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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

rascalc : a jackknife approach to estimating single- and multitracer galaxy covariance matrices

ABSTRACT To make use of clustering statistics from large cosmological surveys, accurate and precise covariance matrices are needed. We present a new code to estimate large-scale galaxy two-point correlation function (2PCF) covariances in arbitrary survey geometries that, due to new sampling techniques, runs ∼104 times faster than previous codes, computing finely binned covariance matrices with negligible noise in less than 100 CPU-hours. As in previous works, non-Gaussianity is approximated via a small rescaling of shot noise in the theoretical model, calibrated by comparing jackknife survey covariances to an associated jackknife model. The flexible code, rascalc, has been publicly released, and automatically takes care of all necessary pre- and post-processing, requiring only a single input data set (without a prior 2PCF model). Deviations between large-scale model covariances from a mock survey and those from a large suite of mocks are found to be indistinguishable from noise. In addition, the choice of input mock is shown to be irrelevant for desired noise levels below ∼105 mocks. Coupled with its generalization to multitracer data sets, this shows the algorithm to be an excellent tool for analysis, reducing the need for large numbers of mock simulations to be computed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Logical error rates for the surface code under a mixed coherent and stochastic circuit-level noise model inspired by trapped ions

With fault-tolerant quantum computing (FTQC) on the horizon, it is critical to understand sources of logical errors in plausible hardware implementations of quantum error-correcting codes. Detailed error modeling of computational instructions on particular FTQC architectures will enable the better prediction of error propagation in FT-encoded quantum circuits while revealing where greater attention is needed in hardware design. In this work, we consider logical error rates for the surface code implemented on a hypothetical grid-based trapped-ion quantum charge-coupled device architecture. Specifically, we construct logical channels for the idling surface code and examine its diamond error under a mixed coherent and stochastic circuit-level noise model inspired by trapped ions. We include the coherent dephasing noise that is known to accumulate during physical qubit idling and transport in these systems, determining idling and transport durations using the time-resolved output of an open-source trapped-ion surface code compiler. To estimate expectation values of logical Pauli observables following hardware circuits containing non-Clifford sources of noise, we utilize a Monte Carlo technique to sample from an underlying quasiprobability distribution of Clifford circuits that we independently simulate in a phase-sensitive fashion. We verify error suppression up to code distance 𝑑 = 11 at coherent dephasing rates near and below those of current-generation trapped-ion quantum computers and find that logical error rates align with those of analogous fully stochastic simulations in this regime. Exploring higher dephasing rates at 𝑑 = 3−5, we find evidence for growing coherent rotations about all three logical Pauli axes, increased diagonal logical error process matrix elements relative to those of stochastic simulations, and a reduced dephasing rate threshold. Overall, our work paves a way toward realistic hardware emulation of small fault-tolerant quantum processes, e.g., members of an FTQC instruction set.

Quantum benchmarking↗
DOE OSTI2025

Search for heavy neutral resonances decaying to tau lepton pairs in proton-proton collisions at $\sqrt{s}$=13 TeV

A search for heavy neutral gauge bosons (𝑍′) decaying into a pair of tau leptons is performed in proton-proton collisions at $\sqrt{s}$ =13 TeV at the CERN LHC. The data were collected with the CMS detector and correspond to an integrated luminosity of 138 fb −1 . The observations are found to be in agreement with the expectation from standard model processes. Limits at 95% confidence level are set on the product of the 𝑍′ production cross section and its branching fraction to tau lepton pairs for a range of 𝑍′ boson masses. For a narrow resonance in the sequential standard model scenario, a 𝑍′ boson with a mass below 3.5 TeV is excluded. This is the most stringent limit to date from this type of search.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Guiding Self-Assembly of Active Colloids by Temporal Modulation of Activity

Self-organization phenomena in ensembles of self-propelled particles open pathways to the synthesis of new dynamic states not accessible by traditional equilibrium processes. The challenge is to develop a set of principles that facilitate the control and manipulation of emergent active states. In this study, we report that dielectric rolling colloids energized by a pulsating electric field self-organize into alternating square lattices with a lattice constant controlled by the parameters of the field. We combine experiments and simulations to examine spatiotemporal properties of the emergent collective patterns and investigate the underlying dynamics of the self-organization.We reveal the resistance of the dynamic lattices to compression and expansion stresses leading to a hysteretic behavior of the lattice constant. The general mechanism of pattern synthesis and control in active ensembles via temporal modulation of activity can be applied to other active colloidal systems.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Volumetric Segmentation via Neural Networks Improves Neutron Crystallography Data Analysis

Crystallography is the powerhouse technique for molecular structure determination, with applications in fields ranging from energy storage to drug design. Accurate structure determination, however, relies partly on determining the precise locations and integrated intensities of Bragg peaks in the resulting data. Here, we describe a method for Bragg peak integration that is accomplished using neural networks. The network is based on a U-Net and identifies peaks in three-dimensional reciprocal space through segmentation, allowing prediction of the full 3D peak shape from noisy data that is commonly difficult to process. The procedure for generating appropriate training sets is detailed. Trained networks achieve Dice coefficients of 0.82 and mean IoUs of 0.69. Carrying out integration over entire datasets, it is demonstrated that integrating neural network-predicted peaks results in improved intensity statistics. Furthermore, using a second dataset, the possibility of transfer learning between datasets is shown. Given the ubiquity and growing complexity of crystallography, we anticipate integration by machine learning to play an increasingly important role across the physical sciences. These early results demonstrate the applicability of deep learning techniques for integrating crystallography data and suggest a possible role in the next generation of crystallography experiments.

Sullivan, Brendan T.↗
DOE OSTI2018

Modular Spiking Neural Circuits for Mapping Long Short-Term Memory on a Neurosynaptic Processor

Due to the distributed and asynchronous nature of neural computation through low-energy spikes, brain-inspired hardware systems offer high energy efficiency and massive parallelism. One such platform is the IBM TrueNorth neurosynaptic system. Recently, TrueNorth compatible representation learning algorithms have emerged, achieving close to the state-of-the-art performance in various data sets. However, its application in temporal sequence processing models, such as recurrent neural networks (RNNs), is still only at the proof of concept level. There is an inherent difficulty in capturing temporal dynamics of an RNN using spiking neurons, which is only exasperated by the hardware constraints in connectivity and synaptic weight resolution. This paper presents a design flow that overcomes these difficulties and maps a special case of recurrent networks called long short-term memory (LSTM) onto a spike-based platform. The framework utilizes various approximation techniques, such as activation discretization, weight quantization, and scaling and rounding, spiking neural circuits that implement the complex gating mechanisms, and a store-and-release technique to enable neuron synchronization and faithful storage. While the presented techniques can be applied to map LSTM to any spiking neural network (SNN) simulator/emulator, here we choose the TrueNorth chip as the target platform by adhering to its hardware constraints. Three LSTM applications, parity check, extended Reber grammar, and question classification, are evaluated. The tradeoffs among accuracy, performance, and energy tradeoffs achieved on TrueNorth are demonstrated. Finally, this is compared with the performance on an SNN platform without hardware constraints, which represents the upper bound of the achievable accuracy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Multistep inversion workflow for 3D long-offset damped elastic waves in the Fourier domain

We present a new workflow for imaging damped three-dimensional elastic wavefields in the Fourier domain. The workflow employs a multiscale imaging approach, in which offset lengths are laddered, where frequency content and damping of the data are changed cyclically. Thus, the inversion process is launched using short-offset and low-frequency data to recover the long spatial wavelength of the image at a shallow depth. Increasing frequency and offset length leads to the recovery of the fine-scale features of the model at greater depths. For the fixed offset, we employ (in the imaging process) a few discrete frequencies with a set of Laplace damping parameters. The forward problem is solved with a finite-difference frequency-domain method based on a massively parallel iterative solver. The inversion code is based upon the solution of a least squares optimisation problem and is solved using a nonlinear gradient method. It is fully parallelised for distributed memory computational platforms. Our full-waveform inversion workflow is applied to the 3D Marmousi-2 and SEG/EAGE Salt models with long-offset data. The maximum inverted frequencies are 6 Hz for the Marmousi model and 2 Hz for the SEG/EAGE Salt model. The detailed structures are imaged successfully up to the depth approximately equal to one-third of the maximum offset length at a resolution consistent with the inverted frequencies.

3D full waveform inversion↗
DOE OSTI2018

Low-Background Method of Isotope Markers for Measuring the Efficiency of Intercalation of Graphite by Potassium Atoms

The result of low-background measurements of the gamma activity of graphite-potassium intercalated sample is presented. A germanium gamma spectrometer, used for measurements, was located in the low-background chamber of Baksan Neutrino Observatory. For 384 hours of exposure, 768 decays of K-40 isotope nuclei were registered. This activity corresponds to 85 μg/cm{sup 2} potassium atoms embedded in to graphite lattice. A computer simulation of the intercalation process and the gamma-ray spectrum set is also presented. The accuracy of the potassium concentration determination can be brought to 10{sup –}11–10{sup –}12 g/g for mixture enriched with K-40 isotope.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Pareto Optimization of Analog Circuits Using Reinforcement Learning

Analog circuit optimization and design presents a unique set of challenges in the IC design process. Many applications require the designer to optimize for multiple competing objectives, which poses a crucial challenge. Motivated by these practical aspects, we propose a novel method to tackle multi-objective optimization for analog circuit design in continuous action spaces. In particular, we propose to (i) extrapolate current techniques in Multi-Objective Reinforcement Learning to continuous state and action spaces and (ii) provide for a dynamically tunable trained model to query user defined preferences in multi-objective optimization in the analog circuit design context.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Simple Low-process Radiation Simulation For Unity Game Engine

This is a set of Unity components that use the Unity game engine's transform and collision systems to provide a reasonably representative approximation of any number of unique radiation sources and the collective dose they deliver to a user.

Dunker, Jack [Idaho National Laboratory (INL), Ida↗
DOE OSTI2018

Speculation and replication in temperature accelerated dynamics

Accelerated Molecular Dynamics (AMD) is a class of MD-based algorithms for the long-time scale simulation of atomistic systems that are characterized by rare-event transitions. Temperature-Accelerated Dynamics (TAD), a traditional AMD approach, hastens state-to-state transitions by performing MD at an elevated temperature. Recently, Speculatively-Parallel TAD (SpecTAD) was introduced, allowing the TAD procedure to exploit parallel computing systems by concurrently executing in a dynamically generated list of speculative future states. Although speculation can be very powerful, it is not always the most efficient use of parallel resources. In this paper, we compare the performance of speculative parallelism with a replica-based technique, similar to the Parallel Replica Dynamics method. A hybrid SpecTAD approach is also presented, in which each speculation process is further accelerated by a local set of replicas. Finally and overall, this work motivates the use of hybrid parallelism whenever possible, as some combination of speculation and replication is typically most efficient.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Easing the Control System Application Development for CMS Detector Control System with Automatic Production Environment Reproduction

The Detector Control System (DCS) is one of the main pieces involved in the operation of the Compact Muon Solenoid (CMS) experiment at the LHC. The system is built using WinCC Open Architecture (WinCC OA) and the Joint Controls Project (JCOP) framework which was developed on top of WinCC at CERN. Following the JCOP paradigm, CMS has developed its own framework which is structured as a collection of more than 200 individual installable components each providing a different feature. Everyone of the systems that the CMS DCS consists of is created by installing a different set of these components. By automating this process, we are able to quickly and efficiently create new systems in production or recreate problematic ones, but also, to create development environments that are identical to the production ones. This latter one results in smoother development and integration processes, as the new/reworked components are developed and tested in production-like environments. Moreover, it allows the central DCS support team to easily reproduce systems that the users/developers report as being problematic, reducing the response time for bug fixing and improving the support quality.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

The European ERL Roadmap

Following the European Strategy process in 2019, five Roadmap Panels were set up to prepare the technologies needed for future accelerators and colliders: high-field magnets, SRF, muon colliders, plasma wakefield accelera-tors and Energy Recovery Linacs (ERLs). The ERL Roadmap Panel, consisting of ERL experts from around the world, first developed an overview of current and future ERLs. From this it was possible to carry out a gap analysis to see what R&D would be needed, from which the roadmap could be developed. The European ERL Roadmap [1] focused on three main aspects: 1) the con-tinuation and development of facility programs for which no additional funds are needed, S-DALINAC in Darm-stadt and MESA in Mainz; 2) technology development for room-temperature HOM damping and twin-axis SRF cavities; 3) the timely upgrade of bERLinPro for 100 mA current and the construction of PERLE at Orsay as a dedi-cated 10 MW power multi-turn facility. The roadmap entails a vision of a future energy frontier electron-positron and electron-hadron collider and describes a high-quality ERL program for 4.4K SRF technology at high Q0.

Hutton, A.↗
DOE OSTI2019

Powering the Blue Economy: Exploring Opportunities for Marine Renewable Energy in Various Maritime

The blue economy is an emerging sector that will require energy to allow many scientific and commercial endeavors to reach their potential. The U.S. Department of Energy’s Water Power Technologies Office seeks to understand marine and coastal opportunities for which marine energy could fulfill those energy needs. This report documents the material gathered during a year-long fact-finding effort engaging users and developers, through literature review, workshops, interviews, and national lab analyses, as well as a Request for Information process. Each market was assessed by a set of common analyses: opportunity summary; application description and power requirements; market description, power options, and geographic relevance; marine energy potential value proposition; and path forward including research and development needs and potential partners. The major finding is that there are more markets with potential than anticipated, both for Power at Sea (including ocean observation and navigation, underwater vehicle charging, marine aquaculture, marine algae, and seawater mining), and Resilient Coastal Communities (including desalination, coastal resiliency and disaster recovery, and community-scale isolated power systems). The enabling attributes of marine energy resources include that they are abundant, geographically diverse, energy dense, predictable, and complementary to other energy sources. This report can help direct analysis and research and development efforts by government, scientists, developers, and other stakeholders to more deeply understand and meet specific technical and economic requirements to power emerging opportunities in the blue economy.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Illinois Distributed Generation Rebate Calculation Considerations

What is the value of distributed generation to the distribution system and how do we assign that value to a rebate? This white paper provides a preliminary look at the potential distributed generation valuation and compensation options for Illinois, taking into consideration data needs and availability, as well as stakeholder input. Pacific Northwest National Laboratory (PNNL) is supporting the Illinois Commerce Commission (ICC) with initial stakeholder engagement to advance the conversation around distributed generation valuation in Illinois. PNNL’s educational support will help set the stage for a productive formal process as the ICC will be called upon, in relatively short order, to start formal distributed generation valuation proceedings in response to Illinois Public Act 99-0906, also known as the Future Energy Jobs Act (FEJA), and codified in Illinois Public Utilities Act Section 16-107.6.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Atmospheric System Research Treatment of Convection in Next-Generation Climate Models: Challenges and Opportunities Workshop Report

A workshop sponsored by the U.S. Department of Energy (DOE) Atmospheric System Research (ASR) Program was held at the Pacific Northwest National Laboratory (PNNL) on 3-5 February 2016. This workshop was a response to the rapid approach of climate models with cloud-permitting (1- to 10-km grid spacing) resolutions. The expansion of computational resources and advances in numerical methods are making such models a reality. The workshop participants considered specifically the new set of challenges for representing convective cloud processes in this generation of models. The challenges arise from the fact that some aspects of convection are partly resolved. Short- and long-term strategies that would lead to accurately representing convection in these models were discussed, and opportunities for the ASR program to effectively leverage DOE’s unique capabilities, high-performance computing resources, and Atmospheric Radiation Measurement (ARM) Climate Research Facility observational facilities to this end were identified. The workshop was organized around the premise that a strategy to accurately treat convection in the next generation of climate models comprises addressing challenges on three core themes and their integration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Alloying titanium and niobium via electron beam cold hearth melting

Electron beam cold hearth melting of titanium and niobium was performed to assess the feasibility of this technique for uranium processing and to determine system requirements for LLNL applications. The demonstration consisted of (1) alloying titanium and niobium, (2) feeding and melting scrap of various forms and (3) consolidating powder feedstock. Emphasis was placed on the former, with focused efforts to produce and deliver stoichiometric amounts of titanium and niobium to the hearth for alloying. This effort demonstrated the ability to melt via electron beam and cast titanium into a thin-walled (~0.06”) niobium tube. This process was performed repeatably and an optimal set of operational parameters was identified through an iterative approach. Three alloyed ingots were produced using niobium tubes filled with titanium, by casting and slip-fit. The alloyed ingots were characterized using multiple approaches and were shown to be comprised of columnar grains, low inclusion amounts and a small degree of ordered (center to edge, top to bottom) variation in niobium concentration. Based on these findings, it is concluded that alloying can be accomplished in a single step, without the need for an additional melting step after electron beam cold hearth melting. Details of these analyses, along with efforts to adopt cold hearth melting technology for scrap and powder recycle are provided herein.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

CST R9120-B 30x60 Media Pretreatment and Digestion Standard Development to Support Tank Closure Cesium Removal 1A (TCCR-1A) Operations

In support of continued operations of Savannah River Remediation’s (SRR) ion exchange process to remove radioactive cesium from Savannah River Site (SRS) dissolved saltcake, referred to as the Tank Closure Cesium Removal 1A process (TCCR-1A; containing the second set of at-tank ion exchange columns), SRNL was tasked with: 1) validating the field protocol planned for pretreating the crystalline silicotitanate (CST) ion exchange media to be used in the columns, 2) preparing CST media for use in in-tank batch contact testing, and 3) developing a digestion standard to verify complete CST dissolution prior to characterization following each in-tank batch contact test. A procedure (SRNL L29 Manual, ITS-0229) was developed previously in support of the TCCR Demonstration (which contained the first set of ion exchange columns) based on evaluations of a different CST production lot with a larger particle size range to document the protocol for pretreating CST utilizing conditions similar to what will be performed in the field.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗