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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Comprehensive Monitoring for Heterogeneous Geographically Distributed Storage

Storage capacity at CMS Tier-1 and Tier-2 sites reached over 100 Petabytes in 2014, and will be substantially increased during Run 2 data taking. The allocation of storage for the individual users analysis data, which is not accounted as a centrally managed storage space, will be increased to up to 40%. For comprehensive tracking and monitoring of the storage utilization across all participating sites, CMS developed a space monitoring system, which provides a central view of the geographically dispersed heterogeneous storage systems. The first prototype was deployed at pilot sites in summer 2014, and has been substantially reworked since then. In this paper we discuss the functionality and our experience of system deployment and operation on the full CMS scale.

Ratnikova, N.↗
DOE OSTI2021

Distributed deep reinforcement learning for simulation control

Abstract Several applications in the scientific simulation of physical systems can be formulated as control/optimization problems. The computational models for such systems generally contain hyperparameters, which control solution fidelity and computational expense. The tuning of these parameters is non-trivial and the general approach is to manually ‘spot-check’ for good combinations. This is because optimal hyperparameter configuration search becomes intractable when the parameter space is large and when they may vary dynamically. To address this issue, we present a framework based on deep reinforcement learning (RL) to train a deep neural network agent that controls a model solve by varying parameters dynamically. First, we validate our RL framework for the problem of controlling chaos in chaotic systems by dynamically changing the parameters of the system. Subsequently, we illustrate the capabilities of our framework for accelerating the convergence of a steady-state computational fluid dynamics solver by automatically adjusting the relaxation factors of the discretized Navier–Stokes equations during run-time. The results indicate that the run-time control of the relaxation factors by the learned policy leads to a significant reduction in the number of iterations for convergence compared to the random selection of the relaxation factors. Our results point to potential benefits for learning adaptive hyperparameter learning strategies across different geometries and boundary conditions with implications for reduced computational campaign expenses 4 4 Data and codes available at https://github.com/Romit-Maulik/PAR-RL . .

42 ENGINEERING↗
DOE OSTI2024

Project Dinos I: A joint lensing–dynamics constraint on the deviation from the power law in the mass profile of massive ellipticals

The mass distribution in massive elliptical galaxies encodes their evolutionary history, thus providing an avenue to constrain the baryonic astrophysics in their evolution. The power-law assumption for the radial mass profile in ellipticals has been sufficient to describe several observables to the noise level, including strong lensing and stellar dynamics. In this paper, we quantitatively constrained any deviation, or the lack thereof, from the power-law mass profile in massive ellipticals through joint lensing–dynamics analysis of a large statistical sample with 77 galaxy–galaxy lens systems. We performed an improved and uniform lens modelling of these systems from archival Hubble Space Telescope imaging using the automated lens modelling pipeline dolphin. We combined the lens model posteriors with the stellar dynamics to constrain the deviation from the power law after accounting for the line-of-sight lensing effects, a first for analyses on galaxy–galaxy lenses. We find that the Sloan Lens ACS Survey lens galaxies with a mean redshift of 0.2 are consistent with the power-law profile within 1.1σ (2.8σ) and the Strong Lensing Legacy Survey lens galaxies with a mean redshift of 0.6 are consistent within 0.8σ (2.1σ), for a spatially constant (Osipkov–Merritt) stellar anisotropy profile. We adopted the spatially constant anisotropy profile as our baseline choice based on previous dynamical observables of local ellipticals. However, spatially resolved stellar kinematics of lens galaxies are necessary to differentiate between the two anisotropy models. Future studies will use our lens models to constrain the mass distribution individually in the dark matter and baryonic components.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Plastic homogeneity in nanoscale heterostructured binary and multicomponent metallic eutectics: An overview

Heterostructured materials comprised of relatively soft/hard disparate phases typically exhibit composite strengthening but lack plastic deformability at ambient temperatures. However, heterostructured systems comprised of nanoscale phases can simultaneously enhance yield strength and strain hardening, thereby promoting uniform distribution of plastic flow. In this review, the atomic-scale deformation mechanisms in model systems of eutectic alloys, Al-Al 2 Cu and Al-Si, refined to nanoscales via laser rapid solidification are discussed, and compared with literature on multi-component (high entropy) eutectics such as Ni-Al-Fe-based with Cr and/or Co additions. The nano-lamellar Al-Al 2 Cu structures exhibit unit defect mechanisms not reported in monolithic Al 2 Cu intermetallic: localized shear on {0 1 1} and shear-induced faults on {1 2 1} planes, constrained by closely-spaced dislocation arrays in Al confined by Al/Al 2 Cu interfaces. The unexpected plasticity mechanisms are enabled by slip continuity in nanoscale Al-Al 2 Cu eutectics associated with the orientation relationship and interface habit planes. In nano-fibrous Al-Si eutectic, tensile ductility at strength approaching 600 MPa is observed resulting from dislocation plasticity in the nano-Al channels and cracking in Si nanofibers. Molecular dynamics simulations show that Al dislocations easily cross-slip (screw) or climb (edge) along Al-Si interfaces, making slip transmission difficult. The propagation of nano-cracks is suppressed by surrounding strain hardening Al, retaining good ductility of the sample, in spite of lack of direct slip transmission. Finally, the critical unit mechanisms of slip transmission and interface-enabled plasticity observed in nanoscale eutectic binary systems can also explain the strength-ductility relationship in multi-component eutectics and homogeneously distributed plastic flow with increasing microstructural heterogeneity.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Gas Content and Kinematics in Clumpy, Turbulent Star-forming Disks

We present molecular gas-mass estimates for a sample of 13 local galaxies whose kinematic and star-forming properties closely resemble those observed in z ≈ 1.5 main-sequence galaxies. Plateau de Bure observations of the CO[1-0] emission line and Herschel Space Observatory observations of the dust emission both suggest molecular gas-mass fractions of ∼20%. Moreover, dust emission modeling finds T {sub dust} < 30 K, suggesting a cold dust distribution compared to their high infrared luminosity. The gas-mass estimates argue that z ∼ 0.1 DYNAMO galaxies not only share similar kinematic properties with high- z disks, but they are also similarly rich in molecular material. Pairing the gas-mass fractions with existing kinematics reveals a linear relationship between f {sub gas} and σ / v {sub c}, consistent with predictions from stability theory of a self-gravitating disk. It thus follows that high gas-velocity dispersions are a natural consequence of large gas fractions. We also find that the systems with the lowest t {sub dep} (∼0.5 Gyr) have the highest ratios of σ / v{sub c} and more pronounced clumps, even at the same high molecular gas fraction.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Achieving Higher Order Accuracy in Space in Hydrodynamic Simulations of Self-Gravitating Gas

Modern astrophysical simulation codes employ a variety of numerical algorithms capable of achieving higher-order accuracy in both space and time. Albeit they succeed in achieving an effective higher spatial resolution and in suppressing the numerical damping of waves, to our knowledge, all current astrophysical simulations invoking self-gravity are limited to second-order accuracy in space. If we can devise an algorithm to evaluate self-gravity with a higher-order spatial accuracy, we can better the evaluation of the gravitational acceleration and gravitational energy release which dictate the evolution of many astrophysical systems. Herein, we present a numerical algorithm for self-gravitating hydrodynamics capable of achieving fourth-order accuracy for a given density distribution on a Cartesian uniform grid. First, we derive the cell-averaged gravitational potential at fourth-order accuracy from the cell-averaged density by solving the Poisson equation. Next, we obtain the cell average of the product of the density and gravitational acceleration, which differs from the cell-averaged density multiplied by the cell-averaged gravitational acceleration. We then show the verification of the algorithm by applying it to critical test problems: (1) maintaining equilibria of self-gravitating slabs, even upon advection, (2) evolving a polytropic sphere with a massive power-law envelope, and (3) conservation of specific entropy during the propagation of a sound wave.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Estimating the Value of Improved Distributed Photovoltaic Adoption Forecasts for Utility Resource Planning

Misforecasting the adoption of customer-owned distributed photovoltaics (DPV) can have operational and financial implications for utilities; forecasting capabilities can be improved, but generally at a cost. This paper informs this decision-space by using a suite of models to explore the capacity expansion and operation of the Western Interconnection over a 15-year period across a wide range of DPV growth rates and misforecast severities. The system costs under a misforecast are compared against the costs under a perfect forecast, to quantify the costs of misforecasting. Using a simplified probabilistic method applied to these modeling results, an analyst can make a first-order estimate of the financial benefit of improving a utility’s forecasting capabilities, and thus be better informed about whether to make such an investment. For example, under our base assumptions, a utility with 10 TWh per year of retail electric sales who initially estimates that DPV growth could range from 2% to 7.5% of total generation over the next 15 years could expect total present-value savings of approximately $4 million if they could reduce the severity of misforecasting to within ±25%. Utility resource planners can compare those savings against the costs needed to achieve that level of precision, to guide their decision on whether to make an investment in tools or resources.

14 SOLAR ENERGY↗
DOE OSTI2026

Numerical Modeling & Optimization of the iProTech Pitching Inertial Pump (PIP) Wave Energy Converter (WEC) (CRADA Final Report)

This project represents a continuation of the collaboration between iProTech and NLR to simulate, optimize and design the iProTech Pitching Inertial Pump (PIP) device. The objectives of this TEAMER project are twofold: 1. Refining the physical characteristics of the existing iProTech PIP WEC-Sim model to enhance the model’s fidelity and include controllable components. Key model enhancements target the inclusion of Coulomb friction, the introduction of a controllable bypass valve, and the replacement of traditional check valves with advanced motorized ones. 2. Exploring traditional and advanced control algorithms. From traditional methods like latching control to cutting-edge reinforcement learning (RL) algorithms, the goal is to ensure the PIP device's adaptability and optimal performance across a range of ocean conditions. NLR is tasked with augmenting the WEC-Sim model and implementing the control algorithms, culminating in performance comparison analyses. iProTech will update their existing 3D models, advise on model improvements, and determine crucial system metrics. WEC-Sim, developed in MATLAB/SIMULINK with Simscape Multibody, is the main piece of software that will be used in this project. Coupled with the MATLAB RL Toolbox, it offers a robust platform for in-depth simulation and optimization of the iProTech PIP device. Building on previous work to explore the PIP design space and optimize its geometry, mass distribution, center of gravity and other key parameters, this project aims to refine iProTech’s existing numerical models and develop effective control algorithms that can seamlessly integrate into their future hardware testing campaigns.

16 TIDAL AND WAVE POWER↗
DOE OSTI2026

Reconstruction of 6D Phase Space

A ‘Phase Space’ is a mathematical representation of all possible physical states of matter of a physical volume or system. Particle beams at Fermilab exist in a six-dimensional phase space: three position dimensions, and three momentum dimensions. To ‘reconstruct’ that space means to take measurement data from virtual detectors along those beams and map out where particles are and how they’re moving, using computational methods. In this experiment, we simulated a particle beam (Fig 1) and used the position distribution of each particle at each detector to map out the magnitude of the beam’s initial momentum.

Shirlee, Jermaine [DuPage Coll.]↗
DOE OSTI2026

Final Report: A Multi-Channel Fusion Product

The goal of this project was to measure charged fusion products from the d(d,p)t reaction in MAST-U plasmas as a function of time and position with good energy resolution using a system of up to six charged particle detectors. The data from this new diagnostic will make it possible to determine the neutral beam ion density profile as a function of R, z, and t with reduced model dependency and contribute new information to a global analysis of fast ion diagnostic data needed for the determination of the fast ion distribution function (velocity space tomography).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

MULTIPLE POPULATIONS IN THE OLD AND MASSIVE SMALL MAGELLANIC CLOUD GLOBULAR CLUSTER NGC 121

We used a combination of optical and near-UV Hubble Space Telescope photometry and FLAMES/ESO-VLT high-resolution spectroscopy to characterize the stellar content of the old and massive globular cluster (GC) NGC 121 in the Small Magellanic Cloud (SMC). We report on the detection of multiple stellar populations, the first case in the SMC stellar cluster system. This result enforces the emerging scenario in which the presence of multiple stellar populations is a distinctive-feature of old and massive GCs regardless of the environment, as far as the light-element distribution is concerned. We find that second-generation (SG) stars are more centrally concentrated than first-generation (FG) ones. More interestingly, at odds with what is typically observed in Galactic GCs, we find that NGC 121 is the only cluster so far to be dominated by FG stars that account for more than 65% of the total cluster mass. In the framework where GCs were born with 90%–95% of FG stars, this observational finding would suggest that either NGC 121 experienced a milder stellar mass-loss with respect to Galactic GCs or it formed a smaller fraction of SG stars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Preparation of the Multi-Site Data Processing at the Vera C. Rubin Observatory

The Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST) Camera is scheduled to start taking data in the summer of 2025. The Data Release Production will run the LSST Science Pipe software at data facilities in the US, France and the UK. The LSST Science Pipeline consists of complex directed acyclic graphs (DAGs) of tasks. Rubin will use the Production and Distributed Analysis (PanDA) workflow and workload management system to orchestrate this complex workflow and the distribution of workloads to the data facilities. When run end-to-end by a team of data production staff, this processing (the Science Pipelines, distributed by the workflow and workload management system) is referred to as a 'campaign'. This paper describes the central services and data facility specific services that support this multi-site data process model, including the service deployment infrastructure, the workload and workflow system, the Campaign Management tools, and connection to Rubin Data Management. This paper will also mention the experience of processing the Rubin Commissioning Camera data. All these are part of the effort to scale up the processing capabilities for the expected very large data volume from the LSST Camera.

Yang, Wei [SLAC]↗
DOE OSTI2015

Analysis of stochastically forced quasi-periodic attractors

A problem of the analysis of stochastically forced quasi-periodic auto-oscillations of nonlinear dynamic systems is considered. A stationary distribution of random trajectories in the neighborhood of the corresponding deterministic attractor (torus) is studied. A parametric description of quadratic approximation of the quasipotential based on the stochastic sensitivity functions (SSF) technique is given. Using this technique, we analyse a dispersion of stochastic flows near the torus. For the case of two-torus in three-dimensional space, the stochastic sensitivity function is constructed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Radiation Belt Remediation: A Complex Engineered System (RBR-ACES) (Institutional Computing Report)

We have performed the simulation campaigns in support of LDRD-DR project Radiation Belt Remediation: A Complex Engineered System (RBR-ACES). This project involves modeling wave generation and wave propagation in plasma environment and studying the effect of waves on the distribution of high energy electrons with the focus on electrons appeared after a high-altitude nuclear explosion (HANE). One of the major goal of this research is strong validation of the numerical models with laboratory experiments and space-based experiments and observations.

42 ENGINEERING↗
DOE OSTI2024

CloudZero Phase 2 Technical Report

Expand upon the successful Phase 1 net zero cloud test proof of concept by moving actual OT systems to the cloud and proving cloud feasibility to support various OT technologies such as IoT, Machine Learning, etc. Explore threat analysis when these technologies are moved to the cloud. A detailed analysis in NREL ARIES Cyber Range will be used to conduct deeper analysis of cloud suitability to support OT and net zero system operations in a higher fidelity representative environment. Outputs will identify, quantify, and document the results and cyber security risks associated with the move of these OT technologies in a formal delivered report. Programmatic Benefits: Identify cloud integration challenges for energy systems characterize the cloud threat space, contribute to policy and standards discussions, empower the sector to change their cloud culture where appropriate.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

An Optimized Parameterization of Sub‐Grid Scale Advection for Convection Permitting Models

Convection‐permitting models (CPMs) explicitly resolve deep convection yet under‐resolve the organized lateral exchanges among drafts and their environment that control entrainment/detrainment, precipitation efficiency, and mesoscale structure. In this work, we introduce the Optimized Advection Scheme (OAS), which introduces a small rotation of the Cartesian frame of reference for the horizontal winds relative to other variables used in advection that induces cross‐gradient transport to mimic under‐resolved convective mixing. The rotation angle is selected to minimize the Kullback–Leibler divergence between the simulated and satellite observed precipitation intensity distributions, yielding a physically consistent perturbation that is computationally inexpensive and portable. Optimized Advection Scheme is implemented in WRF and evaluated over Amazon (April 2014). It shifts precipitation–precipitable‐water joint distributions toward lighter rain, reduces overly intense rates, and improves mesoscale convective system (MCS) lifetime and propagation. Mechanistically, the added cross‐gradient transport promotes convective detrainment and environmental mixing, which cools and moistens the mid‐troposphere, weakens downward momentum transport, alleviates excessive downwelling shortwave biases, and warms the surface temperature. The optimized rotation angle yields comparable improvements at 4‐km and 1‐km grid spacing, demonstrating resolution‐independent benefits across the CPM gray zone. By targeting the dynamical root of under‐mixed convective circulations, rather than tuning model microphysics or closures, OAS delivers robust, scale‐aware improvements in precipitation statistics, cloud vertical structure, and characteristics of MCS (MCSs), offering a practical pathway to more reliable CPM simulations for weather and climate applications.

CPM↗
DOE OSTI2023

Ensuring thermodynamic consistency with invertible coarse-graining

Coarse-grained models are a core computational tool in theoretical chemistry and biophysics. A judicious choice of a coarse-grained model can yield physical insights by isolating the essential degrees of freedom that dictate the thermodynamic properties of a complex, condensed-phase system. The reduced complexity of the model typically leads to lower computational costs and more efficient sampling compared with atomistic models. Designing “good” coarse-grained models is an art. Generally, the mapping from fine-grained configurations to coarse-grained configurations itself is not optimized in any way; instead, the energy function associated with the mapped configurations is. In this work, we explore the consequences of optimizing the coarse-grained representation alongside its potential energy function. We use a graph machine learning framework to embed atomic configurations into a low-dimensional space to produce efficient representations of the original molecular system. Because the representation we obtain is no longer directly interpretable as a real-space representation of the atomic coordinates, we also introduce an inversion process and an associated thermodynamic consistency relation that allows us to rigorously sample fine-grained configurations conditioned on the coarse-grained sampling. We illustrate that this technique is robust, recovering the first two moments of the distribution of several observables in proteins such as chignolin and alanine dipeptide.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Virtual Infrastructure Twins: Software Testing Platforms for Computing-Instrument Ecosystems

Science ecosystems are being built by federating computing systems and instruments located at geographically distributed sites over wide-area networks. These computing-instrument ecosystems are expected to support complex workflows that incorporate remote, automated AI-driven science experiments. Their realization, however, requires various designs to be explored and software components to be developed, in order to support the orchestration of distributed computations and experiments. It is often too expensive, infeasible, or disruptive for the entire ecosystem to be available during the typically long software development and testing periods. We propose a Virtual Infrastructure Twin (VIT) of the ecosystem that emulates its network and computing components, and incorporates its instrument software simulators. It provides a software environment nearly identical to the ecosystem to support early development and testing, and design space exploration. We present a brief overview of previous digital infrastructure twins that culminated in the VIT concept, including (i) the virtual science network environment for developing software-defined networking solutions, and (ii) the virtual federated science instrument environment for testing the federation software stack and remote instrument control software. We briefly describe VITs for Nion microscope steering and access to GPU systems.

Rao, Nageswara↗