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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 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

A method to generate small-scale, high-resolution sedimentary bedform architecture models representing realistic geologic facies

Small-scale (mm to m) sedimentary structures (e.g. ripple lamination, cross-bedding) have received a great deal of attention in sedimentary geology. The influence of depositional heterogeneity on subsurface fluid flow is now widely recognized, but incorporating these features in physically-rational bedform models at various scales remains problematic. The current investigation expands the capability of an existing set of open-source codes, allowing generation of high-resolution 3D bedform architecture models. The implemented modifications enable the generation of 3D digital models consisting of laminae and matrix (binary field) with characteristic depositional architecture. The binary model is then populated with petrophysical properties using a textural approach for additional analysis such as statistical characterization, property upscaling, and single and multiphase fluid flow simulation. One example binary model with corresponding threshold capillary pressure field and the scripts used to generate them are provided, but the approach can be used to generate dozens of previously documented common facies models and a variety of property assignments. An application using the example model is presented simulating buoyant fluid (CO 2 ) migration and resulting saturation distribution.

58 GEOSCIENCES↗
DOE OSTI2016

Three dimensional (3D) microstructure-based finite element modeling of Al-SiC nanolaminates using focused ion beam (FIB) tomography

Al-SiC nanolaminate composites show promise as high performance coating materials due to their combination of strength and toughness. Although a significant amount of modeling effort has been focused on materials with an idealized flat nanostructure, experimentally these materials exhibit complex undulating layer geometries. This work utilizes FIB tomography to characterize this nanostructure in 3D and finite element modeling to determine the effect that this complex structure has on the mechanical behavior of these materials. A sufficiently large volume was characterized such that a 1 × 2 μm micropillar could be generated from the dataset and compared directly to experimental results. The mechanical response from this nanostructure was then compared to pillar models using simplified structures with perfectly flat layers, layers with sinusoidal waviness, and layers with arc segment waviness. The arc segment based layer geometry showed the best agreement with the experimentally determined structure, indicating it would be the most appropriate geometry for future modeling efforts. - Highlights: •FIB tomography was used to determine the structure of an Al-SiC nanolaminate in 3D. •FEM was used to compare the deformation of the nanostructure to experimental results. •Idealized structures from literature were compared to the FIB determined structure. •Arc segment based structures approximated the FIB determined structure most closely.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Prestack reverse time migration for 3D marine reflection seismic data

Prestack reverse time migration (RTM) is a method for imaging the subsurface using the inner product of wavefield extrapolation in shot domain and in receiver domain. It is well known that RTM is better for preserving amplitudes and phases than other prestack migrations. Since 3D seismic data is huge data volume and it needs heavy computing works, it requires parallel computing in order to have a meaningful depth image of the 3D subsurface. We implemented a parallelized version of 3D RTM for prestack depth migration. The results of numerical example for 3D SEG/EAGE salt model showed good agreement with the original geological model. We applied RTM to offshore 3D seismic reflection data. The study area is 12 × 25 km with 120 survey lines. Shot and receiver spacing is 25 m and 12.5 m. The line spacing is 100 m. Shot gathers were preprocessed to enhance signal to noise ratio and velocity model was calculated from conventional stack velocity. Both of them were used to obtain 3D image using RTM. The results show reasonable subsurface image.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

A Computational-experimental Study to Simulate Mixing and Thermal Stratification in SFRs

This NEUP project 16-10579 entitled “A Computational-Experimental Study to Simulate Mixing and Thermal Stratification in SFRs”, has investigated important phenomena of thermal stratification and mixing in Sodium-cooled Faster reactors (SFRs). A liquid metal experimental set-up was built at Kansas State University to generate high fidelity experimental data and validate computational models. The scope of the work involved - scaled down design of experimental facility, construction and commissioning of the new facility, conducting thermal-hydraulics experiments relevant to the physics of thermal stratification and mixing in the plena, developing 3D CFD models of the experiments, developing SAS4A/SASSYS-1 system model of the liquid metal experimental facility , survey of previous data in literature on stratification experiments and recommendations for improved models.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2020

ISEE System Technical Report

The Immersive Simulations and Engineering Environment (ISEE) Laboratory at Kennedy Space Center is a tool used to assist with operation simulation, for Human Factors operation activities, assisting future missions. The simulations created are important because they ensure that simulated operations are performed for customers, to assist with requirements. Simultaneously, each simulation will allow stakeholders to determine any and all risk associated with the Human Factors involved in a specific assignment. My internship consists of multiple project elements. The first of which, was to assist the Integrations branch chief in developing a growth rate algorithm proof. The integral part of this project, involved learning to powerup and perform the operational procedures of the ISEE lab, capturing and creating characters used in the CAD model virtual environment. In doing so, this led to use the software to model and 3D print screw cap structures for mock-up. The structures will be used to manipulate weight change out used in mock-up design and construction. These structures will also be used in future mock-up models constructed in the lab.

Darryl A J Minor↗
NASA NTRSDate not supplied

Expedited Model Building Method for Rocket Nozzle Side Loading

Statistical analysis of test data is currently the preferred method of creating models for uncharacterized side loading in rocket nozzles. However, statistical analysis requires multiple data sets to be reliable; getting these sets requires building and testing multiple rocket motors, which is not feasible given the incredible time and cost required to do so. By using a combination of geometry, simplified finite element analysis (FEA) analogs, and algebra we can create a limited predictive model from only one test data set. Once created, the model requires only the input from one strain gauge located at each yaw and pitch attachment bracket for the actuation system. This process is not computationally intensive, therefore saving an abundance of time and budget over using full 3D FEA models to develop a similar predictive model. To develop the model, conversion factors between the strain at the gauge locations and corresponding actuator load is derived from the data. These conversion factors are used to create a “conversion ellipse” that bounds the constitutive properties of the nozzle as one lumped factor. Using a 2D cross-sectional analog of the nozzle exit plane, we create a function that allows us to determine the azimuthal location of the unexpected load based on the ratio between yaw and pitch strain readings. Combining this with the “conversion ellipse” yields a function that given the strain reading outputs an induced actuator load, regardless of the azimuthal location of the unexpected load. As previously mentioned, this predictive model is limited in its application as there is inaccuracy introduced by the use of data by only one test as well as simplifying assumptions. This approach makes a useful tool to quickly determine whether uncharacterized actuator loading events can damage actuation systems or induce loading that exceeds design limits.

Seetha A Kolli↗
DOE OSTI2025

Additive Manufactured Compact Microwave Absorbers

A high-performance, compact microwave absorber was created using Fused Deposition Modeling (FDM) 3D printing. Both a narrowband and a broadband absorber were created. The narrowband absorber was designed at 4.9 GHz, mid-band in WR-187 waveguide. The broadband absorber tried to achieve the best attenuation across the entire 3.95 to 5.85 GHz band. Two types of carbon loaded polylactic acid (PLA) plastic and one type of unloaded PLA were 3D printed with variable percentages of air to achieve different values of effective dielectric constant and loss tangent. The absorber comprised five or six rectangular pieces of these plastic materials. The thickness and fill factor values for each piece were optimized to minimize reflection through fast analytic modeling in MATLAB®. The results were then verified by HFSS® simulation as well. The stack progressed from the lowest loss and lowest dielectric constant to the highest at the shorting end. The final narrowband load had simulated return loss of 87 dB at 4.9 GHz with an analytic solution in MATLAB. The measured return loss of the 3D printed attenuator was 73 dB at 4.929 GHz. The total length of the absorber was 2.44 inches. A commercial absorber for WR-187 with return loss of 40 dB has length of 13 inches. The experiment proves that an effective and compact microwave absorber can be created using 3D printing.

36 MATERIALS SCIENCE↗
DOE OSTI2014

TU-F-BRF-04: Registration of 3D Transesophageal Echocardiography and X-Ray Fluoroscopy Using An Inverse Geometry X-Ray System

Purpose: To develop a method for the fusion of 3D echocardiography and Scanning-Beam Digital X-ray (SBDX) fluoroscopy to assist with catheter device and soft tissue visualization during interventional procedures. Methods: SBDX is a technology for low-dose inverse geometry x-ray fluoroscopy that performs digital tomosynthesis at multiple planes in real time. In this study, transesophageal echocardiography (TEE) images were fused with SBDX images by estimating the 3D position and orientation (the “pose”) of the TEE probe within the x-ray coordinate system and then spatially transforming the TEE image data to match this pose. An initial pose estimate was obtained through tomosynthesis-based 3D localization of points along the probe perimeter. Position and angle estimates were then iteratively refined by comparing simulated projections of a 3D probe model against SBDX x-ray images. Algorithm performance was quantified by imaging a TEE probe in different known orientations and locations within the x-ray field (0-30 degree tilt angle, up to 50 mm translation). Fused 3D TEE/SBDX imaging was demonstrated by imaging a tissue-mimicking polyvinyl alcohol cylindrical cavity as a catheter was navigated along the cavity axis. Results: Detected changes in probe tilt angle agreed with the known changes to within 1.2 degrees. For a 50 mm translation along the source-detector axis, the detected translation was 50.3 mm. Errors for in-plane translations ranged from 0.1 to 0.9 mm. In a fused 3D TEE/SBDX display, the catheter device was well visualized and coincident with the device shadow in the TEE images. The TEE images portrayed phantom boundaries that were not evident under x-ray. Conclusion: Registration of soft tissue anatomy derived from TEE imaging and device imaging from SBDX x-ray fluoroscopy is feasible. The simultaneous 3D visualization of these two modalities may be useful in interventional procedures involving the navigation of devices to soft tissue anatomy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

A Hybrid Deep Learning Approach to Cosmological Constraints from Galaxy Redshift Surveys

We present a deep machine learning (ML)–based technique for accurately determining σ g and Ω m from mock 3D galaxy surveys. The mock surveys are built from the AbacusCosmos suite of N -body simulations, which comprises 40 cosmological volume simulations spanning a range of cosmological parameter values, and we account for uncertainties in galaxy formation scenarios through the use of generalized halo occupation distributions (HODs). We explore a trio of ML models: a 3D convolutional neural network (CNN), a power spectrum–based fully connected network, and a hybrid approach that merges the two to combine physically motivated summary statistics with flexible CNNs. We describe best practices for training a deep model on a suite of matched-phase simulations, and we test our model on a completely independent sample that uses previously unseen initial conditions, cosmological parameters, and HOD parameters. Despite the fact that the mock observations are quite small (~0.07 h -3 Gpc 3 ) and the training data span a large parameter space (six cosmological and six HOD parameters), the CNN and hybrid CNN can constrain estimates of σ g and Ω m to ~3% and ~4%, respectively.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

SU-C-303-03: Dosimetric Model of the Beagle Needed for Pre-Clinical Testing of Radiopharmaceuticals

Purpose: Large animal models, most popularly beagles, have been crucial surrogates to humans in determining radiation safety levels of radiopharmaceuticals. This study aims to develop a detailed beagle phantom to accurately approximate organ absorbed doses for therapy nuclear medicine preclinical studies. Methods: A 3D NURBS model was created subordinate to a whole body CT of an adult beagle. Bones were harvested and CT imaged to offer macroscopic skeletal detail. Samples of trabecular spongiosa were cored and imaged to offer microscopic skeletal detail for bone trabeculae and marrow volume fractions. Results: Organ masses in the model are typical of an adult beagle. Trends in volume fractions for skeletal dosimetry are fundamentally similar to those found in existing models of other canine species. Conclusion: This work warrants its use in further investigations of radiation transport calculation for electron and photon dosimetry. This model accurately represents the anatomy of a beagle, and can be directly translated into a useable geometry for a voxel-based Monte Carlo radiation transport program such as MCNP6. Work supported by a grant from the Hyundai Hope on Wheels Foundation for Pediatric Cancer Research.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Deep Learning-based Parameterization of Complex 3D CO2 Saturation Data in Large-scale Geological Carbon Storage

In deep learning (DL), dimension reduction plays a pivotal role in improving training efficiency and minimizing overfitting, especially when working with complex datasets like three-dimensional (3D) saturation data. In the context of geological carbon storage (GCS), 3D saturation data introduces unique challenges due to its sparse nature and sharp transitions at plume boundaries, known as shock fronts. To tackle these challenges, we developed a novel DL framework that combines dimension reduction with advanced 3D reconstruction techniques. Our approach utilizes latent variables derived from 2D average saturation fields to efficiently capture the essential features of high-dimensional data while reducing the number of variables. This enhances both the robustness and accuracy of DL models, making the framework more practical for real-world applications. By offering a tailored solution for modeling complex 3D saturation dynamics, this framework holds significant potential for environmental monitoring, energy storage, and other geological applications.

Wang, Hongsheng [University of Texas at Austin]↗
DOE OSTI2014

Emerging Technologies in the Built Environment: Geographic Information Science (GIS), 3D Printing, and Additive Manufacturing

Abstract 1: Geographic information systems emerged as a computer application in the late 1960s, led in part by projects at ORNL. The concept of a GIS has shifted through time in response to new applications and new technologies, and is now part of a much larger world of geospatial technology. This presentation discusses the relationship of GIS and estimating hourly and seasonal energy consumption profiles in the building sector at spatial scales down to the individual parcel. The method combines annual building energy simulations for city-specific prototypical buildings and commonly available geospatial data in a GIS framework. Abstract 2: This presentation focuses on 3D printing technologies and how they have rapidly evolved over the past couple of years. At a basic level, 3D printing produces physical models quickly and easily from 3D CAD, BIM (Building Information Models), and other digital data. Many AEC firms have adopted 3D printing as part of commercial building design development and project delivery. This presentation includes an overview of 3D printing, discusses its current use in building design, and talks about its future in relation to the HVAC industry. Abstract 3: This presentation discusses additive manufacturing and how it is revolutionizing the design of commercial and residential facilities. Additive manufacturing utilizes a broad range of direct manufacturing technologies, including electron beam melting, ultrasonic, extrusion, and laser metal deposition for rapid prototyping. While there is some overlap with the 3D printing talk, this presentation focuses on the materials aspect of additive manufacturing and also some of the more advanced technologies involved with rapid prototyping. These technologies include design of carbon fiber composites, lightweight metals processing, transient field processing, and more.

New, Joshua Ryan↗
DOE OSTI2022

DEEPER: An Intergrated Platform for Deeper Roots

Crops with deeper roots would have multiple benefits, including better drought tolerance, reduced requirement for nitrogen fertilizer, and better sequestration of atmospheric CO 2 . DEEPER is an integrated platform of phenomic, genomic, and in silico technologies to generate maize lines with deeper roots. DEEPER is: LEADER (Leaf Elemental Accumulation from Deep Roots) is a breakthrough technology to nondestructively measure rooting depth by using the plant itself as a sensor. LEADER uses handheld X-ray Fluorescence spectrometry to quantify foliar accumulation of elements that are differentially distributed in the soil profile. LEADER is nondestructive and is orders of magnitude cheaper, faster, and more precise than any competing assay of rooting depth in the field. LEADER is able to distinguish deep-rooted from shallow-rooted maize lines in the field without the need for costly and noisy soil coring. RootRobot/DIRT3D, to automatically phenotype root architecture in any field, combining RootRobot, a mechatronics platform to excavate, clean, section, and image mature root crowns, with DIRT3D, software to quantify architectural traits in 3D. Anatomics, a high-throughput platform to phenotype root anatomy, combining LAT 2.0, a technology for 3D imaging of root anatomy and composition, with RootScan3D, software to automatically extract 3D anatomical and cell wall composition metrics from LAT 2.0 output. Using this platform we discovered two novel root traits, parenchyma cell wall thickness and multiseriate cortical sclerenchyma, that improve rooting depth and drought tolerance in maize and wheat. OpenSimRoot/Deep, software to simulate root interaction with hard subsoils. Using this platform we discovered novel concepts regarding how to increase crop rooting depth by modulating how individual root axes respond to hard soil. DeepGenes, a toolkit of genes, parent lines, and genomic selection strategies to enable breeding hybrids with deeper roots. We discovered 3 novel root genes that increase rooting depth in maize and wheat. DEEPER discovered novel root phenotypes for deeper rooting, and delivered validated ideotypes for deeper-rooted maize; novel technologies to rapidly assess root depth, root architecture and anatomy in field-grown plants; novel software tools for root modeling and 3D image analysis of root architecture and anatomy; and validated genes and genomic selection models to deploy traits for deeper rooting in maize breeding. Each DEEPER technology is transformative in its own right, and exceeds existing technologies. They are mutually synergistic, deployable for field-grown plants, and are ready for application. The phenotyping and modeling technologies are readily applicable to many crops, and genetic leads in maize may have utility in other grasses. Taken as a whole they represent a transformative platform to develop deeper-rooted crops, with greater drought tolerance, reduced fertilizer requirement, and greater carbon sequestration.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

VALIDATION OF A RELAP5 POINT KINETICS MODEL OF TREAT

Development of advanced nuclear fuels requires testing of fuel specimens under various power-cooling mismatch conditions. The Transient Reactor Test (TREAT) facility at the Idaho National Laboratory will be used to provide transient nuclear heating of fuel specimens. Experiments will be conducted to support assessment of accident tolerant fuel designs being proposed for light water reactor applications. The experiments to be conducted at TREAT will provide data for the assessment of advanced, multi-physics computer codes. However, before the experiments can be performed, calculations are required to demonstrate that they will meet program objectives and that they can be performed safely in TREAT in the event of an unplanned reactivity insertion accident that occurs during the experiment. The safety calculations for the first experiments need to be performed in the next year and therefore will be performed with an existing computer code, RELAP5-3D. A point kinetics model of TREAT was developed for RELAP5-3D. The purpose of the model is to calculate the reactor power during experiments and to support the accident analyses of those experiments. The RELAP5-3D model was validated using data from nine TREAT experiments conducted previously. The RELAP5-3D model generates results that are in reasonable agreement with measured values of maximum core power, energy deposition, and maximum fuel temperature for a wide range of reactivity insertions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2013

Three-dimensional imaging of copper pillars using x-ray tomography within a scanning electron microscope: A simulation study based on synchrotron data

While microelectronic devices are frequently characterized with surface-sensitive techniques having nanometer resolution, interconnections used in 3D integration require 3D imaging with high penetration depth and deep sub-micrometer spatial resolution. X-ray tomography is well adapted to this situation. In this context, the purpose of this study is to assess a versatile and turn-key tomographic system allowing for 3D x-ray nanotomography of copper pillars. The tomography tool uses the thin electron beam of a scanning electron microscope (SEM) to provoke x-ray emission from specific metallic targets. Then, radiographs are recorded while the sample rotates in a conventional cone beam tomography scheme that ends up with 3D reconstructions of the pillar. Starting from copper pillars data, collected at the European Synchrotron Radiation Facility, we build a 3D numerical model of a copper pillar, paying particular attention to intermetallics. This model is then used to simulate physical radiographs of the pillar using the geometry of the SEM-hosted x-ray tomography system. Eventually, data are reconstructed and it is shown that the system makes it possible the quantification of 3D intermetallics volume in copper pillars. The paper also includes a prospective discussion about resolution issues.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Validation of Deterministic Broadband Ground Motion and Variability from Dynamic Rupture Simulations of Buried Thrust Earthquakes

According to the article, we numerically model broadband ground motion (up to 5–7.5 Hz⁠) from blind‐thrust scenario earthquakes matching the fault geometry of the 1994 Mw 6.7 Northridge earthquake. Several realizations are modeled (by varying the hypocenter location in the dynamic rupture simulation) in a 1D‐layered velocity profile. In addition, we include Q(f )⁠, nonlinear effects from Drucker–Prager plasticity, and superimpose small‐scale medium complexity in both a 1D‐layered and 3D velocity model within the subsequent wave propagation. We investigate characteristics of the ground motion and its variability up to 50 km from the fault by comparing them with ground‐motion prediction equations (GMPEs), simple proxy metrics, as well as strong ground motion records from the Northridge event. We find that median ground motion closely follows the trend predicted by GMPEs and that the intraevent standard deviation, although varying with hypocenter location, lies near that of GMPE models. Plasticity affects ground‐motion amplitudes in regions near the source, reducing intraevent variability above ∼0.5 Hz⁠. Heterogeneity in the velocity structure on both the regional and small scales is needed for the simulated data to match two proxy metrics: the period‐to‐period correlation of spectral acceleration (SA) and the ratio of maximum‐to‐median SA. Although small‐scale heterogeneity has a negligible effect on median SA for this style of rupture, it serves to significantly increase the cumulative absolute velocity, better agreeing with observations. When compared with strong‐motion data, we find that long‐wavelength velocity structure within our deterministic simulations reduces bias at both short and long periods. Finally, synthetic ground motion at both footwall and hanging‐wall sites has no clear dependence on the distance to rupture (at both short and long periods); directivity is likely overpowering any hanging‐wall effect.

Geochemistry & Geophysics↗
DOE OSTI2023

SCALE Modeling of the Sodium Cooled Fast-Spectrum Advanced Burner Test Reactor

This report documents the modeling and simulation of a sodium-cooled fast reactor (SFR) as part of a U.S. Nuclear Regulatory Commission–sponsored project to assess the modeling and simulation capabilities for accident progression, source term, and consequence analysis for advanced reactor technologies with the Oak Ridge National Laboratory code SCALE and the Sandia National Laboratories (SNL) code MELCOR. Based on publicly available benchmark specifications, a fully heterogeneous 3D SCALE model of the 250 MWth Advanced Burner Test Reactor (ABTR) was developed to demonstrate SCALE’s capabilities for full-core reactivity analysis, fuel inventory prediction, and decay heat analysis of an SFR. The benchmark specifications contain modeling details for the ABTR core at the beginning of equilibrium cycle (BOEC) at operating conditions; they were derived from a 2006 preconceptual design report produced by Argonne National Laboratory. The ABTR was designed to demonstrate reactor-based transmutation of transuranics, that is, to “burn” transuranics recovered from light-water reactor (LWR) spent fuel. The ABTR’s fuel is designed to operate in 4 month cycles using uranium/transuranic (U/TRU) metallic fuel, with a TRU content of approximately 20%, at a conversion ratio of approximately 0.6. Various reactivity calculations were performed with SCALE for the ABTR and, where possible, compared with results available in the open literature. Additionally, SCALE was used to perform a full-core depletion calculation over the 4 month cycle to obtain the nuclide inventory at the end of equilibrium cycle (EOEC). These nuclide inventories, decay heat, power profiles, and reactivity feedback coefficients at EOEC represent the initial conditions for analyzing severe accident scenarios with MELCOR.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Real Space Quantum Cluster Formulation for the Typical Medium Theory of Anderson Localization

We develop a real space cluster extension of the typical medium theory (cluster-TMT) to study Anderson localization. By construction, the cluster-TMT approach is formally equivalent to the real space cluster extension of the dynamical mean field theory. Applying the developed method to the 3D Anderson model with a box disorder distribution, we demonstrate that cluster-TMT successfully captures the localization phenomena in all disorder regimes. As a function of the cluster size, our method obtains the correct critical disorder strength for the Anderson localization in 3D, and systematically recovers the re-entrance behavior of the mobility edge. From a general perspective, our developed methodology offers the potential to study Anderson localization at surfaces within quantum embedding theory. This opens the door to studying the interplay between topology and Anderson localization from first principles.

36 MATERIALS SCIENCE↗