Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Simulations”

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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Influence of Wetting on Viscous Fingering Via 2D Lattice Boltzmann Simulations

We present simulations of two-phase flow using the Rothman and Keller colour gradient Lattice Boltzmann method to study viscous fingering when a “red fluid” invades a porous model initially filled with a “blue” fluid with different viscosity. We conducted eleven suites of 81 numerical experiments totalling 891 simulations, where each suite had a different random realization of the porous model and spanned viscosity ratios in the range $$M\in [0.01,100]$$ M ϵ [ 0.01 , 100 ] and wetting angles in the range $$\theta _w\in [180^\circ ,0^\circ ]$$ θ w ϵ [ 180 ° , 0 ° ] to allow us to study the effect of these parameters on the fluid-displacement morphology and saturation at breakthrough (sweep). Although sweep often increased with wettability, this was not always so and the sweep phase space landscape, defined as the difference in saturation at a given wetting angle relative to saturation for the non-wetting case, had hills, ridges and valleys. At low viscosity ratios, flow at breakthrough is localized through narrow fingers that span the model. After breakthrough, the flow field continues to evolve and the saturation continues to increase albeit at a reduced rate, and eventually exceeds 90% for both non-wetting and wetting cases. The existence of a complicated sweep phase space at breakthrough, and continued post-breakthrough evolution suggests the hydrodynamics and sweep is a complicated function of wetting angle, viscosity ratio and time, which has major potential implications to Enhanced Oil Recovery by water flooding, and hence, on estimates of global oil reserves. Validation of these results via experiments is required to ensure they translate to field studies.

Engineering↗
DOE OSTI2020

Monte Carlo simulations of Cu/Ni–Si–Mn co-precipitation in duplex stainless steels

First-Passage Kinetic Monte Carlo (FPKMC) simulations of species migration in duplex stainless steels were performed in order to establish relationships between alloy content, segregation behavior, and the formation of Ni-Si-Mn rich particles in cast duplex stainless steels during thermal aging. The Ni-Si-Mn-rich second phase forms after extended aging at reactor operating temperatures and degrades alloy properties. Simulations of Ni-Si-Mn cluster formation were validated through comparison with experimental results obtained through Atom Probe Tomography (APT) on similar alloy compositions, identifying several trends. First, Cu promotes the formation of Ni-Si-Mn clusters, but only when Ni or Mn prefer segregation to the surface of Cu particles; without the segregation of these species, the critical composition for the clusters to form was not achieved. Second, the width of precipitate-denuded zones near ?/d interfaces increases with decreasing Cu content. This finding was in strong agreement with APT results, further validating our model. Finally, our model predicts that Ni-Si-Mn cluster formation will be the most extensive when the Si:Mn ratio is approximately 1:1 and the least extensive when one of these key elements is less concentrated (Mn = 0.5 at.% or Si = 0.5 at.%). The implications of these results on how to improve alloy properties are discussed.

Cu co-precipitation, Atom probe tomography (APT), ↗
DOE OSTI2021

Simulations of Events for the LUX-ZEPLIN (LZ) Dark Matter Experiment

The LUX-ZEPLIN dark matter search aims to achieve a sensitivity to the WIMP-nucleon spin-independent cross-section down to (1–2) ×10−12 pb at a WIMP mass of 40 GeV/ c 2 . This paper describes the simulations framework that, along with radioactivity measurements, was used to support this projection, and also to provide mock data for validating reconstruction and analysis software. Of particular note are the event generators, which allow us to model the background radiation, and the detector response physics used in the production of raw signals, which can be converted into digitized waveforms similar to data from the operational detector. Inclusion of the detector response allows us to process simulated data using the same analysis routines as developed to process the experimental data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Atomic Diffusion, Segregation, and Grain Boundary Migration in Nickel-Based Alloys from Molecular Dynamics Simulations

Grain boundary diffusion and metal mobility in alloys control material performance in many applications and yet remain poorly understood at a mechanistic level. With advances in accessible time and length scales for computational molecular simulations, and recent force field developments, we now possess tools to help unravel those mechanisms. Using large-scale molecular dynamics simulations, here we examined vacancy-mediated diffusion processes in Ni-5Cr alloy with low and high-energy grain boundaries. We show that atomic diffusion inside the grain boundary plane is about four times higher than bulk diffusion, at any temperature, and exhibits a typical Arrhenius behavior with a very small energy barrier (0~.8 eV for Cr and 0.7 eV for Ni within 1300-1600 K). Additionally, the fastest diffusing species inverts; Cr diffusion was faster than Ni in the bulk but slower in the grain boundaries. This is attributed to the creation of high cohesive energy clusters of Cr at the grain boundary. Grain boundary migration was also observed to be temperature dependent and appears to be two times higher in the 5% Cr alloy than in pure Ni, highlighting the important role of the alloying element on grain boundary motion.

Simonnin, Pauline GN↗
DOE OSTI2020

Simulation scaling studies of reactor core two-phase flow using direct numerical simulation

Tremendous growth in supercomputing power in recent years has resulted in the emergence of high-resolution flow analysis methods as an advanced research tool to evaluate single and two-phase flow behavior. In particular, unstructured mesh-based methods have been applied to analyze flows in complex reactor core geometries, including those of light water reactors (LWR). The finite-element based code, PHASTA, is utilized to perform large-scale simulations of two-phase bubbly flows in LWR geometries. Given the large computational cost of direct numerical simulation (DNS) coupled with interface tracking methods (ITM), typical domains encompass a portion of a single subchannel. In the presented research, the state-of-the-art analysis of turbulent two-phase flows in complex LWR subchannel geometries are demonstrated at both prototypical reactor parameters as well as scaled low pressure conditions. Three different cases are studied, a high-pressure simulation in prototypical reactor subchannel geometry, a low-pressure case in prototypical geometry and a final low-pressure case in a geometry scaled up to conserve the ratio between the bubble size and the domain pitch. Utilizing advanced statistical processing tools, these simulation conditions are compared to shed light on the relevancy of two-phase flow characteristics given the significant differences between LWR and low-pressure conditions. These findings can lead to the generation of useful guiding principles when researchers need to scale the two-phase flow behavior captured at low pressure and temperature conditions to those at reactor operating conditions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Verification of a Monte Carlo binary collision model for simulating elastic and inelastic collisions in particle-in-cell simulations

We present the development and verification of a Monte Carlo binary collision model for simulating elastic and inelastic collisions in particle-in-cell simulations. We apply the corrected binary collision model originally developed for charged-particles collisions to all considered scattering channels, including Coulomb collisions, elastic neutral–neutral and charged–neutral collisions, ionization, excitation, and fusion. The model's implementation is described and verified through a series of simulations, including charged- and neutral-particle thermal equilibration, slowing of electrons in warm solid-density aluminum, collisional damping of a Langmuir wave, helium gas breakdown in an applied electric field, and thermonuclear and beam–target fusion. Then, we demonstrate the model within simulations of hydrogen plasma formation in the Princeton Field-Reversed Configuration as well as of the burning of aneutronic fusion fuel p-11B. The latter includes measurement of the fusion power density in a low-density plasma and fusion production due to the stopping of a proton ignitor beam in a compressed boron target.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Insights into the structure and dynamics of K + ions at the muscovite–water interface from machine learning potential simulations

The surfaces of many minerals are covered by naturally occurring cations that become partially hydrated and can be replaced by hydronium or other cations when the surface is exposed to water or an aqueous solution. These ion exchange processes are relevant to various chemical and transport phenomena, yet elucidating their microscopic details is challenging for both experiments and simulations. Here, in this work, we make a first step in this direction by investigating the behavior of the native K + ions at the interface between neat water and the muscovite mica (001) surface with ab-initio -based machine learning molecular dynamics and enhanced sampling simulations. Our results show that the desorption of the surface K + ions in pure ion-free water has a significant free energy barrier irrespective of their local surface arrangement. In contrast, facile K + diffusion between mica’s ditrigonal cavities characterized by different Al/Si orderings is observed. This behavior suggests that the K + ions may favor a dynamic disordered surface arrangement rather than complete desorption when exposed to deionized water.

Ab-initio molecular dynamics↗
DOE OSTI2025

Heterogeneous energetic material damage simulator (HEDS): A deep learning approach to simulate damage–sensitivity linkages

Damage in the microstructures of energetic materials (EMs), such as propellants and plastic bonded explosives (PBXs), can significantly alter their response to external loads. Both sensitization and desensitization can occur, causing concerns with safety and performance in the field; predictive models that connect damage and the sensitivity of EMs can enable design and provide confidence in their robustness and reliability. However, modeling of damage evolution is challenging for real microstructures of EMs; samples of damaged EMs are difficult to obtain, thereby hindering experiments and direct numerical simulations to determine the sensitivity of EMs at various stages of damage. Here, we develop an approach to generate synthetic, i.e., in silico produced, damaged microstructures for use in simulations to connect damage levels to sensitivity. The development of the present workflow to generate and impose varying levels of damage in microstructures, known as HEDS (Heterogeneous Energetic Material Damage Simulator), begins with a small set of images of damaged PBXs and combines a collection of deep neural network techniques to generate microstructures with varying levels of damage. By making the synthetic microstructures conform closely to those observed in available real, imaged microstructures, we develop an ensemble of damaged microstructures that can be used for in silico shock experiments. HEDS develops these microstructure ensembles as level set fields, which are directly employed in a sharp interface Eulerian hydrocode where shock simulations are performed to quantify the energy release rate from hotspot fields generated in the microstructure. These capabilities can be useful for the analysis and assessment of changes in the sensitivity of EMs and to design formulations that are less susceptible to damage-induced changes in sensitivity and performance.

Fang, Irene (ORCID:0009000844557122)↗
DOE OSTI2020

Wind Farm Simulation and Layout Optimization in Complex Terrain: Preprint

This work reports on incorporating complex terrain into wind farm simulations for the purpose of layout optimization. Adding complex terrain boundary conditions to NREL's medium fidelity computational fluid dynamics model, WindSE, produces significant separation, flow curvature, and speedup effects that would otherwise be difficult to capture with lower-fidelity models or a flat-terrain assumption. These flow features, in turn, can significantly impact the optimal turbine array layout. We demonstrate the impact of complex terrain on flow in both an idealized and real-world setting, and discuss modifications to the code that enable gradient-based optimization using terrain-aware adjoint gradients. Through several optimization case studies, we show that the layout optimization process takes advantage of speedup effects on terrain high points, and leverages flow curvature effects that modify wake trajectories. This yields substantial power improvements over gridded layouts, and hints at future research directions in simulation and optimization for wake trajectories in complex terrain.

17 WIND ENERGY↗
DOE OSTI2024

Transformational Regional-Scale Earthquake Simulations with the DOE EarthQuake SIMulation Exascale Framework

Earthquakes present worldwide risk to economic and human safety. The 2023 earthquakes in Turkiye provided a reminder of the potential for catastrophic consequences with 50,700 deaths and 15.7 million people affected. The ability to predict ground motions and infrastructure damage for earthquakes continues to be a challenging problem for scientists and engineers. Until now, estimates of ground motions have been performed empirically by looking at sparse data from past earthquakes. This approach can provide statistical information on intensity amplitudes but cannot inform site-specific ground motions essential to developing the most effective resilience. Interest has grown in large-scale computational models to simulate earthquakes at regional scale. The U.S. Department of Energy EarthQuake SIMulation (EQSIM) framework was developed for regional-scale earthquake simulations at unprecedented fidelity, taking advantage of emerging GPU-accelerated systems. This article describes the EQSIM workflow and demonstrates regional-scale simulations with the new computational capability available to scientists in their quest to mitigate future disasters.

58 GEOSCIENCES↗
DOE OSTI2021

Predicting the Dissolution Rate of Borosilicate Glasses using QSPR analysis based on molecular dynamics simulations

Quantitative Structure Property Relationship (QSPR) analysis based on molecular dynamics (MD) simulations is a promising approach for establishing the composition-property relationships of glass and other materials with complex structures. A series of 20 borosilicate and boroaluminosilicate glasses have been modeled by using MD simulations with recently developed effective potentials. Short- and medium-range structures of these glasses were analyzed and, based on these structural information, QSPR analysis of the initial dissolution rate (r0) was made and compared with measured r0 at 90°C and pH 9 using various structural descriptors such as percentage of bridging oxygen species, network connectivity and average ring size. The structural descriptors, Fnet, containing energetic information such as single bond strength and other structural information were also used. It was found that overall network connectivity, average ring size and Fnet give reasonable predictions of the r0 of studied glasses, given the conditions that the glasses are homogeneous and dissolve congruently. Modifying glass compositions to account preferential release of modifiers gives a better prediction for incongruently dissolving glasses. The results were compared with our recent work of predicting glass dissolution behavior from compositions using the topological-constraints-based models.

Du, Jincheng↗
DOE OSTI2024

The Pele Simulation Suite for Reacting Flows at Exascale

In this work, we present the Pele suite of software tools for compressible and incompressible reacting flows. The Pele suite leverages several different libraries, notably AMReX and SUNDIALS, to achieve performance portability on heterogeneous computing architectures across the supercomputing landscape. The Pele suite is comprised of PeleC, a compressible reacting flow block-structured adaptive mesh refinement solver, PeleLMeX, a low-Mach number reacting flow block-structured adaptive mesh refinement solver, Pele-Physics, a library for transport, thermodynamics, finite rate chemistry, soot, spray and radiation physics. The objective of this paper is (i) to present the code development efforts necessary to achieve highly effective and scalable applications for exascale machines and (ii) to detail the performance results of the Combustion-Pele project applications on Oak Ridge National Laboratory's Frontier. We show good weak and strong scaling results for both PeleC and PeleLMeX up to more than 50 billion cells on more than 4096 Frontier graphics processing unit nodes. We also present a capability demonstration simulation of a dual-fuel pulse compression ignition engine (six adaptive mesh refinement levels, and 60 billion cells or 2.1 trillion degrees of freedom) on Frontier, to date one of the largest simulations performed on the first exascale-class supercomputer.

adaptive mesh refinement↗
DOE OSTI2025

Hydrologic Model Data for the East Fork Poplar Creek Watershed Simulated with the Advanced Terrestrial Simulator (ATS): Streamflow and Network Expansion–Contraction Dynamics

This dataset supports hydrologic modeling and stream network expansion–contraction analysis for the East Fork Poplar Creek (EFPC) Watershed in Tennessee. It includes a Jupyter notebook for model setup, model configuration files, simulation outputs, and derived products used to evaluate model performance and investigate stream dynamics under varying hydrologic conditions. The dataset was generated using the Watershed Workflow Python package and the Advanced Terrestrial Simulator (ATS), enabling integrated surface–subsurface hydrologic simulations using a stream-aligned mesh. Outputs include high-resolution time series of streamflow, active network length, water table depth, and related hydrologic variables. Also included are spatially explicit stream persistency indices and classifications of reaches as perennial or non-perennial. These data facilitate reproducibility and support further research on stream intermittency and variability in network extent.The model data archive is organized in following directories:1) model_setup_inputsContains the Watershed Workflow Jupyter notebooks (accessed through any open source code editor), selected input datasets, and resulting ATS input files, including XML files (access through any open source code editor), computational mesh (.exo files can be viewed using Paraview), and meteorological forcing files (.h5 files can be accessed through h5py python package and HDFView open source software). 2) model_outputsIncludes ATS simulation outputs relevant to this study. Time series of spatially integrated or averaged variables (e.g., streamflow, water table depth) are provided as CSV files. Select spatial fields (e.g., ponded depth and water table depth) are saved as pickled Python objects to reduce file size, and can be accessed through pickle package in Python. Key geometry objects from Watershed Workflow—such as the surface mesh and river tree—are also included to support analysis of streamflow persistency and expansion–contraction dynamics. These files can also be accessed through Watershed Workflow Python package.3) model_evaluationProvides observed streamflow time series and field survey-based flow regime classifications used to evaluate model performance. Jupyter notebooks for processing ATS outputs and comparing model predictions with observations to build confidence in the model prior to scientific analysis are also included.4) Q_L_relationshipsContains workflows for generating time series of discharge, active network length, and related hydrologic variables used in the stream network expansion–contraction analysis. Includes routines for delineating baseflow-dominated periods. For each catchment, notebooks and processed data (as pickled DataFrames accessed through Pandas Python package) are provided. 5) figure_scriptsProvides the Jupyter notebooks used to generate the figures presented in the paper.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Monte Carlo simulation analysis for radiation damage on Glidcop Al-15 caused by 17-20 MeV/u heavy ions

The Facility for Rare Isotope Beams (FRIB) SRF linear heavy-ion accelerator is designed to accelerate all ions up to uranium to a maximum beam power of 400 kW. Several beam intercepting devices (BIDs) are essential to the successful operation of the accelerator, including a low power charge selector (LPCS) made of copper containing 0.15% precipitated aluminum oxide by weight called Glidcop Al-15. As FRIB ramps up the primary beam power beyond the current 20 kW level, the charge selector must withstand higher radiation damage rates, typically measured in displacements per atom (dpa). Significant beam induced radiation damage including significant deformation, like swelling, blistering, and cracking has been observed on a recently removed LPCS. We also observed physical features up to about 5.5 mm wide and appear to be deeper than the projected range of any ions. This paper presents the results of Monte Carlo simulations carried out using the Particle and Heavy Ion Transport code System (PHITS), quantifying the total damage dose and ion concentration, etc. Simulating an accurate irradiation history is essential to determining the scope of post irradiation examination (PIE) work.

Fletcher, Ethan [Michigan State U.]↗
DOE OSTI2019

Integrated Modeling and Simulation Capability For Full Scale Multi-Physics Simulation and Visualization of Microreactor Concept

Microreactors are small mobile transportable nuclear reactors with thermal power less than 20 MWt that are designed to meet the needs of remote areas, military installations, emergency operations, and disaster relief zones. These reactor are concepts that are intended to be factory-manufacturable, easily transportable, and will allow for semi- or full-autonomous operation. To assist with development of microreactors, modeling and experimentation need to be performed with verification and validation to gain confidence in the models and tools. The objective of this study is apply advanced modeling and simulation capabilities being developed by the DOE Office of Nuclear Energy Nuclear Energy Advanced Modeling and Simulation (NEAMS) program to perform integrated modeling and simulation capability for multiphysics simulation of the microreactor concepts. This activity will provide an opportunity to exercise the codes to provide both gain experience and to provide feedback to the developers.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Impact of Rheology Models on Horizontal Well Polymer Flooding in a Heavy Oil Reservoir on Alaska North Slope: A Simulation Study

Polymer rheology can have either a positive or a negative effect on polymer flooding performance under varied circumstances. Many researchers have studied the effect of polymer rheology in a vertical well, but no field scale studies have been conducted to investigate whether polymer rheology is beneficial to polymer flooding in heavy oil reservoirs developed by horizontal wells. In this paper, we conducted a numerical simulation study to examine the effect of HPAM polymer rheology on a polymer flooding pilot, which is the first-ever project conducted on a heavy oil reservoir from Alaska North Slope (ANS) developed by horizontal wells. Three rheology types were considered in the study including the apparent viscosity measured during coreflooding of using a HPAM polymer, the bulk viscosity measured with a viscometer, and a Newtonian flow model. The results suggest that using the bulk viscosity in simulation underestimates the conformance control and the water-oil-ratio reduction capability of the HPAM polymer solution. When the apparent viscosity is used, the incremental oil and sweep were largely increased, and the optimal recovery period of polymer flooding was extended greatly, especially for the heterogeneous formations. Therefore, the rheology type of polymer plays a significant role in the incremental oil recovery and injection profile of the horizontal well system given the pilot test conditions. This study has provided practical guidance to field operators for the ongoing polymer flooding pilot on ANS and will also provide valuable information for other polymer projects conducted in similar conditions.

Leng, Jianqiao↗