Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “computer simulation”

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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Transferability of data-driven, many-body models for CO 2 simulations in the vapor and liquid phases

Here, extending on the previous work by Riera et al. [J. Chem. Theory Comput. 16, 2246–2257 (2020)], we introduce a second generation family of data-driven many-body MB-nrg models for CO 2 and systematically assess how the strength and anisotropy of the CO 2 –CO 2 interactions affect the models’ ability to predict vapor, liquid, and vapor–liquid equilibrium properties. Building upon the many-body expansion formalism, we construct a series of MB-nrg models by fitting one-body and two-body reference energies calculated at the coupled cluster level of theory for large monomer and dimer training sets. Advancing from the first generation models, we employ the charge model 5 scheme to determine the atomic charges and systematically scale the two-body energies to obtain more accurate descriptions of vapor, liquid, and vapor–liquid equilibrium properties. Challenges in model construction arise due to the anisotropic nature and small magnitude of the interaction energies in CO 2 , calling for the necessity of highly accurate descriptions of the multidimensional energy landscape of liquid CO 2 . These findings emphasize the key role played by the training set quality in the development of transferable, data-driven models, which, accurately representing high-dimensional many-body effects, can enable predictive computer simulations of molecular fluids across the entire phase diagram.

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

Potential design problems for ITER fusion device

The international thermonuclear experimental reactor (ITER) is a worldwide project currently being built in France for the demonstration of the feasibility of thermonuclear technologies for future realization of successful commercial fusion energy. ITER is of the tokamak based design using strong magnetic fields to confine the very hot plasma needed to induce the fusion reaction. Tokamak devices are currently the front leading designs. Building a successful magnetic fusion device for energy production is of great challenge. A key obstacle to such design is the performance during abnormal events including plasma disruptions and so-called edge-localized modes (ELMs). In these events, a massive and sudden release of energy occurs quickly, due to loss of full or partial plasma confinement, leading to very high transient power loads on the reactor surface boundaries. A successful reactor design should tolerate several of these transient events without serious damages such as melting and vaporization of the structure. This paper highlights, through comprehensive state-of-the-art computer simulation of the entire ITER interior design during such transient events, e.g., ELMs occurring at normal operation and disruptions during abnormal operation, potential serious problems with current plasma facing components (PFCs) design. The HEIGHTS computer package is used in these simulations. The ITER reactor design was simulated in full and exact 3D geometry including all known relevant physical processes involved during these transient events. The current ITER divertor design may not work properly and may requires significant modifications or new innovative design to prevent serious damage and to ensure successful operation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

A Scalable Reduced‐Order Model for the Steady Navier–Stokes Equations

Scaling up new scientific technologies from laboratory to industry often involves demonstrating performance on a larger scale. Computer simulations can accelerate design and predictions in the deployment process, though traditional numerical methods are computationally intractable even for intermediate pilot plant scales. Recently, the component reduced order modeling method has been developed to tackle this challenge by combining projection reduced order modeling and discontinuous Galerkin domain decomposition. However, while many scientific or engineering applications involve nonlinear physics, this method has only been demonstrated for various linear systems. In this work, the component reduced order modeling method is extended to steady Navier–Stokes flow, with application to general nonlinear physics in view. The large‐scale, global domain is decomposed into a combination of small‐scale unit component. Linear subspaces for flow velocity and pressure are identified via proper orthogonal decomposition over sample snapshots collected from each small‐scale unit component. Velocity bases are augmented with a pressure supremizer to satisfy the inf–sup condition for stable pressure prediction. Two different nonlinear reduced order modeling methods are employed and compared for efficient evaluation of nonlinear advection: A third‐order tensor projection operator and the empirical quadrature procedure. The proposed method is demonstrated on the flow over arrays of five different unit objects, achieving a 23‐fold speedup with less than 4% relative error in domains up to 256 times larger than the unit components. Furthermore, a numerical experiment with the pressure supremizer strongly indicates the need for a supremizer for stable pressure prediction. A comparison between the tensorial approach and the empirical quadrature procedure revealed a slight advantage of the empirical quadrature procedure. The framework is compared with an alternating Schwarz‐based reduced‐order approach, demonstrating improved efficiency and robustness for the DG‐based global solver while retaining flexibility for sub‐scale iterative solvers. The method is further extended to a coupled advection–diffusion and Navier–Stokes system, illustrating its applicability to multi‐physics problems and its potential for more general, inter‐coupled nonlinear systems.

42 ENGINEERING↗
DOE OSTI2021

RKKY coupled local-moment magnetism in NaFe 1 – x Cu x As

A central question in a large class of strongly correlated electron systems, including heavy fermion compounds and iron pnictides, is the identification of different phases and their origins. It has been shown that the antiferromagnetic (AFM) phase in some heavy fermion compounds is induced by Ruderman-Kittel-Kasuya-Yosida (RKKY) interaction between localized moments, and that the competition between this interaction and Kondo effect is responsible for quantum criticality. However, conclusive experimental evidence of the RKKY interaction in pnictides is lacking. Here, using high resolution 23 Na NMR measurements on lightly Cu-doped metallic single crystals of NaFe 1–x Cu x As (x ≈ 0.01) and numerical simulation, we show direct evidence of the RKKY interaction in this pnictide system. Aided by computer simulation, we identify the 23 Na NMR satellite resonances with the RKKY oscillations of spin polarization at Fe sites. Our 23 Na spin-lattice and spin-spin relaxation data exhibit a signature of an itinerant and inhomogeneous AFM phase in this system, accompanied by a simulation of Cu-induced perturbation to the ordered moments on the Fe sites. Our NMR results indicate coexistence of local and itinerant magnetism in lightly Cu-doped NaFe 1–x Cux As.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Elimination LArTPC Simulation Uncertainty

Liquid Argon Time Projection Chambers (LArTPC) are essential for detecting muons and neutrinos by capturing electrons released during particle collisions, which drift toward wire planes under an electric field and induce currents measured to reconstruct particle paths. However, LArTPCs face challenges from effects such as electron-ion recombination, electron diffusion, and electron attenuation, complicating data simulation. The Short Baseline Neutrino (SNB) detector aims to measure neutrinos before oscillation occurs. To bridge the gap between simulation and actual data, we propose modifying the amplitude and width of signals on the TPC wires, addressing uncertainties by adjusting signal characteristics to better match observed data. A Gaussian fit to current waveforms produces hits with associated charge and width, and by comparing data and simulated values, discrepancies highlight areas where the model fails. Initial results indicate the current modification algorithm may increase divergence between simulation and data, necessitating further refinement. A discovered bug in the WireModMakeHist_plug.cpp file, which incorrectly computed simulation and data ratios, underscores the need for precise algorithm adjustments. Future work involves correcting code errors, fine-tuning the model, and conducting multiple simulation runs to enhance statistical confidence and reduce uncertainties, ultimately aiming for accurate LArTPC operation and reliable neutrino detection.

Mkrtchyan, Ka'ren↗
DOE OSTI2023

Generic EMT Modeling for IBR

In support of IEEE P2800.2, PNNL is developing an informative annex about “Generic EMT Modeling for IBR”. A literature review has been conducted, covering an IEEE Task Force, Cigre Working Group, IEEE standards, NERC reports, and research articles. In addition, the vendors of widely used simulation tools have been contacted to verify the availability of real-code models of inverters. Illustrative computer simulations will be conducted, once real-code models become accessible. If the simulation results of a real-code model are obtained, a comparative study will be performed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

High resolution numerical simulations of methane pool fires using adaptive mesh refinement

The ability to accurately predict the structure and dynamics of pool fires using computational simulations is of great interest in a wide variety of applications, including accidental and wildland fires. However, the presence of physical processes spanning a broad range of spatial and temporal scales poses a significant challenge for simulations of such fires, particularly at conditions near the transition between laminar and turbulent flow. Here, in this study, we examine the transition to turbulence in methane pool fires using high-resolution simulations with multi-step finite rate chemistry, where adaptive mesh refinement (AMR) is used to directly resolve small-scale flow phenomena. We perform three simulations of methane pool fires, each with increasing diameter, corresponding to increasing inlet Reynolds and Richardson numbers. As the diameter increases, the flow transitions from organized vortex roll-up via the puffing instability to much more chaotic mixing associated with finger formation along the shear layer and core collapse near the inlet. These effects combine to create additional mixing close to the inlet, thereby enhancing fuel consumption and causing more rapid acceleration of the fluid above the pool. We also make comparisons between the transition to turbulence and core collapse in the present pool fires and in inert helium plumes, which are often used as surrogates for the study of buoyant reacting flows.

42 ENGINEERING↗
DOE OSTI2021

Cognitive simulation models for inertial confinement fusion: Combining simulation and experimental data

The design space for inertial confinement fusion (ICF) experiments is vast, and experiments are extremely expensive. Researchers rely heavily on computer simulations to explore the design space in search of high-performing implosions. However, ICF multiphysics codes must make simplifying assumptions, and thus deviate from experimental measurements for complex implosions. For more effective design and investigation, simulations require input from past experimental data to better predict future performance. In this work, we describe a cognitive simulation method for combining simulation and experimental data into a common, predictive model. This method leverages a machine learning technique called “transfer learning,” the process of taking a model trained to solve one task, and partially retraining it on a sparse dataset to solve a different, but related task. In the context of ICF design, neural network models are trained on large simulation databases and partially retrained on experimental data, producing models that are far more accurate than simulations alone. Here, we demonstrate improved model performance for a range of ICF experiments at the National Ignition Facility and predict the outcome of recent experiments with less than 10% error for several key observables. We discuss how the methods might be used to carry out a data-driven experimental campaign to optimize performance, illustrating the key product—models that become increasingly accurate as data are acquired.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Multilevel Techniques for Compression and Reduction of Scientific Data---The Unstructured Case

Previous work on multilevel techniques for compression and reduction of scientific data is extended to the case of data given on unstructured meshes in two and three dimensions. The centerpiece of the work is a decomposition algorithm which is shown to be optimal, in terms of both storage and operational complexity, applicable to unstructured grids in both two and three dimensions, and which implicitly gives a Riesz basis that can be exploited to reduce the data while maintaining rigorous bounds on the loss incurred. The flexibility of the approach is illustrated by applications to potential flow around an airfoil and the effect of compression on quantities of interest relevant to airfoil design; compression of computational simulation of a nonlinear reaction-diffusion system with special attention given to the problem of time series reduction; and, data from a simulation of magnetically confined plasma in a fusion reactor reduced so as to preserve the electric field computed from the data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Chapter 18: Learning and Tracking Ad Hoc Fiducial Markers in Spatial Augmented Reality

We describe a spatial augmented reality system with a tangible user interface used to control computer simulations of complex systems. In spatial augmented reality, the user’s physical space is augmented with projected imagery, blending real objects with projected information, and a tangible user interface enables users to manipulate physical objects as controllers for interactive visualizations. Our system learns ad hoc objects in the user’s environment as fiducial markers (i.e., objects that are visually recognized and tracked). When combined with simulation and visualization tools, these interfaces allow the user to control simulations or ensembles of simulations via physical objects using apt metaphors. While other research has leveraged the use of depth cameras, our system enables the use of standard cameras in readily available smartphones and webcams and has an implementation that runs completely in JavaScript in the web browser. We discuss the prerequisite object-recognition requirements for such tangible user interfaces and describe computer-vision and machine-learning algorithms meeting those requirements. We conclude by presenting example applications, which are also available online.

energy distribution↗
DOE OSTI2022

Evaluation of Physical Security Risk for Potential Implementation of FLEX using Dynamic Simulation Methods

The requirements for United States nuclear power plants to maintain a large onsite physical security force contribute to their large operational costs. The cost of maintaining the current physical security posture is approximately 10% of the overall operation and maintenance budget for commercial nuclear power plants. The goal of the Light Water Reactor Sustainability Program Physical Security Pathway is to develop tools, methods, and technologies and provide the technical basis for an optimized physical security posture. This pathway will analyze and minimize the conservatisms built into current security postures in order to reduce security costs while still ensuring adequate security and operational safety. The research performed at Idaho National Laboratory within this pathway has successfully developed a dynamic force-on-force (FOF) modeling framework using various computer simulation tools and integrated them with the dynamic assessment Event Modeling Risk Assessment using Linked Diagrams (EMRALD) tool. This document provides an overview of lessons learned in applying a dynamic computational framework that links results from a commercially available FOF simulation tool, a commercially available thermal-hydraulic tool, and EMRALD to an operating commercial nuclear power plant. This process of including plant procedures and multiple analysis results is being called Modeling and Analysis for Safety Security using Dynamic EMRALD Framework. Previous reports described how a user could integrate their plant-specific FOF models with the dynamic simulation tool EMRALD, model operator actions, integrate with probabilistic risk assessment tools, such as Computer Aided Fault Tree Analysis System or Systems Analysis Programs for Hands-on Integrated Reliability Evaluations, and with thermal-hydraulic tools, such as RELAP-5. Previous reports applied various combinations of available simulations codes with EMRALD using generic plant models to demonstrate how to perform the analysis. This report documents the results of applying the dynamic computational framework to an actual nuclear facility using their security scenarios and timelines. The purpose of this study was to verify that results achieved using generic models are similar to actual plant results and to refine our guidance of the use of the framework. Such an assessment enables further analysis, such as what-if scenarios and staff-reduction evaluation, thereby optimizing physical security at plants. NOTE: The work performed in this report is based on a generic EMRALD model with actual plant data used for the analysis. However, only the generic model and general results of the analysis are in the report. No plant’s sensitive information is discussed in this report. The discussion shows examples of insights that can be obtained from the MASS-DEF methodology.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

SECURED: Simulator-Enhanced Control and Understanding of Reactor systems for cyber-Event Defense

The study discusses a learning approach for analyzing cyber-events in reactor systems using integrated hardware and personal computer simulator models. Key points include the rise in cyber-attacks and their sophistication in industrial control systems (ICS), the necessity for awareness, understanding, resource allocation, and preparation to combat these threats, and the digital transformation of old and new nuclear plants, increasing their exposure to cyber threats. It highlights the cyber vulnerabilities of advanced reactor systems, which rely on digital instrumentation and control for operations and safety functions, making them susceptible to cyber-attacks. The approach involves demonstrating reactor system plant ICS cyber-attacks under various operational conditions utilizing tools like simulator models and hardware-based kits. A strategic solution approach tailored to critical infrastructure is emphasized, along with community engagement for public and government support, adopting effective learning approaches, and the preparation for anticipated future challenges. The presentation concludes with a call to action to address challenges, leverage opportunities, and advance through lesson learning in cybersecurity for nuclear energy systems.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

A Computational Framework for Simulations of Dissipative Nonadiabatic Dynamics on Hybrid Oscillator-Qubit Quantum Devices

Here, we introduce a computational framework for simulating nonadiabatic vibronic dynamics on circuit quantum electrodynamics (cQED) platforms. Our approach leverages hybrid oscillator-qubit quantum hardware with midcircuit measurements and resets, enabling the incorporation of environmental effects such as dissipation and dephasing. To demonstrate its capabilities, we simulate energy transfer dynamics in a triad model of photosynthetic chromophores inspired by natural antenna systems. We specifically investigate the role of dissipation during the relaxation dynamics following photoexcitation, where electronic transitions are coupled to the evolution of quantum vibrational modes. Our results indicate that hybrid oscillator-qubit devices, operating with noise levels below the intrinsic dissipation rates of typical molecular antenna systems, can achieve the simulation fidelity required for practical computations on near-term and early fault-tolerant quantum computing platforms.

Hamiltonians↗
DOE OSTI2021

Discussion on molecular dynamics (MD) simulations of the asphalt materials

The application of asphalt materials in pavement engineering has been increasingly widespread and sophisticated over the past several decades. Variations in the properties of asphalt binder during mixing, transportation, and paving can affect the performance of asphalt pavement. However, the asphalt material is a non-homogeneous and complex organic substance, consisting of various molecules with widely various molecular weights, elemental compositions, and structures. This complexity leads to difficulties for researchers to clearly and immediately understand the properties of asphalt materials and their variations. The multi-scale research approach combines macroscopic experimental data and microscopic simulation results from a practical engineering perspective. It helps to improve the understanding of asphalt materials. The molecular dynamics (MD) simulation proposes a corresponding molecular model of asphalt material based on experimental data, and the simulation algorithm is able to derive properties similar to those of real asphalt. Here, this paper provides a comprehensive review of the current studies on MD simulation of asphalt materials, including modeling, properties, and multi-scale analysis. As a key part of the computational simulation, this paper discusses the typical asphalt binder and asphalt-aggregate interface models constructed by different groups, and also presents their differences from real samples and their feasibility based on fundamental properties. After the introduction of molecular models, the extensive work made by researchers based on molecular models is categorically reviewed and discussed. The strengths and weaknesses of MD simulation methods in the study of asphalt materials are also summarized in order to provide the reader with a more comprehensive understanding of the relevant contents and to guide subsequent research.

36 MATERIALS SCIENCE↗
DOE OSTI2023

(Project 18-15502) Reducing Uncertainty in Radionuclide Transport Prediction Using Multiple Environmental Tracers (Final Report)

In order to successfully site and design a nuclear waste disposal facility, DOE scientists are required to show safe containment of the radioactive waste for up to 1 million years. A significant hurdle to accurately and convincingly demonstrating disposal safety is predicting the fate of radioactive elements once they enter the groundwater system surrounding the repository. These predictions are often made with computer models, which contain accurate physics of groundwater movement and chemical reactions that occur during groundwater flow. As computer power increases, the physics and chemistry of these computer simulators can become more and more realistic and the physically based error decreases. However, the ability of these computer models to provide accurate predictions in a specific place, over long time periods, requires the scientists and engineers to know the subsurface properties of the Earth that control groundwater movement. In particular, groundwater scientists and engineers need to know the groundwater fluid velocity, which can change over time and strongly vary with location within the groundwater system. Because the Earth’s subsurface cannot be directly seen, and can only be sampled at drilling locations, the properties of the groundwater system are never known completely, and computer models of groundwater transport will always have some amount of uncertainty. This project’s principal goal was to use chemicals and isotope “tracers”, which have been introduced to the groundwater system by natural processes over long time periods, to help inform computer models of the groundwater velocity and subsurface properties. The goal was to calculate how much better predictions of groundwater transport were when these “tracers” were used to inform the computer models.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Novel Relativistic Electronic Structure Theories for Actinide-Containing Compounds

Actinides of importance to basic energy sciences contain electrons moving at speed comparable to the speed of light. Reliable computational simulation of these electrons and hence actinide chemistry requires accurate description of relativistic effects. The present project advances computational actinide chemistry with development of new methodologies, algorithms, and computer programs in relativistic quantum chemistry, as well as applications to actinide chemistry and spectroscopy. A new “electrons-only” exact two-component approach has been developed to provide efficient treatments of relativistic effects, while maintaining chemical accuracy. New computational algorithms developed here extend the applicability of relativistic electron-correlation methods to larger molecules. The method-development work in this project also features the first implementation of analytic gradient technique for relativistic electron-correlation methods, which provides significantly enhanced ability to compute properties for molecules containing actinides. The applicability and usefulness of these new methods and computer programs have been demonstrated in calculations of actinide-containing molecules to facilitate understanding of actinide chemistry and spectroscopy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

The ENDF/B Nuclear Data Library and Its Impact on Reactor Simulations

The ENDF/B library, which is developed, maintained, and distributed by the Cross Section Evaluation Working Group, is the main source of nuclear data for analyses and computational simulations in nuclear applications, like different nuclear reactors concepts, radiation shielding, medical applications, astrophysics, etc. The library is constantly being improved and updated, with each release bringing an optimal representation of nuclear interactions as they are understood in their time. The most recent release, ENDF/B-VIII.1, represents a significant improvement in terms of the performance and consistency of the measured differential data relative to previous versions, as it combines the most recent experimental differential data and advanced theoretical nuclear models. As one of the many highlights, ENDF/B-VIII.1 restores a high-burnup depletion performance, comparable to ENDF/B-VII.1, that had been degraded in ENDF/B-VIII.0, while further improving the performance in criticality benchmarks, such as those in the Mosteller’s suite. Additionally noteworthy is the improved performance of ENDF/B-VIII.1 in radiation shielding and thick-target leakage spectrum integral experiments, which are also important for fusion and reactor applications. In this work we present in a very summarized way the main updates implemented in the ENDF/B-VIII.1 release and its main impacts, and also begin to delineate the path forward as to what to expect in the future for the next ENDF/B release, which, based on the timeline of the past few releases, is estimated to happen around 5 years from now. We emphasize that the ENDF/B-VIII.1 release was the product of an enormous collaborative effort among many authors and that for a complete detailed picture, the reader is strongly encouraged to refer to the article accompanying the release, which is currently in the publication process, but available as preprint [G. P. A. Nobre et al. arXiv Preprint arXiv: 2511.03564 (2025)].

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Hybrid Quantum Mechanical, Molecular Mechanical, and Machine Learning Potential for Computing Aqueous-Phase Adsorption Free Energies on Metal Surfaces

Performing reliable computer simulations of elementary processes occurring at metal–water interfaces is pivotal for novel catalyst design in sustainable energy applications. Computational catalyst design hinges on the ability to reliably and efficiently compute the potential energy surface (PES) of the system. Here, due to the large system sizes needed for studying processes at liquid water–metal interfaces, these systems can currently not be described using density functional theory (DFT). In this work, we used a hybrid quantum mechanical, molecular mechanical, and machine learning potential for studying the adsorption behavior of phenol, atomic hydrogen, 2-butanol, and 2-butanone on the (0001) facet of Ru under reducing conditions when Ru is not oxidized. Specifically, we describe the adsorbate and the surrounding metal atoms at the DFT level of theory. Here, we also considered the electrostatic field effect of the water molecules on adsorbate–metal interactions. Next, for the water–water and water–adsorbate interactions, we used established classical force fields. Finally, for the water–Ru surface interaction, for which no reliable force fields have been published, we used Behler–Parrinello high-dimensional neural network potentials (HDNNPs). Employing this setup, we used our explicit solvation for metal surface (eSMS) approach to compute the aqueous-phase effect on the low-coverage adsorption of selected molecules and atoms on the (0001) facet of Ru. In agreement with previous experimental and computational studies of oxygenated molecules over transition metal facets, we found that liquid water destabilizes the tested adsorbates on Ru(0001). Interestingly, our findings indicate that adsorbates on Ru are less affected by the presence of an aqueous phase than on other transition metals (e.g., Pt), highlighting the necessity of experimental investigations of Ru-based catalytic systems in liquid water.

Adsorption↗