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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 325 records · Page 18

Ray-tracing image simulations of transparent objects with complex shape and inhomogeneous refractive index

Optical images of transparent three-dimensional objects can be different from a replica of the object’s cross section in the image plane, due to refraction at the surface or in the body of the object. Simulations of the object’s image are thus needed for the visualization and validation of physical models. We report ray tracing image simulations that achieved high physical fidelity, reproducing optical behaviors and image features not rendered in previous studies. We replicated brightfield microscopy images of drops with complex shapes, and images of pressure and shock waves traveling inside them. For high physical fidelity, the simulations must replicate the spatial and angular distribution of illumination rays, and both the experiment and the simulation must be designed for accurate optical modeling. The simulations are highly sensitive to the properties of the drops and can be used to diagnose and refine fluid dynamics models. The simulated images can also be optimized to extract multiple 3D properties from experimental images. Compared to specialized single-shot 3D imaging methods, this approach has the advantage that it preserves the experimental simplicity, the high resolution, and the visual interpretability characteristic to basic optical imaging. The techniques introduced here are directly applicable to optical microscopy, so they can be used in other fields, such as microfluidics and biology, to expand the type and the accuracy of three-dimensional information that can be extracted from basic optical images.

Cavitation↗

Moltensaltpropnet

MoltenSaltPropnet is a physics-informed machine learning framework that aims to predict the thermophysical properties of molten fluoride and chloride salt mixtures, which are crucial for the design and safety of Generation IV molten salt reactors. The code processes data from the Molten-Salt Thermal Properties Database (MSTDB-TP) and the Janz compendium, converting critically evaluated correlations into fast, differentiable surrogate models for density, viscosity, thermal conductivity, and heat capacity across 448 distinct salt systems. The implementation consists of several key components: 1. Data Curation: The code parses and cleans the raw data, normalizing elemental mole fractions and extracting relevant regression coefficients for various thermophysical properties. 2. Feature Engineering: It generates fixed-length numerical descriptors that encapsulate the composition and temperature, incorporating polynomial interaction terms and dimensionality-reduction techniques to optimize model performance. 3. Coefficient Learning: Four different machine learning architectures are employed: a deep residual network (ResNet), a Kolmogorov–Arnold network (KAN), a sparsity-inducing neural network (SNN), and classical regression models. Each model learns to predict coefficients that define the temperature-dependent correlations for the thermophysical properties. 4. Property Reconstruction: The predicted coefficients are used to compute temperature-dependent property values, ensuring positivity and monotonic trends through a composite loss function that enforces physical constraints. 5. User Interface: An open-source web application enables users to filter the database, train task-specific models, and visualize the results, allowing for rapid exploration of candidate salt mixtures. MoltenSaltPropnet bridges the gap between limited experimental data and high-fidelity reactor simulations, providing a powerful tool for researchers in the field of molten salt reactors and advanced nuclear energy systems.

Retamales, Mauricio Eduardo Tano [Idaho National L↗

Retrofit Energy Analysis and Central Thermal modeling (REACT) v1.0

REACT is a website designed to simplify the analysis and decision-making process for retrofitting existing central plant heating and cooling systems with advanced heat pump technologies. The tool evaluates the technical and economic viability of replacing traditional boilers with various options including water-to-water or air-to-water heat pumps, which can provide efficient and lower-cost heating and cooling. It allows users to compare current central plant configurations with retrofit scenarios, assessing energy consumption, life-cycle costs, and environmental impact. Retrofitting traditional boiler and chiller systems with water-to-water or air-to-water heat pumps can significantly reduce energy consumption and lower lifecycle costs. The REACT provides: User-Friendly Tools: A user friendly web interface for quick, intuitive analysis accessible to non-experts. Advanced Modeling: A Python-powered engine for detailed parametric studies, optimization, and research applications. Comprehensive Analysis: Lifecycle cost evaluation, energy consumption modeling, and environmental impact assessment. Visual Insights: A variety of plots to visualize system performance and design trade-offs. The engine for the website (REACT) bases on several Python libraries, and the website will be hosted on an ETA server.

Kim, Donghun [Lawrence Berkeley National Laborator↗

CSRI Summer Proceedings 2021

The Computer Science Research Institute (CSRI) brings university faculty and students to Sandia National Laboratories for focused collaborative research on Department of Energy (DOE) computer and computational science problems. The institute provides an opportunity for university researches to learn about problems in computer and computational science at DOE laboratories, and help transfer results of their research to programs at the labs. Some specific CSRI research interest areas are: scalable solvers, optimization, algebraic preconditioners, graph-based, discrete, and combinatorial algorithms, uncertainty estimation, validation and verification methods, mesh generation, dynamic load-balancing, virus and other malicious-code defense, visualization, scalable cluster computers, beyond Moore’s Law computing, exascale computing tools and application design, reduced order and multiscale modeling, parallel input/output, and theoretical computer science. The CSRI Summer Program is organized by CSRI and includes a weekly seminar series and the publication of a summer proceedings.

97 MATHEMATICS AND COMPUTING↗

CSRI Summer Proceedings 2021

The Computer Science Research Institute (CSRI) brings university faculty and students to Sandia National Laboratories for focused collaborative research on Department of Energy (DOE) computer and computational science problems. The institute provides an opportunity for university researches to learn about problems in computer and computational science at DOE laboratories, and help transfer results of their research to programs at the labs. Some specific CSRI research interest areas are: scalable solvers, optimization, algebraic preconditioners, graph-based, discrete, and combinatorial algorithms, uncertainty estimation, validation and verification methods, mesh generation, dynamic load-balancing, virus and other malicious-code defense, visualization, scalable cluster computers, beyond Moore’s Law computing, exascale computing tools and application design, reduced order and multiscale modeling, parallel input/output, and theoretical computer science. The CSRI Summer Program is organized by CSRI and includes a weekly seminar series and the publication of a summer proceedings.

97 MATHEMATICS AND COMPUTING↗

Remote Autonomous Vehicle Extended Network (RAVEN)

Unmanned Aerial Vehicles (UAVs) are increasingly utilized across a broad spectrum of applications. While many operations occur within a localized environment where the operator maintains visual contact with the aircraft, more advanced missions often require Beyond Visual Line of Sight (BVLOS) capabilities. These BVLOS operations introduce significant safety and regulatory challenges. Improper execution can endanger not only the UAV but also other aircraft, people, and property.

42 ENGINEERING↗

Interdisciplinary Research Collaborative Trains Students to See Through Turbulent Systems

Despite the availability of interdisciplinary academic training programs, the practice of environmental science is often hampered by a lack of convergence across diverse disciplines. This gap is particularly salient in settings characterized by complex environmental issues, such as multiple-use coastal ecosystems. In response, we developed and implemented a training, research, and communication framework to provide undergraduates with an authentic operative experience working at the interface of interdisciplinary science and public decision-making within a case study of marine renewable energy. In our program, students gained hands-on experience with the scientific process and learned how to make information relevant, useful, and accessible to diverse stakeholder groups. Application of this framework demonstrates that the process of integrating data from biological (visual and acoustic monitoring of fish and marine mammals), physical (hydrodynamics), and social (local ecological knowledge) sciences can provide a more complete understanding of complex and turbulent ecosystems for better informed decision-making. We offer several recommendations to facilitate the adaptation and implementation of our interdisciplinary framework to diverse research contexts, with a focus on interdisciplinary training for the next generation of marine scientists.

54 ENVIRONMENTAL SCIENCES↗

ExpoKids: An R-based tool for characterizing aggregate chemical exposure during childhood

Background: Aggregate exposure, the combined exposures to a single chemical from all pathways, is a critical children’s health issue. Objective: The primary objective is to develop a tool to illustrate potential differences in aggregate exposure at various childhood lifestages and the adult lifestage. Methods: We developed ExpoKids (an R-based tool) using oral exposure estimates across lifestages generated by US EPA’s Exposure Factors Interactive Resource for Scenarios Tool (ExpoFIRST). Results: ExpoKids is applied to illustrate aggregate oral exposure, for ten media, as average daily doses (ADD) and lifetime average daily doses (LADD) in five graphs organized across seven postnatal childhood lifestages and the adult lifestage. This data visualization tool conveys ExpoFIRST findings, from available exposure data, to highlight the relative contributions of media and lifestages to chemical exposure. To evaluate the effectiveness of ExpoKids, three chemical case examples (di[2-ethylhexyl] phthalate [DEHP], manganese, and endosulfan) were explored. Data available from the published literature and databases for each case example were used to explore research questions regarding media and lifestage contributions to aggregate exposure. Significance: These illustrative case examples demonstrate ExpoKids’ versatile application to explore a diverse set of children’s health risk assessment and management questions by visually depicting specific media and lifestage contributions to aggregate exposure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

“Understanding Robustness Lottery”: A Geometric Visual Comparative Analysis of Neural Network Pruning Approaches

Deep learning approaches have provided state-of-the-art performance in many applications by relying on large and overparameterized neural networks. However, such networks are very brittle and are difficult to deploy on resource-limited platforms. Model pruning, i.e., reducing the size of the network, is a widely adopted strategy that can lead to a more robust and compact model. Many heuristics exist for model pruning, but our understanding of the pruning process remains limited due to the black-box nature of a neural network model. Empirical studies show that some heuristics improve performance whereas others can make models more brittle. Here, this work aims to shed light on how different pruning methods alter the network’s internal feature representation and the corresponding impact on model performance. To facilitate a comprehensive comparison and characterization of the high-dimensional model feature space, we introduce a visual geometric analysis of feature representations. We evaluated a set of critical geometric concepts decomposed from the commonly adopted classification loss and used them to design a visualization system to compare and highlight the impact of pruning on model performance and feature representation. The proposed tool provides an environment for an in-depth comparison of pruning methods and a comprehensive understanding of how the model responds to common data corruption. By leveraging the proposed visualization, machine learning researchers can reveal the similarities between pruning methods and redundancy in robustness evaluation benchmarks, obtain geometric insights about the differences between pruned models that achieve superior robustness performance, and identify samples that are robust or fragile to model pruning and common data corruption.

Li, Zhimin [Univ. of Utah, Salt Lake City, UT (Uni↗

Direct Visualization of Laser-Induced Coalescence and Alloying of Au into Ag Nanowires

Noble metal nanocomposites with controlled morphology and composition have been largely useful in a wide variety of applications like catalysis, plasmonics, and biological applications. Herein, we show pulsed-laser-assisted fabrication of beaded Au-Ag nanowires with a variety of morphologies and compositions via coalescence and alloying of Au nanoparticles (NP) into a Ag nanowire (NW). Direct visualization of the evolution process with in situ laser heating transmission electron microscopy (ILH-TEM) leads to unambiguous insights into the mechanism of formation for the first time. Ag, being a soft material, melts at the surface to bridge the gap between the NP-NW, forming a cup-like morphology underneath the Au NP via capillary action. Progressive laser irradiation leads to wetting of the Au NP with Ag, forming an envelope around the NP. This is associated with the formation of a valley in Ag NW around the NP, which flattens gradually by partial embedding of the NP. Interdiffusion of Au into Ag and vice versa sets in at this stage, leading to the depletion of Au from the Au-rich NP region. Prolonged irradiation leads to gradual intermixing of Au-Ag forming beaded Au-doped Ag nanowires with homogeneous composition. Such a step-by-step understanding of the coalescence and alloying process has implications in nanowelding, which holds the future in designing efficient transparent conductors and printed electronics.

Isik, Tugba↗

Accobeam - Acoustic Collimated Beam

Researchers at Los Alamos have developed a collimated acoustic imaging technology for non-destructive characterization of highly attenuating media, such as concrete, rocks, mud, and metal casings. The technology is used to investigate structural defects that could compromise important assets such as well boreholes, building structures and sensitive materials like explosives. Current acoustic methods are often unable to penetrate such materials deeply for more informative analysis, which limits what can be learned about asset structural integrity, crucial information companies require to make investment decisions such as fixing or replacing structures well before assets are completely compromised. ACCObeam provides requisite penetration and high-resolution acoustic imaging with applications in borehole imaging, explosives threat evaluation, and structural health evaluation. This technology will potentially save companies significant money by producing accurate and useful visual analyses to better understand the actual condition of assets in the field and respond accordingly. Los Alamos is searching for a collaboration partner to develop this technology for commercial applications that will lead to licensing opportunities for broad industry deployment.

36 MATERIALS SCIENCE↗

Aquifer Injection Modeling (AIM) Toolbox User Guide

The Aquifer Injection Modeling Toolbox (“AIM Toolbox”) software was developed by the Pacific Northwest National Laboratory (PNNL) for the U.S. Environmental Protection Agency’s (EPA) to provide a collection of analytical solutions suitable for evaluating the potential extent of the area impacted by subsurface injection operations. Subsurface injection operations are regulated under the EPA’s Underground Injection Control (UIC) program and are typically related to oil/gas development, waste disposal, or subsurface mining or storage. The analytical algorithms provided in the AIM Toolbox each have different approaches/assumptions/focus with respect to the nature and processes in subsurface and the nature of the injection operations. Collectively the set of analysis algorithms provides a broader evaluation of the area that can potentially be impacted by an injection operation. By providing estimates for the injectate plume extent, the software supports technical aspects of planning, evaluation, and overseeing injection activities. That is, the results help assess when further regulatory controls (e.g., monitoring, reporting) may be required and, in the case of disposal into an underground source of drinking water, the extent of the impacted area would require exemption from protection under the Safe Drinking Water Act. The AIM Toolbox software is available as a single-page web application, providing an interface to provide the necessary inputs, and both chart and map panes for visualizing the results. This User Guide describes the AIM Toolbox software, information required, user interactions, and the underlying basis of the calculations.

58 GEOSCIENCES↗

Aquifer Injection Modeling (AIM) Toolbox User Guide

The Aquifer Injection Modeling Toolbox (“AIM Toolbox”) software was developed by the Pacific Northwest National Laboratory (PNNL) for the U.S. Environmental Protection Agency’s (EPA) to provide a collection of analytical solutions suitable for evaluating the potential extent of the area impacted by subsurface injection operations. Subsurface injection operations are regulated under the EPA’s Underground Injection Control (UIC) program and are typically related to oil/gas development, waste disposal, or subsurface mining or storage. The analytical algorithms provided in the AIM Toolbox each have different approaches/assumptions/focus with respect to the nature and processes in subsurface and the nature of the injection operations. Collectively the set of analysis algorithms provides a broader evaluation of the area that can potentially be impacted by an injection operation. By providing estimates for the injectate plume extent, the software supports technical aspects of planning, evaluation, and overseeing injection activities. That is, the results help assess when further regulatory controls (e.g., monitoring, reporting) may be required and, in the case of disposal into an underground source of drinking water, the extent of the impacted area would require exemption from protection under the Safe Drinking Water Act. The AIM Toolbox software is available as a single-page web application, providing an interface to provide the necessary inputs, and both chart and map panes for visualizing the results. This User Guide describes the AIM Toolbox software, information required, user interactions, and the underlying basis of the calculations.

54 ENVIRONMENTAL SCIENCES↗

Direct Visualization and Manipulation of Tunable Quantum Well State in Semiconducting Nb 2 SiTe 4

We report quantum well states (QWSs) can form at the surface or interfaces of materials with confinement potential. They have broad applications in electronic and optical devices such as high mobility electron transistor, photodetector, and quantum well laser. The properties of the QWSs are usually the key factors for the performance of the devices. However, direct visualization and manipulation of such states are, in general, challenging. In this work, by using angle-resolved photoemission spectroscopy (ARPES) and scanning tunneling microscopy/spectroscopy (STM/STS), we directly probe the QWSs generated on the vacuum interface of a narrow band gap semiconductor Nb 2 SiTe 4 . Interestingly, the position and splitting of QWSs could be easily manipulated via potassium (K) dosage onto the sample surface. Our results suggest Nb 2 SiTe 4 to be an intriguing semiconductor system to study and engineer the QWSs, which has great potential in device applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A review of smart building sensing system for better indoor environment control

Here this paper aims to provide a systemic review of how indoor sensors influence in managing optimal energy saving, thermal comfort, visual comfort, and indoor air quality in the built environment. The optimal management of energy saving and occupant comfort plays a vital role in the built environment because the occupant's productivity and health are highly influenced by indoor environmental quality. In order to do this, there must be a functional sensing system that connects the environment variables (e.g., temperature) with building environmental control systems such as the heating, ventilation, and air-conditioning system. This paper starts with an overview of the importance of energy saving and occupant comfort in the built environment. It then discusses sensors and their importance in the built environment and reviews the different types of sensors, which explains them in terms of how they influence the indoor built environment and occupant productivity. The paper further explores the application of sensors in the built environment and analyzes this in terms of energy saving, thermal comfort, visual comfort, and indoor air quality. Following this, the data analysis is discussed in terms of data, information, and knowledge accrued from the sensors. Lastly, the paper discusses the future challenges for the improvement of building indoor environmental quality and energy saving by the application of sensors.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Visualization of Plasmonic Couplings Using Ultrafast Electron Microscopy

Hybrids of graphene and metal plasmonic nanostructures are promising building blocks for applications in optoelectronics, surface-enhanced scattering, biosensing, and quantum information. An understanding of the coupling mechanism in these hybrid systems is of vital importance to its applications. Previous efforts in this field mainly focused on spectroscopic studies of strong coupling within the hybrids with no spatial resolution. In this study, we report direct imaging of the local plasmonic coupling between single Au nanocapsules and graphene step edges at the nanometer scale by photon-induced near-field electron microscopy in an ultrafast electron microscope for the first time. The proximity of a step in the graphene to the nanocapsule causes asymmetric surface charge density at the ends of the nanocapsules. Computational electromagnetic simulations confirm the experimental observations. The results reported here indicate that this hybrid system could be used to manipulate the localized electromagnetic field on the nanoscale, enabling promising future plasmonic devices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Perspective: Fundamentals of coalescence-related dislocations, applied to selective-area growth and other epitaxial films

Although selective area growth (SAG) and coalesced SAG (cSAG) have been utilized extensively for many years to moderate the material quality of lattice-mismatched films, the geometrical factors controlling dislocations in coalesced films are difficult to visualize, and some confusion regarding the topology of dislocations for cSAG still persists. In this paper, we describe the topology of dislocations during island coalescence for cSAG, framed in terms of fundamental dislocation properties and virtual dislocations, which are used as a helpful visualization tool. In conclusion, we also show how the results and methods are generally applicable to coalescence of any other epitaxial film.

36 MATERIALS SCIENCE↗

Advances in Nb 3 Sn superconducting radiofrequency cavities towards first practical accelerator applications

Abstract Nb 3 Sn is a promising next-generation material for superconducting radiofrequency cavities, with significant potential for both large scale and compact accelerator applications. However, so far, Nb 3 Sn cavities have been limited to continuous wave accelerating fields <18 MV m −1 . In this paper, new results are presented with significantly higher fields, as high as 24 MV m −1 in single cell cavities. Results are also presented from the first ever Nb 3 Sn-coated 1.3 GHz 9-cell cavity, a full-scale demonstration on the cavity type used in production for the European XFEL and LCLS-II. Results are presented together with heat dissipation curves to emphasize the potential for industrial accelerator applications using cryocooler-based cooling systems. The cavities studied have an atypical shiny visual appearance, and microscopy studies of witness samples reveal significantly reduced surface roughness and smaller film thickness compared to typical Nb 3 Sn films for superconducting cavities. Possible mechanisms for increased maximum field are discussed as well as implications for physics of RF superconductivity in the low coherence length regime. Outlook for continued development is presented.

43 PARTICLE ACCELERATORS↗