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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Beam Hardening Artifact Reduction in X-Ray CT Reconstruction of 3D Printed Metal Parts Leveraging Deep Learning and CAD Models

Nondestructive evaluation (NDE) of additively manufactured (AM) parts is important for understanding the impacts of various process parameters and qualifying the built part. X-ray computed tomography (XCT) has played a critical role in rapid NDE and characterization of AM parts. However, XCT of metal AM parts can be challenging because of artifacts produced by standard reconstruction algorithms as a result of a confounding effect called “beam hardening.” Beam hardening artifacts complicate the analysis of XCT images and adversely impact the process of detecting defects, such as pores and cracks, which is key to ensuring the quality of the parts being printed. In this work, we propose a novel framework based on using available computer-aided design (CAD) models for parts to be manufactured, accurate XCT simulations, and a deep-neural network to produce high-quality XCT reconstructions from data that are affected by noise and beam hardening. Using extensive experiments with simulated data sets, we demonstrate that our method can significantly improve the reconstruction quality, thereby enabling better detection of defects compared with the state of the art. We also present promising preliminary results of applying the deep networks trained using CAD models to experimental data obtained from XCT of an AM jet-engine turbine blade.

Ziabari, Amir↗
DOE OSTI2023

3D Source Reconstruction Using Coded Aperture Gamma-Ray Imaging

Recent measurements with coded-aperture imagers demonstrate material mass determination in a holdup setting to an accuracy within a few percent. This capability is of particular interest to the Surplus Plutonium Disposition (SPD) project, which aims to dilute and dispose of surplus plutonium oxide. Gamma-ray imagers can be used to determine holdup without interrupting normal operations. In this work, we examine techniques for 3D source localization and mass determination using gamma-ray imagers. Coded-aperture imagers provide excellent source localization within the 2D image plane; however, multiple imagers operating in tandem are necessary to identify source location in 3D space. A Maximum Likelihood Expectation-Maximization (MLEM) method for fitting detector mappings is a powerful tool for accomplishing this task. MLEM allows 3D source localization to be simultaneously constrained using multiple gamma-ray imagers by constructing the basis for the MLEM fit using detector mappings from different detector locations stitched together. Each of these basis points represents a singular response from a source in 3D space and is generated using Monte Carlo simulations of sources placed individually at different locations throughout the imager’s field of view. Additionally, implementing knowledge of the physical equipment in the simulations of the glovebox used for the SPD project incorporates attenuation effects that are needed to calculate material holdup.

Laminack, Alex↗
NASA NTRS2007

Automated Recognition of 3D Features in GPIR Images

A method of automated recognition of three-dimensional (3D) features in images generated by ground-penetrating imaging radar (GPIR) is undergoing development. GPIR 3D images can be analyzed to detect and identify such subsurface features as pipes and other utility conduits. Until now, much of the analysis of GPIR images has been performed manually by expert operators who must visually identify and track each feature. The present method is intended to satisfy a need for more efficient and accurate analysis by means of algorithms that can automatically identify and track subsurface features, with minimal supervision by human operators. In this method, data from multiple sources (for example, data on different features extracted by different algorithms) are fused together for identifying subsurface objects. The algorithms of this method can be classified in several different ways. In one classification, the algorithms fall into three classes: (1) image-processing algorithms, (2) feature- extraction algorithms, and (3) a multiaxis data-fusion/pattern-recognition algorithm that includes a combination of machine-learning, pattern-recognition, and object-linking algorithms. The image-processing class includes preprocessing algorithms for reducing noise and enhancing target features for pattern recognition. The feature-extraction algorithms operate on preprocessed data to extract such specific features in images as two-dimensional (2D) slices of a pipe. Then the multiaxis data-fusion/ pattern-recognition algorithm identifies, classifies, and reconstructs 3D objects from the extracted features. In this process, multiple 2D features extracted by use of different algorithms and representing views along different directions are used to identify and reconstruct 3D objects. In object linking, which is an essential part of this process, features identified in successive 2D slices and located within a threshold radius of identical features in adjacent slices are linked in a directed-graph data structure. Relative to past approaches, this multiaxis approach offers the advantages of more reliable detections, better discrimination of objects, and provision of redundant information, which can be helpful in filling gaps in feature recognition by one of the component algorithms. The image-processing class also includes postprocessing algorithms that enhance identified features to prepare them for further scrutiny by human analysts (see figure). Enhancement of images as a postprocessing step is a significant departure from traditional practice, in which enhancement of images is a preprocessing step.

Park, Han↗
DOE OSTI2022

3D Equilibrium Reconstruction and MHD Studies in Stellarators (Final Report)

This is the final technical report for the grant Three Dimensional Equilibrium Reconstruction and MHD Studies in Stellarators. The major goals of this project were to: further develop V3FIT code capabilities, continue to support experiments using the V3FIT code, continue theoretical support for the CTH experiment at Auburn, particularly in the area of NIMROD simulations of CTH discharges. Dr. Lopez Ortiz has made significant progress on his analysis of NIMROD simulations of CTH MHD phenomena. In particular, his study has focused on the fixed point dynamics and energy flow amongst toroidal Fourier modes in sawtooth oscillations simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Reconstruction of 3D Concrete Microstructures Combining High-Resolution Characterization and Convolutional Neural Network for Image Segmentation

After water, concrete is the second most used material in the world. Concrete’s forming adaptability and low-cost constituents make it a predominant material used in the construction of civil infrastructures in nuclear power plants such as concrete biological shields, containment buildings, turbine buildings, fuel handling and storage buildings, underground piping for cooling, cooling towers, and so on. Depending on environmental and operating conditions, these passive structures are subject to time-dependent phenomena that can either enhance (e.g., continued hydration) or degrade concrete’s structural performance. Unlike components such as the reactor pressure vessel and the primary circuit, concrete composition varies regionally because it is manufactured using local aggregates and cement. Hence, concrete performance metrics over time cannot be derived confidently using empirical relations. Alternatively, the specific characteristics of the local concrete constituents and their assemblage in concrete must be considered.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

The Satellite Flythrough and Reconstruction Softwares at CCMC

The next-generation of model data visualization to be offered at the Community Coordinated Modeling Center (CCMC) will be based on Kamodo, an open source python package. To increase the usefulness of our services, we are also developing new capabilities based on this software, called the satellite flythrough and the reconstruction tools, to be offered both as packages for offline analysis and through an online interface (coming soon). The satellite flythrough software ‘flies’ a satellite trajectory, whether real or imaginary, through either model data hosted at CCMC or on a personal machine. This service greatly simplifies the complexity of users’ access to model data, abstracting away the time-consuming details of model data formats and interpolation. We demonstrate execution times of a few seconds to a few minutes for several example flythroughs of a trajectory stretching over a few days, depending on the parameters chosen. We also demonstrate a reconstruction tool built on top of the satellite flythrough software, for use with mission planning and model-data comparisons. This tool, based on reconstructions provided for the GDC Science and Technology Definition Team, converts multiple, simultaneous satellite flythroughs into two-dimensional reconstructions. The reconstruction tool provides a software capability for satellite constellations to determine how many satellites are needed and in what configuration to resolve the desired features in the model data. Both tools are currently available through GitHub for a selection of CCMC-hosted ITM models. Finally, we present initial results from work in progress and plans for future work, including an expansion of the reconstruction tool to provide 3D reconstruction capabilities and a line-of-sight calculation tool.

software, python↗
NASA NTRS2021

3D Shape Reconstruction of Small Bodies from Sparse Features

The autonomous approach of spacecraft to a small body (comet or asteroid) relies on using all available information at each phase of the approach. This paper presents new algorithms for global shape reconstructions from sparse tracked surface points. These methods leverage estimates from earlier phases, such as rotation pole, as well as a priori knowledge, such as a genus-0 body (i.e. without boundaries or topological holes). A mapping algorithm is proposed, which performs faithful reconstructions while enforcing genus-0 output through spherical parameterization. To estimate the shape of permanently shadowed regions of the body, a symmetry reconstruction method is added to the reconstruction algorithms. This method is shown to substantially increase the reconstruction accuracy but is subject to the symmetry of the body perpendicular to the rotation pole. The proposed mapping algorithm is compared to stateof- the-practice surface reconstruction algorithms, assessing their accuracy and ability to correctly generate genus-0 shape models for 2400 datasets and three small bodies. The proposed spherical parameterization algorithm performed consistently with the state-of-the-practice while being the only algorithm to always produce genus-0 shape models.

Nesnas, Issa↗
DOE OSTI2021

Imaging moiré flat bands in three-dimensional reconstructed WSe 2 /WS 2 superlattices

Moiré superlattices in transition metal dichalcogenide (TMD) heterostructures can host novel correlated quantum phenomena due to the interplay of narrow moiré flat bands and strong, long-range Coulomb interactions. However, microscopic knowledge of the atomically reconstructed moiré superlattice and resulting flat bands is still lacking, which is critical for fundamental understanding and control of the correlated moiré phenomena. Here we quantitatively study the moiré flat bands in three-dimensional (3D) reconstructed WSe 2 /WS 2 moiré superlattices by comparing scanning tunnelling spectroscopy (STS) of high-quality exfoliated TMD heterostructure devices with ab initio simulations of TMD moiré superlattices. A strong 3D buckling reconstruction accompanied by large in-plane strain redistribution is identified in our WSe 2 /WS 2 moiré heterostructures. STS imaging demonstrates that this results in a remarkably narrow and highly localized K-point moiré flat band at the valence band edge of the heterostructure. A series of moiré flat bands are observed at different energies that exhibit varying degrees of localization. Our observations contradict previous simplified theoretical models but agree quantitatively with ab initio simulations that fully capture the 3D structural reconstruction. Furthermore, our results reveal that the strain redistribution and 3D buckling in TMD heterostructures dominate the effective moiré potential and the corresponding moiré flat bands at the Brillouin zone K points.

36 MATERIALS SCIENCE↗