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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

A cell-centered AMR-ALE framework for 3D multi-material hydrodynamics. Part II: linesweep ALE rezoning for nonconformal block-structured AMR meshes

The simulation of flows presenting contact discontinuities, vorticity, and large variations in spatial scales can be performed in a framework coupling Arbitrary Lagrangian Eulerian (ALE) algorithms and Adaptive Mesh Refinement (AMR). This coupling requires adaptation of ALE rezoning techniques to meshes containing nonconformal nodes arising from both the AMR topology and the junction of mesh blocks. Here, in this paper, we present an ALE rezoning strategy that is compatible with such meshes, and that can also act as a disentangling algorithm. Emphasis is put on an algorithm that respects intrinsic Lagrangian mesh properties in order to preserve accuracy around discontinuities. To that end, we adapt the weighted linesweep algorithm to nonconformal block-structured AMR meshes. Then, we present control parameters introduced in the method for it to be applicable in practical situations. Notably, the method is coupled to a specific metric optimization in order to palliate some shortcomings of the linesweep method. Finally, numerical test cases are presented that feature the capabilities of the ALE-AMR algorithm for flows that present discontinuities, vorticity, and a variety of scales. Notably, we show that our ALE-AMR algorithm gives results at least similar to Euler-AMR, but provides better accuracy in cases where discontinuities are involved, thanks to a method that respects the Lagrangian features of the mesh. Additionally, it enables Euler-AMR-like computations on domains with temporally varying domain boundaries.

Adaptive mesh refinement↗
DOE OSTI2023

Embedded anchoring of multi-material assemblies by friction riveting process

In this paper, we report on work that focused on extending the capability and broaden the applicability of the friction-riveting process for joining stacks composed of a wide range of multi-layer polymer-to-metals and similar and dissimilar metals. We first present direct experimental evidence of our use of this process to join aluminum-to-steel dissimilar metals with steel rivets. We have demonstrated for the first time the use of magnesium as a rivet material for joining carbon fiber reinforced polymer (CFRP) stacks, aluminum as a rivet material to laminate magnesium to CFRP, and aluminum-to-aluminum similar metal joining and aluminum-to-steel dissimilar metal joining with steel rivets. Our work sheds light on detailed process parameter optimization and the corresponding process response behavior, thus advancing our understanding of this complex joining method for a wide range of material combinations.

Friction-riveting, magnesium rivet, carbon fiber r↗
DOE OSTI2025

Scale-Up of Friction Self-piercing Riveting Process for Multi-material Joints

A single-class joining process known as “friction self-piercing riveting (F-SPR)” has been developed for joining various low-ductility lightweight materials on a laboratory scale. The frictional heat generated during the F-SPR process improved local ductility, resulting in crack-free joints and robust mechanical performance. This innovative joining technology was further advanced through the scale-up of the process using a new system with several key features (e.g., automatic rivet feeding and clamping system, vacuum system) toward industry readiness. The new integrated F-SPR systems were effectively demonstrated for joining different material combinations (e.g., carbon fiber composite to 7075 Al alloy, 7075 Al alloy to 7075 Al alloy, and 7075 Al alloy to casting Al Aural 5) with a unified technique. Crack-free joint with adequate mechanical interlocking resulted in good mechanical joint strength for each material combination. Then, the process was successfully scaled up by producing multiple joints without any cracks on larger CFC-Al and Al-Al components by the new integrated system, bringing it closer to industrial application.

Lim, Yong Chae [ORNL] (ORCID:0000000321773988)↗
DOE OSTI2022

A multi-material platform for imaging of single cell-cell junctions under tensile load fabricated with two-photon polymerization

We previously reported a single-cell adhesion micro tensile tester (SCAμTT) fabricated from IP-S photoresin with two-photon polymerization (TPP) for investigating the mechanics of a single cell-cell junction under defined tensile loading. A major limitation of the platform is the autofluorescence of IP-S, the photoresin for TPP fabrication, which significantly increases background signal and makes fluorescent imaging of stretched cells difficult. In this study, we report the design and fabrication of a new SCAμTT platform that mitigates autofluorescence and demonstrate its capability in imaging a single cell pair as its mutual junction is stretched. By employing a two-material design using IP-S and IP-Visio, a photoresin with reduced autofluorescence, we show a significant reduction in autofluorescence of the platform. Further, by integrating apertures onto the substrate with a gold coating, the influence of autofluorescence on imaging is almost completely mitigated. With this new platform, we demonstrate the ability to image a pair of epithelial cells as they are stretched up to 250% strain, allowing us to observe junction rupture and F-actin retraction while simultaneously recording the accumulation of over 800 kPa of stress in the junction. In conclusion, the platform and methodology presented here can potentially enable detailed investigation of the mechanics of and mechanotransduction in cell-cell junctions and improve the design of other TPP platforms in mechanobiology applications.

Autofluorescence↗
DOE OSTI2024

A machine-learning-aided data recovery approach for predicting multi-material thermal behaviors in advanced test reactor capsules

Instrumented experiments conducted at test reactors are essential to the deployment of new advanced reactor systems. Designing new experiments and generating data on specific reactor conditions require significant investments in terms of both time and cost. Finite element analysis software can be used to create high-fidelity models of experiment environments in order to support the actual experiments, but computation time remains a concern in terms of applying outcomes to real-time usage of data (e.g., a digital twin [DT]). Here, the present research proposes a machine-learning (ML) aided approach to making temperature and displacement predictions based on the thickness of the outer gas gap on the experimental capsule used for in-pile demonstration of a novel new thermal conductivity probe in the Advanced Test Reactor (ATR). This capsule consisted of U10Zr fuel, a rodlet, sodium, and inner and outer capsules. Gas gaps existed between the fuel and the rodlet, and between the inner and the outer capsule. The learning data pertained to an experimental capsule's radial distributions of temperature and displacement, as obtained based on Abaqus and the physical features. For the first step of ML sequence, the temperature was predicted using three positional parameters. Next, the displacement was predicted using seven additional parameters. Each physical feature was normalized in order to be both nondimensional and standardized. The temperature and displacement predictions showed good agreement with the simulation results in all cases involving interpolation and extrapolation. Furthermore, data similarity enhancement increased the similarity between the training and the target data, thereby increasing the predictive accuracy of the ML models. In certain extrapolation cases involving limited original ML model accuracy, data similarity enhancement and data recovery was able to somewhat improve this accuracy.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Optical emissivity dataset of multi-material heterogeneous designs generated with automated figure extraction

Optical device design is typically an iterative optimization process based on a good initial guess from prior reports. Optical properties databases are useful in this process but difficult to compile because their parsing requires finding relevant papers and manually converting graphical emissivity curves to data tables. Here, we present two contributions: one is a dataset of thermal emissivity records with design-related parameters, and the other is a software tool for automated colored curve data extraction from scientific plots. We manually collected 64 papers with 176 figures reporting thermal emissivity and automatically retrieved 153 colored curve data records. The automated figure analysis software pipeline uses Faster R-CNN for axes and legend object detection, EasyOCR for axes numbering recognition, and k-means clustering for colored curve retrieval. Additionally, we manually extracted geometry, materials, and method information from the text to add necessary metadata to each emissivity curve. Finally, we analyzed the dataset to determine the dominant classes of emissivity curves and determine the underlying design parameters leading to a type of emissivity profile.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Three-dimensional visualization of nanoparticle lattices and multi-material frameworks

We report advances in nanoscale self-assembly have enabled the formation of complex nanoscale architectures. However, the development of self-assembly strategies toward bottom-up nanofabrication is impeded by challenges in revealing these structures volumetrically at the single-component level and with elemental sensitivity. Leveraging advances in nano-focused hard x-rays, DNA-programmable nanoparticle assembly, and nanoscale inorganic templating, we demonstrate nondestructive three-dimensional imaging of complexly organized nanoparticles and multimaterial frameworks. In a three-dimensional lattice with a size of 2 micrometers, we determined the positions of about 10,000 individual nanoparticles with 7-nanometer resolution, and identified arrangements of assembly motifs and a resulting multimaterial framework with elemental sensitivity. The real-space reconstruction permits direct three-dimensional imaging of lattices, which reveals their imperfections and interfaces and also clarifies the relationship between lattices and assembly motifs.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Stealthy Cyber Anomaly Detection On Large Noisy Multi-material 3D Printer Datasets Using Probabilistic Models

As Additive Layer Manufacturing (ALM) becomes pervasive in industry, its applications in safety critical component manufacturing are being explored and adopted. However, ALM's reliance on embedded computing renders it vulnerable to tampering through cyber-attacks. Sensor instrumentation of ALM devices allows for rigorous process and security monitoring, but also results in a massive volume of noisy data for each run. As such, in-situ, near-real-time anomaly detection is very challenging. The ideal algorithm for this context is simple, computationally efficient, minimizes false positives, and is accurate enough to resolve small deviations. In this paper, we present a probabilistic-model-based approach to address this challenge. To test our approach, we analyze current measurements from a polymer composite 3D printer during emulated tampering attacks. Our results show that our approach can consistently and efficiently locate small changes in the presence of substantial operational noise.

Yoginath, Srikanth↗
DOE OSTI2021

Laser-Interference Surface Preparation for Enhanced Coating Adhesion and Adhesive Joining of Multi-Materials (Final Project Report)

This report investigates a laser-interference surface treatment as a non-contact, i.e., without major solid/liquid medium application or abrasion, and non-chemical surface preparation method for aerospace coating systems. It was proposed to use the laser-interference technique to structure surfaces of Al and/or Ti, creating "rough" surfaces with pre-engineered series of ridges and valleys at submicron scale. The science goal of this study was to develop an understanding of the surface microstructure, topology, and physical mechanisms that would improve adhesion and corrosion protection of Al2024-T3. Microstructure analysis indicates that the laser-interference structuring (LIS) was found to reduce the formation of CuMn-rich precipitates in Al 2024-T3 over a 500-800 nm depth from top surface. The X-cut and cross-hatch coating adhesion ratings indicate that the LIS specimens meet the performance requirements in the coating adhesion specifications by having a higher or identical ranking to those specimens prepared with current state-of-the-art chemical conversion or sulfuric acid anodizing. After the ASTM B117 corrosion exposure, it was found that the laser processed specimens exhibited only few blisters. It was found that the corrosion damage was minimized at a laser rastering speed of 4 mm/s, for which only 33% of specimens developed very minor corrosion damage. The ASTM D1654 creepage ratings, used to evaluate corrosion damage along the scribe lines, were found to be at least nine for all coated panels. These results indicate that the laser-interference technique with the additional acetone wiping has the potential to be further developed as a minor chemical surface preparation technique for chromate-containing epoxy primers coatings.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Revisiting Multi-Material Composite Structures with Homogenized Composite Properties

Composite structures inherently develop residual stresses during their curing process. Driven predominately by mismatched thermal strains between differing materials or ply orientations, but also affected by curing process phenomena like polymer shrinkage, these residual stresses can lead to failure within composite structures. There are several methods varying in complexity that can be used to model the development of residual stresses, all of which are capable of capturing sufficient detail to understand the residual stress state at the ply level. However, explicitly modeling all plies of a layup in a composite structure can be prohibitively expensive based on the number of plies, structure size, and required element size. The computational cost can be reduced through the homogenization of the composite layup without losing much fidelity of the overall response of the structure. The homogenization process reduces the many plies of a laminate to a single lamina that reduces complexity and increases the mesh size where a single element can span multiple plies. This report focuses on verification and validation efforts for a homogenization process using a suite of finite element simulations rather than an analytic solution derived from classical laminate theory. Initial verification using representative element volumes indicated there was minimal error in the homogenization process; however, this compounded to a small, but acceptable error in strip and split ring experimental composite structures. The error does under predict the residual stress state in the strip and split ring and should be accounted for when simulating composite structures with homogenized properties.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Characterization of Multi-Material Interfaces Within Fibrous Structures (CRADA Final Report)

This project aimed to characterize the electrical, ionic, and thermal material properties of printed materials onto various textile and leather substrates. Furthermore, the material interfaces were investigated as well via characterization techniques such as SEM, TEM, and FTIR for example. Results from these studies will be utilized to properly formulate and tune process variables for enhancing the durability of devices and mitigate risks during commercial scale manufacturing studies of interest to Funxion’s product development.

36 MATERIALS SCIENCE↗