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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 OSTI2014

Critical Configuration and Physics Measurements for Beryllium Reflected Assemblies of U(93.15)O 2 Fuel Rods (1.506-cm Pitch and 7-Tube Clusters)

Cadmium ratios were measured with enriched uranium metal foils at various locations in the assembly with the fuel tube at the 1.506-cm spacing. They are described in the following subsections. The experiment configuration was the same as the first critical configuration described in HEU-COMP-FAST-004 (Case 1). The experimenter placed 0.75-cm-diameter × 0.010-cm-thick 93.15%-235U-enriched uranium metal foils with and without 0.051-cm-thick cadmium covers at various locations in the core and top reflector. One part of the cadmium cover was cupshape and contained the uranium foil. The other part was a lid that fit over the exposed side of the foil when it was in the cup shaped section of the cover. As can be seen in the logbook, two runs were required to obtain all the measurements necessary for the cadmium ratio. The bare foil measurements within the top reflector were run first as part of the axial foil activation measurements. The results of this run are used for both the axial activation results and the cadmium ratios. Cadmium covered foils were then placed at the same location through the top reflector in a different run. Three pairs of bare and cadmium covered foils were also placed through the core tank. One pair was placed at the axial center of a fuel tube 11.35 cm from the center of the core. Two pairs of foils were placed on top of fuel tubes 3.02 and 12.06 cm from the center of the core. The activation of the uranium metal foils was measured after removal from the assembly using two lead shielded NaI scintillation detectors as follows. The NaI scintillators were carefully matched and had detection efficiencies for counting delayed-fission-product gamma rays with energies above 250 KeV within 5%. In all foil activation measurements, one foil at a specific location was used as a normalizing foil to remove the effects of the decay of fission products during the counting measurements with the NaI detectors. The normalization foil was placed on one NaI scintillator and the other foil on the other NaI detector and the activities measured simultaneously. The activation of a particular foil was compared to that of the normalization foil by dividing the count rate for each foil by that of the normalization foil. To correct for the differing efficiencies of the two NaI detectors, the normalization foil was counted in Detector 1 simultaneously with the foil at position x in Detector 2, and then the normalization foil was counted simultaneously in Detector 2 with the foil from position x in Counter 1. The activity of the foil from position x was divided by the activity of the normalization foil counted simultaneously. This resulted in obtaining two values of the ratio that were then averaged. This procedure essentially removed the effect of the differing efficiencies of the two NaI detectors. Differing efficiencies of 10% resulted in errors in the ratios measured to less than 1%. The background counting rates obatined with the foils used for the measurements on the NaI detectors before their irradiation measurement were subtracted from all count rates. The results of the cadmium ratio measurements are given in Table 1.3-1 and Figure 1.3-1. “No correction has been made for self shielding in the foils” (Reference 3).

reactivity worth measurements↗
DOE OSTI2019

Evidence for Highly Variable, Region-Specific Patterns of T-Cell Epitope Mutations Accumulating in Mycobacterium tuberculosis Strains

Vaccines that confer protection through induction of adaptive T-cell immunity rely on understanding T-cell epitope (TCE) evolution induced by immune escape. This is poorly understood in tuberculosis (TB), an ancient, chronic disease, where CD4 T-cell immunity is of recognized importance. We probed 905 functionally validated, curated human CD4 T cell epitopes in 79 Mycobacterium tuberculosis (Mtb) whole genomes from India. This screen resulted in identifying 64 mutated epitopes in these strains initially using a computational pipeline and subsequently verified by single nucleotide polymorphism (SNP) analysis. SNP based phylogeny revealed the 79 Mtb strains to cluster to East African Indian (EAI), Central Asian Strain (CAS), and Beijing (BEI) lineages. Eighty-nine percent of the mutated T-cell epitopes (mTCEs) identified in the 79 Mtb strains from India has not previously been reported. These mTCEs were encoded by genes with high nucleotide diversity scores including seven mTCEs encoded by six antigens in the top 10% of rapidly divergent Mtb genes encoded by these strains. Using a T cell functional assay readout, we demonstrate 62% of mTCEs tested to significantly alter CD4 T-cell IFNγ and/or IL2 secretion with associated changes in predicted HLA-DR binding affinity: the gain of function mutations displayed higher predicted HLA-DR binding affinity and conversely mutations resulting in loss of function displayed lower predicted HLA-DR binding affinity. Most mutated antigens belonged to the cell wall/cell processes, and, intermediary metabolism and respiration families though all known Mtb proteins encoded mutations. Analysis of the mTCEs in an SNP database of 5,310 global Mtb strains identified 82% mTCEs to be significantly more prevalent in Mtb strains isolated from India, including 36 mTCEs identified exclusively in strains from India. These epitopes had a significantly higher predicted binding affinity to HLA-DR alleles that were highly prevalent in India compared to HLA-DR alleles rare in India, highlighting HLA-DR maybe an important driver of these mutations. This first evidence of region-specific TCE mutations potentially employed by Mtb to escape host immunity has important implications for TB vaccine design.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2012

3D neutronic/thermal-hydraulic coupled analysis of MYRRHA

The current tendency in multiphysics calculations applied to reactor physics is the use of already validated computer codes, coupled by means of an iterative approach. In this paper such an approach is explained concerning neutronics and thermal-hydraulics coupled analysis with MCNPX and COBRA-IV codes using a driver program and file exchange between codes. MCNPX provides the neutronic analysis of heterogeneous nuclear systems, both in critical and subcritical states, while COBRA-IV is a subchannel code that can be used for rod bundles or core thermal-hydraulics analysis. In our model, the MCNP temperature dependence of nuclear data is handled via pseudo-material approach, mixing pre-generated cross section data set to obtain the material with the desired cross section temperature. On the other hand, COBRA-IV has been updated to allow for the simulation of liquid metal cooled reactors. The coupled computational tool can be applied to any geometry and coolant, as it is the case of single fuel assembly, at pin-by-pin level, or full core simulation with the average pin of each fuel-assembly. The coupling tool has been applied to the critical core layout of the SCK-CEN MYRRHA concept, an experimental LBE cooled fast reactor presently in engineering design stage. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

Toward High Fidelity LES Simulations of 5 x 5 PWR Fuel Bundle with Mixing Vane

The present work illustrates one example of a computational fluid dynamics (CFD) application in the nuclear engineering field. Since CFD is one of the most powerful tools available at the actual state of the art that could in principle help and assist the design process, a compromise should be established between the accuracy of the CFD numerical model (RANS - LES - DNS) and the computational cost of the simulations. In this spirit, this work will present the computational results from two different CFD model categories, Large Eddy Simulations (LES) and Reynolds-averaged Navier-Stokes (RANS) models. Both treat the flow turbulence issue in two separate ways, which differ mostly in the resolution of the turbulence statistics and the computational cost. The single-phase hydraulic problem presented involves the steady-state turbulent flow field modelling and resolution around a scaled PWR mixing vane grid, designed by Westinghouse and tested by Texas A and M University. The role of the mixing vane/spacer grid is to enhance the turbulent mixing and hence heat transfer of the core coolant around fuel bundles, thus increasing the departure of nucleate boiling-critical heat flux (DNB-CHF) point, as well as important structural functions for the rods bundles. The authors numerically studied the flow field characteristics at the region downstream of the spacer grids and validated their results to particle imagery velocimetry (PIV) measurements. Dominguez and Hassan performed two-dimensional time resolved PIV (TR-PIV) measurements within a 5 x 5 PWR rod bundle with spacer-grids that utilized a matching index of refraction (MIR) approach. Their averaged data showed a rather uniform direction velocity profile after the spacer grid while the downstream illustrated a no slip wall profile. The available PIV flow field experimental results from Texas A and M show complex structures of the flow field downstream the mixing vanes with the formation of secondary flows that tend to enhance the turbulent heat transfer, due to the mixing vanes geometry itself. Computational results will be validated with the available experimental data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

Dynamic Adaptable Asynchronous Progress Model for MPI RMA Multiphase Applications

Casper is a process-based asynchronous progress model for MPI one-sided communication on multi-and many-core architectures. The one-sided communication is not truly one-sided in most MPI implementations: the target process still relies on software progress to complete incoming operations. Casper allows the user to specify an arbitrary number of cores dedicated to background ghost processes and transparently redirects the RMA operations to ghost processes by utilizing the PMPI redirection and MPI-3 shared-memory technologies. Although Casper benefits applications that suffer from lack of asynchronous progress, the operation redirection design might not support complex multiphase applications effectively, which often involve dynamically changing communication density and computing workloads. In this paper, we present an adaptive mechanism in Casper to address the limitation of static asynchronous progress in multiphase applications. For this we exploit two adaptive strategies, a user-guided strategy and a fully transparent and automatic strategy based on self-profiling and prediction, to dynamically reconfigure the asynchronous progress in Casper according to real-time performance characteristics during multiphase execution. We evaluate the adaptive approaches in both microbenchmarks and a real quantum chemistry application suite, NWChem, on the Cray XC30 supercomputer and an Intel Omni-Path cluster.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

An Orthogonal Recursive Bisection (ORB) Based Time Advancement Algorithm for CFD-DEM Solvers

The time integration of the granular phase in coupled computational fluid dynamics (CFD) – discrete element method (DEM) simulations presents a unique computational challenge brought about by the large variations in particle collisional time scales. Particles in the dilute regions of the computational domain can be advanced with large time steps while dense regions require much smaller time increments. However, the time step size in most solvers is globally set as the limit for accuracy and stability imposed by the collisions and is typically orders of magnitude less than that required away from collisions. This work addresses this precise issue and provides a strategy to avoid the use of a global conservative small time step size for the entire set of particles.A novel time stepping algorithm for CFD-DEM solvers using a partitioning approach using orthogonal recursive bisection (ORB) that allows for variable time steps among particles is described and its computational performance is compared against baseline explicit methods, typically used in several CFD-DEM solvers. ORB has advantages of being relatively quick and easy to update incrementally and has the required heuristic behavior (i.e., it will split the region in half with a cluster on each side) when groups of particles are well separated (clustered). The algorithm presented in this work uses a local time stepping approach to resolve collisional time scales for subsets of particles that are present at the leaves of the ORB, thereby resulting in substantial reduction of computational cost. The parallel implementation of this method where a ``knapsack” algorithm is used in tandem with ORB for effective load-balancing is also presented, where a best possible partitioning is obtained based on number of particles and local time-stepping costs. The algorithm is tested against benchmark problems with varying particle distributions that include fluidized bed and riser flow scenarios. Preliminary results indicate that the approach is 2-3X faster than traditional explicit methods for problems that involve both dense and dilute regions, while maintaining the same level of accuracy.

adaptive timestepping↗
DOE OSTI2021

Projector-Free Capped-Fragment Scheme within Density Functional Embedding Theory for Covalent and Ionic Compounds

Quantum-mechanics-(QM)-based simulations now routinely aid in understanding and even discovering new chemistries involving molecules and materials exhibiting desired functionalities. Ab initio correlated wavefunction (CW) theories systematically improve QM methods, with many exhibiting high accuracy. However, execution of CW methods requires expensive computations that typically scale poorly with system size. Divide-and-conquer approaches partition large systems into smaller fragments; a lower level of theory treats fragment interactions while a preferred higher level of theory describes the important fragment. These methods offer ways to incorporate CWs into chemical simulations of large systems, e.g., biomolecules, surfaces, large inorganic clusters, bulk crystals, etc. Here we propose a partitioning protocol that utilizes capping atoms to saturate severed covalent bonds at fragment interfaces and density functional embedding theory (DFET) to describe fragment interactions. The capping groups in each fragment provide an ad-hoc potential that approximates the effects of the environment. An embedding potential optimized via DFET then serves as an augmentation of the capping group to simulate the effects of the environment. We concurrently use an auxiliary fragment (a separate system comprised of only the combined capping groups) to account for, and thereby correct, the electron density contributions of all the capping groups added to all of the fragments. This method depends only on the capped-subsystem and auxiliary-fragment electron densities, forgoing, as with the original DFET developed for metallic systems, orbital-based projector approaches that determine a nonlocal action of the embedding potential onto the fragment electrons. By using an auxiliary fragment, the method maintains a purely electron-density-dependent embedding potential, substantially lessening the cost and leading to simpler implementation. In this work, we demonstrate the utility of our capped-DFET and ensuing capped embedded CW method in two contrasting systems, namely, an organic molecule and an ionic metal oxide cluster.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Truck platooning in the U.S. national road network: A system-level modeling approach

Truck platooning enables a group of trucks to move close together, which helps reduce truck fuel use and increase effective road capacity. In this paper, a system-level equilibrium model is developed to characterize spontaneous truck platooning with coexistence of non-platooning vehicles in a network, by explicitly accounting for the interlocking relationship among platoon formation time, truck fuel saving, and increase in effective road capacity. To equilibrate the relationships, an algorithm is proposed which involves a diagonalization approach and a bush based algorithm to solve decomposed subproblems. The condition of proportionality is imposed to obtain unique traffic flows for each class of vehicles on road links. In addition, a spatially constrained multivariate clustering technique is employed to construct origin/destination zones that are smaller than the coarse Freight Analysis Framework (FAF) zones, while maintaining reasonable computational burden for network traffic assignment. Model implementation in the U.S. shows that platooning could lead to 7.9% fuel saving among platoonable trucks in 2025 and a comparable increase in effective capacity of platoonable road links, which would account for 60% of rural interstate roads. The fuel saving and road capacity improvement translate into an annual cost reduction of $\$$868 million for the U.S. intercity trucking sector and reduced road infrastructure investment needs worth $\$$4.8 billion. Extensive sensitivity analysis further reveals that fuel saving of platoonable trucks increases with platoon size but decreases with inter-truck distance in a platoon. Fuel saving potential suggests that priority should be given to rural rather than urban roads in deploying platooning technologies. As we expected, greater market penetration of platooning technologies means higher fuel saving and greater increase in effective road capacity.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Electromagnetic Transient (EMT) Simulation Algorithms for Evaluation of Large-Scale Extreme Fast Charging Systems (T&D Models)

Simulation of high-fidelity models of extreme fast charging (XFC) systems and large-area power grids with many XFCs can be time consuming in traditional simulators. Traditional simulators use a single method of discretization for all the components that results in imposing a large computational burden of inverting a large matrix as well as increased computations related to single method of discretization (that is typically a trapezoidal method). To overcome the problem of simulating large-area power grids with many XFCs, in this paper, advanced numerical simulation algorithms are applied for the first time together to reduce the dimension of matrix inversion. Here, the algorithms include numerical stiffness-based segregation, time constant-based segregation, clustering and aggregation on differential algebraic equations (DAEs), and multi-order integration approaches. These algorithms apply multiple discretization algorithms rather than a single discretization algorithm that further reduces the computational burden. The approaches mentioned here have resulted in speed-up of up to 18x in the simulation of a single distribution system with 15 XFCs and of up to 271x in the simulation of a transmission-distribution system with 300 XFCs in multiple distribution feeders with respect to conventional simulators (like power systems computer aided design [PSCAD]).

42 ENGINEERING↗
DOE OSTI2013

PoPLAR: Portal for Petascale Lifescience Applications and Research

Background: We are focusing specifically on fast data analysis and retrieval in bioinformatics that will have a direct impact on the quality of human health and the environment. The exponential growth of data generated in biology research, from small atoms to big ecosystems, necessitates an increasingly large computational component to perform analyses. Novel DNA sequencing technologies and complementary high-throughput approaches–such as proteomics, genomics, metabolomics, and meta-genomics–drive data-intensive bioinformatics. While individual research centers or universities could once provide for these applications, this is no longer the case. Today, only specialized national centers can deliver the level of computing resources required to meet the challenges posed by rapid data growth and the resulting computational demand. Consequently, we are developing massively parallel applications to analyze the growing flood of biological data and contribute to the rapid discovery of novel knowledge. Methods: The efforts of previous National Science Foundation (NSF) projects provided for the generation of parallel modules for widely used bioinformatics applications on the Kraken supercomputer. We have profiled and optimized the code of some of the scientific community’s most widely used desktop and small-cluster-based applications, including BLAST from the National Center for Biotechnology Information (NCBI), HMMER, and MUSCLE; scaled them to tens of thousands of cores on high-performance computing (HPC) architectures; made them robust and portable to next-generation architectures; and incorporated these parallel applications in science gateways with a web-based portal. Results: This paper will discuss the various developmental stages, challenges, and solutions involved in taking bioinformatics applications from the desktop to petascale with a front-end portal for very-large-scale data analysis in the life sciences. Conclusions: This research will help to bridge the gap between the rate of data generation and the speed at which scientists can study this data. The ability to rapidly analyze data at such a large scale is having a significant, direct impact on science achieved by collaborators who are currently using these tools on supercomputers.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

On Achieving High Accuracy in Quantum Chemical Calculations of 3 d Transition Metal-Containing Systems: A Comparison of Auxiliary-Field Quantum Monte Carlo with Coupled Cluster, Density Functional Theory, and Experiment for Diatomic Molecules

According to the article, the bond dissociation energies of a set of 44 3d transition metal-containing diatomics are computed with phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC) utilizing a correlated sampling technique. We investigate molecules with H, N, O, F, Cl, and S ligands, including those in the 3dMLBE20 database first compiled by Truhlar and co-workers with calculated and experimental values that have since been revised by various groups. In order to make a direct comparison of the accuracy of our ph-AFQMC calculations with previously published results from 10 DFT functionals, CCSD(T), and icMR-CCSD(T), we establish an objective selection protocol which utilizes the most recent experimental results except for a few cases with well-specified discrepancies. With the remaining set of 41 molecules, we find that ph-AFQMC gives robust agreement with experiment superior to that of all other methods, with a mean absolute error (MAE) of 1.4(4) kcal/mol and maximum error of 3(3) kcal/mol (parentheses account for reported experimental uncertainties and the statistical errors of our ph-AFQMC calculations). In comparison, CCSD(T) and B97, the best performing DFT functional considered here, have MAEs of 2.8 and 3.7 kcal/mol, respectively, and maximum errors in excess of 17 kcal/mol (for the CoS diatomic). While a larger and more diverse data set would be required to demonstrate that ph-AFQMC is truly a benchmark method for transition metal systems, our results indicate that the method has tremendous potential, exhibiting unprecedented consistency and accuracy compared to other approximate quantum chemical approaches.

Chemistry↗
DOE OSTI2025

Massively parallel phase-field simulations targeting exascale

The interface thickness in the phase-field (PF) method limits its simulation scales. Consequently, large-scale PF simulations become prohibitively expensive for resolving the extremely fine microstructures that typically form during rapid solidification processing. This challenge is significant in predicting microstructure evolution in metal additive manufacturing and has been identified by the United States Department of Energy’s Exascale Computing Project. Here, to address this, we develop a multi-GPU and MPI-based massively parallel simulation code, utilizing state-of-the-art algorithms, software, and libraries, for large-scale three-dimensional (3D) PF simulations. We report the first GPU-parallel PF simulations on Frontier (currently the second TOP500 exascale cluster) and Summit machines, taking dendritic growth as an example problem. We evaluate the parallel performance of our implementation using scaling studies with more than 24 000 GPUs (among the largest known computations to date) and the acceleration performance using large-scale simulations of dendritic growth in 3D. Finally, massively parallel GPUs in these supercomputers enabled the first coupled multiscale simulations of laser melting and subsequent dendritic solidification on the scale of a full melt-pool, demonstrating the feasibility of performing PF simulations with a point total over 2 billion grid points within an acceptable time.

Exascale↗
DOE OSTI2018

Wang–Landau approach to the simulation of water clusters

The Wang–Landau Monte Carlo method [Wang FG, Landau DP. Efficient, multiple-range random walk algorithm to calculate the density of states. Phys Rev Lett. 2001;86:2050-2053; Determining the density of states for classical statistical models: a random walk algorithm to produce a flat histogram. Phys Rev E. 2001;64:056101] has been established as an effective computational approach for studying complex systems. In this study, we review the properties of 6 popular empirical water potentials, including a recently proposed explicit 3-body potential, obtained by applying the Wang–Landau method to the simulation of water clusters. Finally, comparing to numerous classical and first principle calculations, we show that several classical water models can provide a consistent description of the structural and thermodynamical properties of water clusters partially in agreement of ab initio results, although they were designed to reproduce macroscopic properties of water at ambient conditions.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2012

Warewulf 3.0

Warewulf is a scalable systems management suite originally developed to manage large high-performance Linux clusters. Focused on general scalable systems management, it includes a framework for system configuration, management, provisioning/installation, monitoring, event notification, and more via a modular plugin architecture. Install the components and features you need or leverage the existing system configuration stored within Warewulf to create custom solutions to meet your performance needs. One of the goals of the project is to grow the project by allowing other organizations and developers to contribute back to the project under an open source BSD license. We have been successful with gaining support within the open source community already and have contributors and support in not only the government and academic space but also the commercial sector (e.g. Intel). Being both open source and vendor neutral puts Warewulf in a unique position to be supported and utilized as an open standard in High Performance Computing (HPC). Warewulf is an active member of various HPC initiatives and groups and is considered one of the most utilized, extensible and scalable clustering toolkits available.

Kurtzer, GregoryM.↗
DOE OSTI2014

Variation in Optoelectronic Properties of Azo Dye-Sensitized TiO 2 Semiconductor Interfaces with Different Adsorption Anchors: Carboxylate, Sulfonate, Hydroxyl and Pyridyl Groups

The optoelectronic properties of four azo dye-sensitized TiO2 interfaces are systematically studied as a function of a changing dye anchoring group: carboxylate, sulfonate, hydroxyl, and pyridyl. The variation in optoelectronic properties of the free dyes and those in dye/TiO 2 nanocomposites are studied both experimentally and computationally, in the context of prospective dye-sensitized solar cell (DSSC) applications. Experimental UV/vis absorption spectroscopy, cyclic voltammetry, and DSSC device performance testing reveal a strong dependence on the nature of the anchor of the optoelectronic properties of these dyes, both in solution and as dye/TiO2 nanocomposites. First-principles calculations on both an isolated dye/TiO2 cluster model (using localized basis sets) and each dye modeled onto the surface of a 2D periodic TiO2 nanostructure (using plane wave basis sets) are presented. Detailed examination of these experimental and computational results, in terms of light harvesting, electron conversion and photovoltaic device performance characteristics, indicates that carboxylate is the best anchoring group, and hydroxyl is the worst, whereas sulfonate and pyridyl groups exhibit competing potential. Different sensitization solvents are found to affect critically the extent of dye adsorption achieved in the dye-sensitization of the TiO2 semiconductor, especially where the anchor is a pyridyl group.

anchor↗
DOE OSTI2024

Empowering Machine Learning Forecasting of Labquake Using Event‐Based Features and Clustering Characteristics

Abstract Following recent advances of machine learning (ML), we present a novel approach to extract spatiotemporal seismo‐mechanical features from Acoustic Emission (AE) catalogs to empower ML‐based forecasting. The AE data were recorded during laboratory stick‐slip experiments on granite samples cut by rough faults. Based on the features computed for a past time window, a random forest (RF) classifier is used to forecast the occurrence of a large magnitude event ( M AE > 3.5) in the next time window. Event‐based features allow us to associate informative time‐space characteristics to each feature and nearest‐neighbor clustering analysis enables us to separate background and clustered seismicity and train individual models. The results show that the separation of AEs enhances the forecasting accuracy from 73.2% for the entire catalog up to 82.1% and 89.0% if background and clustered events are used separately. The presented new approach may be upscaled for applications to forecast tectonic earthquakes.

Karimpouli, Sadegh↗