Results for “multiscale methods” — Page 30

DOE OSTI2023

Multiscale Electricity Modeling for Evaluating Carbon Capture and Sequestration Technologies (Final Report)

Carbon capture and sequestration (CCS) technologies that can operate with a high degree of operating flexibility could provide necessary electric grid flexibility in a system with high shares of variable renewables. This project examines the deployment and dispatch potential of twelve unique flexible CCS (FLECCS) technologies that encompass post-combustion carbon dioxide (CO 2 ) capture designs, concepts using a storage media to enable energy arbitrage, and hybrid processes that integrate CCS with direct air capture (DAC) for flexibility with net zero or negative CO 2 emissions. FLECCS technology potential is explored with a multi-model, multi-scale framework including the Regional Energy Deployment System (ReEDS) electric sector capacity expansion model (CEM) and the PLEXOS production cost model (PCM). Innovative methods were developed to represent FLECCS technology operating modes, performance, and cost in the two models. ReEDS was then used to simulate nine scenarios for each FLECCS technology, three CO 2 emissions price futures reaching $\$$150, $\$$225, and $\$$300/tCO 2 in 2050; and three scenarios for FLECCS technology deployment favorability relative to competing technologies. For each CO 2 price and reference FLECCS favorability, the 2050 infrastructures from ReEDS model are downscaled and implemented in PLEXOS to examine hourly dispatch under detailed operational constraints that are not included in ReEDS. FLECCS technologies exhibited a wide range of deployment potential ranging from none to several hundred gigawatts of capacity, with outcomes highly sensitive to input cost and performance parameters that are inherently highly uncertain. When deployed, FLECCS tended to displace a combination of wind, solar, and natural gas-based technologies rather than supporting increased renewable deployment. As a result, CO 2 emissions reductions facilitated by FLECCS deployment tended to come with higher overall system costs and electricity prices. When economically competitive, FLECCS technologies can contribute significant flexible generation and firm capacity to the grid, but continued technology development and an expanded analytical scope are necessary to fully understand FLECCS deployment potential its impact on the electric power sector. Follow-on analysis incorporating captured CO 2 tax credit value from the Inflation Reduction Act (IRA) and other potential policy scenarios could be particularly valuable, as this policy can substantially change the relative competitiveness of FLECCS technologies.

03 NATURAL GAS↗

DOE OSTI2022

Sealing fractures to increase underground storage security: Lessons learned from a multiscale multim

Explore the source record for details and available documents.

Hajirezaie, Sassan↗

NASA NTRS1990

Multiscale vector fields for image pattern recognition

A uniform processing framework for low-level vision computing in which a bank of spatial filters maps the image intensity structure at each pixel into an abstract feature space is proposed. Some properties of the filters and the feature space are described. Local orientation is measured by a vector sum in the feature space as follows: each filter's preferred orientation along with the strength of the filter's output determine the orientation and the length of a vector in the feature space; the vectors for all filters are summed to yield a resultant vector for a particular pixel and scale. The orientation of the resultant vector indicates the local orientation, and the magnitude of the vector indicates the strength of the local orientation preference. Limitations of the vector sum method are discussed. Investigations show that the processing framework provides a useful, redundant representation of image structure across orientation and scale.

Low, Kah-Chan↗

DOE OSTI2024

Sol-gel derived silicate-phosphate glass SiO 2 –P 2 O 5 –CaO–TiO 2 : The effect of titanium isopropoxide on porosity and thermomechanical stability

Despite of several decades lasting extensive research of bioactive and bioresorbable glasses the systematic parametrization and determination of the key factors affecting porosity and thermomechanical characteristics still remains challenging. Here, we present silica-phosphate glasses, with the composition 70SiO 2 - 20P 2 O 5 - (10-x)CaO-xTiO 2 (mol%; x = 0, 2.5, 5, and 7.5), prepared by sol -gel method and reinforced by titanium dioxide via titanium isopropoxide (TTIP) incorporation which demonstrated tunable variation of porosity from micro-to macro -region and superb mechanical integrity during the calcination process. The presence of 7.5 mol% TiO 2 promotes dimensional stability up to 1000°C as investigated by thermomechanical analysis. The XRD showed the dominant presence of silicon phosphate [Si(P 2 O 7 )], titanium phosphate [Ti(P 2 O 7 )] and calcium phosphates [β-Ca(P 2 O 6 ) and γ- Ca 2 (P 2 O 7 )]. The effect of TiO 2 doping on the multiscale morphology and porosity was investigated by means of SEM, MIP, μCT, N 2 adsorption and USAXS/SAXS. Increasing TiO 2 content leads to the formation of open porosity up to 70vol% and drives the formation of a refined interconnected macroporosity of 2-30 μm. In contrast, mesoporosity with a dominance of 3-6nm pores decreases in all samples with increasing TiO 2 content. USAXS/SAXS revealed an increase in primary particle size with increasing TiO 2 content which is in good agreement with the nitrogen physisorption analysis showing that microporosity decreases with increasing TiO2 content.

36 MATERIALS SCIENCE↗

NASA NTRS2016

Study of the Spacecraft Potential Under Active Control and Plasma Density Estimates During the MMS Commissioning Phase

Each spacecraft of the recently launched magnetospheric multiscale MMS mission is equipped with Active Spacecraft Potential Control (ASPOC) Instruments, which control the spacecraft potential in order to reduce spacecraft charging effects. ASPOC typically reduces the spacecraft potential to a few volts. On several occasions during the commissioning phase of the mission, the ASPOC instruments were operating only on one spacecraft at a time. Taking advantage of such intervals, we derive photoelectron curves and also perform reconstructions of the uncontrolled spacecraft potential for the spacecraft with active control and estimate the electron plasma density during those periods. We also establish the criteria under which our methods can be applied.

Andriopoulou, M.↗

DOE OSTI2020

Imaging transient solidification behavior

Solidification processing offers the first opportunity to control microstructure, properties, and performance in metallic alloy components. Until recently, microstructural evaluations were limited to post-solidification characterization by destructive methods. We review the development of time-resolved, in situimaging techniques capable of capturing solid-liquid interfacial evolution in metallic alloys with high spatial and temporal resolution underdiverse solidification conditions relevant for applications ranging from conventional directional solidification, crystal growth, and casting,to welding and additive manufacturing. These experiments enable direct visualization of transient behaviors that would otherwise remain unknown, uniquely providinginsights into the physics that impact microstructure and defect development and strategies for microstructuralcontrol and defect mitigation. Understanding microstructural evolution and the characteristics that form under various solidification conditions is essential for the development of multiscale, experimentallyinformed predictive modeling. This is highlightedby solidification simulations that utilize in situmeasurements of solidification dynamics from state-of-the-art experimental techniques.

36 MATERIALS SCIENCE↗

NASA NTRS2011

A Globally Stable Lyapunov Pointing and Rate Controller for the Magnetospheric MultiScale Mission (MMS)

The Magnetospheric MultiScale Mission (MMS) is scheduled to launch in late 2014. Its primary goal is to discover the fundamental plasma physics processes of reconnection in the Earth's magnetosphere. Each of the four MMS spacecraft is spin-stabilized at a nominal rate of 3 RPM. Traditional spin-stabilized spacecraft have used a number of separate modes to control nutation, spin rate, and precession. To reduce the number of modes and simplify operations, the Delta-H control mode is designed to accomplish nutation control, spin rate control, and precession control simultaneously. A nonlinear design technique, Lyapunov's method, is used to design the Delta-H control mode. A global spin rate controller selected as the baseline controller for MMS, proved to be insufficient due to an ambiguity in the attitude. Lyapunov's design method was used to solve this ambiguity, resulting in a controller that meets the design goals. Simulation results show the advantage of the pointing and rate controller for maneuvers larger than 90 deg and provide insight into the performance of this controller.

Shah, Neerav↗

NASA NTRSDate not supplied

Hierarchical Multiscale Process Modeling of A Textile Composite Y-Joint for the Aurora D8 Aircraft

Woven polymer matrix composites (PMCs) are widely used in aerospace applications for their favorable specific properties. However, the behavior of the inter- and intra-tow matrix during manufacturing of woven PMCs is difficult to isolate experimentally due to geometric and processing complexities. Classical closed-form homogenization approaches allow for composite thermos-chemo-mechanical properties to be characterized at any fiber volume fraction. In this work, virtual curing is applied to the inter- and intra-tow matrix materials of a plain weave repeating unit cell (RUC). Thermo-chemo-mechanical property evolution within the tows is calculated using the Concentric Cylinder Model (CCM) and the Rule of Mixtures (ROM). Curing is implemented through user-written subroutines within the commercial finite element method software Abaqus. Virtual curing results are compared with those from a linear-elastic thermal cool down simulation in Abaqus. Results indicate that tow property evolution during curing has a non-negligible effect on the final stress state.

curing↗

DOE OSTI2022

MISPR : an open-source package for high-throughput multiscale molecular simulations

Computational tools provide a unique opportunity to study and design optimal materials by enhancing our ability to comprehend the connections between their atomistic structure and functional properties. However, designing materials with tailored functionalities is complicated due to the necessity to integrate various computational-chemistry software (not necessarily compatible with one another), the heterogeneous nature of the generated data, and the need to explore vast chemical and parameter spaces. The latter is especially important to avoid bias in scattered data points-based models and derive statistical trends only accessible by systematic datasets. Here, we introduce a robust high-throughput multi-scale computational infrastructure coined MISPR (Materials Informatics for Structure–Property Relationships) that seamlessly integrates classical molecular dynamics (MD) simulations with density functional theory (DFT). By enabling high-performance data analytics and coupling between different methods and scales, MISPR addresses critical challenges arising from the needs of automated workflow management and data provenance recording. The major features of MISPR include automated DFT and MD simulations, error handling, derivation of molecular and ensemble properties, and creation of output databases that organize results from individual calculations to enable reproducibility and transparency. In this work, we describe fully automated DFT workflows implemented in MISPR to compute various properties such as nuclear magnetic resonance chemical shift, binding energy, bond dissociation energy, and redox potential with support for multiple methods such as electron transfer and proton-coupled electron transfer reactions. The infrastructure also enables the characterization of large-scale ensemble properties by providing MD workflows that calculate a wide range of structural and dynamical properties in liquid solutions. MISPR employs the methodologies of materials informatics to facilitate understanding and prediction of phenomenological structure–property relationships, which are crucial to designing novel optimal materials for numerous scientific applications and engineering technologies.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Bridging Nano- and Microscale X-Ray Tomography for Battery Research by Leveraging Artificial Intelligence

X-ray computed tomography (CT) is a non-destructive imaging technique in which contrast originates from the materials' absorption coefficient. The recent development of laboratory nanoscale CT (nano-CT) systems has pushed the spatial resolution for battery material imaging to voxel sizes of 50 nm, a limit previously achievable only with synchrotron facilities. Given the non-destructive nature of CT, in situ and operando studies have emerged as powerful methods to quantify morphological parameters, such as tortuosity factor, porosity, surface area and volume expansion, during battery operation or cycling. Combined with artificial intelligence and machine learning analysis techniques, nano-CT has enabled the development of predictive models to analyse the impact of the electrode microstructure on cell performances or the influence of material heterogeneities on electrochemical responses. In this Review, we discuss the role of X-ray CT and nano-CT experimentation in the battery field, discuss the incorporation of artificial intelligence and machine learning analyses and provide a perspective on how the combination of multiscale CT imaging techniques can expand the development of predictive multiscale battery behavioural models.

diagnostics↗

NASA NTRS2014

Orbit Determination Accuracy Analysis of the Magnetospheric Multiscale Mission During Perigee Raise

The Goddard Space Flight Center (GSFC) Flight Dynamics Facility (FDF) will provide orbit determination and prediction support for the Magnetospheric Multiscale (MMS) mission during the missions commissioning period. The spacecraft will launch into a highly elliptical Earth orbit in 2015. Starting approximately four days after launch, a series of five large perigee-raising maneuvers will be executed near apogee on a nearly every-other-orbit cadence. This perigee-raise operations concept requires a high-accuracy estimate of the orbital state within one orbit following the maneuver for performance evaluation and a high-accuracy orbit prediction to correctly plan and execute the next maneuver in the sequence. During early mission design, a linear covariance analysis method was used to study orbit determination and prediction accuracy for this perigee-raising campaign. This paper provides a higher fidelity Monte Carlo analysis using the operational COTS extended Kalman filter implementation that was performed to validate the linear covariance analysis estimates and to better characterize orbit determination performance for actively maneuvering spacecraft in a highly elliptical orbit. The study finds that the COTS extended Kalman filter tool converges on accurate definitive orbit solutions quickly, but prediction accuracy through orbits with very low altitude perigees is degraded by the unpredictability of atmospheric density variation.

Determination↗

DOE OSTI2022

Sequential Decision Making (SDM) for Mesh Refinement and Model Selection in Multiscale, Multi-Physics Applications

Intelligent automation and decision support are needed to enhance computational efficiency and robustness in multiscale and multi-physics problems, including materials science, manufacturing, and climate and weather modeling. Current scientific computing approaches for enabling decisions by scientists fail to explore the role of learning, reasoning, and probabilistic planning. Often these decisions are not performed in real-time during the computation but are made prior to the start of the computation, which must be interrupted in order to make changes to the prior choices. Such interruptions at different stages of the computation increase the total computing time and the need for a human expert to frequently monitor the results. State of art scientific computing methods consist of rule-based algorithms that cannot automatically adapt to a dynamically changing computing environment. The development of a Sequential Decision Making (SDM) framework will automate scientific computing by optimizing the policies for mesh refinement, time-stepping, model and algorithm selection, resource allocation, and pre and post-processing. Our agent SDM framework for scientific computing will consist of data-driven learning (Classifier), automated reasoning (contextual knowledge), and probabilistic planning (Reinforcement Learning). In this project, we focused on three problems to demonstrate our SDM framework on a set of ordinary and partial differential equations. Classification of Lorenz system regions using Feed-Forward Neural Networks examined learning in the SDM framework. On the other hand, reasoning and planning in the SDM framework were used in two problems: adaptive time-stepping for nonlinear ODEs using on-policy RL algorithms, and adaptive mesh refinement for 2-D PDEs using off-policy RL algorithms.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Advanced Fuels Campaign Execution Plan

The Advanced Fuels Campaign (AFC) Execution Plan outlines the strategy, mission, scope, near-term and long-term goals, structure, and organization associated with nuclear fuels and materials research, development, and demonstration activities within the Department of Energy’s (DOE) Nuclear Fuel Cycle and Supply Chain (NFCSC) program. NFCSC has been given responsibility to identify and mature advanced fuel technologies for the DOE using a science-based approach, focused on developing a fundamental understanding of nuclear fuels and materials to drive development of integrated nuclear fuel and materials technology. This science-based approach combines theory, experiments, and multiscale modeling and simulation to achieve a predictive understanding of relevant behaviors ranging from fuel fabrication processes (and their resulting fuel microstructures) through fuel/cladding performance under irradiation (in contrast to more empirical, observation-based approaches frequently used in fuel performance modeling and fuel qualification). The traditional scope of AFC includes the evaluation and development of multiple fuel forms to support two fuel cycle options: once-through and full recycle. The word “fuel” is used generically to include conventional fuels, transmutation targets, and any associated cladding or duct materials. The once-through fuel cycle addresses advanced light water reactor fuels with enhanced performance, extended burnup, and reduced waste generation. In fiscal year (FY) 2012, AFC’s scope expanded to include research, development, and demonstration (RD&D) for light water reactor (LWR) fuels with enhanced accident tolerance. Fuel fabrication activities include the development of innovative methods to enhance process efficiencies, reduce waste, and improve control over as-fabricated fuel microstructural properties to achieve desired in-reactor performance. Using modern modeling and simulation approaches, the objective is to predict fresh fuel properties given the feedstock characteristics and fabrication process parameters. The performance-related activities include small-scale, in-reactor, and out-of-reactor phenomenological testing (distinct from, but synergistic with, integral prototypic testing) and extensive, quantitative characterization (focusing on characterization of fuel and cladding materials at the scale of microstructure) both before and after testing. Larger-scale, prototypic experiments are conducted in concert with phenomenological testing to drive a Fuel Development and Qualification program, incorporating a fundamental understanding of fuel behavior performance characteristics. Then, using the tools developed under the productive science-based approach, fuels will be optimized to meet specific performance requirements, thereby minimizing the need to repeatedly perform large-scale, integral experiments over a wide parametric range as a means of experimental exploration. Two significant initiatives are underway within AFC. First, a gap analysis completed in early FY 2019 identified critical irradiation testing needs that are lacking within the national light water reactor (LWR) fuels testbed since the shutdown of the Halden Reactor in 2018. The identified gaps are for instrumented, prototypic testing of LWR fuels, especially under boiling water reactor conditions, ramp conditions, and conditions leading to fuel failure; these needs exist for supporting current LWR fuels and their possible extension to higher burnups, but are especially urgent relative to near-term development and qualification of accident-tolerant fuels. Recommendations that resulted from the Halden Gap Analysis focused on enhancements at Advanced Test Reactor (ATR) and Transient Reactor Test Facility (TREAT) to fill gaps in testing capabilities relative to these needs. Second, a concerted effort to develop and demonstrate a systematic approach to accelerating the development, testing, and qualification of new fuel systems has been initiated. This is highlighted by a test strategy that combines the considerable advances in multiscale, mechanistic fuel modeling of recent years with a MiniFuel separate effects test program in the High Flux Isotope Reactor (HFIR) and a Fission Accelerated Steady-state Testing (FAST) semi-integral accelerated test program in ATR. This approach is being tested/demonstrated using the metallic fuel system, but if successful it is expected to be extensible to multiple fuel types and diverse applications. This document includes an overview of the NFCSC program, a definition of science-based development of nuclear fuels, near-term goals for Advanced LWR fuels (ALFs), and longer-term goals for Advanced Reactor Fuels (ARFs) RD&D. This includes the activities that will be conducted to achieve success toward the grand challenge, as well as the goals and milestones to be achieved over the next few decades of research and development. Long-term goals are based on the DOE Office of Nuclear Energ

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Advanced Fuels Campaign Execution Plan

The Advanced Fuels Campaign (AFC) Execution Plan outlines the strategy, mission, scope, near-term and long-term goals, structure, and organization associated with nuclear fuels and materials research, development, and demonstration activities within the Department of Energy’s (DOE) Nuclear Fuel Cycle and Supply Chain (NFCSC) program. NFCSC has been given responsibility to identify and mature advanced fuel technologies for the DOE using a science-based approach, focused on developing a fundamental understanding of nuclear fuels and materials to drive development of integrated nuclear fuel and materials technology. This science-based approach combines theory, experiments, and multiscale modeling and simulation to achieve a predictive understanding of relevant behaviors ranging from fuel fabrication processes (and their resulting fuel microstructures) through fuel/cladding performance under irradiation (in contrast to more empirical, observation-based approaches frequently used in fuel performance modeling and fuel qualification). The traditional scope of AFC includes the evaluation and development of multiple fuel forms to support two fuel cycle options: once-through and full recycle. The word “fuel” is used generically to include conventional fuels, transmutation targets, and any associated cladding or duct materials. The once-through fuel cycle addresses advanced light water reactor fuels with enhanced performance, extended burnup, and reduced waste generation. In fiscal year (FY) 2012, AFC’s scope expanded to include research, development, and demonstration (RD&D) for light water reactor (LWR) fuels with enhanced accident tolerance. Fuel fabrication activities include the development of innovative methods to enhance process efficiencies, reduce waste, and improve control over as-fabricated fuel microstructural properties to achieve desired in-reactor performance. Using modern modeling and simulation approaches, the objective is to predict fresh fuel properties given the feedstock characteristics and fabrication process parameters. The performance-related activities include small-scale, in-reactor, and out-of-reactor phenomenological testing (distinct from, but synergistic with, integral prototypic testing) and extensive, quantitative characterization (focusing on characterization of fuel and cladding materials at the scale of microstructure) both before and after testing. Larger-scale, prototypic experiments are conducted in concert with phenomenological testing to drive a Fuel Development and Qualification program, incorporating a fundamental understanding of fuel behavior performance characteristics. Then, using the tools developed under the productive science-based approach, fuels will be optimized to meet specific performance requirements, thereby minimizing the need to repeatedly perform large-scale, integral experiments over a wide parametric range as a means of experimental exploration. Two significant initiatives are underway within AFC. First, a gap analysis completed in early FY 2019 identified critical irradiation testing needs that are lacking within the national light water reactor (LWR) fuels testbed since the shutdown of the Halden Reactor in 2018. The identified gaps are for instrumented, prototypic testing of LWR fuels, especially under boiling water reactor conditions, ramp conditions, and conditions leading to fuel failure; these needs exist for supporting current LWR fuels and their possible extension to higher burnups, but are especially urgent relative to near-term development and qualification of accident-tolerant fuels. Recommendations that resulted from the Halden Gap Analysis focused on enhancements at Advanced Test Reactor (ATR) and Transient Reactor Test Facility (TREAT) to fill gaps in testing capabilities relative to these needs. Second, a concerted effort to develop and demonstrate a systematic approach to accelerating the development, testing, and qualification of new fuel systems has been initiated. This is highlighted by a test strategy that combines the considerable advances in multiscale, mechanistic fuel modeling of recent years with a MiniFuel separate effects test program in the High Flux Isotope Reactor (HFIR) and a Fission Accelerated Steady-state Testing (FAST) semi-integral accelerated test program in ATR. This approach is being tested/demonstrated using the metallic fuel system, but if successful it is expected to be extensible to multiple fuel types and diverse applications. This document includes an overview of the NFCSC program, a definition of science-based development of nuclear fuels, near-term goals for Advanced LWR fuels (ALFs), and longer-term goals for Advanced Reactor Fuels (ARFs) RD&D. This includes the activities that will be conducted to achieve success toward the grand challenge, as well as the goals and milestones to be achieved over the next few decades of research and development. Long-term goals are based on the DOE Office of Nuclear Energ

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS2002

Initialization of Formation Flying Using Primer Vector Theory

In this paper, we extend primer vector analysis to formation flying. Optimization of the classical rendezvous or free-time transfer problem between two orbits using primer vector theory has been extensively studied for one spacecraft. However, an increasing number of missions are now considering flying a set of spacecraft in close formation. Missions such as the Magnetospheric MultiScale (MMS) and Leonardo-BRDF (Bidirectional Reflectance Distribution Function) need to determine strategies to transfer each spacecraft from the common launch orbit to their respective operational orbit. In addition, all the spacecraft must synchronize their states so that they achieve the same desired formation geometry over each orbit. This periodicity requirement imposes constraints on the boundary conditions that can be used for the primer vector algorithm. In this work we explore the impact of the periodicity requirement in optimizing each spacecraft transfer trajectory using primer vector theory. We first present our adaptation of primer vector theory to formation flying. Using this method, we then compute the AV budget for each spacecraft subject to different formation endpoint constraints.

Mailhe, Laurie↗

DOE OSTI2020

Towards improved speed and accuracy of laser powder bed fusion simulations via representation of multiple time scales

Here, we report the result of investigations into alternative representations of the temporal evolution of the laser powder bed fusion (LPBF) process. In order to provide the reader with sufficient context for the following discussion, the modeling challenge and its underlying cause, as well as current attempts to provide a satisfactory solution, will be discussed. Next, the author will describe two numerical methods (multirate time integration and parallel-in-time) to better represent the temporal scales of the problem. Finally, the results of applying these methods to a two-dimensional version of the heat transfer portion of the LPBF problem will be presented, reporting on both convergence and performance behavior, which indicate the possibility of significant speedup of solution calculations (40–100 times), along with well-characterized effects on solution accuracy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2020

Neural Network Repair of Lossy Compression Artifacts in the Sept 2015 – March 2016 Duration of the MMS/FPI Dataset

During the Sept 2015 –March 2016 duration (sometimes referred to as Phase 1A) of the Magnetospheric Multiscale Mission (MMS), the Dual Electron Spectrometers (DES) were configured to generously utilize lossy compression. While this maximized the number of velocity distribution functions downlinked, it cameat the expense of lost information content for a fractionof the frames. Following this period of lossy compression, the DES was re-configured in a way that allowed for 95% of the framesto arrive to the ground without loss. Using this high-quality set offrameson-orbit observations, we compressed and decompressed the frameson the ground to create a side-by-side record of the compression effect. This record was used to drive an optimization method that (a) derived basis functions capable of approximating the lossless sample space and with non-negative coefficients and (b) fitted a function which maps the lossy framesto basis weights that recreate the framewithout compression artifacts. This methodis introduced and evaluated in this paper.Data users should expect a higher level of confidence in the absolute scale of density/temperature measurements andnotice less sinusoidal bias in the velocity X and Y components(GSE).

Magnetosphere, Neural Networks, Image Processing, ↗

DOE OSTI2020

An extended/generalized phase-field finite element method for crack growth with global-local enrichment

In this paper, an extended/generalized finite element method (XFEM/GFEM) for simulating quasistatic crack growth based on a phase-field method is presented. The method relies on approximations to solutions associated with two different scales: a global scale, that is, structural and discretized with a coarse mesh, and a local scale encapsulating the fractured region, that is, discretized with a fine mesh. A stable XFEM/GFEM is employed to embed the displacement and damage fields at the global scale. The proposed method accommodates approximation spaces that evolve between load steps, while preserving a fixed background mesh for the structural problem. In addition, a prediction-correction algorithm is employed to facilitate the dynamic evolution of the confined crack regions within a load step. Several numerical examples of benchmark problems in two- and three-dimensional quasistatic fracture are provided to demonstrate the approach.

multiscale↗