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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Performance analysis of static locking in replicated distributed database systems

Data replication and transaction deadlocks can severely affect the performance of distributed database systems. Many current evaluation techniques ignore these aspects, because it is difficult to evaluate through analysis and time consuming to evaluate through simulation. A technique is used that combines simulation and analysis to closely illustrate the impact of deadlock and evaluate performance of replicated distributed database with both shared and exclusive locks.

Kuang, Yinghong↗
DOE OSTI2020

Rupture Dynamics Simulations of Shallow Crustal Earthquakes on Reverse Slip Faults

The main goal of this study was to perform dynamic rupture simulations in order constrain the characterization of kinematic rupture models implemented in techniques for simulating strong ground motion for crustal earthquakes. First, we investigated the rupture process of the 2008 Iwate-Miyagi Nairiku earthquake by developing a dynamic rupture model on a reverse fault using a trial-and-error technique that produced a slip distribution and near-fault ground motion that matched the recorded ones. The simulations were performed in the frequency range 0-2 Hz, using a 3D staggered grid finite-difference method and a linear slip weakening friction law. Constrained by the observed slip distribution and consistent with dynamic rupture models, the derived kinematic rupture model of the Iwate-Miyagi Nairiku earthquake contains areas with relatively large slip rate, representing strong motion generation areas, set against lower amplitude heterogeneous background slip, and a relatively low slip rate in the weak zone of the top-most crust (upper 3km). Second, we performed rupture dynamics modeling to constrain shallow slip characterization in rupture models for strike-slip crustal earthquakes. The objective was to establish general rules about the characterization of slip rate function and slip at shallow depths and in the strong motion generation areas (SMGAs). The simulations of spontaneous rupture were performed in the frequency range 0-2.0Hz, using a 3D staggered-grid finite-difference method and a layer over half-space 1D crustal velocity model with a minimum shear-wave velocity of 2.8 km/s. In order to account for changes in material ductility and reduction of stress drop, observed in the shallow crust (upper 3-5 km), and the transition from ductile state to brittle state in the upper seismogenic zone, in our stress models we included a shallow weak zone (<4km). In this zone the stress drop was set to zero at the free surface and gradually increased with depth, while the slip weakening distance was set to 75 cm at the free surface and decreased to 50 cm at the base of the weak zone. As in the case of reverse faulting during the Iwate-Miyagi Nairiku earthquake, from these computations we found a systematic change in the shape of the slip-rate function, from Kostrov-type in the deeper part of the fault to a more symmetric cosine-type in the upper few kilometers, near the free-surface. Moreover, the average slip duration in the weak zone, with respect to slip duration in the deeper parts of the fault, increases by at most a factor of 1.5. We found a systematic and gradual change in the shape of the slip-rate function from Kostrov-type in the asperity areas (SMGAs), to more symmetric cosine-type in the upper few km near the free-surface, on the long period motion generation area (LMGA). The effective rise time in the LMGA, with respect to that in the SMGAs, increases by at most a factor of 2. Effective rise time is the time difference between the time at which the slip rate drops to a level that is equal to 25% of its peak and the onset time of the signal. In addition, the slip in the LMGA located above the SMGAs is almost the same as the one in the SMGAs, and about 1.5 times larger than the average slip.

58 GEOSCIENCES↗
NASA NTRS1987

Approximate Simulation of Turbulence

Computed spectra resemble von Karman spectra of frequencies of interest. Numerical technique yields simulated atmospheric-turbulence spectra that closely approximates von Karman spectra within frequency ranges of interest for aircraft response. Suitable for computation in that they represent stable systems and roll off as f-2 at high frequencies outside range of interest.

Campbell, C. W.↗
NASA NTRS1960

A Radiant Heater to Simulate Aerodynamic Heating in a Wind Tunnel

A recently developed radiant-heating test technique for simulation of aerodynamic heating in wind tunnel is describes. The heating device, which utilized quartz-tube lamps, was operated successfully while exposed directly to a supersonic airstream. Tests were made on a calibration panel, and experimental temperature and pressure data are presented. Results indicate that initial heating rates of about 26 Btu/(sq ft) (sec) are obtainable at a distance of 12 inches from the heater. Further applications of the basic design are discussed briefly.

Trussell, Donald H.↗
NASA NTRS2002

Analysis of Composite Skin-Stiffener Debond Specimens Using Volume Elements and a Shell/3D Modeling Technique

The debonding of a skin/stringer specimen subjected to tension was studied using three-dimensional volume element modeling and computational fracture mechanics. Mixed mode strain energy release rates were calculated from finite element results using the virtual crack closure technique. The simulations revealed an increase in total energy release rate in the immediate vicinity of the free edges of the specimen. Correlation of the computed mixed-mode strain energy release rates along the delamination front contour with a two-dimensional mixed-mode interlaminar fracture criterion suggested that in spite of peak total energy release rates at the free edge the delamination would not advance at the edges first. The qualitative prediction of the shape of the delamination front was confirmed by X-ray photographs of a specimen taken during testing. The good correlation between prediction based on analysis and experiment demonstrated the efficiency of a mixed-mode failure analysis for the investigation of skin/stiffener separation due to delamination in the adherents. The application of a shell/3D modeling technique for the simulation of skin/stringer debond in a specimen subjected to three-point bending is also demonstrated. The global structure was modeled with shell elements. A local three-dimensional model, extending to about three specimen thicknesses on either side of the delamination front was used to capture the details of the damaged section. Computed total strain energy release rates and mixed-mode ratios obtained from shell/3D simulations were in good agreement with results obtained from full solid models. The good correlations of the results demonstrated the effectiveness of the shell/3D modeling technique for the investigation of skin/stiffener separation due to delamination in the adherents.

Krueger, Ronald↗
DOE OSTI2019

Kinetic Monte Carlo Simulations of Chemical Reactions on Surfaces

Lattice based kinetic Monte Carlo (kMC) simulations are a powerful tool for micro-kinetic modeling. The kinetic Monte Carlo technique stochastically simulates chemical reaction processes (e.g. adsorption, desorption, diffusion), where the probability of a given reaction process being selected is weighted by its rate constant. The open source software package, KMOS1, allows fast construction of kMC simulations by automatically implementing a computationally efficient kMC framework, thus allowing the researcher to focus on accurate parameterization and formulation of the kinetic model. From this, the spatiotemporal evolution (e.g. concentration, surface configuration, turnover frequencies) of crystal surfaces or bulk crystalline structures is obtained. KMOS uses the variable step-size method implementation of kMC. At each step, the VSSM updates available events, calculates the corresponding transition rates and simulation time, and selects one of the available events. The lattice based kMC technique has many potential applications within SRNL where chemical kinetics are of interest. By transitioning through time along a trajectory of configuration space, fundamental insights to a system's dominant reactions and parameters can be gained, leading to improved materials and process design. In this work, we have established capabilities for fast implementation of kMC simulations through the installation and testing of the KMOS software on SRNL high performance computing resources. The parameterization of kMC simulations is often performed from first-principles energetic calculations. For the purposes of this work, the test cases use arbitrary species and thus, have arbitrary parameterization. In order to demonstrate the use of KMOS, two primary test cases are shown. Case 1 involves simple adsorption and desorption. Case 2 involves a slightly more complex mechanism. The evolution of the surface concentration and the final surface configuration for simulation Case 2 is shown. Rate-limiting processes and rate-limiting configurations are not always known or understood, but kMC provides information pertaining to both. The capability to implement efficient micro-kinetic models using the kinetic Monte Carlo technique has been established through the testing and installation of KMOS on SRNL HPC resources.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1978

Measurement of transient strain and surface temperature on simulated turbine blades using noncontacting techniques

Noncontacting techniques were used to measure strain and temperature in thermally cycled simulated turbine blades. An electro-optical extensometer was used to measure the displacement between parallel targets mounted on the leading edge of the blades throughout a complete heating and cooling cycle. An infrared photographic pyrometry method was used to measure blade steady state surface temperature. The blade was cyclically heated and cooled by moving it into and out of a Mach 1 hot-gas stream. Transient leading edge strain and steady state surface temperature distributions are presented for blades of three different configurations.

Calfo, F. D.↗
NASA NTRS2002

Resource Selection Using Execution and Queue Wait Time Predictions

Computational grids provide users with many possible places to execute their applications. We wish to help users select where to run their applications by providing predictions of the execution times of applications on space shared parallel computers and predictions of when scheduling systems for such parallel computers will start applications. Our predictions are based on instance based learning techniques and simulations of scheduling algorithms. We find that our execution time prediction techniques have an average error of 37 percent of the execution times for trace data recorded from SGI Origins at NASA Ames Research Center and that this error is 67 percent lower than the error of user estimates. We also find that the error when predicting how long applications will wait in scheduling queues is 95 percent of mean queue wait times when using our execution time predictions and this is 57 percent lower than if we use user execution time estimates.

Warren, Smith↗
NASA NTRS2002

Resource Selection Using Execution and Queue Wait Time Predictions

Computational grids provide users with many possible places to execute their applications. We wish to help users select where to run their applications by providing predictions of the execution times of applications on space shared parallel computers and predictions of when scheduling systems for such parallel computers will start applications. Our predictions are based on instance based learning techniques and simulations of scheduling algorithms. We find that our execution time prediction techniques have an average error of 37 percent of the execution times for trace data recorded from SGI Origins at NASA Ames Research Center and that this error is 67 percent lower than the error of user estimates. We also find that the error when predicting how long applications will wait in scheduling queues is 95 percent of mean queue wait times when using our execution time predictions and this is 57 percent lower than if we use user execution time estimates.

Smith, Warren↗
NASA NTRS2000

IFSAR Simulation Using the Shooting and Bouncing Ray Technique

Interferometric Synthetic Aperture Radar (IFSAR) is a technique that allows an automated way to carry out terrain mapping. IFSAR is carried out by first generating a SAR image pair from two antennas that are spatially separated. The phase difference between the SAR image pair is proportional to the topography. After registering the SAR images, the difference in phase in each pixel is extracted to generate an interferogram. Since the phase can only be measured within 2pi radians, phase unwrapping is carried out to extract the absolute phase for each pixel that will be proportional to the local height. While IFSAR algorithm is typically applied to measurement data, it is useful to develop an IFSAR simulator to develop a better understanding of the IFSAR technique. The IFSAR simulator can be used in choosing system parameters, experimenting with processing procedures and mission planning. In this paper we will present an IFSAR simulation methodology to simulate the interferogram based on the shooting and bouncing ray (SBR) technique. SBR is a standard ray-tracing technique used to simulate scattering from large, complex targets. SBR is carried out by shooting rays at the target or scene. At the exit point of each ray, a ray-tube integration is done to find its contribution to the total field. A fast algorithm has been developed for the SBR for simulating SAR images of complex targets. In the IFSAR simulation, we build upon the fast SAR simulation technique. Given the antenna pair configuration, radar system parameters and the geometrical description of the scene, we first simulate two SAR images from each antenna. After post processing the two SAR images, we generate an interferogram. Phase unwrapping is then performed on the interferogram to arrive at the desired terrain map. We will present results from the SBR-based IFSAR simulator. The results will include terrain map reconstruction of urban environments. The reconstruction will be compared to the ground truth to examine the fidelity of the simulation. We will also investigate the effect of multi-bounce scattering in urban environments on phase unwrapping and reconstruction.

Houshmand, Bijan↗
DOE OSTI2022

Path Integral Monte Carlo Simulations of Iron Plasmas (Final Technical Report)

This documents is the final technical report for our grant entitled "Path Integral Monte Carlo Simulations of Iron Plasmas" that focused on developing path integral Monte Carlo (PIMC) computer simulations. This techniques will be developed to study plasmas composed of heavier elements including iron and other third row elements. Equations of state (EOS) and transport properties will be derived in the regime of warm dense matter (WDM) and dense plasmas where existing first-principles methods cannot be applied. While standard density functional theory (DFT) has been used to accurately predict the structure of many solids and liquids up to temperatures on the order of 100,000 K, this method is not applicable at much higher temperature because the number of partially occupied electronic orbitals reaches intractably large numbers or the use of finite-temperature free energy functionals in orbital-free DFT introduces an uncontrolled approximation. Here we focus on PIMC methods that become more and more efficient with increasing temperatures and still include all electronic correlation effects. In this approach, electronic excitations increase the efficiency rather than reduce it. While it had commonly been assumed this method could only be applied to elements without core electrons, we showed that PIMC with free-particle nodes works well for first-row elements (PRL 108 (2012) 115502). Most recently, we extended the applicability range of all-electron PIMC to second-row elements by adopting localized nodal surfaces (PRL 115 (2015) 176403). To simulate third-row elements efficiently under WDM conditions, we propose a new method to remove core electrons by introducing pseudo-nodes. We explain our approach step by step and present preliminary results. We focus our method development on getting PIMC simulations of iron to work because of its fundamental importance for WDM and astrophysics. Then we move on to krypton and copper-doped beryllium, a ICF ablator material. We plan to continue working on key second-row material such as Na, Mg, MgO, Al, silica, and silicon-doped plastic ablators. Our collaborators at LLNL, will use our PIMC EOS data both as comparisons to existing semi-empirical, EOS-generating schemes, and as input for continuum radiation hydrodynamics simulations. We will establish an efficient pipeline from PIMC to macroscopic continuum studies of materials response. An emphasis will be placed on benchmarking such methods for plasmas of heavy elements at the very high temperatures (~100 eV) and low densities that are generated when Hohlraum radiation heats the ablator material in indirect drive laser experiments. Results from changes to the EOS will be of immeasurable importance to the designers at the National Ignition Facility (NIF) and at other facilities. Starting with our EOS of Cu-doped Be, our second collaborator at LLE, will perform real-time simulations of laser fusion experiments at the Omega laser and at the NIF to determine how sensitive the compression path depends on the ablator EOS. Since our collaborator also has experience in performing orbital-free DFT calculations, we propose to compare predictions from this method with PIMC results. In joint publications, we plan to analyze the accuracy of different free-energy functionals in order to understand why existing orbital-free DFT calculations do not predict compression peaks along the shock Hugoniot curve that we see with PIMC. The peaks are caused by the ionization of various electron shells. Their accurate characterization is important to compare with experimental results. We will break new ground by developing PIMC techniques that can simulate iron and all other third row elements in the plasma and WDM regimes. We introduce the concept of pseudo-nodes for the efficient treatment of the core-electrons. The EOS and transport properties will be derived and published online in the form of a new WDM database. Our PIMC EOS calculations will benchmark and possibly replace semi-analytical EOS tables like QEOS or SESAME, which will impact the hydrocode simulation community and will affect the design of NIF targets. Our PIMC results will help to improve the accuracy of orbital-free DFT simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1985

Development and testing of a simple assimilation technique to derive average wind fields from simulated scatterometer data

A simple algorithm is developed and tested to derive a regularly spaced wind field in a limited area from simulated multiorbit scatterometer data. The data are generated by sampling a time-varying known wind field, the 1000-mb FGGE data, from a simulated scatterometer. A simple assimilation technique is used to derive a regularly spaced (100-km grid) wind field representation of two-day averages from the simulated data. Several test cases are considered, and it is noted that the assimilation technique might be applicable to large-scale ocean or atmospheric models.

Legler, D. M.↗
DOE OSTI2022

Kinetic theory of particle-in-cell simulation plasma and the ensemble averaging technique

Abstract We derive the kinetic theory of fluctuations in physically and numerically stable particle-in-cell (PIC) simulations of electrostatic plasmas. The starting point is the single-time correlation at the start of the simulation between the statistical fluctuations of the weighted densities of macroparticle centers in the plasma particle phase-space. The fluctuations are associated with different initial conditions, typically due to the random initial conditions (in velocity space) of the macroparticles/simulation plasma, assigned according to their initial distribution of probability. The single-time correlations at all time steps and in each spatial grid cell are then determined from the Laplace–Fourier transforms of the discretized Klimontovich-like equation for the macroparticles and Maxwell’s equations for the fields, as computed by modern PIC codes. We recover the expressions for the electrostatic field and the plasma particle density fluctuation autocorrelation spectra as well as the kinetic equations describing the average evolution of PIC-simulated plasma particles, first derived by Langdon (1970b Proc. 4th Conf. Numerical Simulation of Plasmas ) using a test macroparticle approach perturbing a discretized Vlasovian plasma and then averaging the obtained physical quantity over the initial macroparticle velocity distribution. We generalize and extend these results to the modern algorithms in PIC codes using arbitrary macroparticle weights. Analytical estimates of statistical fluctuation amplitudes are derived as a function of the plasma simulation parameters, using the central limit theorem in the limit of a large number of macroparticles per cell. The theory is then used to analyze the ensemble averaging technique of PIC simulations where statistical averages are performed over ensembles of PIC simulations, modeling the same plasma physics problem but using different statistical realizations of the initial distribution functions of the macroparticles. This method is illustrated by linear Landau damping uncovering (from noise, which is usually considered numerical) the physical fluctuations driven by a single small amplitude electrostatic wave perturbing a PIC simulation plasma in equilibrium.

fluctuations correlations↗
DOE OSTI2020

Development of a Time-Height Profile Assimilation Technique for Large-Eddy Simulation

Mesoscale-to-microscale coupling (MMC) aims to address the limited scope of traditional large-eddy simulations by driving the microscale flow with information concerning large-scale weather patterns provided by mesoscale models. We present a new offline MMC technique for horizontally homogeneous microscale flow conditions, in which internal forcing terms are computed based on mesoscale time–height profiles of mean-flow quantities. The advantage of such an approach is that it can be used to drive a microscale simulation with either mesoscale or observational data, and that it does not rely on specific terms in the mesoscale budget equations, which are typically not part of the default output of a mesoscale solver. The performance of the proposed profile assimilation technique is assessed based on the simulation of a typical diurnal cycle over the Scaled Wind Farm Technology site in west Texas. Results indicate that simple data assimilation techniques lead to unphysically high levels of shear and turbulence caused by the algorithm’s inability to cope with inaccuracies in the mesoscale time–height profiles. Modifying the algorithm to account for vertical coherence in the mesoscale source terms gives the microscale solver a greater ability to correct the provided mesoscale time–height profiles, leading to improved predictions of shear and turbulence statistics. The resulting turbulence statistics are in good agreement with meteorological tower observations and simulation results obtained with state-of-the-art coupling techniques using mesoscale budget components.

data assimilation↗
DOE OSTI2025

Reweighting simulated events using machine-learning techniques in the CMS experiment

Data analyses in particle physics rely on an accurate simulation of particle collisions and a detailed simulation of detector effects to extract physics knowledge from the recorded data. Event generators together with a GEANT -based simulation of the detectors are used to produce large samples of simulated events for analysis by the LHC experiments. These simulations come at a high computational cost, where the detector simulation and reconstruction algorithms have the largest CPU demands. This article describes how machine-learning (ML) techniques are used to reweight simulated samples obtained with a given set of parameters to samples with different parameters or samples obtained from entirely different simulation programs. The ML reweighting method avoids the need for simulating the detector response multiple times by incorporating the relevant information in a single sample through event weights. Results are presented for reweighting to model variations and higher-order calculations in simulated top quark pair production at the LHC. This ML-based reweighting is an important element of the future computing model of the CMS experiment and will facilitate precision measurements at the High-Luminosity LHC.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Deep clustering of protein folding simulations

Background: We investigate the problem of clustering biomolecular simulations using deep learning techniques. Since biomolecular simulation datasets are inherently high dimensional, it is often necessary to build low dimensional representations that can be used to extract quantitative insights into the atomistic mechanisms that underlie complex biological processes. Results: We use a convolutional variational autoencoder (CVAE) to learn low dimensional, biophysically relevant latent features from long time-scale protein folding simulations in an unsupervised manner. We demonstrate our approach on three model protein folding systems, namely Fs-peptide (14 μs aggregate sampling), villin head piece (single trajectory of 125 μs) and β- β- α (BBA) protein (223 + 102 μs sampling across two independent trajectories). In these systems, we show that the CVAE latent features learned correspond to distinct conformational substates along the protein folding pathways. The CVAE model predicts, on average, nearly 89% of all contacts within the folding trajectories correctly, while being able to extract folded, unfolded and potentially misfolded states in an unsupervised manner. Further, the CVAE model can be used to learn latent features of protein folding that can be applied to other independent trajectories, making it particularly attractive for identifying intrinsic features that correspond to conformational substates that share similar structural features. Conclusions: Together, we demonstrate that the CVAE model can quantitatively describe complex biophysical processes such as protein folding.

59 BASIC BIOLOGICAL SCIENCES↗