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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Study of grain boundary transparency in(Yb$_{1-x}$Ca$_x$)Ba$_2$Cu$_3$O bicrystal thin films over a wide temperature, field, and field orientation range

The residual low angle grain boundary (GB) network is still the most important current-limiting mechanism operating in bi-axially textured rare earth barium copper oxide (REBCO) coated conductors. While Ca-doping is well established to improve super-current flow across low angle GBs in weak fields at high temperatures, Ca-doping also depresses T c , making it so far impractical for high temperature applications of REBCO coated conductors. On the other hand, high field magnet applications of REBCO require low temperatures. Here we systematically evaluate the effectiveness of Ca-doping in improving the GB transparency, r GB = J c GB /J c grain , of low angle Yb 1-x Ca x BaCuO [001] tilt bi-crystal films down to 10K and with magnetic fields perpendicular and parallel to the film surfaces, while varying the Ca and oxygen doping level. Using Low Temperature Scanning Laser Microscopy (LTSLM) and Magneto-Optical Imaging (MOI), we found r GB to strongly depend on the angle between magnetic field and the GB plane and clearly identified regimes in which J c GB can exceed J c grain (rGB>1) where the GB pinning is optimized by the field being parallel to the GB dislocations. However, even in this favorable situation, we found that r GB became much smaller at lower temperatures. Calculations of the GB Ca segregation profile predict that the high J c channels between the GB dislocation cores are almost Ca-free. It may be therefore that the positive effects of Ca doping seen by many authors near T c are partly a consequence of the higher Tc of these Ca-free channels.

Li, Pei↗
DOE OSTI2025

Characterization and Optimization of the Fitting of Quantum Correlation Functions

This case study presents a characterization and optimization of an application code for extracting parton distribution functions from high energy electron-proton scattering data. Profiling this application code reveals that the phase-space density computation accounts for 93% of the overall execution time for a single iteration on a single core. When executing multiple iterations in parallel on a multicore system, the application spends 78% of its overall execution time idling due to load imbalance. We address these issues by first transforming the application code from Python to C++ and then tackling the application load imbalance via a hybrid scheduling strategy that combines dynamic and static scheduling. These techniques result in a 62% reduction in CPU idle time and a 2.46x speedup in overall execution time per node. In addition, the typically enabled power-management mechanisms in supercomputers (e.g., AMD Turbo Core, Intel Turbo Boost, and RAPL) can significantly impact intra-node scalability when more than 50% of the CPU cores are used. This finding underscores the importance of understanding system interactions with power management, as they can adversely impact application performance, and highlights the necessity of intra-node scaling tests to identify performance degradation that inter-node scaling tests might otherwise overlook.

Chuang, Pi-Yueh [Virginia Tech,Dept. of Computer S↗
DOE OSTI2018

Metal Amorphous Nanocomposite Soft Magnetic Material-Enabled High Power Density, Rare Earth Free Rotational Machines [Metal Amorphous Nanocomposite (MANC) Soft Magnetic Material (SMM) Enabled High Power Density, Rare Earth Free Rotational Machines]

Metal amorphous nanocomposites (MANCs) are promising soft magnetic materials (SMMs) for power electronic applications offering low power loss at high frequency and maintaining a relatively high flux density. While applications in certain motor designs have been recently modeled, their widespread application awaits scaled manufacturing of MANC materials and proliferation of new higher speed motor designs. A hybrid motor design based on permanent magnets and doubly salient stator and rotor is reported here to develop a compact (a factor of 10 smaller than currently possible in Si steels), high-speed (>1 kHz, electrical), high-power (>2.5 kW) motor by incorporating low loss (<10 W/kg at 1 kHz) MANCs such as recently reported Fe-Ni-based alloys. A feature of this motor design is flux focusing from the permanent magnet allowing use of lower energy permanent magnet chosen from among non-rare earth containing compositions and attractive due to constraints posed by rare earth criticality. A 2-D finite element analysis model reported here indicates that a 2.5 kW hybrid motor may be built with a permanent magnet with a 0.4 T remanence at a rotor speed of 6000 rpm. At a magnetic switching frequency of 1.4 kHz, the core loss may be limited to <3 W by selecting an appropriate MANC SMM. The projected efficiency exceeds 96% not including power loss in the controller. Under full load conditions, the flux density distributions for the SMM stay predominantly <1.3 T, the saturation magnetization of optimized FeNi-based MANC alloys. As a result, the maximum demagnetizing field in the permanent magnet is less than 2.2 × 10 5 A/m sustainable, for example, with a high-grade hard ferrite magnet.

42 ENGINEERING↗
DOE OSTI2021

MemXCT: Design, Optimization, Scaling, and Reproducibility of X-Ray Tomography Imaging

Here, this work extends our previous research entitled "MemXCT: Memory-centric X-ray CT Reconstruction with Massive Parallelization" that was originally published at SC19 conference (Hidayetoglu et al., 2019) with reproducibility of the computational imaging performance. X-ray computed tomography (XCT) is regularly used at synchrotron light sources to study the internal morphology of materials at high resolution. However, experimental constraints, such as radiation sensitivity, can result in noisy or undersampled measurements. Further, depending on the resolution, sample size and data acquisition rates, the resulting noisy dataset can be in the order of terabytes. Advanced iterative reconstruction techniques can produce high-quality images from noisy measurements, but their computational requirements have made their use an exception rather than the rule. We propose a novel memory-centric approach that avoids redundant computations at the expense of additional memory complexity. We develop a memory-centric iterative reconstruction system, MemXCT, that uses an optimized SpMV implementation with two-level pseudo-Hilbert ordering and multi-stage input buffering. We evaluate MemXCT on various supercomputer architectures involving KNL and GPU. MemXCT can reconstruct a large (11Kx11K) mouse brain tomogram in 10 seconds using 4096 KNL nodes (256K cores). The results presented in our original article at the SC19 were based on large-scale supercomputing resources. The MemXCT application was selected for the Student Cluster Competition (SCC) Reproducibility Challenge and evaluated on a variety of cloud computing resources by universities around the world in the SC20 conference. We summarize the results of the top-ranked SCC Reproducibility Challenge teams and identify the most pertinent measures for ensuring the reproducibility of our experiments in this article.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

On the Training and Generalization of Deep Operator Networks

Here, we present a novel training method for deep operator networks (DeepONets), one of the most popular neural network models for operators. DeepONets are constructed by two subnetworks, namely the branch and trunk networks. Typically, the two subnetworks are trained simultaneously, which amounts to solving a complex optimization problem in a high dimensional space. In addition, the nonconvex and nonlinear nature makes training very challenging. To tackle such a challenge, we propose a two-step training method that trains the trunk network first and then sequentially trains the branch network. The core mechanism is motivated by the divide-and-conquer paradigm and is the decomposition of the entire complex training task into two subtasks with reduced complexity. Therein the Gram–Schmidt orthonormalization process is introduced which significantly improves stability and generalization ability. On the theoretical side, we establish a generalization error estimate in terms of the number of training data, the width of DeepONets, and the number of input and output sensors. Numerical examples are presented to demonstrate the effectiveness of the two-step training method, including Darcy flow in heterogeneous porous media.

deep operator networks↗
DOE OSTI2022

The fast neutron source at UTK: a project with Massimo Salvatores

This article is dedicated to the memory of Massimo Salvatores and offers an overview of the history of the design of the Fast Neutron Source (FNS) flexible experiment system at the University of Tennessee. Our collaboration with Massimo set much of the over-arching design goals and inspired the concept that we have today. The decision to design the FNS as a subcritical assembly rather than a critical one stems back to discussions with Massimo Salvatores and his advocacy for subcritical Accelerator Driven Systems (ADS) which coincides with lower licensing time, costs and greater safety for a university-operated nuclear experimental facility. The second contribution of Massimo to the design concept of the FNS was the direct instruction to design the FNS as an extremely flexible facility. This article provides an update on the current design concept and discusses the future innovations in design optimization of flexible, re-configurable nuclear experiments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

Dynamical formation of the GW150914 binary black hole

We explore the possibility that GW150914, the binary black hole (BBH) merger recently detected by Advanced LIGO, was formed by gravitational interactions in the core of a dense star cluster. Using models of globular clusters (GCs) with detailed N-body dynamics and stellar evolution, we show that a typical cluster with a mass of 3×10{sup 5}M{sub ⊙} to 6×10{sup 5}M{sub ⊙} is optimal for forming GW150914-like BBHs that will merge in the local universe. We identify the most likely dynamical processes for forming GW150914 in such a cluster, and we show that the detection of GW150914 is consistent with the masses and merger rates expected for BBHs from GCs. Our results show that dynamical processes provide a significant and well-understood pathway for forming BBH mergers in the local universe. Understanding the contribution of dynamics to the BBH merger problem is a critical step in unlocking the full potential of gravitational-wave astronomy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Supernova neutrino detection in LZ

In the first 10 seconds of a core-collapse supernova, almost all of its progenitor's gravitational potential, O(10 53 ergs), is carried away in the form of neutrinos. These neutrinos, with O(10 MeV) kinetic energy, can interact via coherent elastic neutrino-nucleus scattering (CEνNS) depositing O(1 keV) in detectors. In this work we describe the performances of low-background dark matter detectors, such as LUX-ZEPLIN (LZ), optimized for detecting low-energy depositions, in detecting these neutrino interactions. For instance, a 27 M ⊙ supernova at 10 kpc is expected to produce ~350 neutrino interactions in the 7-tonne liquid xenon active volume of LZ. Based on the LS220 EoS neutrino flux model for a SN, the Noble Element Simulation Technique (NEST), and predicted CEνNS cross-sections for xenon, to study energy deposition and detection of SN neutrinos in LZ. Here we simulate the response of the LZ data acquisition system (DAQ) and demonstrate its capability and limitations in handling this interaction rate. We present an overview of the LZ detector, focusing on the benefits of liquid xenon for supernova neutrino detection. We discuss energy deposition and detector response simulations and their results. We present an analysis technique to reconstruct the total number of neutrinos and the time of the supernova core bounce.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Twisted A-D-A Type Acceptors with Thermally-Activated Delayed Crystallization Behavior for Efficient Nonfullerene Organic Solar Cells

We report that molecular aggregation and crystallization during film coating play a crucial role in the realization of high-performing organic photovoltaics. Strong intermolecular interactions and high solid-state crystallinity are beneficial for charge transport. However, fast crystallization during thin-film drying often limits the formation of the finely phase-separated morphology required for efficient charge generation. Herein, the authors show that twisted acceptor-donor-acceptor (A-D-A) type compounds, containing an indacenodithiophene (IDT) electron-rich core and two naphthalenediimide (NDI) electron-poor units, leads to formation of mostly amorphous phases in the as-cast film, which can be readily converted into more crystalline domains by means of thermal annealing. This design strategy solves the aforementioned conundrum, leading to an optimal morphology in terms of reduced donor/acceptor domain-separation sizes (ca. 13 nm) and increased packing order. Solar cells based on these acceptors with a PBDB-T polymer donor show a power conversion efficiency over 10% and stable morphology, which results from the combined properties of desirable excited-state dynamics, high charge mobility, and optimal aggregation/crystallization characteristics. These results demonstrate that the twisted A-D-A motif featuring thermally-induced crystallization behavior is indeed a promising alternative design approach toward more morphologically robust materials for efficient organic photovoltaics.

14 SOLAR ENERGY↗
DOE OSTI2019

Verification of Reduced Order Modeling Based Uncertainty/Sensitivity Estimator (ROMUSE)

This article presents a number of verification case studies for a recently developed sensitivity/uncertainty code package. The code package, ROMUSE (Reduced Order Modeling based Uncertainty/Sensitivity Estimator) is an effort to provide an analysis tool to be used in conjunction with reactor core simulators, in particular the Virtual Environment for Reactor Applications (VERA) core simulator. ROMUSE has been written in C++ and is currently capable of performing various types of parameter perturbations and associated sensitivity analysis, uncertainty quantification, surrogate model construction and subspace analysis. The current version 2.0 has the capability to interface with the Design Analysis Kit for Optimization and Terascale Applications (DAKOTA) code, which gives ROMUSE access to the various algorithms implemented within DAKOTA, most importantly model calibration. The verification study is performed via two basic problems and two reactor physics models. The first problem is used to verify the ROMUSE single physics gradient-based range finding algorithm capability using an abstract quadratic model. The second problem is the Brusselator problem, which is a coupled problem representative of multi-physics problems. This problem is used to test the capability of constructing surrogates via ROMUSE-DAKOTA. Finally, light water reactor pin cell and sodium-cooled fast reactor fuel assembly problems are simulated via SCALE 6.1 to test ROMUSE capability for uncertainty quantification and sensitivity analysis purposes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

The Role and Value of Interregional Transmission in a Decarbonized U.S. Electricity System

Decarbonizing the U.S. energy system entails a significant expansion of wind and solar power and electrification of end-use applications. Achieving both is more efficient and less costly when interregional transmission capacity is expanded, but the fractured nature of grid planning in the United States is often a barrier to such expansion. Here, we explore the role of interregional transmission under a variety of decarbonization scenarios, using a capacity-expansion model to generate co-optimized portfolios of generation, storage, and transmission that meet decarbonization targets and electrification-driven demand. We explore portfolio and cost differences across 92 scenarios, from scenarios with limited transmission expansion to those that include a meshed high-voltage direct current (HVDC) network. In the core decarbonization scenarios, wind capacity expands by ~10x and solar by ~20x compared to 2020, hundreds of gigawatts of battery storage are deployed, and interregional transmission expands by 3-6x. Transmission expansion occurs nationwide but is concentrated between the central "wind belt" and eastern load centers. The HVDC scenarios result in hundreds of billions of dollars of savings in total system cost, demonstrating the economic benefits of interregional transmission in support of rapid decarbonization.

capacity expansion↗
DOE OSTI2014

Correlation consistent basis sets for explicitly correlated wavefunctions: Pseudopotential-based basis sets for the post-d main group elements Ga–Rn

New correlation consistent basis sets, cc-pVnZ-PP-F12 (n = D, T, Q), for all the post-d main group elements Ga–Rn have been optimized for use in explicitly correlated F12 calculations. The new sets, which include not only orbital basis sets but also the matching auxiliary sets required for density fitting both conventional and F12 integrals, are designed for correlation of valence sp, as well as the outer-core d electrons. The basis sets are constructed for use with the previously published small-core relativistic pseudopotentials of the Stuttgart-Cologne variety. Benchmark explicitly correlated coupled-cluster singles and doubles with perturbative triples [CCSD(T)-F12b] calculations of the spectroscopic properties of numerous diatomic molecules involving 4p, 5p, and 6p elements have been carried out and compared to the analogous conventional CCSD(T) results. In general the F12 results obtained with a n-zeta F12 basis set were comparable to conventional aug-cc-pVxZ-PP or aug-cc-pwCVxZ-PP basis set calculations obtained with x = n + 1 or even x = n + 2. The new sets used in CCSD(T)-F12b calculations are particularly efficient at accurately recovering the large correlation effects of the outer-core d electrons.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

A PARALLEL MONTE CARLO CODE FOR SIMULATING COLLISIONAL N-BODY SYSTEMS

We present a new parallel code for computing the dynamical evolution of collisional N-body systems with up to N {approx} 10{sup 7} particles. Our code is based on the Henon Monte Carlo method for solving the Fokker-Planck equation, and makes assumptions of spherical symmetry and dynamical equilibrium. The principal algorithmic developments involve optimizing data structures and the introduction of a parallel random number generation scheme as well as a parallel sorting algorithm required to find nearest neighbors for interactions and to compute the gravitational potential. The new algorithms we introduce along with our choice of decomposition scheme minimize communication costs and ensure optimal distribution of data and workload among the processing units. Our implementation uses the Message Passing Interface library for communication, which makes it portable to many different supercomputing architectures. We validate the code by calculating the evolution of clusters with initial Plummer distribution functions up to core collapse with the number of stars, N, spanning three orders of magnitude from 10{sup 5} to 10{sup 7}. We find that our results are in good agreement with self-similar core-collapse solutions, and the core-collapse times generally agree with expectations from the literature. Also, we observe good total energy conservation, within {approx}< 0.04% throughout all simulations. We analyze the performance of the code, and demonstrate near-linear scaling of the runtime with the number of processors up to 64 processors for N = 10{sup 5}, 128 for N = 10{sup 6} and 256 for N = 10{sup 7}. The runtime reaches saturation with the addition of processors beyond these limits, which is a characteristic of the parallel sorting algorithm. The resulting maximum speedups we achieve are approximately 60 Multiplication-Sign , 100 Multiplication-Sign , and 220 Multiplication-Sign , respectively.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Nonlinear gyrokinetic predictions of SPARC burning plasma profiles enabled by surrogate modeling

Multi-channel, nonlinear predictions of core temperature and density profiles are performed for the SPARC tokamak accounting for both kinetic neoclassical and fully nonlinear gyro-kinetic turbulent fluxes. A series of flux-tube, nonlinear, electromagnetic simulations using the CGYRO code with six gyrokinetic species are coupled to a nonlinear optimizer using Gaussian process regression techniques. The simultaneous evolution of energy sources, including alpha heat, radiation, and energy exchange, coupled with these high fidelity models and techniques, leads to a converged solution in electron temperature, ion temperature and electron density channels with a minimal number of expensive gyrokinetic simulations without compromising accuracy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

The linker protein ApcI regulates light harvesting under red light in Synechocystis sp. PCC 6803

Phycobilisomes (PBSs) are versatile cyanobacterial antenna complexes that harvest light energy to drive photosynthesis. They can adapt to various light conditions; for example, dismantling under high light to prevent photo-oxidation and arranging in rows under low light to increase light harvesting efficiency. Light quality also influences PBS structure and function, as observed under far-red light exposure. Here, we describe a PBS linker protein, ApcI (previously hypothetical protein Sll1911), expressed specifically under red light (620 nm) or upon chemically induced reduction of the plastoquinone pool. We characterized ApcI in Synechocystis sp. PCC 6803 using mutant analyses, PBS binding experiments, and protein interaction studies. Deletion of apcI conferred high light tolerance on Synechocystis sp. PCC 6803 compared to the wild-type strain, leading to reduced energy transfer from PBSs to the photosystems under high light. Binding experiments revealed that ApcI replaces the linker protein ApcG at the membrane-facing side of the PBS core via a paralogous C-terminal motif. Additionally, the N-terminal region of ApcI interacts with photosystem II. Our findings highlight the importance of PBS remodeling for adaptation to different light conditions. The characterization of ApcI provides insight into the mechanisms by which cyanobacteria optimize light harvesting in response to varying light conditions.

Photosystem↗
DOE OSTI2023

An implicit barotropic mode solver for MPAS-ocean using a modern Fortran solver interface

Here, we demonstrate use of a modern Fortran solver interface to manage solver algorithms for an implicit barotropic mode solver in the Model for Predictions Across Scales-Ocean (MPAS-O). ForTrilinos, a Fortran interface to Trilinos that contains a large collection of solver capabilities written in C++, has been implemented in MPAS-O to provide access to a suite of linear solver options. By virtue of the simplified wrapper and interface generator (SWIG) automation tool that generates modern Fortran interfaces to C++ code, we were able to implement the Fortran solver interface in MPAS-O using a familiar Fortran coding style while minimizing performance degradation. The ForTrilinos solver interface is written within MPAS-O’s time stepping modules as a subroutine in conjunction with MPAS-O code. Applied to an idealized ocean and a high-resolution realistic ocean test case, parallel performance of ForTrilinos solvers is examined. It is found that parallel scalability of the ForTrilinos solvers is highly dependent on the number of global synchronization points per solver iteration in each iterative solver algorithm. ForTrilinos solvers perform best compared to the Fortran hand-crafted (FHC) solver when the amount of work per processor is large enough. However, parallel scalability is better with the FHC solver and so when the work per core is modest FHC outperforms ForTrilinos. The intercomparison between the ForTrilinos and FHC solvers reveals that this performance hit in the ForTrilinos solver mostly comes from the global synchronization process, while suggesting that the matrix-vector multiplication process in the FHC solver needs to be optimized for better performance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Final Report: SECA Core Technology Program - PNNL

This report summarizes results from experimental and modeling studies performed by researchers at Pacific Northwest National Laboratory on behalf of the Solid-State Energy Conversion Alliance (SECA) Core Technology Program. The work was performed from 1999 through 2014, under FWP 40552. PNNL’s scientific and technical contributions included development/evaluation of improved materials and fabrication processes for solid oxide fuel cell (SOFC) components, development/implementation of modeling tools to facilitate cell and stack design and optimization, and improved understanding/mitigation of SOFC performance degradation mechanisms. Primary areas of contribution were 1) Materials and fabrication processes, 2) Modeling and simulation tools, 3) Understanding of degradation mechanisms, and 4) New test protocols. The report contains brief descriptions of primary scientific and technical achievements; references to detailed descriptions of the work (patents, papers, and reports) are also provided.

30 DIRECT ENERGY CONVERSION↗