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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 OSTI2016

Composition and Realization of Source-to-Sink High-Performance Flows: File Systems, Storage, Hosts, LAN and WAN

A number of Department of Energy (DOE) science applications, involving exascale computing systems and large experimental facilities, are expected to generate large volumes of data, in the range of petabytes to exabytes, which will be transported over wide-area networks for the purpose of storage, visualization, and analysis. To support such capabilities, significant progress has been made in various components including the deployment of 100 Gbps networks with future 1 Tbps bandwidth, increases in end-host capabilities with multiple cores and buses, capacity improvements in large disk arrays, and deployment of parallel file systems such as Lustre and GPFS. High-performance source-to-sink data flows must be composed of these component systems, which requires significant optimizations of the storage-to-host data and execution paths to match the edge and long-haul network connections. In particular, end systems are currently supported by 10-40 Gbps Network Interface Cards (NIC) and 8-32 Gbps storage Host Channel Adapters (HCAs), which carry the individual flows that collectively must reach network speeds of 100 Gbps and higher. Indeed, such data flows must be synthesized using multicore, multibus hosts connected to high-performance storage systems on one side and to the network on the other side. Current experimental results show that the constituent flows must be optimally composed and preserved from storage systems, across the hosts and the networks with minimal interference. Furthermore, such a capability must be made available transparently to the science users without placing undue demands on them to account for the details of underlying systems and networks. And, this task is expected to become even more complex in the future due to the increasing sophistication of hosts, storage systems, and networks that constitute the high-performance flows. The objectives of this proposal are to (1) develop and test the component technologies and their synthesis methods to achieve source-to-sink high-performance flows, and (2) develop tools that provide these capabilities through simple interfaces to users and applications. In terms of the former, we propose to develop (1) optimization methods that align and transition multiple storage flows to multiple network flows on multicore, multibus hosts; and (2) edge and long-haul network path realization and maintenance using advanced provisioning methods including OSCARS and OpenFlow. We also propose synthesis methods that combine these individual technologies to compose high-performance flows using a collection of constituent storage-network flows, and realize them across the storage and local network connections as well as long-haul connections. We propose to develop automated user tools that profile the hosts, storage systems, and network connections; compose the source-to-sink complex flows; and set up and maintain the needed network connections. These solutions will be tested using (1) 100 Gbps connection(s) between Oak Ridge National Laboratory (ORNL) and Argonne National Laboratory (ANL) with storage systems supported by Lustre and GPFS file systems with an asymmetric connection to University of Memphis (UM); (2) ORNL testbed with multicore and multibus hosts, switches with OpenFlow capabilities, and network emulators; and (3) 100 Gbps connections from ESnet and their Openflow testbed, and other experimental connections. This proposal brings together the expertise and facilities of the two national laboratories, ORNL and ANL, and UM. It also represents a collaboration between DOE and the Department of Defense (DOD) projects at ORNL by sharing technical expertise and personnel costs, and leveraging the existing DOD Extreme Scale Systems Center (ESSC) facilities at ORNL.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Contributions of Solar + Storage to Future Power Needs

The costs of solar photovoltaics (PV) have been dropping in recent years, leading to increasing installations of solar PV systems and growing interest in how the technology will impact the electric grid. Additionally, as battery costs decline, there is increasing interest in understanding the benefits and limitations of battery storage for the grid as well as potential co-benefits of coupling battery storage and photovoltaics. This paper presents recent methodological developments to more accurately represent the value and limitations of coupled PV and battery systems in capacity expansion models. These are demonstrated using the Resource Planning Model (RPM), which co-optimizes capacity investments, transmission investments, and reduced-order dispatch through 2045. We simulate the evolution of the generation and transmission system in the Western Interconnection both with and without a coupled PV and battery technology option under two core scenarios - a baseline scenario and a high renewable penetration scenario - coupled with sensitivities assuming low and mid PV and battery cost projections. We analyze the degree to which a variety of configurations of coupled PV + Battery systems are able to meet future electricity needs, under which system conditions this coupled technology becomes beneficial to the electric grid and identify the displaced technologies when coupled solar and storage is introduced into the model. We find that capturing the benefits of co-locating these systems becomes increasingly important as the penetration of solar PV rises, and that in particular it is important to accurately capture the ability of these technologies to shift energy, provide firm capacity, and reduce expected curtailment.

14 SOLAR ENERGY↗
DOE OSTI2018

ATF Transient Prescription Tests in TREAT

EXECUTIVE SUMMARY The Transient Reactor Test facility (TREAT) was constructed in the late 1950’s and provided thousands of transient irradiations before being placed in standby mode in 1994. In 2017, it resumed operation in order to reclaim its crucial role in nuclear-heated safety research. TREAT is a transient reactor where inherently-safe core physics, a nimble transient rod drive system, and a philosophy of continual facility improvement work together to enable flexible power maneuvers for fuel safety research. While the facility’s flexible design and multi-mission nature saw historic experiments for numerous transient types, TREAT was not specifically adapted to optimize or demonstrate its full performance capability for Light Water Reactor (LWR) postulated accidents including Hot Zero Power Reactivity Initiated Accidents (HZP-RIA) and Loss of Coolant Accidents (LOCA). The physics of HZP-RIA drive very brief pulses with fairly large energy excursions. TREAT is currently capable of approaching HZP-RIA pulse widths through transients initiated on a large step insertion of reactivity and terminated shortly thereafter by rapid re-insertion of the transient rods (“clipping”). LOCAs are postulated to occur quite differently, starting from normal power operations followed by a long period of lower power decay heat. TREAT is able to simulate LOCA events with an initial flattop transient for tens of seconds, followed by a sizeable power reduction, to a longer segment where specimen fission heating represents internal decay heat generation. Two reactor physics testing campaigns were undertaken to address the HZP-RIA type transients, neither of which had been performed in any great measure historically to address data gaps in the timing, repeatability of clipping and effect of dynamic transient rod motions on core-to-specimen fission power coupling. The first campaign, referred to as the Accident Tolerant Fuel (ATF) transient prescription tests, employed dosimeters in the core to characterize the effect of rod motions on specimen power coupling for clipped, unclipped, and low-level steady state operations each with approximately the same moderate core energy release. This campaign was accompanied by efforts to measure dosimetry and compare results to analytic predictions. The other HZP-RIA campaign, referred to as Narrow Pulse Width (NPW) transient prescriptions, employed higher step insertions with increased core energy release to demonstrate TREAT’s capability in achieving the narrowest-possible pulse width. Additionally, a series of LOCA transient prescriptions were also performed to demonstrate how well TREAT could perform long-duration shaped transients. Both NPW and LOCA transient prescriptions did not include dosimeters but used existing plant power instrumentation to produce transient power data. All three transient prescription campaigns were successfully carried out in TREAT. The ATF-3 transient prescriptions showed that TREAT can perform clipped transients with remarkable repeatability. Measurement and modeling both showed that the power coupling in small, fissile dosimeters does not change by more than 8% between clipped, unclipped, and steady state runs while uncertainty sources in both the modeling and measurement methods were identified and found to be on the order of 20% in total. Overall, the ATF-3 transient prescription tests were successful in determining repeatability and consistency of dosimeter power coupling, developing processes for modeling and measuring this crucial parameter, and demonstrating the need for continued efforts in transient prescription work at TREAT in support of future experiment design and post test data interpretation. The NPW and LOCA transient prescriptions were also successfully performed to exhibit TREAT’s capability for these important LWR accident categories. The NPW transients showed pulse widths of ~90 ms, which were the narrowest ever achieved in TREAT to date and relevant for the upper end range of HZP-RIA simulation. This effort provided crucial data for calibrating kinetic models to be used in enhanced pulse-narrowing strategies in upcoming irradiations. Similarly, The LOCA transient prescriptions showed that TREAT can simulate the needed nuclear heating and event time scales for LOCA fuel safety research and provided essential data for future experiment design.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Boosting the Oxygen Reduction Performance via Tuning the Synergy between Metal Core and Oxide Shell of Metal−Organic Frameworks‐Derived Co@CoO x

Abstract Co core@Co oxide shell (Co@CoO x ) catalysts represent a large family with promising oxygen reduction reaction (ORR) catalytic activity. However, inadequate understanding of Co@CoO x synergy prohibits further pursuit of catalytic performance enhancement. Herein, a Co zeolitic−imidazolate framework was converted into metallic Co, followed by controlled air treatment to form Co@CoO x . The composition and structure evolution as a function of air treatment temperature were studied thoroughly through conventional and synchrotron (both ex‐situ and in‐situ) characterizations, confirming the coexistence of CoO and Co 3 O 4 in the shell. The optimal catalyst showed an ORR half‐wave potential of 0.87 V (vs. RHE) in an alkaline half‐cell and delivered high discharge capacity in an aprotic Li−O 2 battery (7,124 mAh g Cat+C −1 ) and an aqueous Zn−air battery (694 mAh g Zn −1 ) with good performance retention after durability test. Modeling simulation and density functional theory calculation confirmed the charge donation from metal core to oxide shell and shed light on new insights of how metal@metal oxide synergy impacted the ORR via tuning the charge conductivity, oxygen affinity and intermediate transfer pathway. This work opens up a venue to boost ORR catalytic activity from an interfacial synergy perspective.

Wang, Hao↗
DOE OSTI2019

Twin-core sunflower-type photonic quasicrystal fibers incorporated gold, silver, and copper microwire: an ultrashort and broad bandwidth polarization splitter

Polarization splitters are beneficial in the field of passive optical devices which are principally used in the coherent optical communication systems. An ideal polarization splitter must possess an efficient coupling with significant optical bandwidth. Hence, we proposed a novel metal-filled polarization splitter based on twin-core sunflower-type photonic quasicrystal fiber (PQF). The characteristics of the proposed splitter such as coupling length, extinction ratio, and available optical bandwidth were investigated by using the commercially available software, COMSOL Multiphysics. These aforementioned characteristics were determined by optimizing the geometrical parameters of proposed PQF—first by using gold-filled PQF (AuPQF). With optimized geometrical parameters, the splitter achieved an ultra-short coupling length of 132 µm and an ultra-broad bandwidth of 301 nm (wavelength range 1.36–1.68 µm) with an extinction ratio below than − 20 dB which comprised E + S+C + L+U band. Secondly, a comparative study to use silver- and copper-filled PQF (AgPQF and CuPQF) was explored. Both AgPQF and CuPQF retained a short length with adequate bandwidth and a significant extinction ratio below than − 20 dB. The AgPQF has a coupling length of 137 µm with a bandwidth of 136 nm which operated at 1.44 µm wavelength, while CuPQF with 134 µm lengths with a bandwidth of 149 nm and operated at 1.50 µm wavelengths.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Plasma Radiation Source on the Basis of the Gas Puff with Outer Plasma Shell in the Circuit of a Mega-Ampere Load Current Doubler

Characteristics of Z-pinch plasma radiation in the form of a double shell neon gas puff with outer plasma shell are investigated in the microsecond implosion mode. Experiments are performed using a GIT-12 mega-joule generator with load current doubler having a ferromagnetic core at implosion currents up to 5 MA. Conditions for matching of the nonlinear load with the mega-ampere current multiplier circuit are determined. The load parameters (plasma shell characteristics and mass and geometry of gas puff shells) are optimized on the energy supplied to the gas puff and n energy characteristics of radiation. It is established that the best modes of K-shell radiation in neon are realized for such radial distribution of the gas-puff material at which the compression velocity of the shell is close to a constant and amounts to 27–30 cm/μs. In these modes, up to 40% of energy supplied to the gas puff is converted into K-shell radiation. The reasons limiting the efficiency of the radiation source with increasing implosion current are analyzed. A modernized version of the energy supply from the current doubler to the Z-pinch is proposed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

HAM: Hotspot-Aware Manager for Improving Communications with 3D-Stacked Memory

merging High-Performance Computing (HPC) workloads, such as graph analytics, machine learning, and big data science, are data-intensive. Data-intensive workloads usually present fine-grained memory accesses with limited or no data locality, and thus incur frequent cache misses and low utilization of memory bandwidth. 3D-stacked memory devices such as Hybrid Memory Cube (HMC) and High Bandwidth Memory (HBM) can provide significantly higher bandwidth than conventional memory modules. However, the traditional interfaces and optimization methods for JEDEC DDR devices do not allow to fully exploit the potential performance of 3D-stacked memory with the massive amount of irregular memory accesses of data-intensive applications. In this paper, we propose a novel Hotspot-Aware Manager (HAM) infrastructure for 3D-stacked memory devices capable of optimizing memory access streams via request aggregation, hotspot detection, and in-memory prefetching. %and an associated hotspot-aware page policy. We present the HAM design and implementation, and simulate it on a system using RISC-V embedded cores with attached HMC devices. We extensively evaluate HAM with over 12 benchmarks and applications representing diverse irregular memory access patterns. The results show that, on average, HAM reduces redundant requests by 37.51\% and increases the prefetch buffer hit rate by 4.2 times, compared to a baseline streaming prefetcher. On the selected benchmark set, HAM provides performance gains of 21.81\% in average (up to 34.28\%) and power savings of 35.07\% over a standard 3D-stacked memory.

Wang, Xi↗
DOE OSTI2019

Scalable Deep Learning via I/O Analysis and Optimization

Scalable deep neural network training has been gaining prominence because of the increasing importance of deep learning in a multitude of scientific and commercial domains. Consequently, a number of researchers have investigated techniques to optimize deep learning systems. Much of the prior work has focused on runtime and algorithmic enhancements to optimize the computation and communication. Despite these enhancements, however, deep learning systems still suffer from scalability limitations, particularly with respect to data I/O. This situation is especially true for training models where the computation can be effectively parallelized, leaving I/O as the major bottleneck. In fact, our analysis shows that I/O can take up to 90% of the total training time. Thus, in this article, we first analyze LMDB, the most widely used I/O subsystem of deep learning frameworks, to understand the causes of this I/O inefficiency. Based on our analysis, we propose LMDBIO—an optimized I/O plugin for scalable deep learning. LMDBIO includes six novel optimizations that together address the various shortcomings in existing I/O for deep learning. Lastly, our experimental results show that LMDBIO significantly outperforms LMDB in all cases and improves overall application performance by up to 65-fold on a 9,216-core system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

JGI-Trichoderma v1.0

There is a series of Python and bash scripts to parse genomics datasets used to evaluate the coevolution of gene families and the feature importance of gene families using an SVM classifier. - Cover analysis: takes a list of single-copy genes in a set of genomes, aligns and builds the gene trees to determine if two gene families have a signature of covariation with one another. It parses the files to run phykit cover script described here: https://jlsteenwyk.com/PhyKIT/usage/index.html - SVM-classifier: This Python script is an SVM-based genomic classifier designed for biological data analysis. It combines machine learning with feature selection to identify important genomic markers and classify biological samples. Core Functionality: The script uses Support Vector Machines from scikit-learn to classify genomic data, incorporating SelectKBest for automated feature selection and leave-one-out cross-validation for performance assessment. It operates in multiple modes: feature ranking, optimal combination discovery, and sample prediction. Primary Applications: Genomic sample classification and biomarker discovery Feature importance analysis in high-dimensional biological datasets Prediction of sample categories based on genomic profiles Research applications requiring robust classification of biological data Key Advantages: High-dimensional handling: SVMs excel with genomic data's typical high feature-to-sample ratios Integrated feature selection: Reduces noise and computational overhead while identifying key markers Probability estimation: Provides confidence scores essential for biological interpretation Validation robustness: Leave-one-out cross-validation ensures reliable performance metrics Operational flexibility: Multiple analysis modes support different research phases from exploration to prediction

Stecca Steindorff, Andrei [Lawrence Berkeley Natio↗
DOE OSTI2025

Comparative study of spectral broadening and few-cycle compression of Yb:KGW laser pulses in gas-filled hollow-core fibers

While industrial-grade Yb-based amplifiers have become very prevalent, their limited gain bandwidth has created a large demand for robust spectral broadening techniques that allow for few-cycle pulse compression. In this work, we perform a comparative study between several atomic and molecular gases as media for spectral broadening in a hollow-core fiber geometry. Exploiting nonlinearities such as self-phase modulation, self-steepening, and stimulated Raman scattering, we explore the extent of spectral broadening and its dependence on gas pressure, the critical power for self-focusing, and the optimal regime for few-cycle pulse compression. Using a 3-mJ, 200-fs input laser pulses, we achieve 17 fs, few-cycle pulses with 80% fiber energy transmission efficiency. The optimal parameters can be scaled for higher or lower input pulse energies with appropriate gas parameters and fiber geometry.

Shalaby, Islam (ORCID:0000000332846636)↗
DOE OSTI2020

Mirostructure Characterization of Friction Consolidated Copper-Nickel using a Machine Learning Approach: Developing Process to Microstructure Associations

Friction consolidation (FC) is a solid phase processing approach where discrete material forms such as powders, chips, nuggets, etc. are densified via shear deformation. The precursors are placed in a billet container and brought in contact with a rotating tool that applying the desirable amount of normal force. Under the combined action of the rotation and normal pressure, the discrete precursor is consolidated through porosity reduction and shear deformation. FC is increasingly being studied as an attractive approach to manufacturing fully dense parts from powder forms owing to its ability to mix, alloy and consolidate difficult-to-process precursors in minimal number of process steps. Material consolidation and deformation in shear consolidation processes have been studied extensively previously for different material combinations previously. However, despite the extensive research in this area, understanding of the mechanistic processes in pore consolidation, deformation-induced mixing and material solubility during FC is still evolving. Material development using solid phase processing approaches such as FC is often performed based on research experience/education, which can be biased. Conventional analysis and simulation tools in this area tend to be successful only when material thermodynamic pathways and microstructural evolution sequences resulting from processing are clearly defined or known. They are not as effective for emerging advanced manufacturing technologies where material evolution pathways are not well established. The ability to predict optimal process parameters based on material chemistry and bulk properties is essential to accelerate materials design and processing, as are an understanding of the relevant structure-processing-property relationships. These structure-processing-property-performance relationships are at the core of materials science research. Microstructure characterization provides the link to these four core areas, often through visualizing material microstructure using imaging techniques. However, linking microstructure image data (i.e., micrographs) to variables of interest (e.g., processing parameters, material chemistry) in a reproducible, generalizable, and quantitative manner is a significant challenge. Typically, quantitatively linking image data to processing history relies on significant domain knowledge and manual or subject matter expert (SME)-heuristic based image analysis. Such an approach to image analysis has the potential to be biased, inefficient, and difficult to replicate.

36 MATERIALS SCIENCE↗
DOE OSTI2024

SEAS Communication Engine: An Extensible, Flexible Wrapper for Co-Simulation Agents

When modeling and analyzing the power grid and other large scale systems, researchers often express scenarios as optimization problems and feed them into advanced software solvers. In order to allow multiple solvers to communicate with each other and share data from different domains, the National Renewable Energy Laboratory (NREL) and associated Department of Energy (DOE) labs have developed a software framework called the Hierarchical Engine for Large-scale Infrastructure Co-Simulation (HELICS). HELICS allows cosimulation via a collection of client libraries for different languages that can be called from the appropriate optimization software. However, these client libraries do not provide a higher level of abstraction beyond reading and writing data off of the shared HELICS bus. In this paper, we describe a new software library called the SEAS Communication Engine that exposes a higher-level API for running cosimulation problems. The SEAS Engine provides a class-based abstraction on top of the Python HELICS client, in order to allow users to implement their domain-specific cosimulations without needing to interact with core HELICS primitives. This will make adoption of HELICS and cosimulation in general easier, by exposing a simpler API. In the second part of the paper, we validate our library on a collection of different simulation examples, including the canonical IEEE 13 Bus Feeder. Lastly, we demonstrate using the SEAS Engine to directly call domain-specific code written in the Julia programming language. Our hope is that this will serve as a template for easily calling software in different programming languages via the SEAS Engine, thereby avoiding code duplication and complexity.

co-simulation↗
DOE OSTI2015

SU-E-T-500: Initial Implementation of GPU-Based Particle Swarm Optimization for 4D IMRT Planning in Lung SBRT

Purpose 4D-IMRT planning, combined with dynamic MLC tracking delivery, utilizes the temporal dimension as an additional degree of freedom to achieve improved OAR-sparing. The computational complexity for such optimization increases exponentially with increase in dimensionality. In order to accomplish this task in a clinically-feasible time frame, we present an initial implementation of GPU-based 4D-IMRT planning based on particle swarm optimization (PSO). Methods The target and normal structures were manually contoured on ten phases of a 4DCT scan of a NSCLC patient with a 54cm3 right-lower-lobe tumor (1.5cm motion). Corresponding ten 3D-IMRT plans were created in the Eclipse treatment planning system (Ver-13.6). A vendor-provided scripting interface was used to export 3D-dose matrices corresponding to each control point (10 phases × 9 beams × 166 control points = 14,940), which served as input to PSO. The optimization task was to iteratively adjust the weights of each control point and scale the corresponding dose matrices. In order to handle the large amount of data in GPU memory, dose matrices were sparsified and placed in contiguous memory blocks with the 14,940 weight-variables. PSO was implemented on CPU (dual-Xeon, 3.1GHz) and GPU (dual-K20 Tesla, 2496 cores, 3.52Tflops, each) platforms. NiftyReg, an open-source deformable image registration package, was used to calculate the summed dose. Results The 4D-PSO plan yielded PTV coverage comparable to the clinical ITV-based plan and significantly higher OAR-sparing, as follows: lung Dmean=33%; lung V20=27%; spinal cord Dmax=26%; esophagus Dmax=42%; heart Dmax=0%; heart Dmean=47%. The GPU-PSO processing time for 14940 variables and 7 PSO-particles was 41% that of CPU-PSO (199 vs. 488 minutes). Conclusion Truly 4D-IMRT planning can yield significant OAR dose-sparing while preserving PTV coverage. The corresponding optimization problem is large-scale, non-convex and computationally rigorous. Our initial results indicate that GPU-based PSO with further software optimization can make such planning clinically feasible. This work was supported through funding from the National Institutes of Health and Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Optimizing a Multiple Right-Hand Side Dslash Kernel for Intel Knights Corner

Lattice Quantum Chromo-dynamics (LQCD) stands unique as the only computationally tractable, non-perturbative, and model-independent quantum field theory of the strong nuclear force. LQCD achieves tractability by discretizing our familiar 4-dimensional space-time onto a hypercubic lattice. The core component of the linear solver used in LQCD is the Wilson-Dirac operator whose finite difference component is called the Dslash operator. Dslash is a nearest neighbor stencil operator summing matrix-vector multiplications over lattice points. The arithmetic intensity of a regular Dslash operator acting on a single vector in single precision is between 0.88-2.29 (depending on the tricks employed) making it memory bandwidth bound on most current architectures, including Xeon Phi. Maximizing the performance of Dslash on Xeon Phi requires deliberate exploitation of its architectural features. One key feature of Xeon Phi is its powerful vector processing unit with lengthy vector registers. There is a class of LQCD computations which aims to solve the Dirac equation for the same lattice gauge fields multiple times. In this case one can gain additional reuse of the gauge field, and potentially simplified vectorization, through applying Dslash to several vectors at the same time; often referred to as Multiple Right Hand Side (MRHS) Dslash. Previous work in this area focused on applying this approach to the Highly Improved Staggered operator, and in cases to the multi-Grid algorithm for Wilson clover fermions. Here, we present two approaches to MRHS Dslash: a vector register blocking approach and one using the software package QPhiX with a custom Code Generator for low-level intrinsics. We explore the Knights Corner instruction set, memory hierarchy, and threading capabilities. For standard lattice sizes used in testing, we observed significant speedups, with sustained performance of over 700 GFLOPS (single precision) in one instance. We achieved up to 27% of theoretical peak performance compared to a maximum of 12% obtained by the previous single RHS method in QPhiX.

Joó, Bálint↗
DOE OSTI2022

MEITNER Resource Team Modeling and Simulation Support to Holos-Quad Reactor Development (Final CRADA Report)

The main objective of this CRADA is to provide Argonne National Laboratory (ANL)’s modeling and simulation capabilities via ARPA-E's MEITNER (Modeling-Enhanced Innovations Trailblazing Nuclear Energy Reinvigoration) Resource Team (RT) arrangement to support the demonstration of the viability of HolosGen’s Holos-Quad reactor design. The Holos-Quad reactor design is an advanced reactor concept that incorporates many new design features, such as the neutron-coupled Subcritical Power Modules (SPMs) in its core design, elimination of balance of plant (BOP) by direct integration of a helium Brayton cycle power conversion system with each SPM, among many other innovative features. The demonstration of the viability of such an innovative reactor design warrants iterations of modeling and simulation and testing. The purpose of this project is to utilize ANL’s modeling and simulation capabilities in nuclear reactor analysis and power conversion system analysis to inform HolosGen and the Design Team (DT) in the design and optimization of the Holos-Quad concept. The major work scopes of this project include: to investigate conceptual designs and materials for radiation shielding to protect personnel and internal components such as turbomachinery; Assess the the helium Brayton cycle power conversion system performance in both nominal and load following conditions; Investigate power conversion components and overall system performance; Identify control strategies to enable load following; Perform simulations of HolosGen’s subscale simulator and using available test data for code validation/benchmark purpose; Perform core thermal-hydraulics, safety analysis, and structural analysis.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

StoreRush: An Application-Level Approach to Harvesting Idle Storage in a Best Effort Environment

For a production HPC system where storage devices are shared between multiple applications and managed in a best effort manner, contention is often a major problem leading to some storage devices being more loaded than others and causing a significant reduction in I/O throughput. In this paper, we describe our latest efforts StoreRush to resolve this practical issue at the application level without requiring modification to the file and storage system. The proposed scheme uses a two-level messaging system to harvest idle storage via re-routing I/O requests to a less congested storage location so that write performance is improved while limiting the impact on read by throttling re-routing if deemed too much. An analytical model is derived to guide the setup of optimal throttling factor. The proposed scheme is verified against production applications Pixie3D, XGC1 and QMCPack during production windows, which very well demonstrated the effectiveness (e.g., up to 1.8x improvement in write) and scalability of our approach (up to 131,072 cores).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

AlGaN/GaN Core-Shell Nanofin Diodes on Si Substrates for Vertical GaN Electronics

We demonstrate plasma-assisted MBE selective-area growth of GaN/AlGaN core-shell structures on Si(111) as a path to vertical GaN devices. The selective-area growth enables the full vertical and uniform core-shell fin structures to be realized in a continuous growth without breaking vacuum. TEM images and EDS mapping of the core-shell structures show well-aligned crystal structure and sharp heterointerfaces. Dislocation filtering was observed in STEM imaging of the fin structure. P-N junction diodes fabricated with GaN/AlGaN core-shell structures reveal ideality factors as low as 1.5, and the reverse-bias leakage is consistent with trap-assisted space-charge-limited conduction. While practical challenges exist, including material-related leakage, growth-related challenges and optimization, this demonstration of p-n junction by this method may provide a path to vertical Superjunction device concepts in GaN and related materials.

Xiong, Juncheng [University of Notre Dame, IN (Uni↗
DOE OSTI2017

Impurity screening behavior of the high-field side scrape-off layer in near-double-null configurations: prospect for mitigating plasma–material interactions on RF actuators and first-wall components

The impurity screening response of the high-field side (HFS) scrape-off layer (SOL) to localized nitrogen injection is investigated on Alcator C-Mod for magnetic equilibria spanning lower-single-null, double-null and upper-single-null configurations under otherwise identical plasma conditions. L-mode, EDA H-mode and I-mode discharges are investigated. HFS impurity screening is found to depend on magnetic flux balance and the direction of B × $\nabla$B relative to the most active divertor. Impurity 'plume' emission patterns indicate that both parallel and perpendicular (E × B) flows in the SOL contribute to the 'flushing' of impurities towards the active divertor, thereby affecting the overall impurity screening behavior. Despite the fact that the HFS SOL is extremely narrow in near-double-null configurations, this SOL is able to screen locally injected nitrogen at least as effectively as the low-field side (LFS) SOL—up to a factor of 10 more effective, depending on specific plasma conditions and whether the magnetic geometry produces parallel flows that work with or against E × B flows. For situations in which the E × B drift of the impurity ions opposes parallel flow toward the primary divertor, HFS impurity screening is found to be least effective. When E × B drifts assist parallel flow toward the primary divertor, HFS impurity screening is found to be very effective. These data support the idea of placing RF actuators and close-fitting wall components on the HFS of the tokamak. Finally, with this configuration, near-double-null magnetic topologies may be used for active control of plasma parameters at the antenna/plasma interface for optimal RF coupling, mitigate the generation of local impurities from plasma–material interactions and, taking advantage of favorable plasma flows and good screening properties of the HFS SOL, further minimize the impact of wall-born impurity sources on the plasma core.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗