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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Identification of high transverse momentum top quarks in pp collisions at $ \sqrt{s}=8 $ TeV with the ATLAS detector

This study presents studies of the performance of several jet-substructure techniques, which are used to identify hadronically decaying top quarks with high transverse momentum contained in large-radius jets. The efficiency of identifying top quarks is measured using a sample of top-quark pairs and the rate of wrongly identifying jets from other quarks or gluons as top quarks is measured using multijet events collected with the ATLAS experiment in 20.3 fb -1 of 8 TeV proton-proton collisions at the Large Hadron Collider. Predictions from Monte Carlo simulations are found to provide an accurate description of the performance. The techniques are compared in terms of signal efficiency and background rejection using simulations, covering a larger range in jet transverse momenta than accessible in the dataset. Finally and additionally, a novel technique is developed that is optimized to reconstruct top quarks in events with many jets.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

A general CFD framework for fault-resilient simulations based on multi-resolution information fusion

We develop a general CFD framework for multi-resolution simulations to target multiscale problems but also resilience in exascale simulations, where faulty processors may lead to gappy, in space-time, simulated fields. We combine approximation theory and domain decomposition together with statistical learning techniques, e.g. coKriging, to estimate boundary conditions and minimize communications by performing independent parallel runs. To demonstrate this new simulation approach, we consider two benchmark problems. First, we solve the heat equation (a) on a small number of spatial “patches” distributed across the domain, simulated by finite differences at fine resolution and (b) on the entire domain simulated at very low resolution, thus fusing multi-resolution models to obtain the final answer. Second, we simulate the flow in a lid-driven cavity in an analogous fashion, by fusing finite difference solutions obtained with fine and low resolution assuming gappy data sets. We investigate the influence of various parameters for this framework, including the correlation kernel, the size of a buffer employed in estimating boundary conditions, the coarseness of the resolution of auxiliary data, and the communication frequency across different patches in fusing the information at different resolution levels. In addition to its robustness and resilience, the new framework can be employed to generalize previous multiscale approaches involving heterogeneous discretizations or even fundamentally different flow descriptions, e.g. in continuum-atomistic simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Bias Correction in Urban Building Energy Modeling for Chicago Using Machine Learning

Urban-scale building energy modeling (UBEM) holds promise for optimizing energy usage across extensive geographic regions. However, there is a recognized bias between simulated energy consumption and actual measured data. This study, based on building data from Chicago, delved into bias correction techniques for enhancing the accuracy of UBEM energy consumption estimates. Initially, the AutoBEM simulation yielded a normalized mean bias error (NMBE) of 1.1% and 51% of Coefficient of the Variation of the Root Mean Square Error (CVRMSE) after outlier exclusion. To address this, three bias correction methods were deployed: Average Mean Bias Error based bias correction, Quantile mapping bias correction, and Machine learning-based bias correction using Linear Regression and Random Forest models. Post-correction results exhibited marked improvement. The NMBE values were diminished to 0 for Average MBE-based, 0.36 for Quantile Mapping, and 0 for Machine Learning-based corrections. Concurrently, the CVRMSE values registered reductions from an original 51 to 50.8 for Quantile Mapping, and 38.56 for Machine Learning-based corrections, pointing towards the effectiveness of specific bias correction methods in refining the precision of UBEM energy predictions. Such accurate estimations are paramount for informed energy planning and urban policy-making.

Chowdhury, Shovan↗
DOE OSTI2016

Performance of coincidence-based PSD on LiF/ZnS Detectors for Multiplicity Counting

Abstract: Mass accountancy measurement is a nuclear nonproliferation application which utilizes coincidence and multiplicity counters to verify special nuclear material declarations. With a well-designed and efficient detector system, several relevant parameters of the material can be verified simultaneously. 6LiF/ZnS scintillating sheets may be used for this purpose due to a combination of high efficiency and short die-away times in systems designed with this material, but involve choices of detector geometry and exact material composition (e.g., the addition of Ni-quenching in the material) that must be optimized for the application. Multiplicity counting for verification of declared nuclear fuel mass involves neutron detection in conditions where several neutrons arrive in a short time window, with confounding gamma rays. This paper considers coincidence-based Pulse-Shape Discrimination (PSD) techniques developed to work under conditions of high pileup, and the performance of these algorithms with different detection materials. Simulated and real data from modern LiF/ZnS scintillator systems are evaluated with these techniques and the relationship between the performance under pileup and material characteristics (e.g., neutron peak width and total light collection efficiency) are determined, to allow for an optimal choice of detector and material.

Robinson, Sean M.↗
DOE OSTI2021

DeepMerge – II. Building robust deep learning algorithms for merging galaxy identification across domains

In astronomy, neural networks are often trained on simulation data with the prospect of being used on telescope observations. Unfortunately, training a model on simulation data and then applying it to instrument data leads to a substantial and potentially even detrimental decrease in model accuracy on the new target dataset. Simulated and instrument data represent different data domains, and for an algorithm to work in both, domain-invariant learning is necessary. Here we employ domain adaptation techniques— Maximum Mean Discrepancy (MMD) as an additional transfer loss and Domain Adversarial Neural Networks (DANNs)— and demonstrate their viability to extract domain-invariant features within the astronomical context of classifying merging and non-merging galaxies. Additionally, we explore the use of Fisher loss and entropy minimization to enforce better in-domain class discriminability. We show that the addition of each domain adaptation technique improves the performance of a classifier when compared to conventional deep learning algorithms. We demonstrate this on two examples: between two Illustris-1 simulated datasets of distant merging galaxies, and between Illustris-1 simulated data of nearby merging galaxies and observed data from the Sloan Digital Sky Survey. The use of domain adaptation techniques in our experiments leads to an increase of target domain classification accuracy of up to ~20%. With further development, these techniques will allow astronomers to successfully implement neural network models trained on simulation data to efficiently detect and study astrophysical objects in current and future large-scale astronomical surveys.

galaxies: interactions↗
DOE OSTI2019

A hierarchical approach for modeling X-ray beamlines: application to a coherent beamline

Herein, different approaches to simulate a modern X-ray beamline are considered. Several methodologies with increasing complexity are applied to discuss the relevant parameters that quantify the beamline performance. Parameters such as flux, dimensions and intensity distribution of the focused beam, and coherence properties are obtained from simple analytical calculations to sophisticated computer simulations using ray-tracing and wave optics techniques. A latest-generation X-ray nanofocusing beamline for coherent applications (ID16A at the ESRF) has been chosen to study in detail the issues related to highly demagnifying synchrotron sources and exploiting the beam coherence. The performance of the beamline is studied for two storage rings: the old ESRF-1 (emittance 4000 pm) and the new ESRF-EBS (emittance 150 pm). In addition to traditional results in terms of flux and beam sizes, an innovative study on the partial coherence properties based on the propagation of coherent modes is presented. The different algorithms and methodologies are implemented in the software suite OASYS . These are discussed with emphasis placed upon the their benefits and limitations of each.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Improving the off-axis spatial resolution and dynamic range of the NIF X-ray streak cameras (invited)

We report simulations and experiments that demonstrate an increase in spatial resolution of the NIF core diagnostic x-ray streak cameras by at least a factor of two, especially off axis. A design was achieved by using a corrector electron optic to flatten the field curvature at the detector plane and corroborated by measurement. In addition, particle in cell simulations were performed to identify the regions in the streak camera that contribute the most to space charge blurring. These simulations provide a tool for convolving synthetic pre-shot spectra with the instrument function so signal levels can be set to maximize dynamic range for the relevant part of the streak record.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Fine precipitation scenarios of AlZnMg(Cu) alloys revealed by advanced atomic-resolution electron microscopy study Part I: Structure determination of the precipitates in AlZnMg(Cu) alloys

Although they are among the most important precipitation-hardened materials for industry applications, the high-strength AlZnMg(Cu) alloys have thus far not yet been understood adequately about their underlying precipitation scenarios in relation with the properties. This is partly due to the fact that the structures of a number of different precipitates involved in electron microscopy in association with quantitative image simulations have to be employed; a systematic study of these hardening precipitates in different alloys is also necessary. In Part I of the present study, it is shown that there are five types of structurally different precipitates including the equilibrium η-phase precipitate. Using two state-of-the-art atomic-resolution imaging techniques in electron microscopy in association with quantitative image simulations, we have determined and clarified all the unknown precipitate structures. It is demonstrated that atomic-resolution imaging can directly suggest approximate structure models, whereas quantitative image analysis can refine the structure details that are much smaller than the resolution of the microscope. This combination is crucially important for solving the difficult structure problems of the strengthening precipitates in AlZnMg(Cu) alloys. - Highlights: Part I: • We determine and verify all the key precipitate structures in AlMgZn(Cu) alloys. • We employ aberration-corrected scanning transmission electron microscopy (STEM). • We use aberration-corrected high-resolution TEM (HRTEM) for the investigations. • We obtain atomic-resolution images of the precipitates and model their structures. • We refine all precipitate structures with quantitative image simulation analysis. Part II: • The hardening precipitates in AlZnMg alloys shall be classified into two groups. • Two precipitation scenarios coexist in the alloys. • The precipitation behavior of such an alloy depends on the alloy's composition. • Very detailed phase/structure transformations among the precipitates are revealed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A Practical Framework for Simulating Time-Resolved Spectroscopy Based on a Real-Time Dyson Expansion

Time-resolved spectroscopy is a powerful tool for probing electron dynamics in molecules and solids, revealing transient phenomena on subfemtosecond time scales. The interpretation of experimental results is often enhanced by parallel numerical studies, which can provide insight and validation for experimental hypotheses. However, developing a theoretical framework for simulating time-resolved spectra remains a significant challenge. The most suitable approach involves the many-body nonequilibrium Green's function formalism, which accounts for crucial dynamical many-body correlations during time evolution. While these dynamical correlations are essential for observing emergent behavior in time-resolved spectra, they also render the formalism prohibitively expensive for large-scale simulations. Substantial effort has been devoted to reducing this computational cost─through approximations and numerical techniques─while preserving the key dynamical correlations. The ultimate goal is to enable first-principles simulations of time-dependent systems ranging from small molecules to large, periodic, multidimensional solids. Here, in this perspective, we outline key challenges in developing practical simulations for time-resolved spectroscopy, with a particular focus on Green's function methodologies. We highlight a recent advancement toward a scalable framework: the real-time Dyson expansion (RT-DE) [Phys. Rev. Lett. 2024, 133, 226902]. We introduce the theoretical foundation of RT-DE and discuss strategies for improving scalability, which have already enabled simulations of system sizes beyond the reach of previous fully dynamical approaches. We conclude with an outlook on future directions for extending RT-DE to first-principles studies of dynamically correlated, nonequilibrium systems.

Reeves, Cian C. [Univ. of California, Santa Barbar↗
DOE OSTI2016

Benchmark Generation and Simulation at Extreme Scale

The path to extreme scale high-performance computing (HPC) poses several challenges related to power, performance, resilience, productivity, programmability, data movement, and data management. Investigating the performance of parallel applications at scale on future architectures and the performance impact of different architectural choices is an important component of HPC hardware/software co-design. Simulations using models of future HPC systems and communication traces from applications running on existing HPC systems can offer an insight into the performance of future architectures. This work targets technology developed for scalable application tracing of communication events. It focuses on extreme-scale simulation of HPC applications and their communication behavior via lightweight parallel discrete event simulation for performance estimation and evaluation. Instead of simply replaying a trace within a simulator, this work promotes the generation of a benchmark from traces. This benchmark is subsequently exposed to simulation using models to reflect the performance characteristics of future-generation HPC systems. This technique provides a number of benefits, such as eliminating the data intensive trace replay and enabling simulations at different scales. The presented work features novel software co-design aspects, combining the ScalaTrace tool to generate scalable trace files, the ScalaBenchGen tool to generate the benchmark, and the xSim tool to assess the benchmark characteristics within a simulator.

Lagadapati, Mahesh↗
DOE OSTI2013

Molecular dynamics studies of the size and temperature dependence of the kinetics of freezing of Fe nanoparticles

Molecular dynamics (MD) computer simulations have been carried out and a novel modified technique of Voronoi polyhedra has been performed to identify solid-like particles in a molten nanoparticle. This technique works quite well in analyzing the effects of particle size on nucleation rates of iron nanoparticles in the temperature range of 750–1160 K. Nanoparticles with 1436 and 2133 Fe atoms have been examined and the results are compared with those obtained earlier with Fe{sub 331} nanoparticles. Nucleation rates for freezing obtained from MD simulations for Fe{sub 2133} vary from 8.8×10{sup 34} m{sup 3}/s to 4.1×10{sup 35} m{sup 3}/s at over a temperature range from 1160 K to 900 K, Rates for. Fe{sub 1436} and Fe{sub 331} are somewhat higher. Nucleation rates increase as supercooling deepens until the viscosity of the liquid increases sharply enough to slow down the rate. Bt applying classical nucleation theory, the interfacial free energy between solid and liquid cab be estimated From this and other thermodynamic information can be derived a theoretical expression for the size-dependence of the heat of fusion of nanoparticles. Results agreed quite well with those observed in our MD observations. An earlier expression in the literature for this size-dependence was shown to be incorrect. The size dependence of melting point is discussed. - Graphical abstract: Critical nuclei of crystallization. Display Omitted - Highlights: • Solid state material synthesis. • Material structure. • Experimental study of nucleation in condensed materials. • Computation study of nucleation in condensed materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Development of highly porous scaffolds based on bioactive silicates for dental tissue engineering

Graphical abstract: - Highlights: • Synthesis of an Mg-based glass-ceramic via the sol–gel technique. • The heat treatment of the glass-ceramic promoted the crystallization of akermanite. • Akermanite scaffolds coated with gelatin were successfully fabricated. • An HCAp layer was developed on the surface of all scaffolds after 9 days in SBF. - Abstract: Various scaffolding materials, ceramics and especially Mg-based ceramic materials, including akermanite (Ca{sub 2}MgSi{sub 2}O{sub 7}) and diopside (CaMgSi{sub 2}O{sub 6}), have attracted interest for dental tissue regeneration because of their improved mechanical properties and controllable biodegradation. The aim of the present work was the synthesis of an Mg-based glass-ceramic, which would be used for the construction of workable akermanite scaffolds. The characterization of the synthesized material was performed by Fourier Transform Infrared Spectroscopy (FTIR) X-Ray Diffractometry (XRD) and Scanning Electron Microscopy (SEM). Finally, the apatite forming ability of the scaffolds was assessed by immersion in simulated body fluid. The scaffolds were fabricated by the foam replica technique and were subsequently coated with gelatin to provide a functional surface for increased cell attachment. Finally, SEM microphotographs and FTIR spectra of the scaffolds after immersion in SBF solution indicated the inorganic bioactive character of the scaffolds suitable for the intended applications in dental tissue engineering.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Traction–separation relationships for hydrogen induced grain boundary embrittlement in nickel via molecular dynamics simulations

A statistical approach combined with molecular dynamics simulations is used to study the influence of hydrogen on intergranular decohesion. This methodology is applied to a Ni Σ3(112)[11¯0] symmetric tilt grain boundary. Hydrogenated grain boundaries with different H concentrations are constructed using an energy minimization technique with initial H atom positions guided by Monte Carlo simulation results. Decohesion behavior is assessed through extraction of a traction–separation relationship during steady-state crack propagation in a statistically meaningful approach, building upon prior work employing atomistic cohesive zone volume elements (CZVEs). A sensitivity analysis is performed on the numerical approach used to extract the traction–separation relationships, clarifying the role of CZVE size, threshold parameters necessary to differentiate elastic and decohesion responses, and the numerical averaging technique. Results show that increasing H coverage at the Ni Σ3(112)[11¯0] grain boundary asymmetrically influences the crack tip velocity during propagation, leads to a general decrease in the work of separation required for crack propagation, and provides a reduction in the peak stress in the extracted traction–separation relationship. Furthermore the present framework offers a meaningful vehicle to pass atomistically derived interfacial behavior to higher length scale formulations for intergranular fracture.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Simulation of Particle-Material Interactions

This paper gives an overview of the particle transport theory essentials, the basics of particle-material interaction simulation, physical quantities needed to simulate particle transport and interactions in materials, Monte Carlo simulation flow, response of additive detectors, statistical weights and other techniques to minimize statistical errors. Effects in materials under irradiation, materials response related to component lifetime and performance are considered with a focus on high-energy and high-power accelerator applications. Implementation of simulation of particle-material interactions in the modern Monte Carlo codes along with the code s main features and results of recent benchmarking are described.

43 PARTICLE ACCELERATORS↗
DOE OSTI2014

Verification of the helioseismology travel-time measurement technique and the inversion procedure for sound speed using artificial data

We performed three-dimensional numerical simulations of the solar surface acoustic wave field for the quiet Sun and for three models with different localized sound-speed perturbations in the interior with deep, shallow, and two-layer structures. We used the simulated data generated by two solar acoustics codes that employ the same standard solar model as a background model, but utilize different integration techniques and different models of stochastic wave excitation. Acoustic travel times were measured using a time-distance helioseismology technique, and compared with predictions from ray theory frequently used for helioseismic travel-time inversions. It is found that the measured travel-time shifts agree well with the helioseismic theory for sound-speed perturbations, and for the measurement procedure with and without phase-speed filtering of the oscillation signals. This testing verifies the whole measuring-filtering-inversion procedure for static sound-speed anomalies with small amplitude inside the Sun outside regions of strong magnetic field. It is shown that the phase-speed filtering, frequently used to extract specific wave packets and improve the signal-to-noise ratio, does not introduce significant systematic errors. Results of the sound-speed inversion procedure show good agreement with the perturbation models in all cases. Due to its smoothing nature, the inversion procedure may overestimate sound-speed variations in regions with sharp gradients of the sound-speed profile.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Laboratory Resources and Techniques to Evaluate Smart Home Technology: Preprint

Smart home technologies promise to make residential buildings more comfortable, less costly to operate, more energy efficient, and more integrated with the grid, but these systems are difficult to evaluate in traditional laboratory spaces. To aid in the development and evaluation of new home energy management systems (HEMS), NREL built the Systems Performance Laboratory (SPL) within the Energy Systems Integration Facility. SPL has electrical infrastructure for three residential buildings, complete with smart meters, breaker panels and a full complement of major and minor appliances in each 'home.' Cord and plug power connections mean that appliances can easily be swapped for different models. Distributed energy resources (DER), such as residential photovoltaic (PV) inverters and home batteries, are also available for integration. Sensors monitor the power consumption of all loads and controllers can simulate occupancy to drive the appliances in realistic ways. A novel hardware-in-the-loop application was developed to ensure air conditioner cycling by combining a building simulation with a physical air conditioner and a thermostat, which allows us to simulate performance in any climate with any building construction. Another application of the hardware-in-the-loop technique uses a grid simulation to model the grid impact for different control strategies related to smart home technologies. This laboratory is a powerful, flexible tool that can be employed to evaluate the effect that home energy management and other smart home technologies will have at the appliance, whole-home, and distribution feeder levels - all of which are important perspectives for different stakeholders.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Structural analysis of WO 3 -TeO 2 glasses by neutron, high energy X-ray diffraction, reverse Monte Carlo simulations and XANES

The structure of WO 3 -TeO 2 glasses containing 15, 20 and 25 mol% WO 3 are studied by neutron diffraction (ND), high energy X-ray diffraction (XRD) and X-ray Absorption Near Edge spectroscopy (XANES). The short-range structural properties of glasses i.e. Te-O and W-O speciation, coordination number distributions, bond-lengths, and the O-Te-O, O-W-O and O-O-O bond angle distributions in the glass network are determined by the Reverse Monte Carlo (RMC) simulations of the ND and XRD data. RMC technique successfully determined all partial pair correlation functions and the coordination number distributions revealed that glass network consists predominantly of TeO 4 and WO 4 units with small amounts of triangular, penta and hexa co-ordinated units. The average W-O and Te-O bond lengths are in the ranges: 1.69-1.75 +/- 0.01 angstrom and 1.99-2.00 +/- 0.01 angstrom respectively. Both W-O and Te-O correlation peaks are asymmetrical, that indicate a distribution of their bond lengths in the respective structural units. The O-Te-O bond angle distribution has a peak at 107 +/- 2 degrees. Similarly the O-W-O bond angle distribution has a peak at 108 +/- 5 degrees. On increasing the WO3 concentration from 15 to 25 mol%, the average Te-O coordination number decreases from 3.80 to 3.61 +/- 0.02 due to the structural transformation: TeO 4 → TeO 3 , similarly the W-O coordination also decreases and is in the range: 3.79-3.67 +/- 0.02. XANES studies found that the oxidation state of Te and W ions in the glasses are 4 + and 6 + respectively.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Estimation of Future PM2.5- and Ozone-related Mortality over the Continental United States in a Changing Climate: An application of High-resolution Dynamical Downscaling Technique

This paper evaluates the PM2.5- and ozone-related mortality at present (2000s) and in the future (2050s) over the continental United States by using the Environmental Benefits Mapping and Analysis Program (BenMAP-CE). Atmospheric chemical fields are simulated by WRF/CMAQ (horizontal resolution: 12 × 12km), applying the dynamical downscaling technique from global climate-chemistry models under the Representative Concentration Pathways scenario (RCP 8.5). Future air quality results predict that the annual mean PM2.5 concentrations in continental US will decrease nationwide, especially in the eastern US and west coast. However, the ozone concentration is projected to decrease in the Eastern US but increase in the Western US. Future mortality is evaluated under two scenarios (1) holding future population and baseline incidence rate at the present level and (2) decreasing the future baseline incidence rate but increasing the future population. For PM2.5, the entire continental US presents a decreasing trend of PM2.5-related mortality by the 2050s in Scenario (1), primarily resulting from the emissions reduction. While in Scenario (2), almost half of the continental states show a rising tendency of PM2.5-related mortality, due to the dominant influence of population growth. In particular, the highest PM2.5-related deaths and the biggest discrepancy between present and future PM2.5-related deaths will both occur in California in 2050s. For the ozone-related premature mortality, the simulation shows nation-wide rising tendency in 2050s under both two scenarios, mainly due to the increase of ozone concentration and population in the future. Furthermore, the uncertainty analysis shows that the effect of the all causes mortality is much larger than for specific causes. This assessment is the result of the accumulated uncertainty of generating datasets. The uncertainty range of ozone-related all cause premature mortality is narrower than the PM2.5-related all cause mortality, due to its smaller standard deviation of beta parameter.

BenMAP-CE↗