SEARCH · Search NASA

Results for “3D Reconstruction”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 505 records · Page 28

All sources NASA NTRS DOE OSTI

DOE OSTI2021

4D Imaging of ZnO-Coated Nanoporous Al 2 O 3 Aerogels by Chemically Sensitive Ptychographic Tomography: Implications for Designer Catalysts

The 3D chemical structure (4D spectromicroscopy) of nanoporous Al 2 O 3 aerogels coated with ZnO by atomic layer deposition (ALD) was studied by multienergy scanning transmission X-ray microscopy. These materials are representative of a class of designer catalysts in which the nanoporous support is prepared separately from the active catalyst material, which is subsequently introduced by ALD, thereby allowing independent optimization of the morphology, chemistry, and spatial distribution of the support and catalyst. The samples studied were prepared by Ga ion and Xe plasma focused ion beam (FIB) milling as well as drop casting from water suspension. Zn L and Al K edge spectra of six samples with three different ZnO loadings were measured to investigate how loading and different sample preparation methods affect the 3D distribution of the ZnO and Al 2 O 3 . Scanning transmission X-ray microscopy (STXM) and ptychographic imaging at two energies each at the Zn L 3 and Al K edge were measured. The ptychography data were analyzed by using the SHARP reconstruction code to generate quantitative 2D chemical maps of the Al 2 O 3 and the ZnO. The STXM and ptychography maps were then measured at a sequence of tilt angles, covering up to 160° of rotation. The 3D structure of the ZnO and Al 2 O 3 was derived from the tilt series data by tomographic reconstruction using a compressed sensing algorithm. A twodimensional spatial resolution (half-period) of 6 nm, measured by Fourier ring correlation, and a 3D spatial resolution (half-period) of 9 nm, measured by Fourier shell correlation, were achieved when using the COSMIC beamline at the Advanced Light Source (ALS). The results show that for all of the ZnO loadings studied there is nonuniform coverage of the ZnO on the Al 2 O 3 aerogel framework. In addition, we found that both FIB methods create sample artifacts, although the distortion was less with Xe plasma than Ga ion FIB.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Comprehensive characterization of the structure of Zr-based metallic glasses

Structure of metallic glasses fascinates as the generic amorphous structural template for ubiquitous systems. Its specification necessitates determination of the complete hierarchical structure, starting from short-range-order (SRO) → medium-range-order (MRO) → bulk structure and free volume (FV) distribution. This link has largely remained elusive since previous investigations adopted one-technique-at-a-time approach, focusing on limited aspects of any one domain. Reconstruction of structure from experimental data inversion is non-unique for many of these techniques. As a result, complete and precise structural understanding of glass has not emerged yet. In this work, we demonstrate the first experimental pathway for reconstruction of the integrated structure, for and glasses. Our strategy engages diverse (×7) multi-scale techniques [XAFS, 3D-APT, ABED/NBED, FEM, XRD, PAS, FHREM] on the same glass. This strategy complemented mutual limitations of techniques and corroborated common parameters to generate complete, self-consistent and precise parameters. Further, MRO domain size and inter-void separation were correlated to identify the presence of FV at MRO boundaries. This enabled the first experimental reconstruction of hierarchical subset: SRO → MRO → FV → bulk structure. The first ever image of intermediate region between MRO domains emerged from this link. We clarify that determination of all subsets is not our objective; the essence and novelty of this work lies in directing the pathway towards finite solution, in the most logical and unambiguous way.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Optimal 3D chemical imaging with multimodal electron tomography

Accurate mapping of nanoscale chemistry in three dimensions (3D) has been a longstanding challenge. Modern electron microscopy provides chemical images by electron energy loss spectroscopy (EELS) and energy dispersive x-ray spectrometry (EDX) but requires high fluences that damage specimens. In 3D, the requirements are worse; electron tomography demands many high-fluence chemical maps for reconstruction, creating a tradeoff between resolution, accuracy, and sample survival. Fused multimodal electron tomography (MM-ET) alleviates this requirement by leveraging lower-fluence high-angle annular dark-field (HAADF) images alongside a few chemical maps to dramatically improve chemical resolution. Here, experimental and computational parameter space is systematically explored to determine when MM-ET performs best. Ideal imaging conditions balance sample survival with resolution and chemical specificity; we recommend a tilt range of at least ± 70°, acquiring 40 equally spaced HAADF projections (signal-to-noise > 10), and 7 EELS/EDX maps of each chemistry (signal-to-noise > 4).

36 MATERIALS SCIENCE↗

DOE OSTI2021

Kinetic equilibrium reconstructions of plasmas in the MAST database and preparation for reconstruction of the first plasmas in MAST upgrade

Reconstructions of plasma equilibria using magnetic sensors were routine during operation of the Mega Ampere Spherical Tokamak (MAST) device, but reconstructions using kinetic profiles were not. These are necessary for stability and disruption analysis of the MAST database, as well as for operation in the upgrade to the device, MAST-U. The three-dimensional (3D) code VALEN is used to determine eddy currents in the 3D vessel structures for vacuum coil test shots, which are then mapped to effective resistances in the two-dimensional vessel groupings in the EFIT equilibrium reconstruction code to be used in conjunction with nearby loop voltage measurements for estimated currents in the structures during reconstruction. Kinetic equilibrium reconstructions with EFIT, using all available magnetic sensors as well as Thomson scattering measurements of electron temperature and density, charge exchange recombination spectroscopy measurements of ion temperature, and internal magnetic field pitch angle measurements from a motional Stark effect (MSE) diagnostic are performed for a large database of MAST discharges. Excellent convergence errors are obtained for the portions of the discharges where the stored energy was not too low, and it is found that reconstructions performed with temperature and density measurements but without MSE data usually already match the pitch angle measurements well. A database of 275 kinetic equilibria is used to test the ideal MHD stability calculation capability for MAST. In conclusion, the necessary changes to conducting structure in VALEN, and diagnostic setup in EFIT have been completed for the upgrade from MAST to MAST-U, enabling kinetic reconstructions to commence from the first plasma discharges of the upgraded device.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Coregistered positron emission particle tracking (PEPT) and X-ray computed tomography (CT) for engineering flow measurements

Increasingly, fully 3D experimental measurements of flow in complex engineering geometries are required to validate computational fluid dynamics models that support and inform reactor design and licensing. One barrier to such measurements is the complexity of typical reactor components and subsequent lack of optical access in these systems. To overcome this, the deployment of coregistered positron emission particle tracking (PEPT) and X-ray computed tomography (CT) is explored for flow measurement in reactor thermal hydraulic components and model (scaled) systems. Through this methodology, fully 3D flow information (via PEPT) and detailed internal geometry (via CT) are captured in opaque systems such as pipes, rod bundles, packed beds, etc. The reconstructed flow field and geometry can then be overlain to reveal detailed flow features around internal structures within a given test section. This is enabled through the use of a combined preclinical PET/CT scanner with overlapping PET and CT fields of view. Such measurements are useful for characterizing flow inside such intricate nuclear thermal hydraulic components as core geometries and heat exchangers, among others, and providing valuable 3D validation data for CFD models. In this work, basic tests of this 3D flow/geometry mapping are presented, and the implications of such measurements are discussed. Further, preliminary measurements are made with both point sources and flow in a simple pipe flow geometry to evaluate the capabilities of this technique. PEPT and CT features are coregistered with up to 0.1 mm precision, and pipe flow mean velocity and Reynolds stresses are reconstructed with similar accuracy to previous PEPT demonstrations. The utility of PEPT/CT is shown herein, and suggestions for future measurements are made.

3D flow measurement↗

DOE OSTI2026

BM3DORNL

BM3DORNL is a high-performance, open-source library for removing streak and ring artifacts from computed-tomography (CT) data, developed for neutron imaging at Oak Ridge National Laboratory's Spallation Neutron Source (VENUS beamline) and applicable to X-ray CT as well. Ring artifacts — concentric rings in reconstructed slices caused by detector pixel-to-pixel response non-uniformities — appear as vertical streaks in the sinogram and degrade both image quality and quantitative analysis. BM3DORNL operates in the sinogram domain using an adaptation of the BM3D (block-matching and 3D collaborative filtering) algorithm (Dabov et al., 2007). It provides a dedicated streak-removal mode, a true multi-scale BM3D variant (after Mäkinen et al., 2021) that suppresses wide streaks single-scale methods miss, and an alternative Fourier–SVD method (~2.6× faster) combining FFT-based energy detection with rank-1 SVD. The computationally intensive core is implemented in Rust with parallel (Rayon) block matching, integral-image pre-screening, and optimized transforms, and is exposed through a simple Python API (with an optional GUI) so it integrates directly into existing tomography reconstruction pipelines. It processes both 2D sinograms and 3D sinogram stacks, is pip-installable for Linux and macOS, and is documented at https://bm3dornl.readthedocs.io.

Zhang, Chen [Oak Ridge National Laboratory (ORNL),↗

DOE OSTI2020

High-resolution 3D microwave imaging using an optically tracked linear array

Active three-dimensional microwave or millimeter-wave imaging is typically performed using a linear array that is mechanically scanned over a uniform planar or cylindrical aperture. However, an image can also be formed with a linear array that is scanned over a non-uniform irregular aperture. This requires that the precise position of the array be known for each radar sample. This paper explores high-resolution 3D microwave imaging of stationary targets using an optically tracked manually scanned linear array. The image reconstruction techniques necessary to account for a non-uniform irregular aperture are also developed.

Clark, Richard T.↗

NASA NTRS1992

A feasibility study of hand kinematics for EVA analysis using magnetic resonance imaging

A new method of analyzing the kinematics of joint motion is developed. Magnetic Resonance Imaging (MRI) offers several distinct advantages. Past methods of studying anatomic joint motion have usually centered on four approaches. These methods are x-ray projection, goniometric linkage analysis, sonic digitization, and landmark measurement of photogrammetry. Of these four, only x-ray is applicable for in vivo studies. The remaining three methods utilize other types of projections of inter-joint measurements, which can cause various types of error. MRI offers accuracy in measurement due to its tomographic nature (as opposed to projection) without the problems associated with x-ray dosage. Once the data acquisition of MR images was complete, the images were processed using a 3D volume rendering workstation. The metacarpalphalangeal (MCP) joint of the left index finger was selected and reconstructed into a three-dimensional graphic display. From the reconstructed volumetric images, measurements of the angles of movement of the applicable bones were obtained and processed by analyzing the screw motion of the MCP joint. Landmark positions were chosen at distinctive locations of the joint at fixed image threshold intensity levels to ensure repeatability. The primarily two dimensional planar motion of this joint was then studied using a method of constructing coordinate systems using three (or more) points. A transformation matrix based on a world coordinate system described the location and orientation of a local target coordinate system. Future research involving volume rendering of MRI data focusing on the internal kinematics of the hand's individual ligaments, cartilage, tendons, etc. will follow. Its findings will show the applicability of MRI to joint kinematics for gaining further knowledge of the hand-glove (power assisted) design for extravehicular activity (EVA).

Dickenson, Rueben D.↗

NASA NTRS2017

Comparison of Tomo-PIV Versus Dual Plane PIV on a Synthetic Jet Flow

Particle Imaging Velocimetry (PIV) is a planar velocity measurement technique that has found widespread use across a wide class of engineering disciplines. Tomographic PIV (tomoPIV) is an extension of the traditional PIV technique whereby the velocity across a volume of fluid is measured. TomoPIV provides additional fluid mechanical properties of the flow due to the adjacent planes of velocity information that are extracted. Dual Plane PIV is another approach for providing cross-plane flow field properties. Dual Plane PIV and tomoPIV provide all of the same flow properties, albeit through very different routes with significantly different levels of effort, hence a comparison of their application and performance would prove beneficial in a well-known, highly three dimensional flow field. A synthetic jet flow which has a wide range of flow field features including high velocity gradients and regions of high vorticity was used as a rigorous test bed to determine the capabilities limitations of the Dual Plane PIV and tomoPIV techniques. The results show that compressing 3D particle field information down to a limited number of views does not permit the accurate reconstruction of the flow field. The traditional thin sheet techniques are the best approach for accurate flow field measurements.

Particle Image Velocimetry↗

NASA NTRSDate not supplied

The Next Generation of Lightning Mapping

With the removal of the Lightning Imaging Sensor from the International Space Station, a gap has opened in lightning observation from low-Earth orbit. The CubeSpark mission concept aims to fill this role using a constellation of satellites with radio frequency (RF) sensors and bi-spectral optical imagers to observe lightning flashes more completely and with better resolution than is currently possible from space. In this study, we assess the feasibility of multiple methods of not only mapping lightning locations, but also inferring 3D flash and charge structures. This is done primarily by simulating lightning emissions in the very high frequency (VHF) band, modeling their propagation to orbital sensors, and reconstructing their locations using time-of-arrival (TOA) minimization algorithms. Constellation shape, number, and atmospheric conditions are varied in order to quantify the three main sources of geolocation error: geometric, ionospheric, and instrumental effects. The promising results presented here demonstrate 3D resolution better than 1-2 km in many cases, enabling new applications in meteorology and climate sciences.

CubeSpark↗

DOE OSTI2023

A Deep Learning-Based Workflow for Fast Prediction of 3D State Variables in Geological Carbon Storage: A Dimension Reduction Approach

In this study, we used deep learning techniques, which are a form of artificial intelligence, to create fast and effective models for predicting how fluids flow in underground geological formations. This is important for managing geological carbon storage, a method used to fight climate change by storing carbon dioxide underground. The challenge lies in the complex nature of these underground spaces and the large amount of data needed to accurately simulate them. To overcome these issues, we developed a new workflow that reduces the data’s complexity before training the deep learning model and then reconstructs the predicted results in their original form. We also proposed a unique approach to handle the specific complexities found in 3D saturation fields, a crucial aspect of fluid flow prediction. We tested our method using real-world data from the Gulf of Mexico. Our results show that our approach not only accurately predicts fluid behavior but also significantly reduces computation time. This will greatly improve real-time decision-making and risk assessment in large-scale geological carbon storage operations.

Wang, Hongsheng↗

NASA NTRS2012

Multi-Mission Simulation and Visualization for Real-Time Telemetry Display, Playback and EDL Event Reconstruction

he Jet Propulsion Laboratory's Entry, Descent and Landing (EDL) Reconstruction Task has developed a software system that provides mission operations personnel and analysts with a real time telemetry-based live display, playback and post-EDL reconstruction capability that leverages the existing high-fidelity, physics-based simulation framework and modern game engine-derived 3D visualization system developed in the JPL Dynamics and Real Time Simulation (DARTS) Lab. Developed as a multi-mission solution, the EDL Telemetry Visualization (ETV) system has been used for a variety of projects including NASA's Mars Science Laboratory (MSL), NASA'S Low Density Supersonic Decelerator (LDSD) and JPL's MoonRise Lunar sample return proposal.

Entry, Descent and Landing (EDL) Reconstruction↗

DOE OSTI2024

The use of digital thread for reconstruction of local fiber orientation in a compression molded pin bracket via deep learning

A deep convolutional neural network (DCNN) was used for microstructure reconstruction using artificial intelligence (MR-AI) by predicting local average fiber orientation distributions (FOD) in a 3D prepreg platelet molded composite (PPMC) pin bracket. To train the MR-AI model, surface strain fields from residual stresses simulated in PPMC plates were used as the input to the DCNN. A training dataset included PPMC plates with various degrees of global fiber alignment, based on the information obtained from high-fidelity flow simulation of a pin bracket. Further, the MR-AI model was then deployed to analyze FOD in the 3D pin bracket by conducting thermo-elastic residual stress analysis. Initially, the MR-AI model was established entirely on the synthetic simulation data. Then, a μCT scan of a physically molded pin bracket was used to create a finite element model that provided data for additional validation of the DCNN model. For the μCT scan finite element pin bracket the MR-AI model predicted the distribution of fiber orientation tensor components with MAE of 0.10 indicating a global prediction error of 10%. For the flow simulated pin bracket, the MR-AI model predicted the distribution of fiber orientation tensor components with a global prediction error of 11%. The MR-AI model showed the ability to predict regions of varying alignment in the base and flange of the pin bracket. The proposed MR-AI methodology allows for rapid prediction of FOD in geometrically complex parts and offers a promising path to detecting unique fiber orientation states in molded components.

42 ENGINEERING↗

DOE OSTI2024

Dual X-ray computed tomography-aided classification of melt pool boundaries and flaws in crept additively manufactured parts

In metal additive manufacturing (AM), understanding the process-structure-performance relationships requires a combination of multi-scale characterization techniques that allows for the measurement of the melt pool shape and boundary and classifying various defects and flaws in the AM parts. Such approaches can be destructive, only 2D in nature, or have a small field of view and can be complex to co-register and analyze. Here, in this work, we present a non-destructive 3D inspection technique that employs dual-energy X-ray computed tomography (XCT) along with a model-based iterative reconstruction (MBIR) and a new segmentation algorithm. The proposed approach and algorithm are not only capable of classifying and quantifying flaws such as pores, cracks, and inclusions, but they also allow for the extraction of microstructural features such as melt pool boundaries (MPB) and melt pool regions (MPR), that can help understand process-structure-performance relationships for alloys under study. As an exemplar application, we employed the method for characterization of an additively manufactured aluminum alloy crept under tensile stress at 300 °C for 1064 h. Our results demonstrate high quality segmentation and classification of various flaws and MPB and MPR, for the first time, using 3D X-ray CT inspection. The delineated MPB and MPR in the crept samples reveal the preferential growth paths of cracks that formed during creep deformation. The technique was used for successfully quantifying the characteristics (number of defects, their density, volume fraction, etc.) of the manufacturing-induced pores and creep-induced cracks, which is necessary to better understand the creep failure mechanisms of the material.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Application of machine learning and artificial intelligence to extend EFIT equilibrium reconstruction

Recent progress in the application of machine learning (ML)/artificial intelligence (AI) algorithms to improve the Equilibrium Fitting (EFIT) code equilibrium reconstruction for fusion data analysis applications is presented. A device-independent portable core equilibrium solver capable of computing or reconstructing equilibrium for different tokamaks has been created to facilitate adaptation of ML/AI algorithms. A large EFIT database comprising of DIII-D magnetic, motional Stark effect, and kinetic reconstruction data has been generated for developments of EFIT model-order-reduction (MOR) surrogate models to reconstruct approximate equilibrium solutions. Furthermore, a neural-network MOR surrogate model has been successfully trained and tested using the magnetically reconstructed datasets with encouraging results. Other progress includes developments of a Gaussian process Bayesian framework that can adapt its many hyperparameters to improve processing of experimental input data and a 3D perturbed equilibrium database from toroidal full magnetohydrodynamic linear response modeling using the Magnetohydrodynamic Resistive Spectrum - Feedback (MARS-F) code for developments of 3D-MOR surrogate models.

Gaussian process↗

DOE OSTI2022

2D Reconstruction of Magnetotail Electron Diffusion Region Measured by MMS

Models for collisionless magnetic reconnection in near-Earth space are distinctly characterized as 2D or 3D. In 2D kinetic models, the frozen-in law for the electron fluid is usually broken by laminar dynamics involving structures set by the electron orbit size, while in 3D models the width of the electron diffusion region is broadened by turbulent effects. We present an analysis of in situ spacecraft observations from the Earth's magnetotail of a fortuitous encounter with an active reconnection region, mapping the observations onto a 2D spatial domain. While the event likely was perturbed by low-frequency 3D dynamics, the structure of the electron diffusion region remains consistent with results from a 2D kinetic simulation. As such, the event represents a unique validation of 2D kinetic, and laminar reconnection models.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Anatomical Fraction segmentation in the biomass bales

The U.S. Department of Energy Bioenergy Technologies Office (BETO) is committed to the development of sustainable, nationwide, commercial biofuel production to displace petroleum-derived fuels, increase domestic energy production, and encourage the creation of a domestic bioenergy and bioproducts industry. Operating a commercial-scale bioenergy operation requires significant technological advancements for determining biomass feedstock quality during the preprocessing stage. Usage of non-food feedstocks- e.g., corn-stover, pine residue, and forest residue - at the biorefineries reduces strain on the food supply chain. But the non-food feedstock heterogeneity- physical size, shape, and chemical composition-poses a significant challenge during milling, conveyance, feeding, and biofuel conversion processes. 3D X-Ray imaging (CT) is capable of distinguishing material features by detecting density and compositional differences. But the inherent complexity introduced during harvesting and bailing makes the reconstruction and interpretation of baled biomass materials from x-ray data time consuming, laborious, and expensive. Feedstocks are low-density materials that produce small contrast differences in the x-ray images. This paper focuses on using the shape and texture properties, using 3D image processing techniques like 3D skeletonization, directional statistics to characterize and extract volumetric content of the different tissue samples in the biomass bales.

09 BIOMASS FUELS↗

DOE OSTI2020

3D Cell-centered hydrodynamics with subscale closure model and multi-material remap

We extend a higher-order finite volume cell-centered hydrodynamic (CCH) formulation to include an interface-aware subscale closure model and a multi-material remap for simulating 3D compressible hydrodynamic problems within an arbitrary Lagrangian-Eulerian (ALE) framework. This CCH formulation involves a multidirectional approximate Riemann solution using quadratic polynomial reconstructions of the stress tensor and the velocity. At the subscale level, we determine pair-wise material interactions by solving a distinct approximate Riemann problem at the common interface, using the volume of fluids (VOF) method to find the interface. Material interactions are constrained to ensure smooth pressure equilibration among materials. The accuracy and robustness of the ALE method is demonstrated by simulating a suite of 3D Cartesian multi-material problems covering both gas and solid dynamics, where each test case has two or more materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗