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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 OSTI2017

Human factors and modeling methods in the development of control room modernization concepts - 315

Control room modernization is one of the most challenging and complex upgrade projects that a nuclear power plant can undertake. It can even have a bigger impact on operations than, for example, turbine replacement. The challenges of migrating an analog control system to a distributed control system are already well known and a number of nuclear utilities have embarked upon various levels of effort to upgrade some of the systems in the control room. When planning for control room upgrades, plants have to deal with a multitude of engineering and operational impacts. This will inevitably include several human factors considerations, including physical ergonomics of workstations, viewing angles, lighting, seating, new communication requirements, and new concepts of operation. In helping nuclear power utilities to deal with these challenges, the Idaho National Laboratory (INL) has developed human factors design and evaluation methods to be used in the development of an end-state control room concept and to manage the various phases of the upgrade life cycle. This included interactive sessions with operators in INL's Human System Simulation Laboratory, and three-dimensional modeling to visualize control board changes. To make the various upgrade phases as concrete and as visible as possible, the end-state concept includes a set of visual representations of the control room before and after various upgrade phases to provide the context and a framework within which to consider the various options in the upgrade. This includes the various control systems, human-system interfaces to be replaced, and possible changes to operator workstations. This paper describes how this framework helps to ensure an integrated and cohesive outcome that is consistent with human factors engineering principles and also provide substantial improvement in operator performance. The paper further describes the application of this integrated approach in the strategic modernization program at a nuclear power plant where legacy systems are upgraded to advanced digital technologies through a systematic process that links human factors principles to the systems engineering process. This approach results in an integrated control room architecture beyond what is possible for individual subsystem upgrades alone. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Materials informatics: From the atomic-level to the continuum

We report that in recent years materials informatics, which is the application of data science to problems in materials science and engineering, has emerged as a powerful tool for materials discovery and design. This relatively new field is already having a significant impact on the interpretation of data for a variety of materials systems, including those used in thermoelectrics, ferroelectrics, battery anodes and cathodes, hydrogen storage materials, polymer dielectrics, etc. Its practitioners employ the methods of multivariate statistics and machine learning in conjunction with standard computational tools (e.g., density-functional theory) to, for example, visualize and dimensionally reduce large data sets, identify patterns in hyperspectral data, parse microstructural images of polycrystals, characterize vortex structures in ferroelectrics, design batteries and, in general, establish correlations to extract important physics and infer structure-property-processing relationships. In this Overview, we critically examine the role of informatics in several important materials subfields, highlighting significant contributions to date and identifying known shortcomings. We specifically focus attention on the difference between the correlative approach of classical data science and the causative approach of physical sciences. From this perspective, we also outline some potential opportunities and challenges for informatics in the materials realm in this era of big data.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Calculating Trajectories Associated With Solute Transport in a Heterogeneous Medium

Here, we present a trajectory-based technique for calculating solute transport in a porous medium that has several advantages over existing methods. Unlike streamlines, the extended trajectories are influenced by each of the important parameters governing transport, including molecular diffusion and transverse dispersion. The approach is complete and does not require any additional techniques, such as operator splitting or particle tracking, in order to account for the full dispersion tensor. The semianalytic expressions make it clear how the flow field, the concentration distribution, and the dispersion tensor contribute to the velocity field of an injected solute. The equations are valid for an arbitrary porous medium, including those with rapid spatial variations in properties, overcoming limitations faced by previous approaches based upon asymptotic techniques. A test on a layered model with sharp boundaries indicates that the extended trajectories are compatible with the results of a numerical simulator and differ from streamlines. We also describe a new form of the dispersion tensor that incorporates a known asymmetry. The trajectories indicate that the modifications of the dispersion tensor lead to more focused transport within regions of high conductivity. The trajectories are used to define a semianalytic relationship between solute travel times and variations in solute velocities along a path that may be used for tomographic imaging. In an application to the injection of a radioactive tracer into a Berea sandstone core, monitored using micropositron emission tomographic (micro-PET) observations, the sensitivities are used to map the spatial variations of permeability within the core.

42 ENGINEERING↗
DOE OSTI2022

Visualization of Chiral Electronic Structure and Anomalous Optical Response in a Material with Chiral Charge Density Waves

Chiral materials have attracted significant research interests as they exhibit intriguing physical properties, such as chiral optical response, spin-momentum locking, and chiral induced spin selectivity. Recently, layered transition metal dichalcogenide 1T–TaS 2 has been found to host a chiral charge density wave (CDW) order. Nevertheless, the physical consequences of the chiral order, for example, in electronic structures and the optical properties, are yet to be explored. Here, we report the spectroscopic visualization of an emergent chiral electronic band structure in the CDW phase, characterized by windmill-shaped Fermi surfaces. Further, we uncover a remarkable chirality-dependent circularly polarized Raman response due to the salient in-plane chiral symmetry of CDW, although the ordinary circular dichroism vanishes. Chiral Fermi surfaces and anomalous Raman responses coincide with the CDW transition, proving their lattice origin. Our Letter paves a path to manipulate the chiral electronic and optical properties in two-dimensional materials and explore applications in polarization optics and spintronics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Efficient Lossy Compression for Scientific Data Based on Pointwise Relative Error Bound

An effective data compressor is becoming increasingly critical to today's scientific research, and many lossy compressors are developed in the context of absolute error bounds. Based on physical/chemical definitions of simulation fields or multiresolution demand, however, many scientific applications need to compress the data with a pointwise relative error bound (i.e., the smaller the data value, the smaller the compression error to tolerate). To this end, we propose two optimized lossy compression strategies under a state-of-the-art three-staged compression framework (prediction + quantization + entropy-encoding). The first strategy (called block-based strategy) splits the data set into many small blocks and computes an absolute error bound for each block, so it is particularly suitable for the data with relatively high consecutiveness in space. The second strategy (called multi-threshold-based strategy) splits the whole value range into multiple groups with exponentially increasing thresholds and performs the compression in each group separately, which is particularly suitable for the data with a relatively large value range and spiky value changes. We implement the two strategies rigorously and evaluate them comprehensively by using two scientific applications which both require lossy compression with point-wise relative error bound. Experiments show that the two strategies exhibit the best compression qualities on different types of data sets respectively. In conclusion, the compression ratio of our lossy compressor is higher than that of other state-of-the-art compressors by 17.2-618 percent on the climate simulation data and 30-210 percent on the N-body simulation data, with the same relative error bound and without degradation of the overall visualization effect of the entire data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

An efficient virus–induced gene silencing (VIGS) system for gene functional studies in Miscanthus

Virus-induced gene silencing (VIGS) is a powerful tool for transient gene functional analysis in plants, especially for monocot species (e.g., grasses) that are recalcitrant to transformation. Despite various VIGS systems that have been developed in different plant species, none was previously available for the bioenergy crop Miscanthus. Here, we report the establishment of an efficient and robust VIGS system mediated by Tobacco Rattle Virus (TRV) in Miscanthus. We first investigated the impact of various factors that may affect gene silencing efficiency using the Miscanthus sinensis Phytoene Desaturase (MsPDS) gene as a visual indicator of photobleaching. Then, we optimized the TRV-elicited VIGS procedure using an orthogonal experimental design with four factors (sprout size, Agrobacterium concentration, vacuum infiltration time, and co-incubation time) each at three levels. The following led to the highest silencing efficiency (~76%): inoculation of germinating seedlings (1.0–2.0 mm), Agrobacterium tumefaciens culture grown to optical density at 600 nm (OD 600 ) of 0.4, vacuum infiltration for 90 min, and co-incubation for 5 h. The VIGS system established was applicable for both M. sinensis and M. lutarioriparius, with comparable gene silencing efficiency. We verified the efficacy of the VIGS system via the functional characterization of the role of a MYB transcription factor, MsMYB112, in salt stress tolerance. Expression of MsMYB112 was successfully knocked down using the VIGS system, and this led to compromised salt tolerance in the silenced Miscanthus plants. The TRV-based VIGS system established may, therefore, substantially facilitate functional genomic studies in Miscanthus.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Application of deoxygenation-aeration cycling to control the predatory bacterium Vampirovibrio chlorellavorus in Chlorella sorokiniana cultures

A previously untested approach was evaluated to enable management of the predatory bacterium, Vampirovibrio chlorellavorus, a pathogen of Chlorella sorokiniana, in suspension cultures grown in a laboratory test reactor. Because V. chlorellavorus is an obligate aerobic bacterium, whereas C. sorokiniana grows under aerobic and anaerobic conditions, deoxygenation of the culture was expected to be detrimental to the pathogen, but not to the algal host. The effect of deoxygenation on the uninfected (healthy) C. sorokiniana suspension cells, compared to the C. sorokiniana-V. chlorellavorus co-culture, was studied in relation to biomass, dissolved oxygen, ratio of C. sorokiniana to V. chlorellavorus DNA, and visual and light microscopic observations. Preliminary experiments were conducted to test the effects of different deoxygenation-aeration cycling regimes on performance of V. chlorellavorus-free C. sorokiniana cultures. To an aerobic culture, pure nitrogen gas was introduced to create anoxic conditions, followed by the injection of ambient air to re-establish an aerobic environment. Under this repeated cycling regime, C. sorokiniana was shown to tolerate the anoxic conditions for extended timespans that ranged from 2 to 8 h over a 5-day test period. The analogous aerobic-anoxic cycling with the C. sorokiniana-V. chlorellavorus co-cultures resulted in ‘near-normal’ growth cycle and harvestable biomass, whereas the continuously-aerated (aerobic) co-cultures that were grown without the deoxygenation step in the cycle collapsed in 3 days. Visual and light microscopic observations revealed intact C. sorokiniana cells were present in the deoxygenated cultures, compared to the aerobically-grown, brown-colored algal cultures consisting of collapsed cells. Quantitative polymerase chain reaction analysis showed continuous increases in the ratio of V. chlorellavorus (16S rDNA) to C. sorokiniana (18S rDNA) DNA in the aerated co-cultures, with greater increases during dark periods, while the pathogen-to-host DNA ratio in the deoxygenated co-cultures was relatively low and algal cells did not collapse, as would be expected following pathogen attack.

Algae, Anoxic, Bomass, Infection, Nitrogen, Quanti↗
DOE OSTI2020

Non-visual analysis of miniaturized melt wire arrays for in-pile measurement of peak irradiation temperature

As a part of the in-pile instrumentation program, the Idaho National Laboratory (INL) has established in-house capabilities to fabricate and test new advanced manufactured printed sensors for measurement of peak temperature inside the harsh environment of a nuclear test reactor. Although nuclear test reactors may use standard methods that can provide real-time temperature information, such as thermocouples, the need for feedthroughs for real-time measurements greatly increases the cost of the experiment. Some experiments also present the problem of limited space available for instrumentation. To address this need, INL is working to improve temperature detection options for such applications. The lab is developing advanced manufactured melt wire arrays to determine peak temperatures in experiments with limited space. Furthermore, capabilities to print multiple melt wires with different melting properties on a single miniaturized unit is being established. Recent results and knowledge from this ongoing work have made it possible to develop unique temperature sensors that can accomplish user specific temperature ranges inside the harsh environments experienced during radiation testing.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Tracing Interstellar Magnetic Field Using Velocity Gradient Technique: Application to Atomic Hydrogen Data

The advancement of our understanding of MHD turbulence opens ways to develop new techniques to probe magnetic fields. In MHD turbulence, the velocity gradients are expected to be perpendicular to magnetic fields and this fact was used by González-Casanova and Lazarian to introduce a new technique to trace magnetic fields using velocity centroid gradients (VCGs). The latter can be obtained from spectroscopic observations. We apply the technique to GALFA-H i survey data and then compare the directions of magnetic fields obtained with our technique to the direction of magnetic fields obtained using PLANCK polarization. We find an excellent correspondence between the two ways of magnetic field tracing, which is obvious via the visual comparison and through the measuring of the statistics of magnetic field fluctuations obtained with the polarization data and our technique. This suggests that the VCGs have a potential for measuring of the foreground magnetic field fluctuations, and thus provide a new way of separating foreground and CMB polarization signals.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Coupling Exascale Multiphysics Applications: Methods and Lessons Learned

With the growing computational complexity of science and the complexity of new and emerging hardware, it is time to re-evaluate the traditional monolithic design of computational codes. One new paradigm is constructing larger scientific computational experiments from the coupling of multiple individual scientific applications, each targeting their own physics, characteristic lengths, and/or scales. We present a framework constructed by leveraging capabilities such as in-memory communications, workflow scheduling on HPC resources, and continuous performance monitoring. This code coupling capability is demonstrated by a fusion science scenario, where differences between the plasma at the edges and at the core of a device have different physical descriptions. This infrastructure not only enables the coupling of the physics components, but it also connects in situ or online analysis, compression, and visualization that accelerate the time between a run and the analysis of the science content. Results from runs on Titan and Cori are presented as a demonstration.

Choi, Jong Youl↗
DOE OSTI2019

Function Preserving Projection

With function preserving projection (FPP), we aim to address high-dimensional data exploration challenges common in many scientific applications. Instead of preserving the global or local geometric structure of a dataset like traditional dimensionality reduction methods (e.g., principal component analysis, t-stochastic neighborhood embedding), the proposed approach finds a linear projection that reveal interpretable (yet potentially nonlinear) pattern of the properties of interests defined on a highdimensional domain (e.g., simulation yield defined on the input parameter space). The key insight driving FPP is the fact that while non-linear embeddings are difficult to interpret, humans are highly skilled in understanding complex visual patterns. FPP lets users select the complexity of a pattern they consider interpretable, allows to find a joint projection that explains multiple functions, and provides a confidence statistic (akin to a p-value) indicating how salient the resulting pattern is. We demonstrate the efficacy of the proposed method on several synthetic and scientific datasets for both continuous (regression) and discrete (classification) problems of interests and illustrate the scalability of FPP by finding an optimal projection for close to 40 gigabytes in around 10 minutes.

Liu, SHUSEN↗
DOE OSTI2026

The U.S. Agrivoltaic Shading Tool: A National-Scale Interface for Modeling Light and Shade Patterns in Ten Common Agrivoltaic Configurations

Agrivoltaic systems are dual-use configurations that co-locate agriculture and photovoltaic (PV) infrastructure and require careful design to balance crop performance and energy generation. A critical element of agrivoltaic design is the spatial and temporal distribution of irradiance and shade within and around PV arrays. To support research, planning, and stakeholder decision-making, we introduce the U.S. Agrivoltaic Shading Tool, a novel web-based application that delivers high-resolution irradiance and photosynthetically active radiation (PAR) modeling for ten standardized PV configurations across the conterminous United States. The tool leverages the National Laboratory of the Rockies (NLR) System Advisor Model (SAM) to perform detailed irradiance simulations, using meteorological data from the National Solar Radiation Database (NSRDB). Outputs include seasonal, monthly, weekly, and diurnal patterns of available sunlight, amount of shade, irradiance, and PAR at ground level within agrivoltaic system footprints. For a user's selected location, these results are visualized through interactive visualizations, heatmaps, and time-series plots, designed to be accessible to both technical and non-technical users. In addition to facilitating rapid spatial exploration of agrivoltaic light environments, the tool will offer seamless integration with the InSPIRE Agrivoltaics Design and Analysis Model (ADAM). This optional workflow will allow users to port selected site and configuration parameters into a more advanced modeling environment for further customization of structural layouts, crop-system compatibility, power generation, and technoeconomic performance. Finally, to promote open science, the entire dataset will be hosted and available for open access through the OpenEI platform. By standardizing and disseminating high-quality irradiance data and design tools, the U.S. Agrivoltaic Shading Tool supports a wide range of users, including researchers, landowners, energy developers, and policymakers, in evaluating the agronomic and energetic feasibility of agrivoltaic systems across the United States.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

LensingETC: A Tool to Optimize Multifilter Imaging Campaigns of Galaxy-scale Strong Lensing Systems

Imaging data is the principal observable required to use galaxy-scale strong lensing in a multitude of applications in extragalactic astrophysics and cosmology. In this paper, we develop Lensing Exposure Time Calculator (LensingETC; to optimize the efficiency of telescope-time usage when planning multifilter imaging campaigns for galaxy-scale strong lenses. This tool simulates realistic data tailored to specified instrument characteristics and then automatically models them to assess the power of the data in constraining lens model parameters. We demonstrate a use case of this tool by optimizing a two-filter observing strategy (in the IR and ultraviolet-visual (UVIS)) within the limited exposure time per system allowed by a Hubble Space Telescope (HST) Snapshot program. We find that higher resolution is more advantageous to gain constraining power on the lensing observables, when there is a trade-off between signal-to-noise ratio and resolution; for example, between the UVIS and IR filters of the HST. We also find that, whereas a point-spread function (PSF) with sub-Nyquist sampling allows the sample mean for a model parameter to be robustly recovered for both galaxy–galaxy and point-source lensing systems, a sub-Nyquist-sampled PSF introduces a larger scatter than a Nyquist-sampled one in the deviation from the ground truth for point-source lens systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Determination of the Maturation Status of Dendritic Cells by Applying Pattern Recognition to High-Resolution Images

The maturation or activation status of dendritic cells (DCs) directly correlates with their behavior and immunofunction. A common means to determine the maturity of dendritic cells is from high-resolution images acquired via scanning electron microscopy (SEM) or atomic force microscopy (AFM). While direct and visual, the determination has been made by directly looking at the images by researchers. Here we report a machine learning approach using pattern recognition in conjunction with cellular biophysical knowledge of dendritic cells to determine the maturation status of dendritic cells automatically. The determination from AFM images reaches 100% accuracy. The results from SEM images reaches 94.9%. The results demonstrate the accuracy of using machine learning for accelerating data analysis, extracting information, and drawing conclusions from high-resolution cellular images, paving the way for future applications requiring high-throughput and automation, such as cellular sorting and selection based on morphology, quantification of cellular structure, and DC-based immunotherapy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Operando Optical Microscopy for Visualization of Dendrite Growth in an Argyrodite LPSCl–Polymer Composite Electrolyte

Herein, we demonstrate the utility of optical microscopy as an accessible technique for the in situ visualization of dendrite growth within polymer–sulfide composite solid-state electrolytes. The composite electrolyte features in situ polymerization and cross-linking of the polymer between ceramic particles, which opens up extensive opportunities for accelerated materials discovery, given the vast array of acrylate/methacrylate monomers available. Specifically, the cross-linked polymer poly(triethylene glycol dimethacrylate) (poly(TEGDMA)) was observed to effectively fill pores and inhibit dendrite growth at the lithium metal interface, attributed to its glassy state at room temperature. This work represents the first application of optical microscopy to illustrate that the incorporation of glassy, undoped polymers such as poly(TEGDMA) can serve as a viable strategy for dendrite suppression in solid-state composite electrolytes.

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

Wildfire Risk Evaluation Framework for Grid Operations and Planning

The United States (US) environmental protection agency's (EPA's) climate change indicators for wildfires show a long-term trend of increased annual wildfire activity, larger wildfire size, and more variable dynamics in wildfire behavior. This has caused more frequent preemptive public safety power shutoff (PSPS) events in the regions with recognized high wildfire risk. These preemptive power shutoffs attempt to prevent the ignition of a wildfire but it nonetheless renders the transmission line non-operational, which often sheds load of downstream communities. As wildfires and PSPS events become more frequent, it is crucial to find the communities most at risk of load shedding. To that end, this paper proposes the wildfire risk evaluation of the system (WiRES) framework, which is a performance-based framework that translates extreme weather-related and PSPS event probabilities into a cumulative probability of a non-operational transmission line. This study also provides a geospatial visualization tool that breaks down the entire western electrical coordinating council (WECC) region into 50 km grid cells which can be used to 1) filter out transmission lines with higher than a threshold outage probability, and 2) graphically discover the affected regions and their biophysical and socioeconomic metrics. %such as the social vulnerability index, population density, gross domestic product, etc. Lastly, an impact assessment study is conducted which connects the results of the proposed framework to python and powerworld-based contingency analysis to highlight the applicability of the framework.

Wildfire, Resilience, Extreme Events, Grid Reslien↗
DOE OSTI2021

Reactive Flows in Porous Media: Challenges in Theoretical and Numerical Methods

We review theoretical and computational research, primarily from the past 10 years, addressing the flow of reactive fluids in porous media. The focus is on systems where chemical reactions at the solid–fluid interface cause dissolution of the surrounding porous matrix, creating nonlinear feedback mechanisms that can often lead to greatly enhanced permeability. Here, we discuss insights into the evolution of geological forms that can be inferred from these feedback mechanisms, as well as some geotechnical applications such as enhanced oil recovery, hydraulic fracturing, and carbon sequestration. Until recently, most practical applications of reactive transport have been based on Darcy-scale modeling, where averaged equations for the flow and reactant transport are solved. We summarize the successes and limitations of volume averaging, which leads to Darcy-scale equations, as an introduction to pore-scale modeling. Pore-scale modeling is computationally intensive but offers new insights as well as tests of averaging theories and pore-network models. We include recent research devoted to validation of pore-scale simulations, particularly the use of visual observations from microfluidic experiments.

wormhole formation↗
DOE OSTI2017

Open-Source Integrated Design-Analysis Environment For Nuclear Energy Advanced Modeling & Simulation Final Scientific/Technical Report

The framework created through the Open-Source Integrated Design-Analysis Environment (IDAE) for Nuclear Energy Advanced Modeling & Simulation grant has simplify and democratize advanced modeling and simulation in the nuclear energy industry that works on a range of nuclear engineering applications. It leverages millions of investment dollars from the Department of Energy's Office of Nuclear Energy for modeling and simulation of light water reactors and the Office of Nuclear Energy's research and development. The IDEA framework enhanced Kitware’s Computational Model Builder (CMB) while leveraging existing open-source toolkits and creating a graphical end-to-end umbrella guiding end-users and developers through the nuclear energy advanced modeling and simulation lifecycle. In addition, the work deliver strategic advancements in meshing and visualization for ensembles.

97 MATHEMATICS AND COMPUTING↗