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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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Analysis on burnup step effect for evaluating reactor criticality and fuel breeding ratio

Criticality condition of the reactors is one of the important factors for evaluating reactor operation and nuclear fuel breeding ratio is another factor to show nuclear fuel sustainability. This study analyzes the effect of burnup steps and cycle operation step for evaluating the criticality condition of the reactor as well as the performance of nuclear fuel breeding or breeding ratio (BR). Burnup step is performed based on a day step analysis which is varied from 10 days up to 800 days and for cycle operation from 1 cycle up to 8 cycles reactor operations. In addition, calculation efficiency based on the variation of computer processors to run the analysis in term of time (time efficiency in the calculation) have been also investigated. Optimization method for reactor design analysis which is used a large fast breeder reactor type as a reference case was performed by adopting an established reactor design code of JOINT-FR. The results show a criticality condition becomes higher for smaller burnup step (day) and for breeding ratio becomes less for smaller burnup step (day). Some nuclides contribute to make better criticality when smaller burnup step due to individul nuclide half-live. Calculation time for different burnup step shows a correlation with the time consuming requirement for more details step calculation, although the consuming time is not directly equivalent with the how many time the burnup time step is divided.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2014

Theoretical investigation of the relative stability of Na{sup +}He{sub n} (n = 2–24) clusters: Many-body versus delocalization effects

The solvation of the Na{sup +} ion in helium clusters has been studied theoretically using optimization methods. A many-body empirical potential was developed to account for Na{sup +}–He and polarization interactions, and the most stable structures of Na{sup +}He{sub n} clusters were determined using the basin-hopping method. Vibrational delocalization was accounted for using zero-point energy corrections at the harmonic or anharmonic levels, the latter being evaluated from quantum Monte Carlo simulations for spinless particles. From the static perspective, many-body effects are found to play a minor role, and the structures obtained reflect homogeneous covering up to n = 10, followed by polyicosahedral packing above this size, the cluster obtained at n = 12 appearing particularly stable. The cationic impurity binds the closest helium atoms sufficiently to negate vibrational delocalization at small sizes. However, this snowball effect is obliterated earlier than shell completion, the nuclear wavefunctions of {sup 4}He{sub n}Na{sup +} with n = 5–7, and n > 10 already exhibiting multiple inherent structures. The decrease in the snowball size due to many-body effects is consistent with recent mass spectrometry measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Stabilized quasi-Newton optimization of noisy potential energy surfaces

Optimizations of atomic positions belong to the most commonly performed tasks in electronic structure calculations. Many simulations like global minimum searches or characterizations of chemical reactions require performing hundreds or thousands of minimizations or saddle computations. To automatize these tasks, optimization algorithms must not only be efficient but also very reliable. Unfortunately, computational noise in forces and energies is inherent to electronic structure codes. This computational noise poses a severe problem to the stability of efficient optimization methods like the limited-memory Broyden–Fletcher–Goldfarb–Shanno algorithm. We here present a technique that allows obtaining significant curvature information of noisy potential energy surfaces. We use this technique to construct both, a stabilized quasi-Newton minimization method and a stabilized quasi-Newton saddle finding approach. We demonstrate with the help of benchmarks that both the minimizer and the saddle finding approach are superior to comparable existing methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Charge transfer properties of pentacene adsorbed on silver: DFT study

Charge transfer properties of pentacene adsorbed on silver is investigated using DFT methods. Optimized geometry of pentacene after adsorption on silver indicates distortion in hexagonal structure of the ring close to the silver cluster and deviations in co-planarity of carbon atoms due to the variations in bond angles and dihedral angles. Theoretically simulated absorption spectrum has a symmetric surface plasmon resonance peak around 486nm corresponding to the transfer of charge from HOMO-2 to LUMO. Theoretical SERS confirms the process of adsorption, tilted orientation of pentacene on silver surface and the charge transfers reported. Localization of electron density arising from redistribution of electrostatic potential together with a reduced bandgap of pentacene after adsorption on silver suggests its utility in the design of electro active organic semiconducting devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

An iterative forward analysis technique to determine the equation of state of dynamically compressed materials

Here, we developed an iterative forward analysis (IFA) technique with the ability to use hydrocode simulations as a fitting function for analysis of dynamic compression experiments. The IFA method optimizes over parameterized quantities in the hydrocode simulations, breaking the degeneracy of contributions to the measured material response. Velocity profiles from synthetic data generated using a hydrocode simulation are analyzed as a first-order validation of the technique. We also analyze multiple magnetically driven ramp compression experiments on copper and compare with more conventional techniques. Excellent agreement is obtained in both cases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Evolutionary inverse design of defects at graphene 2D lateral interfaces

Grain boundaries (GBs) in two-dimensional (2D) materials often have a profound impact on various material properties from mechanical to optical to electronic, yet predicting all possible GB formations is a challenge. Here, we introduce a workflow based on an evolutionary algorithm for exploring possible GBs formed at a lateral 2D interface. In a departure from conventional genetic algorithm based structure optimization methods, we perform genetic operations in the near interface region that allow us to be computationally efficient. We benchmark our method using graphene, which is a well-studied 2D material with a wide range of point defects. An empirical potential was used as the surrogate of the evolutionary search. More than 11.5 × 106 structures in total were evaluated for 128 GB orientations, and for each orientation, the ten best structures are recorded. A subset of low energy GBs predicted by empirical potential based search was relaxed by first-principles calculations and used to validate the energetic rank order. With the validated formation energy, we rank-ordered the best 128 GB structures and performed a detailed statistical analysis of primitive rings to find the correlation between the ring distribution and the formation energy. We found that for low energy GBs (below 0.5eV/Å), Stone–Wales defects will dominate, while structures with a higher energy (0.5–1.1eV/Å) show an increasing population of heptagons and nine-membered rings to form seven-nine defect pairs. For structures with energy higher than 1.1eV/Å, the percentage of octagons and nine-membered rings increases, which indicates that these two types of rings are not energetically favorable. Our proposed methodology is broadly applicable to explore defective low dimensional materials and represents a powerful tool that enables a systematic search of GBs of lateral interfaces for 2D materials.

Zhang, Jianan↗
DOE OSTI2014

Optimal recovery of linear operators in non-Euclidean metrics

The paper looks at problems concerning the recovery of operators from noisy information in non-Euclidean metrics. A number of general theorems are proved and applied to recovery problems for functions and their derivatives from the noisy Fourier transform. In some cases, a family of optimal methods is found, from which the methods requiring the least amount of original information are singled out. Bibliography: 25 titles.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Protein folding from heterogeneous unfolded state revealed by time-resolved X-ray solution scattering

One of the most challenging tasks in biological science is to understand how a protein folds. In theoretical studies, the hypothesis adopting a funnel-like free-energy landscape has been recognized as a prominent scheme for explaining protein folding in views of both internal energy and conformational heterogeneity of a protein. Despite numerous experimental efforts, however, comprehensively studying protein folding with respect to its global conformational changes in conjunction with the heterogeneity has been elusive. Here we investigate the redox-coupled folding dynamics of equine heart cytochrome c (cyt-c) induced by external electron injection by using time-resolved X-ray solution scattering. A systematic kinetic analysis unveils a kinetic model for its folding with a stretched exponential behavior during the transition toward the folded state. With the aid of the ensemble optimization method combined with molecular dynamics simulations, we found that during the folding the heterogeneously populated ensemble of the unfolded state is converted to a narrowly populated ensemble of folded conformations. These observations obtained from the kinetic and the structural analyses of X-ray scattering data reveal that the folding dynamics of cyt-c accompanies many parallel pathways associated with the heterogeneously populated ensemble of unfolded conformations, resulting in the stretched exponential kinetics at room temperature. This finding provides direct evidence with a view to microscopic protein conformations that the cyt-c folding initiates from a highly heterogeneous unfolded state, passes through still diverse intermediate structures, and reaches structural homogeneity by arriving at the folded state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Reproducible automated renewable column generation

Preparation of chromatographic columns requires considerable time during chemical separation procedures. Automated systems capable of repeatedly generating renewable, uniformly packed columns would find widespread use in analytical laboratories. Here, a fully automated commercial-off-the-shelf (COTS) system was utilized to pack and unpack 1 mL TEVA and UTEVA columns. To accurately determine the reproducibility of the resin load per column, studies were conducted over several weeks. Method optimization yielded an improvement in loading from 15–19% to 3–5% relative standard deviation. Furthermore, availability of automated COTS equipment capable of reproducibly generating separation columns has the potential to reduce time and costs associated with column separation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Quantitative analysis of cost savings and occupants’ preferences in grid-interactive smart home operation

Many utility companies in the United States have introduced time-of-use (TOU) rates for homeowners with the goal of regulating electricity consumption during peak hours. The electrical appliances in homes include various thermostatically controlled devices, such as air conditioners (AC) for thermal comfort, and nonthermostatically controlled devices such as clothes washers. As a result, homeowners face the complicated challenge of economically operating multiple electrical appliances in their homes while maintaining comfort and convenience. This is usually due to the lack of an explicit understanding of the correlation between cost saving and the users’ comfort. To understand the correlation, this article is designed to construct a framework by integrating three major components: a multi-objective optimization method accommodating multiple competing goals with different weights, a learning-based system modeling approach describing the dynamics and thermal coupling effects of appliances, and a novel comfort index method differentiating preferred and acceptable thermal comfort. Our proposed framework can allow the indoor air temperature to fall into the "preferred" range with a marginal cost increase. Furthermore, the simulation result shows that an additional 8 h for the preferred thermal comfort can be achieved with a cost increase of only 1.77%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Ion-temperature-gradient stability near the magnetic axis of quasisymmetric stellarators

Abstract The stability of the ion-temperature gradient mode in quasisymmetric stellarators is assessed. This is performed using a set of analytical estimates together with linear gyrokinetic simulations. The peak growth rates, their corresponding real frequencies and wave-vectors are identified. A comparison is made between a first-order near-axis expansion model and eleven realistic designs obtained using numerical optimization methods. It is found that while the near-axis expansion is able to replicate the growth rates, real frequencies and perpendicular wave-vector at the inner core (both using simplified dispersion relations and first-principle gyrokinetic simulations), it leads to an overestimation of the growth rate at larger radii. An approximate analytic solution of the ITG dispersion relation for the non-resonant limit suggests growth rates could be systematically higher in quasi-axisymmetric (QA) configurations compared to quasi-helically (QH) symmetric ones. However except for very close to the axis, linear gyrokinetic simulations do not show systematic differences between QA and QH configurations.

Physics↗
DOE OSTI2014

Efficient algorithm for locating and sizing series compensation devices in large power transmission grids: II. Solutions and applications

In a companion manuscript, we developed a novel optimization method for placement, sizing, and operation of Flexible Alternating Current Transmission System (FACTS) devices to relieve transmission network congestion. Specifically, we addressed FACTS that provide Series Compensation (SC) via modification of line inductance. In this manuscript, this heuristic algorithm and its solutions are explored on a number of test cases: a 30-bus test network and a realistically-sized model of the Polish grid (~ 2700 nodes and ~ 3300 lines). The results on the 30-bus network are used to study the general properties of the solutions including non-locality and sparsity. The Polish grid is used as a demonstration of the computational efficiency of the heuristics that leverages sequential linearization of power flow constraints and cutting plane methods that take advantage of the sparse nature of the SC placement solutions. Using these approaches, the algorithm is able to solve an instance of Polish grid in tens of seconds. We explore the utility of the algorithm by analyzing transmission networks congested by (a) uniform load growth, (b) multiple overloaded configurations, and (c) sequential generator retirements.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Topology optimization of permanent magnets for stellarators

In this work, we introduce a topology optimization method to design permanent magnets for advanced stellarators. Recent researches show that permanent magnets have great potentials to simplify stellarator coils. We adopt state-of-the-art numerical techniques to determine the presence of magnets in the entire designing space. The FAMUS code is developed and it can design engineering-feasible permanent magnets for general stellarators satisfying the constraints of the maximum material magnetization and explicit forbidden regions. FAMUS has been successfully verified against the previously proposed linear method. Three different permanent magnet designs together with planar TF coils for a half-Tesla NCSX configuration have been obtained for demonstrations. The designs have good accuracy in generating the desired equilibrium and offer considerably large plasma access on the outboard side. The results show that FAMUS is a flexible, advanced numerical tool for future permanent magnet stellarator designs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Auxiliary heating and current drive physics for the ST-E1 fusion power plant

This work describes the physics basis for the proposed auxiliary heating and current drive system on the ST-E1 fusion power plant. The ST-E1 flattop plasma considered here is fully non-inductive with a bootstrap fraction of 0.9 and the remaining current driven by EC waves. Using the recently published physics-based optimization method for EC launchers (Lopez et al 2025 Plasma Phys. Control. Fusion 67 055012), we show that the target flattop ECCD can be achieved with a net efficiency of 52 kA MW −1 using fundamental O-mode (O1) with frequency range 160–200 GHz launched from the low-field side top half of the vacuum vessel (LFS top-launch). From considering two candidate rampup scenarios, we conclude that LFS top-launch O1 ECCD can be equally effective during the early stages of plasma operation, although poloidal steering might be needed. X-mode waves injected from the LFS midplane are also shown to be effective for rampup even when T e < 1 keV. We also present modeling results for the pre-conceptual design of an ICRH system proposed for ST-E1. Using TORIC, we find that an ICRH system aiming for 42–48 MHz and toroidal mode number n φ ~ 10 robustly achieves dominant ion damping via Helium-3 minority heating transitioning to second-harmonic Tritium heating. We then show that such waves can be efficiently generated by a 5-strap traveling-wave antenna (TWA) using the Petra-M code. The TWA has a 40–45 MHz passband within which ~60% of the power entering the TWA is coupled to the plasma with the remaining ~40% of the power being transmitted through the TWA and possibly recirculated; the power reflected back into the transmission lines is negligible. This passband structure persists even when the evanescent distance is increased by a factor of two, or when the magnetic-field angle is increased by 30°, demonstrating inherent load resilience that will be crucial for effective ICRH on ST-E1.

electron cyclotron↗
DOE OSTI2024

Reinforcement learning pulses for transmon qubit entangling gates

The utility of a quantum computer is highly dependent on the ability to reliably perform accurate quantum logic operations. For finding optimal control solutions, it is of particular interest to explore model-free approaches, since their quality is not constrained by the limited accuracy of theoretical models for the quantum processor—in contrast to many established gate implementation strategies. In this work, we utilize a continuous control reinforcement learning algorithm to design entangling two-qubit gates for superconducting qubits; specifically, our agent constructs cross-resonance and CNOT gates without any prior information about the physical system. Using a simulated environment of fixed-frequency fixed-coupling transmon qubits, we demonstrate the capability to generate novel pulse sequences that outperform the standard cross-resonance gates in both fidelity and gate duration, while maintaining a comparable susceptibility to stochastic unitary noise. We further showcase an augmentation in training and input information that allows our agent to adapt its pulse design abilities to drifting hardware characteristics, importantly, with little to no additional optimization. Our results exhibit clearly the advantages of unbiased adaptive-feedback learning-based optimization methods for transmon gate design.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

SpaRC: scalable sequence clustering using Apache Spark

MOTIVATION: Whole genome shotgun based next-generation transcriptomics and metagenomics studies often generate 100-1000 GB sequence data derived from tens of thousands of different genes or microbial species. Assembly of these data sets requires tradeoffs between scalability and accuracy. Current assembly methods optimized for scalability often sacrifice accuracy and vice versa. An ideal solution would both scale and produce optimal accuracy for individual genes or genomes. RESULTS: In this work we describe an Apache Spark-based scalable sequence clustering application, SparkReadClust (SpaRC), that partitions reads based on their molecule of origin to enable downstream assembly optimization. SpaRC produces high clustering performance on transcriptomes and metagenomes from both short and long read sequencing technologies. It reaches near-linear scalability with input data size and number of compute nodes. SpaRC can run on both cloud computing and HPC environments without modification while delivering similar performance. Our findings demonstrate that SpaRC provides a scalable solution for clustering billions of reads from next-generation sequencing experiments, and Apache Spark represents a cost-effective solution with rapid development/deployment cycles for similar large-scale sequence data analysis problems. AVAILABILITY AND IMPLEMENTATION: https://bitbucket.org/berkeleylab/jgi-sparc.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

The GMRT archive atomic gas survey – II. Mass modelling and dark matter halo properties across late-type spirals

Studying the kinematics and mass modelling of galaxies from H i 21 cm data provides valuable insights into the properties of both the baryonic components and the dark matter halo in nearby galaxies. Despite many observational studies, mass modelling of galaxies remains challenging due to different limitations. For example, most of the previous studies involving mass modelling are based on rotation curves derived from 2D velocity fields from H i or H α spectroscopic observation which are often affected by beam smearing and projection effect. However, kinematic modelling done by fitting the ‘Tilted ring model’ to 3D data cube is not affected by these issues. In this study, we present and compare 3D kinematic modelling of a pilot sample of 11 galaxies from the GMRT archive atomic gas survey (GARCIA) using two different publicly available pipelines. We model the observed H i rotation curve using 3.6-μm infrared data and SDSS r-band data for stellar contribution, H i surface density profile for gas, and Navarro–Frenk–White profile for dark matter halo; and employ the Markov chain Monte Carlo optimization method for parameter estimation. Further, to validate our analysis, we revisit important scaling relations, e.g. the M gas –M star relation, M star –M halo relation, M gas –M halo relation and Baryonic Tully–Fisher relation. Here, the scaling relations from our analysis are broadly consistent with that reported in the literature. A larger sample of galaxies from GARCIA in the near future will allow studying these scaling relations in greater details.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Main belt asteroids taxonomical information from dark energy survey data

While proper orbital elements are currently available for more than 1 million asteroids, taxonomical information is still lagging behind. Surveys like SDSS-MOC4 provided preliminary information for more than 100 000 objects, but many asteroids still lack even a basic taxonomy. In this study, we use Dark Energy Survey (DES) data to provide new information on asteroid physical properties. By cross-correlating the new DES data base with other data bases, we investigate how asteroid taxonomy is reflected in DES data. While the resolution of DES data is not sufficient to distinguish between different asteroid taxonomies within the complexes, except for V-type objects, it can provide information on whether an asteroid belongs to the C- or S-complex. Here, machine learning methods optimized through the use of genetic algorithms were used to predict the labels of more than 68 000 asteroids with no prior taxonomic information. Using a high-quality, limited set of asteroids with data on gri slopes and i − z colours, we detected 409 new possible V-type asteroids. Their orbital distribution is highly consistent with that of other known V-type objects.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗