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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.

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At least 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

THE XMM-NEWTON/EPIC X-RAY LIGHT CURVE ANALYSIS OF WR 6

We obtained four pointings of over 100 ks each of the well-studied Wolf-Rayet star WR 6 with the XMM-Newton satellite. With a first paper emphasizing the results of spectral analysis, this follow-up highlights the X-ray variability clearly detected in all four pointings. However, phased light curves fail to confirm obvious cyclic behavior on the well-established 3.766 day period widely found at longer wavelengths. The data are of such quality that we were able to conduct a search for event clustering in the arrival times of X-ray photons. However, we fail to detect any such clustering. One possibility is that X-rays are generated in a stationary shock structure. In this context we favor a corotating interaction region (CIR) and present a phenomenological model for X-rays from a CIR structure. We show that a CIR has the potential to account simultaneously for the X-ray variability and constraints provided by the spectral analysis. Ultimately, the viability of the CIR model will require both intermittent long-term X-ray monitoring of WR 6 and better physical models of CIR X-ray production at large radii in stellar winds.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

SU-E-T-565: RAdiation Resistance of Cancer CElls Using GEANT4 DNA: RACE

Purpose: The objective of the RACE project is to develop a comparison between Monte Carlo simulation using the Geant4-DNA toolkit and measurements of radiation damage on 3D melanoma and chondrosarcoma culture cells coupled with gadolinium nanoparticles. We currently expose the status of the developments regarding simulations. Methods: Monte Carlo studies are driven using the Geant4 toolkit and the Geant4-DNA extension. In order to model the geometry of a cell population, the opensource CPOP++ program is being developed for the geometrical representation of 3D cell populations including a specific cell mesh coupled with a multi-agent system. Each cell includes cytoplasm and nucleus. The correct modeling of the cell population has been validated with confocal microscopy images of spheroids. The Geant4 Livermore physics models are used to simulate the interactions of a 250 keV X-ray beam and the production of secondaries from gadolinium nanoparticles supposed to be fixed on the cell membranes. Geant4-DNA processes are used to simulate the interactions of charged particles with the cells. An atomistic description of the DNA molecule, from PDB (Protein Data Bank) files, is provided by the so-called PDB4DNA Geant4 user application we developed to score energy depositions in DNA base pairs and sugar-phosphate groups. Results: At the microscopic level, our simulations enable assessing microscopic energy distribution in each cell compartment of a realistic 3D cell population. Dose enhancement factors due to the presence of gadolinium nanoparticles can be estimated. At the nanometer scale, direct damages on nuclear DNA are also estimated. Conclusion: We successfully simulated the impact of direct radiations on a realistic 3D cell population model compatible with microdosimetry calculations using the Geant4-DNA toolkit. Upcoming validation and the future integration of the radiochemistry module of Geant4-DNA will propose to correlate clusters of ionizations with in vitro experiments. All those developments will be released publicly. This work was supported by grants from Plan Cancer 2009-2013 French national initiative managed by INSERM (Institut National de la Sante et de la Recherche Medicale)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

TEAL

TEAL is a financial performance calculator plugin for the RAVEN code, framework, resolving around the computation of Net Present Value and associated financial metrics. TEAL can make use of inflation rates, taxation, escalation factors, capital expenditure economy of scale scaling factors. The unique feature of TEAL is the capability to be linked with RAVEN external models and build corresponding cash flows using the variables computed by those external models. In addition to be able to use the capability to generate cash flows derived from complex physical models generated by RAVEN, another distinctive feature of TEAL is the capability to provide financial risk/probabilistic metrics that can empower RAVEN to perform optimization/analysis driven by financial risk augmentations. Optimization, robust optimization, parametric studies, large parallel simulations, sensitivity analysis, data mining, etc. are just some of the capabilities that can be leveraged.

Alfonsi, Andrea↗
DOE OSTI2024

The LBNF/DUNE Complex for Neutrino Science

The Long Baseline Neutrino Facility (LBNF) provides the underground detector caverns, the beamline to deliver a 1.2MW proton beam, and a target station to produce neutrinos for the international Deep Underground Neutrino Experiment (DUNE). A mile underground, caverns are being excavated and outfitted at the Sanford Underground Research Facility in South Dakota. The beamline facility and an additional near detector facility will be constructed on the Fermilab site in Illinois. DUNE will make precision neutrino oscillation physics measurements and will be sensitive to neutrinos from supernova bursts, nucleon decay, and beyond-standard-model physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Quantifying model prediction sensitivity to model-form uncertainty

Computational and mathematical models are essential to understanding complex systems and phenomena. However, when developing such models, limited knowledge and/or resources necessitates the use of simplifying assumptions. It is therefore crucial to quantify the impact of such simplifying assumptions on the reliability and accuracy of resulting model predictions. This work develops a first-of-its-kind approach to quantify the impact of physics modeling assumptions on predictions. Here, we leverage the emerging field of model-form uncertainty (MFU) representations, which are parameterized modifications to modeling assumptions, in combination with grouped Sobol’ indices to quantitatively measure an assumption’s importance. Specifically, we compute the grouped Sobol’ index for the MFU representation’s parameters as a single importance measure of the assumption for which the MFU representation characterizes uncertainty. To ensure this approach is robust to the subjective choice of how to parameterize a MFU representation, we establish bounds for the difference between sensitivity results for two different MFU representations based on differences in model prediction statistics. The capabilities associated with this approach are demonstrated on three exemplar problems: an upscaled subsurface contaminant transport problem, ablation modeling for hypersonic flight, and nuclear waste repository modeling. We found that our grouped approach is able to assess the impact of modeling assumptions on predictions and offers computational advantages over classical Sobol’ index computation while providing more interpretable results.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2004

DSMC Simulations of Hypersonic Flows With Shock Interactions and Validation With Experiments

The capabilities of a relatively new direct simulation Monte Carlo (DSMC) code are examined for the problem of hypersonic laminar shock/shock and shock/boundary layer interactions, where boundary layer separation is an important feature of the flow. Flow about two model configurations is considered, where both configurations (a biconic and a hollow cylinder-flare) have recent published experimental measurements. The computations are made by using the DS2V code of Bird, a general two-dimensional/axisymmetric time accurate code that incorporates many of the advances in DSMC over the past decade. The current focus is on flows produced in ground-based facilities at Mach 12 and 16 test conditions with nitrogen as the test gas and the test models at zero incidence. Results presented highlight the sensitivity of the calculations to grid resolution, sensitivity to physical modeling parameters, and comparison with experimental measurements. Information is provided concerning the flow structure and surface results for the extent of separation, heating, pressure, and skin friction.

Moss, James N.↗
NASA NTRS2004

DSMC Simulations of Hypersonic Flows With Shock Interactions and Validation With Experiments

The capabilities of a relatively new direct simulation Monte Carlo (DSMC) code are examined for the problem of hypersonic laminar shock/shock and shock/boundary layer interactions, where boundary layer separation is an important feature of the flow. Flow about two model configurations is considered, where both configurations (a biconic and a hollow cylinder-flare) have recent published experimental measurements. The computations are made by using the DS2V code of Bird, a general two-dimensional/axisymmetric time accurate code that incorporates many of the advances in DSMC over the past decade. The current focus is on flows produced in ground-based facilities at Mach 12 and 16 test conditions with nitrogen as the test gas and the test models at zero incidence. Results presented highlight the sensitivity of the calculations to grid resolutions, sensitivity to physical modeling parameters, and comparison with experimental measurements. Information is provided concerning the flow structure and surface results for the extent of separation, heating, pressure, and skin friction.

Moss, James N.↗
NASA NTRS2017

Korea-United States Air Quality (KORUS-AQ) Campaign

The Korea-United States Air Quality (KORUS-AQ) campaign was an international cooperative field study based out of Osan Air Base, Songtan, South Korea (about 60 kilometers south of Seoul) in April-June 2016. A comprehensive suite of instruments capable of measuring atmospheric composition was deployed around the Korean peninsula on aircrafts, ships, and at ground sites in order to characterize local and transboundary pollution. The NASA Goddard Earth Observing System, version 5 (GEOS-5) forecast model was used for near real time meteorological and aerosol forecasting and flight planning during the KORUS-AQ campaign. Evaluation of GEOS-5 against observations from the campaign will help to identify inaccuracies in the models physical and chemical processes in this region within East Asia and lead to further developments of the modeling system.

KORUS-AQ↗
DOE OSTI2014

Fracture Propagation, Fluid Flow, and Geomechanics of Water-Based Hydraulic Fracturing in Shale Gas Systems and Electromagnetic Geophysical Monitoring of Fluid Migration

We investigate fracture propagation induced by hydraulic fracturing with water injection, using numerical simulation. For rigorous, full 3D modeling, we employ a numerical method that can model failure resulting from tensile and shear stresses, dynamic nonlinear permeability, leak-off in all directions, and thermo-poro-mechanical effects with the double porosity approach. Our numerical results indicate that fracture propagation is not the same as propagation of the water front, because fracturing is governed by geomechanics, whereas water saturation is determined by fluid flow. At early times, the water saturation front is almost identical to the fracture tip, suggesting that the fracture is mostly filled with injected water. However, at late times, advance of the water front is retarded compared to fracture propagation, yielding a significant gap between the water front and the fracture top, which is filled with reservoir gas. We also find considerable leak-off of water to the reservoir. The inconsistency between the fracture volume and the volume of injected water cannot properly calculate the fracture length, when it is estimated based on the simple assumption that the fracture is fully saturated with injected water. As an example of flow-geomechanical responses, we identify pressure fluctuation under constant water injection, because hydraulic fracturing is itself a set of many failure processes, in which pressure consistently drops when failure occurs, but fluctuation decreases as the fracture length grows. We also study application of electromagnetic (EM) geophysical methods, because these methods are highly sensitive to changes in porosity and pore-fluid properties due to water injection into gas reservoirs. Employing a 3D finite-element EM geophysical simulator, we evaluate the sensitivity of the crosswell EM method for monitoring fluid movements in shaly reservoirs. For this sensitivity evaluation, reservoir models are generated through the coupled flow-geomechanical simulator and are transformed via a rock-physics model into electrical conductivity models. It is shown that anomalous conductivity distribution in the resulting models is closely related to injected water saturation, but not closely related to newly created unsaturated fractures. Our numerical modeling experiments demonstrate that the crosswell EM method can be highly sensitive to conductivity changes that directly indicate the migration pathways of the injected fluid. Accordingly, the EM method can serve as an effective monitoring tool for distribution of injected fluids (i.e., migration pathways) during hydraulic fracturing operations

02 PETROLEUM↗
DOE OSTI2017

Computational Study of Droplet Dynamics in Dispersed Flow Film Boiling Regime in PWR Geometries

Dispersed flow film boiling (DFFB) regime is exhibited during low-flooding rate conditions following the postulated Loss-of-Coolant Accident (LOCA) in nuclear reactor flow channels. LOCA is a type of design-basis accident scenario, which is crucial for reactor design and licensing. Accurate models to predict the heat transfer in DFFB regime is critical for the reactor to maintain safety limits. The nominal operating linear heat rate is also set based on the maximum linear heat rate determined for a LOCA transient. It is understood that the behavior of entrained droplets in DFFB regime greatly affects the heat transfer by evaporating and desuperheating the surrounding steam. Furthermore, interaction with flow structures also aids in increasing the evaporation rate of entrained droplets. In order to quantify this enhancement in heat transfer, the size of droplets downstream of flow structures (Spacer Grids and Mixing Vanes) is of crucial importance. Thermal hydraulic analysis codes like COBRA-TF, CATHARE-3 and adopt a three-field equation model that allows them to model the droplet field separately. However, to ensure the accuracy of these field equations, various correlations and physical models are required. This paper proposes a method for characterizing the mean Sauter Diameter of droplets across spacer-grids and mixing vanes in PWR sub-channels using PHASTA - a high fidelity flow solver with multiphase capabilities using the level-set method. The PHASTA code is a finite element based computational fluid dynamics code designed for solving compressible and incompressible turbulent flows. It has been demonstrated to be massively scalable (up to 786,432 cores), which is crucial for simulating large realistic domains. The code incorporates the level-set method for interface tracking of the gas-liquid interface.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Feasibility of Formulating Ecosystem Biogeochemical Models From Established Physical Rules

Abstract To improve the predictive capability of ecosystem biogeochemical models (EBMs), we discuss the feasibility of formulating biogeochemical processes using physical rules that have underpinned the many successes in computational physics and chemistry. We argue that the currently popular empirically based approaches, such as multiplicative empirical response functions and the law of the minimum, will not lead to EBM formulations that can be continuously refined to incorporate improved mechanistic understanding and empirical observations of biogeochemical processes. Instead, we propose that EBM parameterizations, as a lossy data compression problem, can be better formulated using established physical rules widely used in computational physics and chemistry, and different biogeochemical processes can be more robustly integrated within a reactive‐transport framework. Through several examples, we demonstrate how mathematical representations derived from physical rules can improve understanding of relevant biogeochemical processes and enable more effective communication between modelers, observationalists, and experimentalists regarding essential questions, such as what measurements are needed to meaningfully inform models and how can models generate new process‐level hypotheses to test in empirical studies. Finally, while empirical models with more parameters are often less robust, physical rules‐based models can be more robust and show lower predictive equifinality, stemming from their enhanced consistency in representations of processes, interactions and spatial scaling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

The transport of suspended sediment in the wake of a marine hydrokinetic turbine: Simulations via a validated Discrete Random Walk (DRW) model

The interaction of sediment with Marine Hydrokinetic (MHK) Turbines is studied via turbulent flow simulation coupled with a model for particle dynamics. The Discrete Random Walk (DRW) model is commonly used for simulations of particle dispersion in environmental flows. A method to improve the accuracy of the DRW model in conjunction with RANS simulations of the flow around MHK turbines is presented. A key issues for the use of the DRW model in marine applications is identified, finding the right characteristic eddy lifetime scale, and a simple methodology based on G.I. Taylor's classical dispersion theory is develop to calibrate this physical model parameter. The model is validated against experiments in the literature and the physics of suspended sediment transport in the wake of an MHK turbine is studied with this improved method. The qualitative changes observed in the particle trajectories agree well with theoretical and empirical observations and the quantitive trends allow for comparison of multiple particle cases under different flow conditions, confirming that this implementation of CFD can become a powerful tool to select the most challenging cases, among the thousands of potential studies on the environmental effects of MHK energy, for further study with experiments and pilot projects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Generative models for simulation of KamLAND-Zen

Abstract The next generation of searches for neutrinoless double beta decay ($$0 \nu \beta \beta $$ 0 ν β β ) are poised to answer deep questions on the nature of neutrinos and the source of the Universe’s matter–antimatter asymmetry. They will be looking for event rates of less than one event per ton of instrumented isotope per year. To claim discovery, accurate and efficient simulations of detector events that mimic$$0 \nu \beta \beta $$ 0 ν β β is critical. Traditional Monte Carlo (MC) simulations can be supplemented by machine-learning-based generative models. This work describes the performance of generative models that we designed for monolithic liquid scintillator detectors like KamLAND to produce accurate simulation data without a predefined physics model. We present their current ability to recover low-level features and perform interpolation. In the future, the results of these generative models can be used to improve event classification and background rejection by providing high-quality abundant generated data.

Physics↗
DOE OSTI2021

Cathode to Target Simulations for Scorpius: I. Simulation Codes and Models

The new Scorpius linear induction electron accelerator is under development for multi-pulse flash radiography of large, explosively-driven hydrodynamic experiments. Beam physics from the cathode to the target was examined with computer simulations, including envelope, ray-trace, and particle-in cell (PIC) codes. Beam instabilities investigated included beam breakup (BBU), image displacement, diocotron, parametric envelope, ion hose, and the resistive wall instability. Beam corkscrew motion and emittance growth from beam mismatch were also studied. The results of these simulations is documented in a series of reports. In this report the computer codes and physical models used for these simulations are described. The conclusion of this study is that Scorpius will produce and accelerate a beam with radiographic quality equivalent to the present accelerators at Los Alamos National Laboratory if the same engineering standards and construction details are upheld.

43 PARTICLE ACCELERATORS↗
DOE OSTI2014

Code Coupling via Jacobian-Free Newton-Krylov Algorithms with Application to Magnetized Fluid Plasma and Kinetic Neutral Models

Jacobian-free Newton-Krylov (JFNK) algorithms are a potentially powerful class of methods for solving the problem of coupling codes that address dfferent physics models. As communication capability between individual submodules varies, different choices of coupling algorithms are required. The more communication that is available, the more possible it becomes to exploit the simple sparsity pattern of the Jacobian, albeit of a large system. The less communication that is available, the more dense the Jacobian matrices become and new types of preconditioners must be sought to efficiently take large time steps. In general, methods that use constrained or reduced subsystems can offer a compromise in complexity. The specific problem of coupling a fluid plasma code to a kinetic neutrals code is discussed as an example.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2007

Runtime and Pressurization Analyses of Propellant Tanks

Multi-element unstructured CFD has been utilized at NASA SSC to carry out analyses of propellant tank systems in different modes of operation. The three regimes of interest at SSC include (a) tank chill down (b) tank pressurization and (c) runtime propellant draw-down and purge. While tank chill down is an important event that is best addressed with long time-scale heat transfer calculations, CFD can play a critical role in the tank pressurization and runtime modes of operation. In these situations, problems with contamination of the propellant by inclusion of the pressurant gas from the ullage causes a deterioration of the quality of the propellant delivered to the test article. CFD can be used to help quantify the mixing and propellant degradation. During tank pressurization under some circumstances, rapid mixing of relatively warm pressurant gas with cryogenic propellant can lead to rapid densification of the gas and loss of pressure in the tank. This phenomenon can cause serious problems during testing because of the resulting decrease in propellant flow rate. With proper physical models implemented, CFD can model the coupling between the propellant and pressurant including heat transfer and phase change effects and accurately capture the complex physics in the evolving flowfields. This holds the promise of allowing the specification of operational conditions and procedures that could minimize the undesirable mixing and heat transfer inherent in propellant tank operation. It should be noted that traditional CFD modeling is inadequate for such simulations because the fluids in the tank are in a range of different sub-critical and supercritical states and elaborate phase change and mixing rules have to be developed to accurately model the interaction between the ullage gas and the propellant. We show a typical run-time simulation of a spherical propellant tank, containing RP-1 in this case, being pressurized with room-temperature nitrogen at 540 R. Nitrogen, shown in blue on the right-hand side of the figures, enters the tank from the diffuser at the top of the figures and impinges on the RP-1, shown in red, while the propellant is being continuously drained at the rate of 1050 lbs/sec through a pipe at the bottom of the tank. The sequence of frames in Figure 1 shows the resultant velocity fields and mixing between nitrogen and RP-1 in a cross-section of the tank at different times. A vortex is seen to form in the incoming nitrogen stream that tends to entrain propellant, mixing it with the pressurant gas. The RP-1 mass fraction contours in Figure 1 are also indicative of the level of mixing and contamination of the propellant. The simulation is used to track the propagation of the pure propellant front as it is drawn toward the exit with the evolution of the mixing processes in the tank. The CFD simulation modeled a total of 10 seconds of run time. As is seen from Figure 1d, after 5.65 seconds the propellant front is nearing the drain pipe, especially near the center of the tank. Behind this pure propellant front is a mixed fluid of compromised quality that would require the test to end when it reaches the exit pipe. Such unsteady simulations provide an estimate of the time that a high-quality propellant supply to the test article can be guaranteed at the modeled mass flow rate. In the final paper, we will discuss simulations of the LOX and propellant tanks at NASA SSC being pressurized by an inert ullage. Detailed comparisons will be made between the CFD simulations and lower order models as well as with test data. Conditions leading to cryo collapse in the tank will also be identified.

Field, Robert E.↗
DOE OSTI2019

Deep multiscale model learning

The objective of this article is to design novel multi-layer neural networks for multiscale simulations of flows taking into account the observed fine data and physical modeling concepts. Our approaches use deep learning techniques combined with local multiscale model reduction methodologies to predict flow dynamics. Using reduced-order model concepts is important for constructing robust deep learning architectures since the reduced-order models provide fewer degrees of freedom. We consider flow dynamics in porous media as multi-layer networks in this work. More precisely, the solution (e.g., pressures and saturation) at the time instant n+1 depends on the solution at the time instant n and input parameters, such as permeability fields, forcing terms, and initial conditions. One can regard the solution as a multi-layer network, where each layer, in general, is a nonlinear forward map and the number of layers relates to the internal time steps. We will rely on rigorous model reduction concepts to define unknowns and connections between layers. It is critical to use reduced-order models for this purpose, which will identify the regions of influence and the appropriate number of variables. Furthermore, due to the lack of available observed fine data, the reduced-order model can provide us sufficient inexpensive data as needed. The designed deep neural network will be trained using both coarse simulation data which is obtained from the reduced-order model and observed fine data. We will present the main ingredients of our approach and numerical examples. Numerical results show that using deep learning with data generated from multiscale models as well as available observed fine data, we can obtain an improved forward map which can better approximate the fine scale model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Improving Variational Autoencoders for New Physics Detection at the LHC With Normalizing Flows

We investigate how to improve new physics detection strategies exploiting variational autoencoders and normalizing flows for anomaly detection at the Large Hadron Collider. As a working example, we consider the DarkMachines challenge dataset. We show how different design choices (e.g., event representations, anomaly score definitions, network architectures) affect the result on specific benchmark new physics models. Once a baseline is established, we discuss how to improve the anomaly detection accuracy by exploiting normalizing flow layers in the latent space of the variational autoencoder.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗