Search NASA⌕ Search

SEARCH · Search NASA

Results for “simulation framework”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

EQSIM—A multidisciplinary framework for fault-to-structure earthquake simulations on exascale computers part I: Computational models and workflow

Computational simulations have become central to the seismic analysis and design of major infrastructure over the past several decades. Most major structures are now “proof tested” virtually through representative simulations of earthquake-induced response. More recently, with the advancement of high-performance computing (HPC) platforms and the associated massively parallel computational ecosystems, simulation is beginning to play a role in increased understanding and prediction of ground motions for earthquake hazard assessments. However, the computational requirements for regional-scale geophysics-based ground motion simulations are extreme, which has restricted the frequency resolution of direct simulations and limited the ability to perform the large number of simulations required to numerically explore the problem parametric space. In this article, recent developments toward an integrated, multidisciplinary earth science-engineering computational framework for the regional-scale simulation of both ground motions and resulting structural response are described with a particular emphasis on advancing simulations to frequencies relevant to engineered systems. This multidisciplinary computational development is being carried out as part of the US Department of Energy (DOE) Exascale Computing Project with the goal of achieving a computational framework poised to exploit emerging DOE exaflop computer platforms scheduled for the 2022–2023 timeframe.

58 GEOSCIENCES↗
DOE OSTI2023

The inclusion of uncertainty in circularity transition modeling: A case study on wind turbine blade end-of-life management

The transition to a more circular economy (CE) is complex and hard to predict, including in sustainable energy technologies. Many sources of uncertainty make it challenging to model CE scenarios and their potential benefits. As an example, the high variability in costs and revenues of different recycling options makes future wind turbine blade recycling highly uncertain. To better understand this challenge, the circular economy, life cycle assessment and visualization (CELAVI) framework - a discrete event simulation and life cycle assessment framework - is modified to incorporate uncertainty analysis capabilities. Moreover, a 3-step procedure that covers different aspects of uncertainty in CE studies and includes a Monte-Carlo analysis is proposed. The procedure is tested in a case study on wind turbine blade recycling using CELAVI. Results highlight that grinding and landfilling costs are the most influential parameters for wind power circularity. The model's output coefficients of variation (when input parameter uncertainties are propagated) are between 92% and 384% depending on the indicator. The approach developed in this study may help researchers and decision-makers who study circularity prioritize their data collection effort. Finally, our method contributes to a mounting yet critical body of research: the measurement of uncertainty in circularity transitions.

17 WIND ENERGY↗
DOE OSTI2017

BeamDyn: a high-fidelity wind turbine blade solver in the FAST modular framework

Here, this paper presents a numerical implementation of the geometrically exact beam theory based on the Legendre-spectral-finite-element (LSFE) method. The displacement-based geometrically exact beam theory is presented, and the special treatment of three-dimensional rotation parameters is reviewed. An LSFE is a high-order finite element with nodes located at the Gauss-Legendre-Lobatto points. These elements can be an order of magnitude more computationally efficient than low-order finite elements for a given accuracy level. The new module, BeamDyn, is implemented in the FAST modularization framework for dynamic simulation of highly flexible composite-material wind turbine blades within the FAST aeroelastic engineering model. The framework allows for fully interactive simulations of turbine blades in operating conditions. Numerical examples are provided to validate BeamDyn and examine the LSFE performance as well as the coupling algorithm in the FAST modularization framework. BeamDyn can also be used as a stand-alone high-fidelity beam tool.

17 WIND ENERGY↗
DOE OSTI2019

An Asynchronous Real-time Co-simulation Platform for Modeling Interaction between Microgrids and Power Distribution Systems

This paper presents the modeling framework of an asynchronous, real-time co-simulation platform for modeling the interactions between microgrids and power distribution systems. Components of each microgrid are simulated on the OPAL-RT eMEGASIM platform so that electromagnetic transients of the inverter units are modeled at a time step of 100 microseconds. The 3-phase unbalanced distribution feeder that microgrids are connected to is simulated by using the OPAL-RT ePHASORSIM so that load transients, capacitor switching, and tap-changing events can be modeled. A MATLAB-based microgrid controller will interface controllable microgrid components through the Modbus communication. This co-simulation framework allows different microgrid controller logic to be developed and tested on a hardware-in-the-loop testbed considering both the inverter-level transient and the dynamic response of loads and utility equipment. Because the controller communicates with controllable devices via actual communication links, the impact of communication errors, delays, or denial-of-service can also be properly quantified.

Xie, Fuhong↗
DOE OSTI2020

Capture and Decomposition of the Nerve Agent Simulant, DMCP, Using the Zeolitic Imidazolate Framework (ZIF-8)

Understanding mechanisms of decontamination of chemical warfare agents (CWA) is an area of intense research aimed at developing new filtration materials to protect soldiers and civilians in case of state-sponsored or terrorist attack. In this study, we employed complementary structural, chemical, and dynamic probes and in situ data collection, to elucidate the complex chemistry, capture, and decomposition of the CWA simulant, dimethyl chlorophosphonate (DMCP). Our work reveals key details of the reactive adsorption of DMCP and demonstrates the versatility of zeolitic imidazolate framework (ZIF-8) as a plausible material for CWA capture and decomposition. Here, the in situ synchrotron-based powder X-ray diffraction (PXRD) and pair distribution function (PDF) studies, combined with Fourier transform infrared (FT-IR) spectroscopy, X-ray photoelectron spectroscopy (XPS), zinc K-edge X-ray absorption near edge structure (XANES), and Raman spectroscopies, showed that the unique structure, chemical state, and topology of ZIF-8 enable accessibility, adsorption, and hydrolysis of DMCP into the pores and revealed the importance of linker chemistry and Zn 2+ sites for nerve agent decomposition. DMCP decontamination and decomposition product(s) formation were observed by thermogravimetric analysis, FT-IR spectroscopy, and phosphorus (P) K-edge XANES studies. Differential PDF analysis indicated that the average structure of ZIF-8 (at the 30 Å scale) remains unchanged after DMCP dosing and provided information on the dynamics of interactions of DMCP with the ZIF-8 framework. Using in situ PXRD and diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), we showed that nearly 90% regeneration of the ZIF-8 structure and complete liberation of DMCP and decomposition products occur upon heating.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Standard Modular Architecture for Consumer End Plug and Play Interfaces

The growth in load and generation sources at the edge of the grid is driving the innovation in power electronic (PE) grid interfaces at the consumer end to improve the grid resiliency, reliability, security, and cost of the future infrastructure. Novel PE technologies are key enablers for the future grid infrastructure to handle the issues that arise because of the projected growth. This paper introduces a novel fundamental building block (FBB) architecture with plug-and play features. An example framework that enables co-ordination of multiple FBBs hierarchically to provide various grid functions is also presented. The FBBs are designed to be equipped with advanced features like online health monitoring, embedded intelligence, and decision-making capability for enhancing the metrics of consumer end plug and play interfaces. The paper elaborates on the proposed architecture and the developed framework i.e., the controls, communication, protection, and the corresponding timing requirements for the building blocks. The architecture and the framework have been validated through simulations and the communication framework has been validated with a control hardware in the loop platform.

Chinthavali, Madhu Sudhan↗
DOE OSTI2023

Meshing, Language Server Protocol, and other User-Oriented MOOSE Framework Improvements to Enhance Reactor Analysis Capabilities and Workflows

The open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) framework underpins most of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) physics applications and coupling methods. Users interact with MOOSE in multiple ways to enable the construction of complex multiphysics models, including but not limited to compilation, input creation and syntax validation, meshing, solving the physics problem via MOOSE-based solvers and coupling, and output inspection. In FY23, numerous enhancements have been made to MOOSE to enhance the user experience. Reactor-oriented meshing capabilities in MOOSE have been expanded, an online tutorial was created and hosted on the MOOSE site, and a hands-on workshop was held for more than 100 users. The Language Server Protocol (LSP) capability has been implemented in MOOSE to better communicate correct syntax to the NEAMS Workbench user interface which is commonly used to validate input and submit jobs by users. Finally, several other user-facing improvements were made including the implementation of improved screen output and logging control, enhancements to the initial condition system, and enhancements of the MultiApp system commonly used for coupling. Collectively, these enhancements were driven by user needs and directly improve user ability to construct complex multiphysics models for nuclear reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Desalination metamodels and a framework for cross-comparative performance simulations

There is an opportunity to save energy and reduce operational expenses when choosing a suitable desalination method aided by computational modeling. Existing models are not conducive to generalized comparisons between different desalination methods. Therefore, the work in this study developed metamodels for six desalination methods, grouped them into thermal and molecular transport families, and validated their predictive performance within 9% difference from published data. This validated framework allowed comparisons of desalination methods at their prescribed ranges of operational conditions that they were designed for. These conditions specify feed salinity ranges of 1.6 to 2.4 g/kg for Capacitive Deionization and Reverse Osmosis (RO), 2.8 to 4.2 g/kg for Electrodialysis, 28 to 42 g/kg for Thermovapor Compression and Humidification-Dehumidification, and 37 to 55 g/kg for Multi-Effect Distillation (MED). Despite different operational conditions, all models exhibit non-linear, positive correlation between energy consumption and system size in response to feed salinity and production rate. The framework is also employed in a cross-comparative analysis between MED and RO whose results suggest that energy intensity for MED is an order of magnitude greater than RO for the same operational conditions, but actual operational costs are comparable. Overall, the framework is ready for deployment in case studies of actual desalination plants.

42 ENGINEERING↗
DOE OSTI2024

Fast and Flexible Inference Framework for Continuum Reverberation Mapping Using Simulation-based Inference with Deep Learning

Continuum reverberation mapping (CRM) of active galactic nuclei (AGN) monitors multiwavelength variability signatures to constrain accretion disk structure and supermassive black hole (SMBH) properties. The upcoming Vera Rubin Observatory’s Legacy Survey of Space and Time will survey tens of millions of AGN over the next decade, with thousands of AGN monitored with almost daily cadence in the deep drilling fields. However, existing CRM methodologies often require long computation time and are not designed to handle such large amounts of data. In this paper, we present a fast and flexible inference framework for CRM using simulation-based inference (SBI) with deep learning to estimate SMBH properties from AGN light curves. We use a long short-term memory summary network to reduce the high dimensionality of the light curve data and then use a neural density estimator to estimate the posterior of SMBH parameters. Using simulated light curves, we find SBI can produce more accurate SMBH parameter estimation with 10 3 –10 5 times speed up in inference efficiency compared to traditional methods. The SBI framework is particularly suitable for wide-field CRM surveys as the light curves will have identical observing patterns, which can be incorporated into the SBI simulation. We explore the performance of our SBI model on light curves with irregular-sampled, realistic observing cadence and alternative variability characteristics to demonstrate the flexibility and limitation of the SBI framework.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Using Machine Learning to Generate a GISS ModelE Calibrated Physics Ensemble (CPE)

A neural network (NN) surrogate of the NASA GISS ModelE atmosphere (version E3) is trained on a perturbed parameter ensemble (PPE) spanning 45 physics parameters and 36 outputs. The NN is leveraged in a Markov Chain Monte Carlo (MCMC) Bayesian parameter inference framework to generate a second posterior constrained ensemble coined a “calibrated physics ensemble,” or CPE. The CPE members are characterized by diverse parameter combinations and are, by definition, close to top-of-atmosphere radiative balance, and must broadly agree with numerous hydrologic, energy cycle and radiative forcing metrics simultaneously. Global observations of numerous cloud, environment, and radiation properties (provided by global satellite products) are crucial for CPE generation. The inference framework explicitly accounts for discrepancies (or biases) in satellite products during CPE generation. We demonstrate that product discrepancies strongly impact calibration of important model parameter settings (e.g., convective plume entrainment rates; fall speed for cloud ice). Structural improvements new to E3 are retained across CPE members (e.g., stratocumulus simulation). Notably, the framework improved the simulation of shallow cumulus and Amazon rainfall while not degrading radiation fields, an upgrade that neither default parameters nor Latin Hypercube parameter searching achieved. Analyses of the initial PPE suggested several parameters were unimportant for output variation. However, many “unimportant” parameters were needed for CPE generation, a result that brings to the forefront how parameter importance should be determined in PPEs. From the CPE, two diverse 45-dimensional parameter configurations are retained to generate radiatively-balanced, auto-tuned atmospheres that were used in two E3 submissions to CMIP6.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Micro–macro finite element modeling method for rub response in abradable coating materials

Gas turbine engines experience “rub” when the rotating blades come in contact with a static abradable coating. This results in extreme strain rates and dynamics inside a high-temperature/high-pressure environment. Current rub models are phenomenological and do not reflect the underlying microstructures, thus limiting their prediction accuracy. In this work, a microstructure-informed, reduced order modeling framework is introduced for simulating abradable coating “rub" behavior. This framework comprises a microscale model constructed based on digitized abradable microstructure and explicitly simulates the mechanical behavior of each constituent phases and their interactions. After calibration and validation with experiment data, the calibrated microscale model is used to generate data across a vast range of applied strain rates and temperature with various load paths. Then, the virtually generated data are used to fit the macroscopic-reduced order model, which enables fast component scale rub simulation without compromising the integrity of the complex material behavior. In conclusion, the proposed effort will address the technical challenge of predicting abradable material behavior during rub through the application of multiscale modeling from microstructure to engines behavior, effectively reducing the development costs and time of new abradable material for better “rub” properties.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Understanding Pore Filling Processes and Adsorption/Desorption Hysteresis in Nanoporous Metal–Organic Frameworks: Insights from Grand Canonical Monte Carlo Simulations and Free Energy Calculations

Grand canonical Monte Carlo (GCMC) simulations were used to investigate pore filling and hysteresis in nanoporous metal-organic frameworks (MOFs). Adsorption and desorption isotherms were calculated for argon at 87 K in 1866 MOFs from the CoRE MOF database and for short n-alkanes in selected MOFs, keeping the adsorbent structure rigid. Analysis of the molecular configurations showed two different mechanisms and origins of hysteresis: one involving a transition of the adsorbate arrangement in the pores similar to a gas-to-liquid transition associated with a large change in the loading and one more similar to a liquid-to-solid transition associated with a relatively small change in the loading. Our GCMC simulations in MOFs with diverse pore topologies indicate exceptions to an empirical relationship for the minimum diameter of a cylindical pore required for hysteresis as a function of the adsorbate diameter and reduced temperature. The simulations reveal some structures where isotherms exhibit two steps in the adsorption branch and only one step in the desorption branch. Hysteresis loops with a different number of adsorption and desorption steps are not common. Here, to better understand why hysteresis is observed in the GCMC simulations, the concept of the transition probability for observing a step in the adsorption isotherm at a given pressure in a GCMC simulation is introduced. We used two different methods to calculate the transition probabilities and find that these yield comparable results. Furthermore, the transition probability provides a measure for the length of GCMC simulations to yield reliable results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

PRISMS-Fatigue computational framework for fatigue analysis in polycrystalline metals and alloys

Abstract The PRISMS-Fatigue open-source framework for simulation-based analysis of microstructural influences on fatigue resistance for polycrystalline metals and alloys is presented here. The framework uses the crystal plasticity finite element method as its microstructure analysis tool and provides a highly efficient, scalable, flexible, and easy-to-use ICME community platform. The PRISMS-Fatigue framework is linked to different open-source software to instantiate microstructures, compute the material response, and assess fatigue indicator parameters. The performance of PRISMS-Fatigue is benchmarked against a similar framework implemented using ABAQUS. Results indicate that the multilevel parallelism scheme of PRISMS-Fatigue is more efficient and scalable than ABAQUS for large-scale fatigue simulations. The performance and flexibility of this framework is demonstrated with various examples that assess the driving force for fatigue crack formation of microstructures with different crystallographic textures, grain morphologies, and grain numbers, and under different multiaxial strain states, strain magnitudes, and boundary conditions.

Chemistry↗
DOE OSTI2025

Multiscale Modeling Framework Using Element‐Based Galerkin Methods for Moist Atmospheric Limited‐Area Simulations

This paper presents a multiscale modeling framework (MMF) to model moist atmospheric limited-area weather. The MMF resolves large-scale convection using a coarse grid while simultaneously resolving local features through numerous fine local grids and coupling them seamlessly. Both large- and small-scale processes are modeled using the compressible Navier-Stokes equations within the Nonhydrostatic Unified Model of the Atmosphere (NUMA), and are discretized using a continuous element-based Galerkin method (spectral elements) with high-order basis functions. Consequently, the large-scale and small-scale models share the same dynamical core but have the flexibility to be adjusted individually. The proposed MMF method is tested in 2D and 3D idealized limited-area weather problems involving storm clouds produced by squall line and supercell simulations. Numerical results from the MMF showed enhanced representation of cloud processes compared to the coarse model.

Kang, Soonpil [Naval Postgraduate School, Monterey↗
DOE OSTI2026

Beam-beam backgrounds for the Cool Copper Collider

In this paper, we present a comprehensive characterization of beam-beam backgrounds for the Cool Copper Collider (C 3 ), a proposed linear e + e - collider designed for precision Higgs studies at center-of-mass energies of 250 and 550 GeV. Using a simulation pipeline based on the Key4hep framework, we evaluate incoherent pair production and hadron photoproduction backgrounds through the SiD detector for baseline, power-efficiency, and high-luminosity C 3 operating scenarios. The occupancy induced by the beam-beam background is evaluated for each scenario, validating the compatibility of the existing SiD detector design with operations at C 3 without substantial modifications. Furthermore, at the same time, the modular simulation framework and analysis methodology presented in this paper offer a versatile toolkit for background studies in future collider proposals, contributing to a common platform for different machine designs.

Analysis and statistical methods↗
DOE OSTI2025

Butterfly valve performance factors using the multiphysics object oriented simulation environment

Butterfly valves are typically used in nuclear reactors to control incompressible fluid flow with high inlet velocities. Performance factors for butterfly valves include the pressure drop across the valve and the loss coefficient from which hydrodynamic torque and flow coefficients can be computed. This work explores a computational fluid dynamics approach for butterfly valve performance factors using the open-source Multiphysics Object Oriented Simulation Environment (MOOSE) framework. While MOOSE is often used in the nuclear energy modeling and simulation community for simulations ranging from fuel characterization to heat pipe simulation, this work employs the MOOSE open-source Navier–Stokes solver capability for simulating butterfly valve performance factors and compares those to experimentally measured results from the Advanced Test Reactor at Idaho National Laboratory at Reynolds numbers in the order of 10 6 for the partially opened configuration. The MOOSE framework results are compared against experimentally measured butterfly valve performance factors across five valve opening angles using meshes with order 10 4 – 10 5 elements. This validation serves to enable MOOSE-based multiphysics simulations incorporating the open-source Navier–Stokes module.

97 - MATHEMATICS AND COMPUTING↗