Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Physics Modeling”

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 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Particle–Continuum Coupling and its Scaling Regimes: Theory and Applications

Abstract This work is motivated by the goal of designing simulation software for technical devices that, at their functional core, rely on atomistic‐scale processes embedded in a larger‐scale fluid environment. The core of the problem is the conceptual and technical approach for coupling particle and continuum representations of a fluid. The state of the art for key aspects including physical modeling, mathematical formalization, computational implementation, and applications, is discussed and organized in a consistent picture across the relevant physical regimes.

Delle Site, Luigi↗
DOE OSTI2014

On the equivalence of the RTI and SVM approaches to time correlated analysis

Recently two papers on how to perform passive neutron auto-correlation analysis on time gated histograms formed from pulse train data, generically called time correlation analysis (TCA), have appeared in this journal [1,2]. For those of us working in international nuclear safeguards these treatments are of particular interest because passive neutron multiplicity counting is a widely deployed technique for the quantification of plutonium. The purpose of this letter is to show that the skewness-variance-mean (SVM) approach developed in [1] is equivalent in terms of assay capability to the random trigger interval (RTI) analysis laid out in [2]. Mathematically we could also use other numerical ways to extract the time correlated information from the histogram data including for example what we might call the mean, mean square, and mean cube approach. The important feature however, from the perspective of real world applications, is that the correlated information extracted is the same, and subsequently gets interpreted in the same way based on the same underlying physics model.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Extracting Knowledge from Data through Catalysis Informatics

Catalysis informatics is a distinct sub-field that lies at the intersection of cheminformatics and materials informatics, but with unique challenges arising from the dynamic, surface-sensitive, multi-scale nature of heterogeneous catalysis. The ideas behind catalysis informatics can be traced back decades, but the field is only recently emerging due to advances in data infrastructure, statistics, machine learning, and computational methods. In this work we review the field from early works on expert systems and knowledge engines to more recent approaches utilizing machine-learning and uncertainty quantification. The data-information-knowledge hierarchy is introduced and used to classify various developments. The chemical master equation and micro-kinetic models are proposed as a quantitative representation of catalysis knowledge, which can be used to generate explanative and predictive hypotheses for the understanding and discovery of catalytic materials. We discuss future prospects for the field, including improved quantitative coupling of experiment/theory, advanced micro-kinetic models, and the development of open-source software tools. As a result, integration of existing chemical and physical models with emerging statistical and computational tools presents a promising route toward the automated design, discovery, and optimization of heterogeneous catalytic processes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

AUTOMATED SOLAR FLARE STATISTICS IN SOFT X-RAYS OVER 37 YEARS OF GOES OBSERVATIONS: THE INVARIANCE OF SELF-ORGANIZED CRITICALITY DURING THREE SOLAR CYCLES

We analyzed the soft X-ray light curves from the Geostationary Operational Environmental Satellites over the last 37 years (1975-2011) and measured with an automated flare detection algorithm over 300,000 solar flare events (amounting to Almost-Equal-To 5 times higher sensitivity than the NOAA flare catalog). We find a power-law slope of {alpha}{sub F} = 1.98 {+-} 0.11 for the (background-subtracted) soft X-ray peak fluxes that is invariant through three solar cycles and agrees with the theoretical prediction {alpha}{sub F} = 2.0 of the fractal-diffusive self-organized criticality (FD-SOC) model. For the soft X-ray flare rise times, we find a power-law slope of {alpha}{sub T} = 2.02 {+-} 0.04 during solar cycle minima years, which is also consistent with the prediction {alpha}{sub T} = 2.0 of the FD-SOC model. During solar cycle maxima years, the power-law slope is steeper in the range of {alpha}{sub T} Almost-Equal-To 2.0-5.0, which can be modeled by a solar-cycle-dependent flare pile-up bias effect. These results corroborate the FD-SOC model, which predicts a power-law slope of {alpha}{sub E} = 1.5 for flare energies and thus rules out significant nanoflare heating. While the FD-SOC model predicts the probability distribution functions of spatio-temporal scaling laws of nonlinear energy dissipation processes, additional physical models are needed to derive the scaling laws between the geometric SOC parameters and the observed emissivity in different wavelength regimes, as we derive here for soft X-ray emission. The FD-SOC model also yields statistical probabilities for solar flare forecasting.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Distribution-Connected PV's Response to Voltage Sags at Transmission-Scale

The ever increasing amount of residential- and commercial-scale distribution-connected PV generation being installed and operated on the U.S.'s electric power system necessitates the use of increased fidelity representative distribution system models for transmission stability studies in order to ensure the continued safe and reliable operation of the grid. This paper describes a distribution model-based analysis that determines the amount of distribution-connected PV that trips off-line for a given voltage sag seen at the distribution circuit's substation. Such sags are what could potentially be experienced over a wide area of an interconnection during a transmission-level line fault. The results of this analysis show that the voltage diversity of the distribution system does cause different amounts of PV generation to be lost for differing severity of voltage sags. The variation of the response is most directly a function of the loading of the distribution system. At low load levels the inversion of the circuit's voltage profile results in considerable differences in the aggregated response of distribution-connected PV Less variation is seen in the response to specific PV deployment scenarios, unless pushed to extremes, and in the total amount of PV penetration attained. A simplified version of the combined CMPLDW and PVD1 models is compared to the results from the model-based analysis. Furthermore, the parameters of the simplified model are tuned to better match the determined response. The resulting tuning parameters do not match the expected physical model of the distribution system and PV systems and thus may indicate that another modeling approach would be warranted.

14 SOLAR ENERGY↗
DOE OSTI2023

Secondary Pion Production using the LINAC Beam on Graphite and Tungsten Targets

The Fermilab 400-MeV Linac primary proton beam can produce precision, single-species secondary beams using a production target in the MeV Test Area experimental hall; specifically, pions from 4 up to 120 MeV kinetic energy. (These low energy pions rapidly decay into a muon beam in a secondary collection and transport beamline.) Although graphite is a standard production target material given its ultra-high temperature tolerance and low impact on the post-target primary beam, secondary pion/muon total production cross sections increase approximately as Z1/3 for positive muons and N2/3 for negative muons. Higher mass targets such as tungsten can potentially increase low-energy m+ and m- rates by factors of 3 and 8, respectively. Initial production studies have confirmed higher muon yield from heavy targets (tungsten vs carbon), but also, surprisingly, show significant differences in pion production between modern hadronic models (GENIEhad) and between GEANT and MCNP, state of the art production modeling codes. This project will further investigate the production discrepancies between these two target materials and between different physics models with high-statistics runs using the GEANT-based code, G4Beamline to better quantify the results and compare with production data which will be obtained using the MTA secondary beamline.

Ahmed, Shiza↗
DOE OSTI2023

Adaptively Learned Modeling for a Digital Twin of Hydropower Turbines with Application to a Pilot Testing System

In the development of a digital twin (DT) for hydropower turbines, dynamic modeling of the system (e.g., penstock, turbine, speed control) is crucial, along with all the necessary data interface, virtualization, and dashboard designs. Since the DT must mimic the actual dynamics of the hydropower turbine accurately, adaptive learning is required to train these dynamic models online so that the models in the DT can effectively follow the representation of the actual hydropower turbine dynamics accurately and reliably. This study presents an adaptive learning method for obtaining the hydropower turbine models for DT development of hydropower systems using the recursive least squares algorithm. To simplify the formulation, the hydropower turbine under consideration was assumed to operate near a fixed operating point, where the system dynamics can be well represented by a set of linear differential equations with constant parameters. In this context, the well-known six-coefficient model for the Francis turbine was formulated as the starting point to obtain input and output models for the turbine. Then, an adaptive learning mechanism was developed to learn model parameters using real-time data from a hydropower turbine testing system. This led to semi-physical modeling, in which first principles and data-driven modeling are integrated to produce dynamic models for DT development. Applications to a pilot system at the Norwegian University of Science and Technology (NTNU) were made, and the models learned adaptively using the data collected from the university’s pilot system. Desired modeling and validation results were obtained.

13 HYDRO ENERGY↗
NASA NTRS1985

Comet Thermal Modeling

Past thermal models of cometary nuclei have tended to be restricted to hemispherical averages and have ignored many important effects such as surface heat flow, rotation period, or coma opacity. A computer based model called KRC/COM was developed which includes these and many other important effects to give a more accurate physical model of sublimation from icy cometary nuclei. Halley's Comet was used as a test case because of the high interest in the 1986 perihelion passage of that comet.

Weissman, P. R.↗
NASA NTRS1989

Supersonic reacting internal flow fields

The national program to develop a trans-atmospheric vehicle has kindled a renewed interest in the modeling of supersonic reacting flows. A supersonic combustion ramjet, or scramjet, has been proposed to provide the propulsion system for this vehicle. The development of computational techniques for modeling supersonic reacting flow fields, and the application of these techniques to an increasingly difficult set of combustion problems are studied. Since the scramjet problem has been largely responsible for motivating this computational work, a brief history is given of hypersonic vehicles and their propulsion systems. A discussion is also given of some early modeling efforts applied to high speed reacting flows. Current activities to develop accurate and efficient algorithms and improved physical models for modeling supersonic combustion is then discussed. Some new problems where computer codes based on these algorithms and models are being applied are described.

Drummond, J. Philip↗
NASA NTRS1991

Visualization techniques to experimentally model flow and heat transfer in turbine and aircraft flow passages

Increased attention to fuel economy and increased thrust requirements have increased the demand for higher aircraft gas turbine engine efficiency through the use of higher turbine inlet temperatures. These higher temperatures increase the importance of understanding the heat transfer patterns which occur throughout the turbine passages. It is often necessary to use a special coating or some form of cooling to maintain metal temperatures at a level which the metal can withstand for long periods of time. Effective cooling schemes can result in significant fuel savings through higher allowable turbine inlet temperatures and can increase engine life. Before proceeding with the development of any new turbine it is economically desirable to create both mathematical and experimental models to study and predict flow characteristics and temperature distributions. Some of the methods are described used to physically model heat transfer patterns, cooling schemes, and other complex flow patterns associated with turbine and aircraft passages.

Russell, Louis M.↗
NASA NTRS1991

Supersonic reacting internal flowfields

The national program to develop a trans-atmospheric vehicle has kindled a renewed interest in the modeling of supersonic reacting flows. A supersonic combustion ramjet, or scramjet, has been proposed to provide the propulsion system for this vehicle. The development of computational techniques for modeling supersonic reacting flowfields, and the application of these techniques to an increasingly difficult set of combustion problems are studied. Since the scramjet problem has been largely responsible for motivating this computational work, a brief history is given of hypersonic vehicles and their propulsion systems. A discussion is also given of some early modeling efforts applied to high speed reacting flows. Current activities to develop accurate and efficient algorithms and improved physical models for modeling supersonic combustion is then discussed. Some new problems where computer codes based on these algorithms and models are being applied are described.

Drummond, J. P.↗
NASA NTRS2009

Modeling of the 22 July 2009 Storm

The magnetic storm on 22 July 2009 is the greatest storm observed since the summer of 2008 when TWINS began its stereo imaging of the magnetosphere, On 22 July 2009, the Dst dropped to nearly -80 nT at 07:00 and 10:00 UT. During the main phase and at the peak of the storm, TWINS 1 and 2 were near apogee and moving from pre-dawn to post-dawn local time. The energetic neutral atom (ENA) Imagers on the 2 spacecraft captured the storm intensification and the formation of the partial ring current. The development of this storm has been simulated using the Comprehensive Ring Current Model (CRCM) to understand and interpret the observed signatures. The CRCM reproduced the double-dip in the Dst index and the simulated ENA flux intensities agree very well with the TWINS images. However, the peak of ion flux predicted by the model is always eastward of the observed maximum by TWINS. This discrepancy posts a challenge to reexamine the physical models employed in the CRCM.

Fok, Mei-Ching↗
DOE OSTI2012

Searching for New Physics with Flavor Violating Observables

In this talk, I review the status and prospects of several low energy flavor observables that are highly sensitive to New Physics effects. In particular I discuss the implications for possible New Physics in b {yields} s transitions coming from the recent experimental results on the B{sub s} mixing phase, the branching ratio of the rare decay B{sub s} {yields} {mu}{sup +}{mu}{sup -}, and angular observables in the B {yields} K* {mu}{sup +}{mu}{sup -} decay. Also the recent evidence for direct CP violation in singly Cabibbo suppressed charm decays and its interpretation in the context of New Physics models is briefly discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Predictive Models of Li-ion Battery Lifetime (Presentation)

Predictive models of Li-ion battery reliability must consider a multiplicity of electrochemical, thermal and mechanical degradation modes experienced by batteries in application environments. Complicating matters, Li-ion batteries can experience several path dependent degradation trajectories dependent on storage and cycling history of the application environment. Rates of degradation are controlled by factors such as temperature history, electrochemical operating window, and charge/discharge rate. Lacking accurate models and tests, lifetime uncertainty must be absorbed by overdesign and warranty costs. Degradation models are needed that predict lifetime more accurately and with less test data. Models should also provide engineering feedback for next generation battery designs. This presentation reviews both multi-dimensional physical models and simpler, lumped surrogate models of battery electrochemical and mechanical degradation. Models are compared with cell- and pack-level aging data from commercial Li-ion chemistries. The analysis elucidates the relative importance of electrochemical and mechanical stress-induced degradation mechanisms in real-world operating environments. Opportunities for extending the lifetime of commercial battery systems are explored.

25 ENERGY STORAGE↗
DOE OSTI2016

CAMPUS: Fully Coupled Multiphysics Modeling and Simulation of LWR and FBR Nuclear Fuel Behavior

Nuclear fuels operate in an environment that involves complex multiphysics phenomena, and the multiphysics behavior is often tightly coupled. The prediction of fuel behavior under irradiation involves very complex material behavior that is not seen in any other engineering discipline. Understanding and predicting the evolving material properties and phenomenal behaviors of nuclear fuels are major challenges for fuel design and behavior prediction. The multiphysics behavior is often a tightly coupled thermal, mechanical and chemical phenomenon associated with a large number of control parameters and uncertainties, which requires an advanced fuel performance modeling and simulation capability to improve the existing reactors performance, to address environmental and reactor safety concerns. Nuclear fuel performance modeling and simulation capability is necessary as a result of the high cost and difficulty in experimental measurements. So, a fuel performance code called CityU Advanced Multiphysics Nuclear Fuels Performance with User-defined Simulations (CAMPUS) was developed to predict both light water reactor and fast reactor fuel behavior. An effective approach was developed using self-defined multiphysics models based on the framework of COMSOL Multiphysics to manage the nonlinearities associated with light water reactor and fast reactor fuels performance analysis. The modelling and simulations approach is of particular importance since it demonstrates highly interrelated and nonlinear fuel performance models can be developed and implemented into a multiphysics platform, and thus more efforts can be put into physics model development and improvement. The modelling results can be used to identify the important phenomena and parameters, to direct and design experiments and to assist in post analysis of expensive nuclear experiments for light water reactor and fast reactor nuclear fuel performance analysis. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2010

Physics-based statistical model and simulation method of RF propagation in urban environments

A physics-based statistical model and simulation/modeling method and system of electromagnetic wave propagation (wireless communication) in urban environments. In particular, the model is a computationally efficient close-formed parametric model of RF propagation in an urban environment which is extracted from a physics-based statistical wireless channel simulation method and system. The simulation divides the complex urban environment into a network of interconnected urban canyon waveguides which can be analyzed individually; calculates spectral coefficients of modal fields in the waveguides excited by the propagation using a database of statistical impedance boundary conditions which incorporates the complexity of building walls in the propagation model; determines statistical parameters of the calculated modal fields; and determines a parametric propagation model based on the statistical parameters of the calculated modal fields from which predictions of communications capability may be made.

Pao, Hsueh-Yuan↗
DOE OSTI2017

Search for narrow resonances in dilepton mass spectra in proton-proton collisions at $\sqrt{s}$ = 13 TeV and combination with 8 TeV data

A search for narrow resonances in dielectron and dimuon invariant mass spectra has been performed using data obtained from proton-proton collisions at $ \sqrt{s} = $ 13 TeV collected with the CMS detector. The integrated luminosity for the dielectron sample is 2.7 fb$^{-1}$ and for the dimuon sample 2.9 fb$^{-1}$. The sensitivity of the search is increased by combining these data with a previously analysed set of data obtained at $ \sqrt{s} = $ 8 TeV and corresponding to a luminosity of 20 fb$^{-1}$. No evidence for non-standard-model physics is found, either in the 13 TeV data set alone, or in the combined data set. Upper limits on the product of production cross section and branching fraction have also been calculated in a model-independent manner to enable interpretation in models predicting a narrow dielectron or dimuon resonance structure. Limits are set on the masses of hypothetical particles that could appear in new-physics scenarios. For the $\mathrm{Z}'_{\text{SSM}}$ particle, which arises in the sequential standard model, and for the superstring inspired $\mathrm{Z}'_{\psi}$ particle, 95% confidence level lower mass limits for the combined data sets and combined channels are found to be 3.37 and 2.82 TeV, respectively. The corresponding limits for Kaluza-Klein gravitons arising in the Randall-Sundrum model of extra dimensions with coupling parameters 0.01 and 0.10 are 1.46 and 3.11 TeV, respectively. Lastly, these results significantly extend previous limits.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Scalable Implicit Solvers with Dynamic Mesh Adaptation for a Relativistic Drift-Kinetic Fokker–Planck–Boltzmann Model

In this work we consider a relativistic drift-kinetic model for runaway electrons along with a Fokker–Planck operator for small-angle Coulomb collisions, a radiation damping operator, and a secondary knock-on (Boltzmann) collision source. Here, we develop a new scalable fully implicit solver utilizing finite volume and conservative finite difference schemes and dynamic mesh adaptivity. A new data management framework in the PETSc library based on the p4est library is developed to enable simulations with dynamic adaptive mesh refinement (AMR), distributed memory parallelization, and dynamic load balancing of computational work. This framework and the runaway electron solver building on the framework are able to dynamically capture both bulk Maxwellian at the low-energy region and a runaway tail at the high-energy region. To effectively capture features via the AMR algorithm, a new AMR indicator prediction strategy is proposed that is performed alongside the implicit time evolution of the solution. This strategy is complemented by the introduction of computationally cheap feature-based AMR indicators that are analyzed theoretically. Numerical results quantify the advantages of the prediction strategy in better capturing features compared with nonpredictive strategies; and we demonstrate trade-offs regarding computational costs. The robustness with respect to model parameters, algorithmic scalability, and parallel scalability are demonstrated through several benchmark problems including manufactured solutions and solutions of different physics models. We focus on demonstrating the advantages of using implicit time stepping and AMR for runaway electron simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗