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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 1,495 records · Page 83

IPACS (Integrated Probabilistic Assessment of Composite Structures): Code development and applications

A methodology and attendant computer code have been developed and are described to computationally simulate the uncertain behavior of composite structures. The uncertain behavior includes buckling loads, stress concentration factors, displacements, stress/strain etc., which are the consequences of the inherent uncertainties (scatter) in the primitive (independent random) variables (constituent, ply, laminate and structural) that describe the composite structures. The computer code, IPACS (Integrated Probabilistic Assessment of Composite Structures), can handle both composite mechanics and composite structures. Application to probabilistic composite mechanics is illustrated by its uses to evaluate the uncertainties in the major Poisson's ratio and in laminate stiffness and strength. IPACS application to probabilistic structural analysis is illustrated by its use to evaluate the uncertainties in the buckling of a composite plate, in the stress concentration factor in a composite panel and in the vertical displacement and ply stress in a composite aircraft wing segment.

Chamis, C. C.↗

Nano-array integrated monolithic devices: toward rational materials design and multi-functional performance by scalable nanostructures assembly

We report the scalable three-dimensional (3-D) integration of functional nanostructures into applicable platforms represents a promising technology to meet the ever-increasing demands of fabricating high performance devices featuring cost-effectiveness, structural sophistication and multi-functional enabling. Such an integration process generally involves a diverse array of nanostructural entities (nano-entities) consisting of dissimilar nanoscale building blocks such as nanoparticles, nanowires, and nanofilms made of metals, ceramics, or polymers. Various synthetic strategies and integration methods have enabled the successful assembly of both structurally and functionally tailored nano-arrays into a unique class of monolithic devices. The performance of nano-array based monolithic devices is dictated by a few important factors such as materials substrate selection, nanostructure composition and nano-architecture geometry. Therefore, the rational material selection and nano-entity manipulation during the nano-array integration process, aiming to exploit the advantageous characteristics of nanostructures and their ensembles, are critical steps towards bridging the design of nanostructure integrated monolithic devices with various practical applications. In this article, we highlight the latest research progress of the two-dimensional (2-D) and 3-D metal and metal oxide based nanostructural integrations into prototype devices applicable with ultrahigh efficiency, good robustness and improved functionality. Lastly, selective examples of nano-array integration, scalable nanomanufacturing and representative monolithic devices such as catalytic converters, sensors and batteries will be utilized as the connecting dots to display a roadmap from hierarchical nanostructural assembly to practical nanotechnology implications ranging from energy, environmental, to chemical and biotechnology areas.

36 MATERIALS SCIENCE↗

A Discrete Hankel Transform Approach to Nuclear Data Processing for Fusion Applications

This study introduces advancements to the numerical solutions employed in the processing of nuclear data for fusion applications. It leverages the convolution theorem and Fourier transform techniques to enhance computational efficiency and broaden applicability. Building upon a previously reported discrete Hankel transform approach for Doppler broadening, this work refines the solution of convolution integrals central to these applications. The methodology provides a general and unified framework for evaluating any convolution operation, regardless of whether the underlying problem involves temperature effects in nuclear reactions. The applicability to the nuclear data processing for fusion is demonstrated by deriving the convolution integrals for some of the fusion-related quantities. As before, the convolution operation utilizes a Gaussian-based kernel; however, the discrete Hankel transform of order $𝛼$ = $\frac{1}{2}$ is now applied to the forward Fourier transform of the nonkernel argument, rather than the inverse Fourier transform. This modification eliminates the need for the integration of the nonkernel, cross section–based function, which is a step that posed challenges for certain pointwise cross-section representations. It also removes the requirement for cross-section linearization. Optimized for graphics processing unit architectures, the approach significantly improves computational performance. These advancements are currently under evaluation as the foundation for the next-generation thermonuclear data file processing codes being developed at Lawrence Livermore National Laboratory.

Nuclear science and engineering↗

Antenna With Embedded Die in Glass Interposer for 6G Wireless Applications

This article presents the antenna-integrated glass interposer for D-band 6G wireless applications using dieembedding technology. Here, we implement the die-embedded package on glass substrates and characterize the electrical performance in the D-band. The electrical characterization employs embedded test dies with the 50-Ω ground–signal–ground (GSG) ports and coplanar waveguides. We achieve low-loss die-to-package transitions by using staggered dielectric vias, which are compared with the transitions of wire-bonding and flip-chip assembly. This article provides detailed information on the design, modeling, fabrication, and characterization of the die-to-package interconnects. This article also demonstrates the integration of microstrip patch antenna array and embedded dies in the D-band. The results show superior electrical performance provided by the die-embedded glass interposer. The die-to-package interconnect exhibits good matching (less than —10-dB S11) and low loss (0.2-dB loss) in the D-band. The integrated 1 × 8 patch antenna array shows 11.6-dB broadside gain and good matching with the embedded die. In addition, by using a temporary carrier, the antenna-integrated glass interposer also has great potential for further heterogeneous integration and thermal management.

42 ENGINEERING↗

Using an Advanced Distribution Management System Test Bed to Evaluate the Impact of Model Quality on Volt/VAR Optimization: Preprint

In this paper, we present a test bed for evaluating existing and future advanced distribution management system (ADMS) applications in a realistic laboratory setting, including other utility management systems and field equipment. We present an example of using it to evaluate the impact of the ADMS network model quality on a Volt/VAR optimization (VVO) application. The test bed integrates a commercial ADMS with a real-time simulation model of a utility distribution feeder. Representative power and controller hardware are integrated through hardware-in-the-loop (HIL) techniques. The performance of the ADMS VVO application is also evaluated for different levels of measurement density. Initial results indicate that a higher model quality achieves the highest possible energy savings while avoiding voltage violations, whereas a lower model quality results in increased energy savings but at the expense of more voltage violations.

ADMS↗

Automated Flight Dynamics Product Generation for the EOS AM-1 Spacecraft

As part of NASA's Earth Science Enterprise, the Earth Observing System (EOS) AM-1 spacecraft is designed to monitor long-term, global, environmental changes. Because of the complexity of the AM-1 spacecraft, the mission operations center requires more than 80 distinct flight dynamics products (reports). To create these products, the AM-1 Flight Dynamics Team (FDT) will use a combination of modified commercial software packages (e.g., Analytical Graphic's Satellite ToolKit) and NASA-developed software applications. While providing the most cost-effective solution to meeting the mission requirements, the integration of these software applications raises several operational concerns: (1) Routine product generation requires knowledge of multiple applications executing on variety of hardware platforms. (2) Generating products is a highly interactive process requiring a user to interact with each application multiple times to generate each product. (3) Routine product generation requires several hours to complete. (4) User interaction with each application introduces the potential for errors, since users are required to manually enter filenames and input parameters as well as run applications in the correct sequence. Generating products requires some level of flight dynamics expertise to determine the appropriate inputs and sequencing. To address these issues, the FDT developed an automation software tool called AutoProducts, which runs on a single hardware platform and provides all necessary coordination and communication among the various flight dynamics software applications. AutoProducts, autonomously retrieves necessary files, sequences and executes applications with correct input parameters, and deliver the final flight dynamics products to the appropriate customers. Although AutoProducts will normally generate pre-programmed sets of routine products, its graphical interface allows for easy configuration of customized and one-of-a-kind products. Additionally, AutoProducts has been designed as a mission-independent tool, and can be easily reconfigured to support other missions or incorporate new flight dynamics software packages. After the AM-1 launch, AutoProducts will run automatically at pre-determined time intervals . The AutoProducts tool reduces many of the concerns associated with the flight dynamics product generation. Although AutoProducts required a significant effort to develop because of the complexity of the interfaces involved, its use will provide significant cost savings through reduced operator time and maximum product reliability. In addition, user satisfaction is significantly improved and flight dynamics experts have more time to perform valuable analysis work. This paper will describe the evolution of the AutoProducts tool, highlighting the cost savings and customer satisfaction resulting from its development. It will also provide details about the tool including its graphical interface and operational capabilities.

Matusow, Carla↗

Low-Cost, Large C-SiC Blisk Fabrication

C-SiC composites offer unique properties for propulsion applications. However, fabrication of low-cost, thick, large scale C-SiC disk for integrally bladed disk (blisk) applications has not been established yet. MER has demonstrated a new process to address this issue. Polymer-based processing was employed for interfacial coatings, consolidation and densification. Up to 40" O.C., 2" thick C-SiC composite processing was established, yielding in excess of 1.8 g/cu cm density. Computer tomography (CT) scans on the 40" O.D., 2" thick C-SiC disk showed no visible delamination, and good density uniformity. Stress-rupture testing in air was conducted at 2200 F, 2400 F and 2550 F.

Kowbel, W.↗

Development and Integration of Predictive Models for Manufacturing and Structural Performance of Carbon Fiber Composites in Automotive Applications (Final Report)

The goal of this project is to develop integrated, state-of-the-art, computational modeling tools based on an integrated computational materials engineering (ICME) methodology that are critically needed to enable structural carbon fiber (CF) applications in automobiles. These tools are designed to predict the manufacturing and structural performance of CF composites, including stochastic effects. During the first phase of the project, the manufacturing and structural performance tools, including a stochastic driver, were developed, calibrated, and validated against coupon and component level test results. For this project, from the manufacturing side, the development efforts were focused on high-pressure resin transfer molding (HP-RTM), a potentially game-changing manufacturing technology that is capable of reaching the 3-5-minute cycle time that is necessary for volume manufacturing of composites. On the structural performance side, the crashworthiness of CF structures was studied. Accordingly, computational tools were developed and validated. The resulting differences between the numerical predictions and the experimental results in the first phase of the project were required to be less than 15%. During the second phase of the project, the manufacturing and performance tools were integrated by mapping the manufacturing outcomes (e.g., fiber angles, residual stresses, degree of cure, and defects) into the structural models. Also, using the tools developed in this project, an automotive assembly currently manufactured in steel (2016 GM Malibu) was redesigned to be manufactured using advanced CF composites with the objective of comparing the performance of the CF assembly with the developed ICME model predictions. The weight, performance and cost of the CF assembly were compared with the baseline steel assembly as well. The CF underbody design was shown to be 30% lighter than the corresponding steel design. The CF underbody assembly withstood the side pole impact with less than half the intrusion for the steel assembly. Excellent correlations within 10% for both peak impact load and intrusion were observed between the numerical predictions and experimental results. Based on the cost models developed in the project, the cost increase per Kg saved was determined to be $22. The project team has prepared a total of 28 publications in various journals and conferences and broadly communicated the project results for the benefit of the composite industry. The project team has also prepared a total of 10 patent applications that were submitted to the US Patent and Trademark office.

36 MATERIALS SCIENCE↗

Evaluation of daily gridded climate products using in situ FLUXNET data and tree growth modeling

Gridded climate data products have facilitated research in climate and ecology by providing meteorological data continuously across large spatial scales. However, the sensitivity of scientific outcomes to dataset choice remains poorly understood, and evaluation using station-based records can favor datasets built heavily on weather stations. Here, we evaluate seven high-resolution daily gridded datasets covering the contiguous United States using independent meteorology from the FLUXNET2015 dataset, with a focus on the implications of dataset choice for process-based tree growth modeling. We find that gridded products tend to capture temperature accurately while consistently overestimating the magnitude and frequency of precipitation and its extremes. Moreover, datasets vary in how they define a ‘day,’ which significantly affects temporal alignment with FLUXNET2015 observations. Despite differences among the datasets, the interannual variability in tree ring simulations is insensitive to dataset choice, likely because daily-scale biases are averaged out through accumulated growth across several months. However, inaccuracies in temperature and precipitation can significantly bias modeled xylem cell production, with systematically higher annual precipitation in the gridded datasets leading to greater xylem production compared to simulations using in situ data. Our results suggest that model applications, especially those that integrate to time scales longer than one day, are likely insensitive to climate dataset choice, but applications that are sensitive to daily climate variations or to absolute climate values need to carefully consider biases in gridded climate products.

54 ENVIRONMENTAL SCIENCES↗

Strategies for Integrating Deep Learning Surrogate Models with HPC Simulation Applications

The emerging trend of the convergence of high performance computing (HPC), machine learning/deep learning (ML/DL), and big data analytics presents a host of challenges for large-scale computing campaigns that seek best practices to interleave traditional scientific simulation-based workloads with ML/DL models. A portfolio of systematic approaches to incorporate deep learning into modeling and simulation serves a vital need when we support AI for science at a computing facility. In this paper, we evaluate several strategies for deploying deep learning surrogate models in a representative physics application on supercomputers at the Oak Ridge Leadership Computing Facility (OLCF). We discuss a set of recommended deployment architectures and implementation approaches. We analyze and evaluate these alternatives and show their performance and scalability up to 1000 GPUs on two mainstream platforms equipped with different deep learning hardware and software stacks.

Yin, Junqi↗

The Development of Reversible Bending Fatigue Tester and Its Application to High Burnup Spent Nuclear Fuel Vibration Integrity Investigation under Normal Transportation

For high burn-up spent nuclear fuel (SNF), it is expected that the spent fuel cladding will have a high population of microcracks and hydrides, including macro-hydrides and micro-hydrides. This will reduce the stress intensity required to advance the crack growth. The linking of these microcracks during vibration loading also reduces the fatigue threshold/incubation period significantly, accelerating fatigue failure. In addition to the damages in cladding, the microstructure of comprising fuel pellets and interfaces of fuel rod have changed dramatically after the high burn-up process. These modifications have a direct impact on the structural integrity and vibration response of SNF rods in transportation.

Fuel Transport↗

Development of Integrated Education, Training and Research Program with Interdisciplinary Applications

Plasma models have been formulated including realistic spatial profiles of both flow and radio frequency induced ponderomotive force. With these inclusions the picture of stability of various plasma and fluid instabilities, as expected, changed drastically with ground-breaking consequences. The inhomogeneous parallel flow and the radio frequency waves can actually shown to stabilize turbulence. This is different from the prevalent notion that both parallel flow shear and radio frequency waves are responsible for the excitation (destabilization) of plasma turbulence. This has several ground-breaking consequences:- (1) the stabilization by parallel flow clearly goes against the conventional notion of the origin of ionospheric oscillation which invokes parallel flow destabilization as the origin, (2) the stabilization by parallel flow opens us a new avenue for improved mode formation in fusion devices - which mostly rely on the perpendicular flow shear stabilization for improved mode formation but the perpendicular flow is damped in a tokamak - so the improved mode formed by the parallel flow can sustain longer and has more prospect for ignition, (3) the complete stabilization of the ITG mode (and consequent suppression of transport) not only explain many unknown phenomena in the space physics but it also raises a prospect for transport barrier formation by the RF waves but not by the RF induced flow (as most works suggest) which is never observed in a tokamak of that magnitude to create a barrier. These are indeed ground-breaking consequences.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗