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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
DOE OSTI2019

A generalized massively parallel ultra-high order FFT-based Maxwell solver

Dispersion-free ultra-high order FFT-based Maxwell solvers have recently proven to be paramount to a large range of applications, including the high-fidelity modeling of high-intensity laser–matter interactions with Particle-In-Cell (PIC) codes. To enable a massively parallel scaling of these solvers, a novel parallelization technique was recently proposed, which consists in splitting the simulation domain into several processor sub-domains, with guard regions appended at each sub-domain boundary. Maxwell's equations are advanced independently on each sub-domain using local shared-memory FFTs (instead of a single distributed global FFT). This implies small truncation errors at sub-domain boundaries, the amplitude of which depends on guard regions sizes and order of the Maxwell solver. For moderate guard region sizes, this ’local’ technique proved to be highly scalable on up to a million cores and notably enabled the 3D modeling of so-called plasma mirrors, for which 8 guard cells only were enough to prevent truncation error growth. Yet, for other applications, the required number of guard cells might be much higher, which would severely limit the parallel efficiency of this technique due to the large volume of guard cells to be exchanged between sub-domains. In this context, we propose a novel parallelization technique that ensures very good scaling of FFT-based solvers with an arbitrarily high number of guard cells. Our ’hybrid’ technique consists in performing distributed FFTs on local groups of processors with guard regions now appended to boundaries of each group of processors. It uses a dual domain decomposition method for the Maxwell solver and other parts of the PIC cycle to keep the simulation load-balanced. This ’hybrid’ technique was implemented in the open source exascale library PICSAR. Benchmarks show that for a large number of guard cells (>16), the ’hybrid’ technique offers up to ×3 speed-up and ×8 memory savings compared to the ’local’ one.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

SU-F-T-370: A Fast Monte Carlo Dose Engine for Gamma Knife

Purpose: To develop a fast Monte Carlo dose calculation algorithm for Gamma Knife. Methods: To make the simulation more efficient, we implemented the track repeating technique on GPU. We first use EGSnrc to pre-calculate the photon and secondary electron tracks in water from two mono-energy photons of 60Co. The total photon mean free paths for different materials and energies are obtained from NIST. During simulation, each entire photon track was first loaded to shared memory for each block, the incident original photon was then splitted to Nthread sub-photons, each thread transport one sub-photon, the Russian roulette technique was applied for scattered and bremsstrahlung photons. The resultant electrons from photon interactions are simulated by repeating the recorded electron tracks. The electron step length is stretched/shrunk proportionally based on the local density and stopping power ratios of the local material. Energy deposition in a voxel is proportional to the fraction of the equivalent step length in that voxel. To evaluate its accuracy, dose deposition in a 300mm*300mm*300mm water phantom is calculated, and compared to EGSnrc results. Results: Both PDD and OAR showed great agreements (within 0.5%) between our dose engine result and the EGSnrc result. It only takes less than 1 min for every simulation, being reduced up to ∼40 times compared to EGSnrc simulations. Conclusion: We have successfully developed a fast Monte Carlo dose engine for Gamma Knife.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Electric Grid Expansion Planning with High Levels of Variable Generation

Renewables are taking a large proportion of generation capacity in U.S. power grids. As their randomness has increasing influence on power system operation, it is necessary to consider their impact on system expansion planning. To this end, this project studies the generation and transmission expansion co-optimization problem of the US Eastern Interconnection (EI) power grid with a high wind power penetration rate. In this project, the generation and transmission expansion problem for the EI system is modeled as a mixed-integer programming (MIP) problem. This study analyzed a time series creation method to capture the diversity of load and wind power across balancing regions in the EI system. The obtained time series can be easily introduced into the MIP co-optimization problem and then solved robustly through available MIP solvers. Simulation results show that the proposed time series generation method and the expansion co-optimization model and can improve the expansion result significantly after considering the diversity of wind and load across EI regions. The improved expansion plan that combines generation and transmission will aid system planners and policy makers to maximize the social welfare. This study shows that modelling load and wind variations and diversities across balancing regions will produce significantly different expansion result compared with former studies. For example, if wind is modeled in more details (by increasing the number of wind output levels) so that more wind blocks are considered in expansion planning, transmission expansion will be larger and the expansion timing will be earlier. Regarding generation expansion, more wind scenarios will slightly reduce wind generation expansion in the EI system and increase the expansion of other generation such as gas. Also, adopting detailed wind scenarios will reveal that it may be uneconomic to expand transmission networks for transmitting a large amount of wind power through a long distance in the EI system. Incorporating more details of renewables in expansion planning will inevitably increase the computational burden. Therefore, high performance computing (HPC) techniques are urgently needed for power system operation and planning optimization. As a scoping study task, this project tested some preliminary parallel computation techniques such as breaking down the simulation task into several sub-tasks based on chronology splitting or sample splitting, and then assigning these sub-tasks to different cores. Testing results show significant time reduction when a simulation task is split into several sub-tasks for parallel execution.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Resiliency in numerical algorithm design for extreme scale simulations

Here this work is based on the seminar titled ‘Resiliency in Numerical Algorithm Design for Extreme Scale Simulations’ held March 1–6, 2020, at Schloss Dagstuhl, that was attended by all the authors. Advanced supercomputing is characterized by very high computation speeds at the cost of involving an enormous amount of resources and costs. A typical large-scale computation running for 48 h on a system consuming 20 MW, as predicted for exascale systems, would consume a million kWh, corresponding to about 100k Euro in energy cost for executing 10 23 floating-point operations. It is clearly unacceptable to lose the whole computation if any of the several million parallel processes fails during the execution. Moreover, if a single operation suffers from a bit-flip error, should the whole computation be declared invalid? What about the notion of reproducibility itself: should this core paradigm of science be revised and refined for results that are obtained by large-scale simulation? Naive versions of conventional resilience techniques will not scale to the exascale regime: with a main memory footprint of tens of Petabytes, synchronously writing checkpoint data all the way to background storage at frequent intervals will create intolerable overheads in runtime and energy consumption. Forecasts show that the mean time between failures could be lower than the time to recover from such a checkpoint, so that large calculations at scale might not make any progress if robust alternatives are not investigated. More advanced resilience techniques must be devised. The key may lie in exploiting both advanced system features as well as specific application knowledge. Research will face two essential questions: (1) what are the reliability requirements for a particular computation and (2) how do we best design the algorithms and software to meet these requirements? While the analysis of use cases can help understand the particular reliability requirements, the construction of remedies is currently wide open. One avenue would be to refine and improve on system- or application-level checkpointing and rollback strategies in the case an error is detected. Developers might use fault notification interfaces and flexible runtime systems to respond to node failures in an application-dependent fashion. Novel numerical algorithms or more stochastic computational approaches may be required to meet accuracy requirements in the face of undetectable soft errors. These ideas constituted an essential topic of the seminar. The goal of this Dagstuhl Seminar was to bring together a diverse group of scientists with expertise in exascale computing to discuss novel ways to make applications resilient against detected and undetected faults. In particular, participants explored the role that algorithms and applications play in the holistic approach needed to tackle this challenge. This article gathers a broad range of perspectives on the role of algorithms, applications and systems in achieving resilience for extreme scale simulations. The ultimate goal is to spark novel ideas and encourage the development of concrete solutions for achieving such resilience holistically.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Predictive dynamic wetting, fluid–structure interaction simulations for braze run-out

Brazing and soldering are metallurgical joining techniques that use a wetting molten metal to create a joint between two faying surfaces. Here, the quality of the brazing process depends strongly on the wetting properties of the molten filler metal, namely the surface tension and contact angle, and the resulting joint can be susceptible to various defects, such as run-out and underfill, if the material properties or joining conditions are not suitable. In this work, we implement a finite element simulation to predict the formation of such defects in braze processes. This model incorporates both fluid–structure interaction through an arbitrary Eulerian–Lagrangian technique and free surface wetting through conformal decomposition finite element modeling. Upon validating our numerical simulations against experimental run-out studies on a silver-Kovar system, we then use the model to predict run-out and underfill in systems with variable surface tension, contact angles, and applied pressure. Finally, we consider variable joint/surface geometries and show how different geometrical configurations can help to mitigate run-out. This work aims to understand how brazing defects arise and validate a coupled wetting and fluid–structure interaction simulation that can be used for other industrial problems.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Implicit sampling combined with reduced order modeling for the inversion of vadose zone hydrological data

Bayesian inverse modeling techniques are computationally expensive because many forward simulations are needed when sampling the posterior distribution of the parameters. Here, in this paper, we combine the implicit sampling method and generalized polynomial chaos expansion (gPCE) to significantly reduce the computational cost of performing Bayesian inverse modeling. There are three steps in this approach: (1) find the maximizer of the likelihood function using deterministic approaches; (2) construct a gPCE-based surrogate model using the results from a limited number of forward simulations; and (3) efficiently sample the posterior distribution of the parameters using implicit sampling method. The cost of constructing the gPCE-based surrogate model is further decreased by using sparse Bayesian learning to reduce the number of gPCE coefficients that have to be determined. We demonstrate the approach for a synthetic ponded infiltration experiment simulated with TOUGH2. The surrogate model is highly accurate with mean relative error that is < 0.035% in predicting saturation and < 0.25% in predicting the likelihood function. The posterior distribution of the parameters obtained using our proposed technique is nearly indistinguishable from the results obtained from either an implicit sampling method or a Markov chain Monte Carlo method utilizing the full mode.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Modeling of a Networked Community Microgrid with High Solar Penetration Considering Control Dynamics of Inverter-Based Resources

Microgrids help facilitate the integration of renewable energy in distribution-level grids and increase the resilience of the electric grid to extreme weather, especially in rural areas. Compared to traditional microgrids, a networked microgrid leverages multiple grid-forming sources to form a potential meshed grid and is more flexible in operation. This paper demonstrates the simulation modeling of an actual networked microgrid located in Adjuntas, Puerto Rico. The model contains representations of power inverters that connect the battery energy storage systems and photovoltaic generation systems to the networked microgrid and is capable of simulating fast grid transients as well as long-term operation of the networked microgrid. The modeling technique for power inverters allows the time-efficient simulation of the microgrid with a minimal penalty on model accuracy.

Li, Dingrui↗
DOE OSTI2023

High-Performance Computing Based EMT Simulation of Large PV or Hybrid PV Plants

Faults in the transmission grid have led to reduced power generation from power electronics resources that are typically not connected to the faulted transmission line. In many of the cases, partial loss of power is observed within the power electronics resources like large photovoltaic (PV) power plants. This phenomena is not captured in existing simulation models and/or simulators. High-fidelity switched system electromagnetic transient (EMT) dynamic models of PV power plants can improve the fidelity of models available for accurate analysis of the impact on PV plants during simulation of faults. However, these models are extremely computationally expensive and take a long time to simulate. Long simulation times limit the ability to use these models as larger regions are studied in EMT simulations with more power electronics resources. In this paper, numerical simulation algorithms are combined with high-performance computing techniques and applied to the high-fidelity switched system EMT model of PV plants. Using these techniques, a speed-up of up to 58x is obtained, while preserving the accuracy of the simulation at greater than 98%.

Debnath, Suman↗
DOE OSTI2022

ADDGALS: Simulated Sky Catalogs for Wide Field Galaxy Surveys

Abstract We present a method for creating simulated galaxy catalogs with realistic galaxy luminosities, broadband colors, and projected clustering over large cosmic volumes. The technique, denoted Addgals (Adding Density Dependent GAlaxies to Lightcone Simulations), uses an empirical approach to place galaxies within lightcone outputs of cosmological simulations. It can be applied to significantly lower-resolution simulations than those required for commonly used methods such as halo occupation distributions, subhalo abundance matching, and semi-analytic models, while still accurately reproducing projected galaxy clustering statistics down to scales of r ∼ 100 h −1 kpc . We show that Addgals catalogs reproduce several statistical properties of the galaxy distribution as measured by the Sloan Digital Sky Survey (SDSS) main galaxy sample, including galaxy number densities, observed magnitude and color distributions, as well as luminosity- and color-dependent clustering. We also compare to cluster–galaxy cross correlations, where we find significant discrepancies with measurements from SDSS that are likely linked to artificial subhalo disruption in the simulations. Applications of this model to simulations of deep wide-area photometric surveys, including modeling weak-lensing statistics, photometric redshifts, and galaxy cluster finding, are presented in DeRose et al., and an application to a full cosmology analysis of Dark Energy Survey (DES) Year 3 like data is presented in DeRose et al. We plan to publicly release a 10,313 square degree catalog constructed using Addgals with magnitudes appropriate for several existing and planned surveys, including SDSS, DES, VISTA, Wide-field Infrared Survey Explorer, and Rubin Observatory’s Legacy Survey of Space and Time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

EXTINCTION LAWS TOWARD STELLAR SOURCES WITHIN A DUSTY CIRCUMSTELLAR MEDIUM AND IMPLICATIONS FOR TYPE IA SUPERNOVAE

Many astronomical objects are surrounded by dusty environments. In such dusty objects, multiple scattering processes of photons by circumstellar (CS) dust grains can effectively alter extinction properties. In this paper, we systematically investigate the effects of multiple scattering on extinction laws for steady-emission sources surrounded by the dusty CS medium using a radiation transfer simulation based on the Monte Carlo technique. In particular, we focus on whether and how the extinction properties are affected by properties of CS dust grains by adopting various dust grain models. We confirm that behaviors of the (effective) extinction laws are highly dependent on the properties of CS grains, especially the total-to-selective extinction ratio R{sub V}, which characterizes the extinction law and can be either increased or decreased and compared with the case without multiple scattering. We find that the criterion for this behavior is given by a ratio of albedos in the B and V bands. We also find that either small silicate grains or polycyclic aromatic hydrocarbons are necessary for realizing a low value of R{sub V} as often measured toward SNe Ia if the multiple scattering by CS dust is responsible for their non-standard extinction laws. Using the derived relations between the properties of dust grains and the resulting effective extinction laws, we propose that the extinction laws toward dusty objects could be used to constrain the properties of dust grains in CS environments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Harnessing Data Movement in Virtual Clusters for In-Situ Execution

As a result of increasing data volume and velocity, Big Data science at exascale has shifted towards the in-situ paradigm, where large scale simulations run concurrently alongside data analytics. With in-situ, data generated from simulations can be processed while still in memory, thereby avoiding the slow storage bottleneck. However, running simulations and analytics together on shared resources will likely result in substantial contention if left unmanaged, as demonstrated in this work, leading to much reduced efficiency of simulations and analytics. Recently, virtualization technologies such as Linux containers have been widely applied to data centers and physical clusters to provide highly efficient and elastic resource provisioning for consolidated workloads including scientific simulations and data analytics. In this paper, we investigate to facilitate network traffic manipulation and reduce mutual interference on the network for in-situ applications in virtual clusters. In order to dynamically allocate the network bandwidth when it is needed, we adopt SARIMA-based techniques to analyze and predict MPI traffic issued from simulations. Although this can be an effective technique, the naïve usage of network virtualization can lead to performance degradation for bursty asynchronous transmissions within an MPI job. Here, we analyze and resolve this performance degradation in virtual clusters.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

High-rate strength response of tantalum from dynamic hole closure experiments

The science and engineering communities have significant interest in experimental platforms to evaluate and improve models for dynamic material deformation. While well-developed platforms exist, there are still gaps to fill for strain and strain rate conditions accessed during impact and other high-rate loading scenarios. To fill one such gap for strength measurements, a platform was recently developed that accesses high strain rate (≥ 10 5 /s) and large strain (≥ 50%) conditions by measuring the transient closure of a cylindrical hole using in situ x-ray imaging. In the work reported here, further refinement of the platform is performed to reduce the potential effects of porosity and anelasticity on the measurement. This helps us to isolate the strength effects that are the focus of the experiment. The updated experimental configuration employs a two-layer flyer design and elongated target to reduce the magnitude of the tensile excursions associated with rarefaction wave interactions. This allows for a more direct assessment of strength models commonly used for dynamic simulations of metals. Here we apply the new technique to well-characterized tantalum material, allowing for a robust connection to other experimental techniques. Deformation localization can be a concern in large strain experiments, and to help inform future use of the experimental platform, we use simulations with a sub-zone treatment of shear banding to explore potential localization behavior. Here we develop and utilize an experimental configuration with improved isolation of strength effects that can be applied to an expanded range of materials.

42 ENGINEERING↗
DOE OSTI2023

Convective and Turbulent Motions in Nonprecipitating Cu. Part III: Characteristics of Turbulence Motions

Velocity field in a nonprecipitating Cu under BOMEX conditions, simulated by SAM with 10-m resolution and spectral bin microphysics is separated into the convective part and the turbulent part, using a wavelet filtering. In Part II of the study properties of convective motions of this Cu were investigated. Here in Part III of the study, the parameters of cloud turbulence are calculated in the cloud updraft zone at different stages of cloud development. The main points of this study are (i) application of a fine-scale LES model of a single convective cloud allowed a direct estimation of turbulence parameters using the resolved flow in the cloud and (ii) the separation of the resolved flow into the turbulence flow and the nonturbulence flow allowed us to estimate different turbulent parameters with sufficient statistical accuracy. We calculated height and time dependences of the main turbulent parameters such as turbulence kinetic energy (TKE), spectra of TKE, dissipation rate, and the turbulent coefficient. It was found that the main source of turbulence in the cloud is buoyancy whose contribution is described by the buoyancy production term (BPT). The shear production term (SPT) increases with height and reaches its maximum near cloud top, and so does BPT. In agreement with the behavior of BPT and SPT, turbulence in the lower cloud part (below the inversion level) is weak and hardly affects the processes of mixing and entrainment. The fact that BPT is larger than SPT determines many properties of cloud turbulence. For instance, the turbulence is nonisotropic, so the vertical component of TKE is substantially larger than the horizontal components. Another consequence of the fact that BPT is larger than STP manifests itself in the finding that the turbulence spectrum largely obeys the -11/5 Bolgiano–Obukhov scaling. The classical Kolmogorov -5/3 scaling dominates for the low part of a cloud largely at the dissolving stage of cloud evolution. Using the spectra obtained we evaluated an “effective” dissipation rate which increases with height from nearly zero at cloud base up to 20 cm 2 s -3 near cloud top. The coefficient of turbulent diffusion was found to increase with height and ranged from 5 m 2 s -1 near cloud base to 25 m 2 s -1 near cloud top. In conclusion, the possible role of turbulence in the process of lateral entrainment and mixing is discussed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Determining Star Formation Thresholds from Observations

Most gas in giant molecular clouds is relatively low-density and forms star inefficiently, converting only a small fraction of its mass to stars per dynamical time. However, star formation models generally predict the existence of a threshold density above which the process is efficient and most mass collapses to stars on a dynamical timescale. A number of authors have proposed observational techniques to search for a threshold density above which star formation is efficient, but it is unclear which of these techniques, if any, are reliable. In this paper we use detailed simulations of turbulent, magnetised star-forming clouds, including stellar radiation and outflow feedback, to investigate whether it is possible to recover star formation thresholds using current observational techniques. Using mock observations of the simulations at realistic resolutions, we show that plots of projected star formation efficiency per free-fall time ϵff can detect the presence of a threshold, but that the resolutions typical of current dust emission or absorption surveys are insufficient to determine its value. In contrast, proposed alternative diagnostics based on a change in the slope of the gas surface density versus star formation rate surface density (Kennicutt-Schmidt relation) or on the correlation between young stellar object counts and gas mass as a function of density are ineffective at detecting thresholds even when they are present. The signatures in these diagnostics sometimes taken as indicative of a threshold in observations, which we generally reproduce in our mock observations, do not prove to correspond to real physical features in the 3D gas distribution.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Inverse prediction of PuO2 processing conditions using Bayesian seemingly unrelated regression with functional data

Over the past decade, a variety of innovative methodologies have been developed to better characterize the relationships between processing conditions and the physical, morphological, and chemical features of special nuclear material (SNM). Different processing conditions generate SNM products with different features, which are known as “signatures” because they are indicative of the processing conditions used to produce the material. These signatures can potentially allow a forensic analyst to determine which processes were used to produce the SNM and make inferences about where the material originated. This article investigates a statistical technique for relating processing conditions to the morphological features of PuO 2 particles. We develop a Bayesian implementation of seemingly unrelated regression (SUR) to inverse-predict unknown PuO 2 processing conditions from known PuO 2 features. Model results from simulated data demonstrate the usefulness of the technique. Applied to empirical data from a bench-scale experiment specifically designed with inverse prediction in mind, our model successfully predicts nitric acid concentration, while results for Pu concentration and precipitation temperature were equivalent to a simple mean model. Our technique compliments other recent methodologies developed for forensic analysis of nuclear material and can be generalized across the field of chemometrics for application to other materials.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2019

Numerical and Physical Simulation of the Fluid Flow in a Beam Blank Mold Fed Through the Center of the Web

Fluid flow inside a beam blank mold fed through a three-port SEN (two lateral ports and one bottom port), positioned at the center of the mold, has been investigated. Literature survey shows that this kind of configuration is not frequently used. It had been shown that it is possible to get a symmetrical flow with this configuration. The downward inclination of the ports should influence the transient fluid flow. The greater the downward inclination, the greater is the instability of the jet and of the interface between the immiscible fluids that simulate the slag/metal behavior. The flow characterization was made by dye dispersion, PIV technique, measurement of the meniscus oscillation using ultrasonic sensors, and CFD simulations. The slag/metal behavior was simulated using water and oils with different physical properties. The results from PIV as well as from observations of the water–oil interface have been used to validate the CFD simulations. Oils with density close to water resulted in more instability at the interface with entrainment starting from fluid flow rate of 125 L/min (equivalent to casting speed of 1 m/min). Decreasing the viscosity of slag (oils) and increasing the casting velocity (water flow rate) result in reduction of the interfacial stability.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Viscous regularization of the full set of nonequilibrium-diffusion Grey Radiation-Hydrodynamic equations

A viscous regularization technique, based on the local entropy residual, was proposed by Delchini et al. (2015) to stabilize the nonequilibrium-diffusion Grey Radiation-Hydrodynamic equations using an artificial viscosity technique. This viscous regularization is modulated by the local entropy production and is consistent with the entropy minimum principle. However, Delchini et al. (2015) only based their work on the hyperbolic parts of the Grey Radiation-Hydrodynamic equations and thus omitted the relaxation and diffusion terms present in the material energy and radiation energy equations. Here in this paper, we extend the theoretical grounds for the method and derive an entropy minimum principle for the full set of nonequilibrium-diffusion Grey Radiation-Hydrodynamic equations. This further strengthens the applicability of the entropy viscosity method as a stabilization technique for radiation-hydrodynamic shock simulations. Radiative shock calculations using constant and temperature-dependent opacities are compared against semi-analytical reference solutions, and we present a procedure to perform spatial convergence studies of such simulations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗