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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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Intelligent Metasurfaces with Continuously Tunable Local Surface Impedance for Multiple Reconfigurable Functions

Electromagnetic metasurfaces can be characterized as intelligent if they are able to perform multiple tunable functions, with the desired response being controlled by a computer influencing the individual electromagnetic properties of each metasurface inclusion. Here, we present an example of an intelligent metasurface that operates in the reflection mode in the microwave frequency range. We numerically show that, without changing the main body of the metasurface, we can achieve tunable perfect absorption and tunable anomalous reflection. The tunability features can be implemented using mixed-signal integrated circuits (ICs), which can independently vary both the resistance and reactance, offering complete local control over the complex surface impedance. The ICs are embedded in the unit cells by connecting two metal patches over a thin grounded substrate and the reflection property of the intelligent metasurface can be readily controlled by a computer. Our intelligent metasurface can have a critical influence on future space-time modulated metasurfaces and a multitude of applications, such as beam steering, energy harvesting, and communications.

42 ENGINEERING↗
DOE OSTI2022

Ab initio coupled-cluster calculations of ground and dipole excited states in He 8

We perform coupled-cluster calculations of ground- and dipole excited-state properties of the 8 He halo nucleus with nucleon-nucleon and three-nucleon interactions from chiral effective field theory, both with and without explicit delta degrees of freedom. By increasing the precision in our coupled-cluster calculations via the inclusion of leading-order three-particle three-hole excitations in the cluster operator, we obtain a ground-state energy and a charge radius that are consistent with experiment, albeit with a slight underbinding. We also investigate the excited states induced by the electric dipole operator and present a discussion on the Thomas-Reiche-Kuhn and cluster sum rules. Lastly, we compute the electric dipole polarizability, providing a theoretical benchmark for future experimental determinations that will study this exotic nucleus.

6 ≤ A ≤ 19↗
DOE OSTI2014

A set of 4D pediatric XCAT reference phantoms for multimodality research

Purpose: The authors previously developed an adult population of 4D extended cardiac-torso (XCAT) phantoms for multimodality imaging research. In this work, the authors develop a reference set of 4D pediatric XCAT phantoms consisting of male and female anatomies at ages of newborn, 1, 5, 10, and 15 years. These models will serve as the foundation from which the authors will create a vast population of pediatric phantoms for optimizing pediatric CT imaging protocols. Methods: Each phantom was based on a unique set of CT data from a normal patient obtained from the Duke University database. The datasets were selected to best match the reference values for height and weight for the different ages and genders according to ICRP Publication 89. The major organs and structures were segmented from the CT data and used to create an initial pediatric model defined using nonuniform rational B-spline surfaces. The CT data covered the entire torso and part of the head. To complete the body, the authors manually added on the top of the head and the arms and legs using scaled versions of the XCAT adult models or additional models created from cadaver data. A multichannel large deformation diffeomorphic metric mapping algorithm was then used to calculate the transform from a template XCAT phantom (male or female 50th percentile adult) to the target pediatric model. The transform was applied to the template XCAT to fill in any unsegmented structures within the target phantom and to implement the 4D cardiac and respiratory models in the new anatomy. The masses of the organs in each phantom were matched to the reference values given in ICRP Publication 89. The new reference models were checked for anatomical accuracy via visual inspection. Results: The authors created a set of ten pediatric reference phantoms that have the same level of detail and functionality as the original XCAT phantom adults. Each consists of thousands of anatomical structures and includes parameterized models for the cardiac and respiratory motions. Based on patient data, the phantoms capture the anatomic variations of childhood, such as the development of bone in the skull, pelvis, and long bones, and the growth of the vertebrae and organs. The phantoms can be combined with existing simulation packages to generate realistic pediatric imaging data from different modalities. Conclusions: The development of patient-derived pediatric computational phantoms is useful in providing variable anatomies for simulation. Future work will expand this ten-phantom base to a host of pediatric phantoms representative of the public at large. This can provide a means to evaluate and improve pediatric imaging devices and to optimize CT protocols in terms of image quality and radiation dose.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2014

SU-E-I-45: Reconstruction of CT Images From Sparsely-Sampled Data Using the Logarithmic Barrier Method

Purpose: To develop and investigate whether the logarithmic barrier (LB) method can result in high-quality reconstructed CT images using sparsely-sampled noisy projection data Methods: The objective function is typically formulated as the sum of the total variation (TV) and a data fidelity (DF) term with a parameter λ that governs the relative weight between them. Finding the optimized value of λ is a critical step for this approach to give satisfactory results. The proposed LB method avoid using λ by constructing the objective function as the sum of the TV and a log function whose augment is the DF term. Newton's method was used to solve the optimization problem. The algorithm was coded in MatLab2013b. Both Shepp-Logan phantom and a patient lung CT image were used for demonstration of the algorithm. Measured data were simulated by calculating the projection data using radon transform. A Poisson noise model was used to account for the simulated detector noise. The iteration stopped when the difference of the current TV and the previous one was less than 1%. Results: Shepp-Logan phantom reconstruction study shows that filtered back-projection (FBP) gives high streak artifacts for 30 and 40 projections. Although visually the streak artifacts are less pronounced for 64 and 90 projections in FBP, the 1D pixel profiles indicate that FBP gives noisier reconstructed pixel values than LB does. A lung image reconstruction is presented. It shows that use of 64 projections gives satisfactory reconstructed image quality with regard to noise suppression and sharp edge preservation. Conclusion: This study demonstrates that the logarithmic barrier method can be used to reconstruct CT images from sparsely-amped data. The number of projections around 64 gives a balance between the over-smoothing of the sharp demarcation and noise suppression. Future study may extend to CBCT reconstruction and improvement on computation speed.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Spatial intratumoral heterogeneity of proliferation in immunohistochemical images of solid tumors

Purpose: The interactions of neoplastic cells with each other and the microenvironment are complex. To understand intratumoral heterogeneity, subtle differences should be quantified. Main factors contributing to heterogeneity include the gradient ischemic level within neoplasms, action of microenvironment, mechanisms of intercellular transfer of genetic information, and differential mechanisms of modifications of genetic material/proteins. This may reflect on the expression of biomarkers in the context of prognosis/stratification. Hence, a rigorous approach for assessing the spatial intratumoral heterogeneity of histological biomarker expression with accuracy and reproducibility is required, since patterns in immunohistochemical images can be challenging to identify and describe. Methods: A quantitative method that is useful for characterizing complex irregular structures is lacunarity; it is a multiscale technique that exhaustively samples the image, while the decay of its index as a function of window size follows characteristic patterns for different spatial arrangements. In histological images, lacunarity provides a useful measure for the spatial organization of a biomarker when a sampling scheme is employed and relevant features are computed. The proposed approach quantifies the segmented proliferative cells and not the textural content of the histological slide, thus providing a more realistic measure of heterogeneity within the sample space of the tumor region. The aim is to investigate in whole sections of primary pancreatic neuroendocrine neoplasms (pNENs), using whole-slide imaging and image analysis, the spatial intratumoral heterogeneity of Ki-67 immunostains. Unsupervised learning is employed to verify that the approach can partition the tissue sections according to distributional heterogeneity. Results: The architectural complexity of histological images has shown that single measurements are often insufficient. Inhomogeneity of distribution depends not only on percentage content of proliferation phase but also on how the phase fills the space. Lacunarity curves demonstrate variations in the sampled image sections. Since the spatial distribution of proliferation in each case is different, the width of the curves changes too. Image sections that have smaller numerical variations in the computed features correspond to neoplasms with spatially homogeneous proliferation, while larger variations correspond to cases where proliferation shows various degrees of clumping. Grade 1 (uniform/nonuniform: 74%/26%) and grade 3 (uniform: 100%) pNENs demonstrate a more homogeneous proliferation with grade 1 neoplasms being more variant, while grade 2 tumor regions render a more diverse landscape (50%/50%). Hence, some cases show an increased degree of spatial heterogeneity comparing to others with similar grade. Whether this is a sign of different tumor biology and an association with a more benign/malignant clinical course needs to be investigated further. The extent and range of spatial heterogeneity has the potential to be evaluated as a prognostic marker. Conclusions: The association with tumor grade as well as the rationale that the methodology reflects true tumor architecture supports the technical soundness of the method. This reflects a general approach which is relevant to other solid tumors and biomarkers. Drawing upon the merits of computational biomedicine, the approach uncovers salient features for use in future studies of clinical relevance.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Unprecedented cloud resolution in a GPU-enabled full-physics atmospheric climate simulation on OLCF’s summit supercomputer

Clouds represent a key uncertainty in future climate projection. While explicit cloud resolution remains beyond our computational grasp for global climate, we can incorporate important cloud effects through a computational middle ground called the Multi-scale Modeling Framework (MMF), also known as Super Parameterization. This algorithmic approach embeds high-resolution Cloud Resolving Models (CRMs) to represent moist convective processes within each grid column in a Global Climate Model (GCM). The MMF code requires no parallel data transfers and provides a self-contained target for acceleration. This study investigates the performance of the Energy Exascale Earth System Model-MMF (E3SM-MMF) code on the OLCF Summit supercomputer at an unprecedented scale of simulation. Hundreds of kernels in the roughly 10K lines of code in the E3SM-MMF CRM were ported to GPUs with OpenACC directives. A high-resolution benchmark using 4600 nodes on Summit demonstrates the computational capability of the GPU-enabled E3SM-MMF code in a full physics climate simulation.

58 GEOSCIENCES↗
DOE OSTI2026

ORCHA: A performance portability system for extreme heterogeneity

Heterogeneity is the prevalent trend in the rapidly evolving high-performance computing (HPC) landscape in both hardware and application software. The diversity in hardware platforms, currently comprising various accelerators and a future possibility of specializable chiplets, poses a significant challenge for scientific software developers aiming to harness optimal performance across different computing platforms while maintaining the quality of solutions when their applications are simultaneously growing more complex. Code synthesis and code generation can provide mechanisms to mitigate this challenge. We have developed a divide and conquer approach where different aspects of performance are handled by different stand-alone tools that are interfaced with the application through generated code. This portability system, ORCHA, enables users to configure and orchestrate their computations among available resources on a platform by specifying a high-level recipe, thereby permitting a many-to-many paradigm where each recipe results in a different variant of the application. The core design goal is to let users decide the application’s hardware mapping and orchestration by editing only the high-level recipe—without modifying the maintained source code or binding the application to a particular runtime system. Tools in ORCHA distribution are: CG-Kit for translating the recipe into an execution graph; Milhoja to execute the graph by orchestrating data and task movement among hardware resources; and Macroprocessor that enables users to define their own code-shorthand for higher composability and easier management of code variants. Additionally, the design of ORCHA permits tools to work in a plug-and-play mode where the application can build and run without CG-Kit and Milhoja, and either tool can be swapped out for other tools with similar capabilities by modifying the code generation portion of ORCHA. In this paper, we describe the design of ORCHA and the role that code-generation plays in isolating applications from tools. We demonstrate the breadth of configurations ORCHA enables with a case study in which an application configuration is realized on three distinct hardware mappings—a GPU-centric, a CPU/GPU balanced, and a CPU/GPU concurrent layouts by using different recipes.

Lee, Youngjun↗
DOE OSTI2019

Edge and Scrape-off-Layer Physics for NSTX-U (Final Report)

U.S. Department of Energy (DOE) supported work at Lodestar Research Corporation under grant DE-FG02-02ER54678 is summarized in this final report. The research conducted under this grant addressed key scientific issues associated with the plasma confinement and fusion energy experimental devices NSTX and its upgrade NSTX-U located at Princeton Plasma Physics Laboratory. Harnessing the energy that is released in fusion reactions would provide a safe and abundant source of power to meet the growing energy needs of the world population. Lodestar investigated the important cm-scale region near the edge of these devices where hot plasma, close to one million degrees, meets material surfaces in what is known as a scrape-off layer (SOL). This critical region is subject to plasma turbulence and plasma flows which must be understood to optimize fusion performance on future machines. The work employed theoretical and theory-based computational models for validation and applied the models to understand experimental results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Rotating Detonation Combustion for Gas Turbines: Modeling and System Synthesis to Exceed 65% Efficiency Goal (Phase II)

As of May 2019, all RDE test hardware and test operations were completed for this program. Over 700 hot fire tests were conducted at 4 facilities with 7 RDE assemblies, with the data available for future analysis. In particular, measured static and dynamic pressure and computational fluid dynamics (CFD) provided basis for pressure gain combustion (PGC) analysis of the Engineering Scale RDE. It was demonstrated via measurements and CFD that a carefully designed diffuser can recover some total pressure of the highly oscillatory RDE exhaust. In general, the isolator/injector is largest contributor of pressure losses; however a low loss design was demonstrated that improves significantly on previous natural-gas/air RDEs. Also, a tailored injector and mixing technique was demonstrated that allowed NG-air RDE operation with overall equivalence ratio of less than 0.6. CFD models by AR, the UofM and Purdue University were extensively used throughout the program to refine diffuser design for improved pressure recovery, to simulate injection and mixing, to estimate turbine interaction, to estimate combustor pressure gain anchored with test data and to provide input to other design and analytical tasks. CFD analyses were completed for many of the configurations tested at Purdue with the 13.4” RDE including the shark fin and low area ratio isolators. Results were compared favorably to available hot fire test particle image velocimetry (PIV) measurements and wave speeds. The results of these CFD analyses suggest a modest pressure gain of 33% with a sufficiently low area ratio isolator. A thermodynamic power plant system model was set up which utilizes an RDE combustor. The performance of the RDE combustor module was scaled based on measurements from the Engineering Scale RDE tests with low loss injector and tailored fuel flow. This combined model indicates potential for significant plant efficiency improvement. The successful tailored fuel injection test result with lower than .6 equivalence ratio has implication that a power plant can use a RDE combustor configuration where all the air flows through the combustion zone thereby not requiring a bypass mixer. In this configuration, the results of the natural gas combined cycle (NGCC) plant system indicate net efficiency of 66.4%.

02 PETROLEUM↗
DOE OSTI2021

The Steel Equivalency Workbook: An X-Ray Transmission Calculator

The Steel Equivalency Spreadsheet was created as a robust, user-friendly method for the following: 1. Determining if it is possible to image an object. 2. Reducing time needed when selecting equipment and preparing for field imaging activities. 3. Reducing the amount of equipment taken for field imaging activities. 4. Determining a starting point for exposure settings prior to imaging an object. 5. Reducing the amount of dose deposited to complete an imaging operation (in the spirit of As Low As Reasonably Achievable, ALARA). The spreadsheet was developed using various physical models to account for different phenomena. Future implementations aim to expand beyond the Digital Radiography and Computed Tomography Single Munition Scanner (DRCT SMS) in standard configuration to include high energy XRGs (Betatrons) and sub-MeV pulsed XRGs (XRS4). Alternative computational methods that compensate for incoherent scattering when calculating relative transmission are also being pursued. Ultimately the spreadsheet exceeded the developmental goal of having less than 10% average error when comparing calculations to real-world images.

36 MATERIALS SCIENCE↗
DOE OSTI2024

From Chaos to Clarity: Autonomous Materials Discovery for Extreme Environments [Slides]

The pursuit of advanced functional materials for energy applications demands an understanding of their behavior under the most challenging conditions. Extreme environments, characterized by intense radiation, high temperatures, and corrosive chemistries, push materials to their limits, often revealing unexpected behaviors and degradation pathways. Traditional materials research approaches, relying on trial-and-error experimentation, are often slow and resource-intensive, ill-suited to the complexities of extreme environments. This talk will explore the transformative potential of autonomous materials science in revolutionizing our understanding of materials synthesis and degradation in extreme environments. By integrating advanced microscopy techniques, artificial intelligence, and robotic experimentation, we can accelerate the discovery and design of resilient materials for a sustainable future. The presentation will highlight recent breakthroughs in autonomous microscopy, computer vision, and machine learning, showcasing their ability to unravel complex material transformations at the atomic scale. The talk will also delve into the challenges and opportunities associated with deploying autonomous systems to probe extreme environments, emphasizing the importance of robust algorithms, real-time data analysis, and adaptive experimentation. The ultimate goal is to empower scientists with unprecedented capabilities to explore, understand, and engineer materials that can withstand the harshest conditions, paving the way for innovations in energy, aerospace, and beyond.

14 SOLAR ENERGY↗
DOE OSTI2026

Co-Simulation Meets AI: MCP-Driven Power System Analysis

GridGPT, a fine-tuned Generative AI model is designed for on-premise use in grid control rooms. This presentation will demonstrate how eGridGPT can seamlessly integrate with control room solutions to offer operators, engineers, and corporate users enhanced guidance and decision support. It is to show how this innovative AI solution can improve state estimation, boost variable energy forecasting, and optimize grid operations. By leveraging eGridGPT's unique features, audience will learn to unlock new levels of automation, predictive analytics, and reliability within their power systems, ultimately leading to reduced downtime and improved operational efficiency.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Predictor-corrector models for lightweight massive machine-type communications in Industry 4.0

Future Industry 4.0 scenarios are characterized by seamless integration between computational and physical processes. To achieve this objective, dense platforms made of small sensing nodes and other resource constraint devices are ubiquitously deployed. All these devices have a limited number of computational resources, just enough to perform the simple operation they are in charge of. The remaining operations are delegated to powerful gateways that manage sensing nodes, but resources are never unlimited, and as more and more devices are deployed on Industry 4.0 platforms, gateways present more problems to handle massive machine-type communications. Although the problems are diverse, those related to security are especially critical. To enable sensing nodes to establish secure communications, several semiconductor companies are currently promoting a new generation of devices based on Physical Unclonable Functions, whose usage grows every year in many real industrial scenarios. Those hardware devices do not consume any computational resource but force the gateway to keep large key-value catalogues for each individual node. In this context, memory usage is not scalable and processing delays increase exponentially with each new node on the platform. In this paper, we address this challenge through predictor-corrector models, representing the key-value catalogues. Models are mathematically complex, but we argue that they consume less computational resources than current approaches. The lightweight models are based on complex functions managed as Laurent series, cubic spline interpolations, and Boolean functions also developed as series. Unknown parameters in these models are predicted, and eventually corrected to calculate the output value for each given key. The initial parameters are based on the Kane Yee formula. An experimental analysis and a performance evaluation are provided in the experimental section, showing that the proposed approach causes a significant reduction in the resource consumption.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

microTrait: A Toolset for a Trait-Based Representation of Microbial Genomes

Remote sensing approaches have revolutionized the study of macroorganisms, allowing theories of population and community ecology to be tested across increasingly larger scales without much compromise in resolution of biological complexity. In microbial ecology, our remote window into the ecology of microorganisms is through the lens of genome sequencing. For microbial organisms, recent evidence from genomes recovered from metagenomic samples corroborate a highly complex view of their metabolic diversity and other associated traits which map into high physiological complexity. Regardless, during the first decades of this omics era, microbial ecological research has primarily focused on taxa and functional genes as ecological units, favoring breadth of coverage over resolution of biological complexity manifested as physiological diversity. Recently, the rate at which provisional draft genomes are generated has increased substantially, giving new insights into ecological processes and interactions. From a genotype perspective, the wide availability of genome-centric data requires new data synthesis approaches that place organismal genomes center stage in the study of environmental roles and functional performance. Extraction of ecologically relevant traits from microbial genomes will be essential to the future of microbial ecological research. Here, we present microTrait , a computational pipeline that infers and distills ecologically relevant traits from microbial genome sequences. microTrait maps a genome sequence into a trait space, including discrete and continuous traits, as well as simple and composite. Traits are inferred from genes and pathways representing energetic, resource acquisition, and stress tolerance mechanisms, while genome-wide signatures are used to infer composite, or life history, traits of microorganisms. This approach is extensible to any microbial habitat, although we provide initial examples of this approach with reference to soil microbiomes.

Karaoz, Ulas↗
DOE OSTI2012

Fukushima Daiichi Unit 3 MELCOR Investigation

The Department of Energy sponsored a Fukushima Daiichi accident study as a collaboration between Sandia, Oak Ridge (ORNL), and Idaho National Laboratories. The purpose of the effort was to compile relevant data, reconstruct the accident progression using computer codes, assess the codes predictive capabilities, and to identify future data needs. The following summarizes MELCOR simulations performed at ORNL on Fukushima Daiichi Unit 3.

Fukushima Daiichi Unit 3↗
DOE OSTI2022

Materials and devices for fundamental quantum science and quantum technologies

Technologies operating on the basis of quantum mechanical laws and resources such as phase coherence and entanglement are expected to revolutionize our future. Quantum technologies are often divided into four main pillars: computing, simulation, communication, and sensing & metrology. Moreover, a great deal of interest is currently also nucleating around energy-related quantum technologies. In this Perspective, we focus on advanced superconducting materials, van der Waals materials, and moiré quantum matter, summarizing recent exciting developments and highlighting a wealth of potential applications, ranging from high-energy experimental and theoretical physics to quantum materials science and energy storage.

Polini, Marco↗
DOE OSTI2024

NEA HTTR LOFC Project Test#3 Benchmark Results

In the second half of FY23, the High Temperature Engineering Test Reactor (HTTR) Loss Of Forced Cooling (LOFC)#3 data for the 9 MW test case with Vessel Cooling System (VCS) off were made available through the Nuclear Energy Agency (NEA) LOFC project framework; the neutronic model developed for the initial test (LOFC#1) achieved a satisfactory level of maturity, demonstrating its accuracy in predicting power evolution and core re-criticality, but LOFC#3 should be used primarily to investigate thermal hydraulic phenomena, as the reactor was shut down prematurely due to overheating in the upper reactor components, which prevented re-criticality; this report focuses on advancing the HTTR thermal hydraulic model to accurately simulate the LOFC#3 scenario, including simulating the LOFC#3 benchmark and generating the corresponding benchmark specifications, aiming to ensure consistency across participant models and provide essential data for future participants, including private industry stakeholders seeking to validate their computational tools.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗