinate embedding layers can lead to robust and accurate PINN models. Numerical examples are presented for several challenging cases where conventional PINN models fail, including wave propagation and reaction–diffusion dynamics, illustrating how the proposed methods can be used to effectively tackle both forward and inverse problems involving partial differential equations with multi-scale behavior.

42 ENGINEERING↗
DOE OSTI2019

Lattice Boltzmann modelling of the coupling between charge transport and electrochemical reactions in a solid oxide fuel cell with a patterned anode

A fundamental understanding of the electrochemical reactions and the associated transport processes in electrodes of solid oxide fuel cells (SOFCs) is critical to the development of new electrode materials. To date, however, our understanding of the electrode processes is still very limited due to the lack of well-designed experiments and carefully-validated predictive models. To facilitate studies in this area, we have developed a numerical model that has taken into consideration of the coupling between the transport of mobile charged species (e.g., ions and electrons) in conducting phases and the electrochemical reactions at the three phase boundaries of an SOFC anode. The validity of this model has been confirmed by the electrochemical performance of test cells with a patterned anode consisting of well-defined electronic and ionic conducting phases. The model is then applied to quantifying the factors that critically influence the performance of a patterned anode, resulting in three key dimensionless parameters governing the coupling of transport and reactions in the anode: the ratio of electronic-to-ionic conductivity (σ el /σ ion ), the dimensionless exchange current density (i ex /i 0 ), and the dimensionless electric potential (Fφ 0 /RT). In particular, it is found that only i ex /i 0 and Fφ 0 /RT play a significant role under typical SOFC operating conditions: anode performance increases with the increase in i ex /i 0 and Fφ 0 /RT. Accordingly, we have constructed a phase map to demonstrate the combined effect of i ex /i 0 and Fφ 0 /RT, which is helpful for rational design and operation of SOFC patterned electrodes of different materials and geometries. More importantly, our present model is also applicable to the study of actual porous SOFC electrodes with known 3D microstructures.

08 HYDROGEN↗