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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 OSTI2026

DUNE Rucio Server Scalabiilty Studies

The DUNE collaboration has an ongoing production effort to simulate the full detectors and to analyze the various prototypes that are currently running. Rucio is used to manage the 40PB of files made to date. When 500 or more jobs were sending output to Rucio simultaneously via Rucio upload, we observed timeouts, unhandled exceptions, and Rucio server restarts due to slow performance. In collaboration with the core Rucio team we did a full review of the Rucio upload code and identified several optimizations that can be made. We also have deployed the Ingress load balancer in front of our Rucio servers and added a database connection pooling utility. These changes led to significant improvement both in reliability and scalability, yet we anticipate even better performance will eventually be required. We describe in this paper the initial state of the system, the various debugging processes that were used, and our plans to further improve scalability.

Calcutt, J. [Brookhaven Natl. Lab.]↗
DOE OSTI2020

NCBI’s Virus Discovery Codeathon: Building “FIVE” —The Federated Index of Viral Experiments API Index

Viruses represent important test cases for data federation due to their genome size and the rapid increase in sequence data in publicly available databases. However, some consequences of previously decentralized (unfederated) data are lack of consensus or comparisons between feature annotations. Unifying or displaying alternative annotations should be a priority both for communities with robust entry representation and for nascent communities with burgeoning data sources. To this end, during this three-day continuation of the Virus Hunting Toolkit codeathon series (VHT-2), a new integrated and federated viral index was elaborated. This Federated Index of Viral Experiments (FIVE) integrates pre-existing and novel functional and taxonomy annotations and virus–host pairings. Variability in the context of viral genomic diversity is often overlooked in virus databases. As a proof-of-concept, FIVE was the first attempt to include viral genome variation for HIV, the most well-studied human pathogen, through viral genome diversity graphs. As per the publication of this manuscript, FIVE is the first implementation of a virus-specific federated index of such scope. FIVE is coded in BigQuery for optimal access of large quantities of data and is publicly accessible. Many projects of database or index federation fail to provide easier alternatives to access or query information. To this end, a Python API query system was developed to enhance the accessibility of FIVE.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2012

Development of fundamental power coupler for high-current superconducting RF cavity

Brookhaven National Laboratory took a project of developing a 704 MHz five-cell superconducting RF cavity for high-current linacs, including Energy Recovery Linac (ERL) for planned electron-hadron collider eRHIC. The cavity will be fed by a high-power RF amplifier using a coaxial Fundamental Power Coupler (FPC), which delivers 20 kW of CW RF power to the cavity. The design of FPC is one of the important aspects as one has to take into account the heat losses dissipated on the surface of the conductor by RF fields along with that of the static heat load. Using a simple simulation model we show the temperature profile and the heat load dissipated along the coupler length. To minimize the heat load on FPC near the cavity end, a thermal intercept is required at an appropriate location on FPC. A 10 K intercept was chosen and its location optimized with our simulation code. The requirement on the helium gas flow rate for the effective heat removal from the thermal intercept is also discussed.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Wind Farm Simulation and Layout Optimization in Complex Terrain: Preprint

This work reports on incorporating complex terrain into wind farm simulations for the purpose of layout optimization. Adding complex terrain boundary conditions to NREL's medium fidelity computational fluid dynamics model, WindSE, produces significant separation, flow curvature, and speedup effects that would otherwise be difficult to capture with lower-fidelity models or a flat-terrain assumption. These flow features, in turn, can significantly impact the optimal turbine array layout. We demonstrate the impact of complex terrain on flow in both an idealized and real-world setting, and discuss modifications to the code that enable gradient-based optimization using terrain-aware adjoint gradients. Through several optimization case studies, we show that the layout optimization process takes advantage of speedup effects on terrain high points, and leverages flow curvature effects that modify wake trajectories. This yields substantial power improvements over gridded layouts, and hints at future research directions in simulation and optimization for wake trajectories in complex terrain.

17 WIND ENERGY↗
DOE OSTI2016

Extreme Scale Plasma Turbulence Simulations on Top Supercomputers Worldwide

The goal of the extreme scale plasma turbulence studies described in this paper is to expedite the delivery of reliable predictions on confinement physics in large magnetic fusion systems by using world-class supercomputers to carry out simulations with unprecedented resolution and temporal duration. This has involved architecture-dependent optimizations of performance scaling and addressing code portability and energy issues, with the metrics for multi-platform comparisons being 'time-to-solution' and 'energy-to-solution'. Realistic results addressing how confinement losses caused by plasma turbulence scale from present-day devices to the much larger $25 billion international ITER fusion facility have been enabled by innovative advances in the GTC-P code including (i) implementation of one-sided communication from MPI 3.0 standard; (ii) creative optimization techniques on Xeon Phi processors; and (iii) development of a novel performance model for the key kernels of the PIC code. Our results show that modeling data movement is sufficient to predict performance on modern supercomputer platforms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

SciDAC Center for Gyrokinetic Particle Simulation of Turbulent Transport in Burning Plasmas

During the first year of the SciDAC gyrokinetic particle simulation (GPS) project, the GPS team (Zhihong Lin, Liu Chen, Yasutaro Nishimura, and Igor Holod) at the University of California, Irvine (UCI) studied the tokamak electron transport driven by electron temperature gradient (ETG) turbulence, and by trapped electron mode (TEM) turbulence and ion temperature gradient (ITG) turbulence with kinetic electron effects, extended our studies of ITG turbulence spreading to core-edge coupling. We have developed and optimized an elliptic solver using finite element method (FEM), which enables the implementation of advanced kinetic electron models (split-weight scheme and hybrid model) in the SciDAC GPS production code GTC. The GTC code has been ported and optimized on both scalar and vector parallel computer architectures, and is being transformed into objected-oriented style to facilitate collaborative code development. During this period, the UCI team members presented 11 invited talks at major national and international conferences, published 22 papers in peer-reviewed journals and 10 papers in conference proceedings. The UCI hosted the annual SciDAC Workshop on Plasma Turbulence sponsored by the GPS Center, 2005-2007. The workshop was attended by about fifties US and foreign researchers and financially sponsored several gradual students from MIT, Princeton University, Germany, Switzerland, and Finland. A new SciDAC postdoc, Igor Holod, has arrived at UCI to initiate global particle simulation of magnetohydrodynamics turbulence driven by energetic particle modes. The PI, Z. Lin, has been promoted to the Associate Professor with tenure at UCI.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Design of Linear Accelerator (LINAC) tanks for proton therapy via Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) approaches

A homemade computer code for designing a Side- Coupled Linear Accelerator (SCL) is written. It integrates a simplified model of SCL tanks with the Particle Swarm Optimization (PSO) algorithm. The computer code main aim is to obtain useful guidelines for the design of Linear Accelerator (LINAC) resonant cavities. The design procedure, assisted via the aforesaid approach seems very promising, allowing future improvements towards the optimization of actual accelerating geometries. (authors)

43 PARTICLE ACCELERATORS↗
DOE OSTI2013

Procedures and Standards for Residential Ventilation System Commissioning: An Annotated Bibliography

Beginning with the 2008 version of Title 24, new homes in California must comply with ANSI/ASHRAE Standard 62.2-2007 requirements for residential ventilation. Where installed, the limited data available indicate that mechanical ventilation systems do not always perform optimally or even as many codes and forecasts predict. Commissioning such systems when they are installed or during subsequent building retrofits is a step towards eliminating deficiencies and optimizing the tradeoff between energy use and acceptable IAQ. Work funded by the California Energy Commission about a decade ago at Berkeley Lab documented procedures for residential commissioning, but did not focus on ventilation systems. Since then, standards and approaches for commissioning ventilation systems have been an active area of work in Europe. This report describes our efforts to collect new literature on commissioning procedures and to identify information that can be used to support the future development of residential-ventilation-specific procedures and standards. We recommend that a standardized commissioning process and a commissioning guide for practitioners be developed, along with a combined energy and IAQ benefit assessment standard and tool, and a diagnostic guide for estimating continuous pollutant emission rates of concern in residences (including a database that lists emission test data for commercially-available labeled products).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Virtual prototyping of liquid metal blanket performance in fusion pilot plant

Liquid metal blanket is a dominant design option for the next step fusion devices responsible for harvesting energy from fusion reaction, and simultaneously producing fuel for the same reaction through tritium breeding. Liquid metal blankets introduce additional complexity to the design due to fluid motion, fluid structure interaction, and magnetohydrodynamic (MHD) effects arising from the motion of the conducting fluid through the magnetic field. They are also directly affected by the plasma heat flux and neutronic fluence. PPPL is currently developing a virtual prototyping system for numerical analysis of the liquid metal blankets for future fusion devices. The system has a customized 3D computational fluid dynamics (CFD) code in its core, allowing MHD flow and conjugate heat transfer analysis in blankets fluids and solids. The code was successfully used before for dual coolant blanket analysis [A. Khodak et al., Fusion Eng. and Des. 137 (2018)]. Recently the same code was modified to allow verified simulation of MHD flows at high Hartmann numbers of several thousand typical for blanket applications. CFD code receives volumetric heat source distribution from the neutronic analysis based on MCNP code. In addition, direct tritium breeding simulation will be performed allowing optimization of the blanket performance. 2D axisymmetric version of neutronics code will be used for rapid optimization, with 3D version employed for detailed analysis. The surface heat distribution on the plasma facing wall will be defined by the software HEAT allowing 3D modeling of the heat flux based on the magnetic field distribution including gyro-orbit effects. Results of thermal analysis are imported into structural analysis code also included in the system. Finally, direct import of CAD geometry will be used for analyzing all components and as a result design option can be efficiently optimized.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

A comparison of different methods to implement higher order derivatives of density functionals

Density functional theory is the dominant approach in electronic structure methods today. To calculate properties higher order derivatives of the density functionals are required. These derivatives might be implemented manually,by automatic differentiation, or by symbolic algebra programs. Different authors have cited different reasons for using the particular method of their choice. This paper presents work where all three approaches were used and the strengths and weaknesses of each approach are considered. It is found that all three methods produce code that is suffficiently performanted for practical applications, despite the fact that our symbolic algebra generated code and our automatic differentiation code still have scope for significant optimization. The automatic differentiation approach is the best option for producing readable and maintainable code.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Designing Critical Experiments Using Gaussian Process Optimization

New nuclear applications may lack similarity between the application and existing ICSBEP benchmarks. Without accurate benchmark data, predictive simulations will have high uncertainty in the estimate of a parameter of interest (such as k eff ). The design of critical experiments tuned for specific applications of interest is one solution to reducing uncertainty in the necessarily nuclear data. We propose an optimization technique to design critical experiments that match the cross-section sensitivities of an application model while minimizing the number of simulation runs in the optimization. The optimization of a critical experiment is slow because the potential design space covers many qualitative variables (types of material and geometries) and corresponding quantitative variables (e.g., material dimensions) and the evaluation of any specific design requires running an expensive code like MCNP1 and Whisper. The optimization of expensive black-box computer codes with quantitative variables has been extensively explored in the literature of design of computer experiments. We propose a modified version of standard Gaussian process (GP) optimization that optimizes over multiple discrete configurations of qualitative variables in parallel which reduces the computational cost of the entire optimization. The goal of this work is to minimize the number of MCNP evaluations while still exploring many different design configurations in parallel.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2010

Simulations of one- and two-dimensional complex plasmas using a modular, object-oriented code

In a complex plasma, charged microparticles ('dust') are added to a background of ions, electrons, and neutral particles. This dust fully interacts with the surrounding plasma and self-consistently alters the plasma environment leading to the emergence of new plasma behavior. Numerical tools that complement experimental investigations can provide important insights into the properties of complex plasmas. This paper discusses a newly developed code, named DEMON (dynamic exploration of microparticle clouds optimized numerically), for simulating a complex plasma. The DEMON code models the behavior of the charged particle component of a complex plasma in a uniform plasma background. The key feature of the DEMON code is the use of a modular force model that allows a wide variety of experimental configurations to be studied without varying the core code infrastructure. Examples of the flexibility of this modular approach are presented using examples of one- and two-dimensional complex plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Optimization of carbon and energy utilization through differential translational efficiency

Control of translation is vital to all species. Here we employ a multi-omics approach to decipher condition-dependent translational regulation in the model acetogen Clostridium ljungdahlii . Integration of data from cells grown autotrophically or heterotrophically revealed that pathways critical to carbon and energy metabolism are under strong translational regulation. Major pathways involved in carbon and energy metabolism are not only differentially transcribed and translated, but their translational efficiencies are differentially elevated in response to resource availability under different growth conditions. We show that translational efficiency is not static and that it changes dynamically in response to mRNA expression levels. mRNAs harboring optimized 5'-untranslated region and coding region features, have higher translational efficiencies and are significantly enriched in genes encoding carbon and energy metabolism. In contrast, mRNAs enriched in housekeeping functions harbor sub-optimal features and have lower translational efficiencies. As a result, we propose that regulation of translational efficiency is crucial for effectively controlling resource allocation in energy-deprived microorganisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Integration of Dakota into the NEAMS Workbench

This report summarizes a NEAMS (Nuclear Energy Advanced Modeling and Simulation) project focused on integrating Dakota into the NEAMS Workbench. The NEAMS Workbench, developed at Oak Ridge National Laboratory, is a new software framework that provides a graphical user interface, input file creation, parsing, validation, job execution, workflow management, and output processing for a variety of nuclear codes. Dakota is a tool developed at Sandia National Laboratories that provides a suite of uncertainty quantification and optimization algorithms. Providing Dakota within the NEAMS Workbench allows users of nuclear simulation codes to perform uncertainty and optimization studies on their nuclear codes from within a common, integrated environment. Details of the integration and parsing are provided, along with an example of Dakota running a sampling study on the fuels performance code, BISON, from within the NEAMS Workbench.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Spin-squeezed Gottesman-Kitaev-Preskill codes for quantum error correction in atomic ensembles

Gottesman-Kitaev-Preskill (GKP) codes encode a qubit in displaced phase-space combs of a continuous-variable (CV) quantum system and are useful for correcting a variety of high-weight photonic errors. Here we propose atomic ensemble analogs of the single-mode CV GKP code by using the quantum central limit theorem to pull back the phase-space structure of a CV system to the compact phase space of a quantum spin system. We study the optimal recovery performance of these codes under error channels described by stochastic relaxation and isotropic ballistic dephasing processes using the diversity combining approach for calculating channel fidelity. Additionally, we find that the spin GKP codes outperform other spin system codes such as cat codes or binomial codes. Our spin GKP codes based on the two-axis countertwisting interaction and superpositions of SU(2) coherent states are direct spin analogs of the finite-energy CV GKP codes, whereas our codes based on one-axis twisting do not yet have well-studied CV analogs. A state preparation scheme for the spin GKP codes is proposed which uses the linear-combination-of-unitaries method, applicable to both the CV and spin GKP settings. Finally, we discuss a fault-tolerant approximate gate set for quantum computing with spin-GKP-encoded qubits, obtained by translating gates from the CV GKP setting using the quantum central limit theorem.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

TEAM project review, year 1

This note summarizes our research activities within the TEAM project between October 2019 and November 2020, funded by the ASCR Advanced Research in Quantum Computing program. Three research efforts have begun during the review period. The first effort, resulting in the JuQBox software, implemented a novel algorithm for optimal control in closed quantum systems based on symplectic time integration and exact calculations of the gradient of the discretized objective function. In our second effort, resulting in a code called Quandary, we consider the optimal control problem for open quantum systems. Here the evolution of the quantum system is modeled by the Lindblad master equation. In this code, we are considering both the realization of quantum gates as well as the optimal reset problem in which a general mixed quantum state is driven towards its ground state. In our third research effort we have begun the development of computational software for what we call Lindblad learning, i.e. the process of characterizing the equations governing our quantum computing hardware.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Development of multi-objective core optimization framework and application to sodium-cooled fast test reactors

The optimization of a Sodium-cooled Fast Reactor (SFR) core is a challenging process, due to the large number of design parameters, the nonlinearities among inputs and outputs, and the complicated correlation among output parameters. This study attempts to develop a generalized framework for the SFR core optimization by coupling the sensitivity analysis, advanced optimization algorithm, and optionally the surrogate modeling. The framework is built based on the fast reactor modeling capability of the Argonne Reactor Computation (ARC) suite and the sensitivity analysis and optimization modules embedded in the DAKOTA code, both have been integrated within the NEAMS Workbench. The genetic algorithm is selected as the optimization method for its robustness, while the option of surrogate modeling is also explored to alleviate the computational burden caused by employing the ARC direct core physics simulation and thus enhance the efficiency of the optimization. Finally, the normalized deviations of performance parameters of the near-optimal solution from those of the ideal core are calculated and used as criteria to down select the final core design. The developed framework is applied to the Advanced Burner Test Reactor (ABTR) core, and optimal solutions are determined by balancing various objectives simultaneously, including peak fast flux, core volume, power, reactivity swing, plutonium mass feed, while at the same time satisfying the predefined constraints due to safety or economics considerations. The optimal ABTR core design obtained using the direct physical simulation and surrogated model are compared and discussed. It is found that using the accurately constructed surrogate models can significantly reduce the required computational time while maintaining satisfactory accuracy.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Particle Swarm Optimisation for group structure optimization for radiotherapy shielding

Neutron transport simulations are ubiquitous in nuclear engineering because they allow one to model experimental systems and render a model platform for easy perturbation of experimental designs. In addition, simulations allow one to gain experimental insight without actually having to go through the trouble of building a physical experiment. Neutron transport simulations can be stochastic or deterministic based. Stochastic neutron transport simulations are typically simulated using the Monte Carlo method and yield very accurate solutions but are computationally expensive, while deterministic methods are typically faster but can be less accurate. Here we focus on optimizing the accuracy of deterministic neutron transport simulations for radiotherapy simulations. Deterministic neutron transport requires discretization of angle, energy, and space to appropriately analyze the system one is trying to model. Discretization of energy is challenging because of the highly variable neutron flux at certain neutron energies. Improper discretization of energy in the transport model can lead to erroneous results and therefore inaccurate interpretations of the solution. In this study, we evaluate Particle Swarm Optimization (PSO) as a mechanism for selecting optimal group structures for radiotherapy shielding. We tested the particle swarm optimization algorithm on radiotherapy shielding problems using Los Alamos National Laboratory's (LANL) main deterministic transport code PARTISN. Results show that the optimized energy group structures generated from the optimization algorithm outperformed LANL's standard energy group structures, and therefore demonstrate utility in using PSO to expedite computation times due to the increased accuracy obtained with a smaller but optimized group structure. (authors)

43 PARTICLE ACCELERATORS↗