Search NASA⌕ Search

SEARCH · Search NASA

Results for “3D Integration”

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.

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

At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

ISSLIVE! Bringing the Space Station to Every Generation

Just 200 miles above us, the International Space Station (ISS) is orbiting. Each day, the astronauts on board perform a variety of activities from exercise, science experiments, and maintenance. Yet, many on the ground don?t know about these daily activities. ISSLive! - an education project - is working to bridge this knowledge gap with traditional education channels such as schools, but also non-traditional channels with the non-technical everyday public. ISSLive! provides a website that seamlessly integrates planning and telemetry data, video feeds, 3D models, and iOS and android applications. Through the site, users are able to view astronauts? daily schedules, in plain English alongside the original data. As an example, when an astronaut is working with a science experiment, a user will be able to read about the activity and for more detailed activities follow provided links to view more information -- all integrated into the same site. Live telemetry data from a predefined set can also be provided alongside the activities. For users to learn more, 3D models of the external and internal parts of the ISS are available, allowing users to explore the station and even select sensors, such as temperature, and view a real-time chart of the data. Even ground operations are modelled with a 3D mission control center, providing users information on the various flight control disciplines and showing live data that they would be monitoring. Some unique activities are also highlighted, and have dedicated spaces to explore in more detail. Education is the focus of ISSLive!, even from the beginning when university students participated in the development process as part of their master?s projects. Focus groups at a Houston school showed interest in the project, and excitement towards including ISSLive! in their classroom. Through this inclusion, student?s knowledge can be assessed with projects, oral presentations, and other assignments. For the public citizens outside of the traditional education system, ISSLive! provides a single, interactive, and engaging experience to learn about the ISS and its role in space exploration, international collaboration, and science. While traditional students are using ISSLive! in the classroom, their parents, grandparents, and friends are using it at home. ISSLive! truly brings the daily operations of the ISS into the daily lives of the public from every generation.

Harris, Philip D.↗
DOE OSTI2024

Robotics for Systems Integration in Buildings: Pilot Study of Viable Approaches to Install Hygrothermal and Rigid Electrical Systems

The Industrialized Construction Innovation (ICI) team at the National Renewable Energy Laboratory (NREL) has been exploring the use of robotics to integrate hygrothermal, mechanical, electrical, and plumbing systems in prefabricated building assemblies (off-site construction) and 3D-printed buildings (on-site construction). Such multisystem integration tasks often require specialized robots and custom end effectors to handle a range of rigid and nonrigid building components. This paper begins with a brief overview of the current state of robotics in construction, followed by a pilot study exploring the use of robotics to integrate a simple prototype multitrade wall assembly composed of structural studs, hygrothermal layer, wall finishing, and electrical fixtures. The study was funded by the US Department of Energy's (DOE's) Advanced Materials and Manufacturing Technologies Office (AMMTO). Insights about the implementation of design for manufacturing and assembly (DfMA) principles in designing the prototype wall for robotic assembly, and selection of appropriate robotic end-effector hardware to handle these components are included. Detailed comparison of computational toolpath simulations of the robotic assembly process and real-life demonstration of the same are presented. Finally, limitations and lessons learned from this study are included, along with future research recommendations for robotic assembly of more complex multitrade assemblies, including potential scenarios such as robotic outfitting of facilities in extraterrestrial environments.

advanced manufacturing↗
NASA NTRS2023

In-Space Manufacturing and Reclamation

The goal of this interdisciplinary senior design project is to develop a self-contained additive manufacturing machine with an integrated part recycler. The system is designed to be a sustainable manufacturing system on long-duration space flights with minimal interaction from on-board astronauts. Following a systems engineering approach, a commercially available and opensource 3D printer and recycler will be modified, integrated, and automated to satisfy the project goal. System components and subcomponents will be verified to meet requirements and risks will be assessed and mitigated.

Stephen Hawes↗
DOE OSTI2024

A fast, matrix-based method to perform omnidirectional pressure integration

Abstract Experimentally-measured pressure fields play an important role in understanding many fluid dynamics problems. Unfortunately, pressure fields are difficult to measure directly with non-invasive, spatially resolved diagnostics, and calculations of pressure from velocity have proven sensitive to error in the data. Omnidirectional line integration methods are usually more accurate and robust to these effects as compared to implicit Poisson equations, but have seen slower uptake due to the higher computational and memory costs, particularly in 3D domains. This paper demonstrates how omnidirectional line integration approaches can be converted to a matrix inversion problem. This novel formulation uses an iterative approach so that the boundary conditions are updated each step, preserving the convergence behavior of omnidirectional schemes while also keeping the computational efficiency of Poisson solvers. This method is implemented in Matlab and also as a GPU-accelerated code in CUDA-C++. The behavior of the new method is demonstrated on 2D and 3D synthetic and experimental data. Three-dimensional grid sizes of up to 125 million grid points are tractable with this method, opening exciting opportunities to perform volumetric pressure field estimation from 3D PIV measurements.

42 ENGINEERING↗
DOE OSTI2020

Dual 3D Ceramic Textile Electrodes: Fast Kinetics for Carbon Oxidation Reaction and Oxygen Reduction Reaction in Direct Carbon Fuel Cells at Reduced Temperatures

Abstract Direct carbon fuel cells (DCFCs) are an efficient energy‐conversion technology capable of generating electricity with carbon‐dioxide‐capture chemistry with solid carbon as fuels. The efficiency and performance of DCFCs depend on the kinetics of the carbon oxidation reactions (COR) and the oxygen reduction reactions (ORR), each occurring at anode and cathode, respectively. The limited active sites paired with reduced temperatures greatly decrease the efficiency of the electrochemical reactions. Ultraporous dual‐3D ceramic textiles (dual‐3DCT) are integrated into electrolyte‐supported DCFCs to enhance charge and mass transfer at the electrodes. Improved COR at the anode is achieved by the synergy between the 3DCT NiO–Ce 0.8 Gd 0.2 O 1.95 (GDC) structure and optimal carbon fuel choice. In a comparative study, DCFCs using graphitic carbon (GC) as fuel show the best COR performance when compared to DCFCs utilizing alternative fuels such as carbon black (CB) and activated carbon (AC). The 3DCT Sm 0.5 Sr 0.5 CoO 3‐δ –GDC (SSC–GDC) composite cathode shows electrochemical performance superior to that of the conventional screen‐printed SSC–GDC. A peak power density of 392 mW cm −2 at 600 °C is obtained in a DCFC using the 3DCT‐anode/electrolyte/3DCT‐cathode configuration, an unprecedented value for any reported DCFC as of yet. This points toward promising applications of dual‐3DCT electrodes for reduced‐temperature DCFCs.

Bian, Wenjuan↗
DOE OSTI2025

Thermodynamic Water Activity Explains the Unusual Electrochemical Stability of Aqueous Deep Eutectic Solvents

The presence of water in nonaqueous deep eutectic solvent (DES) electrolytes has been debated in recent years, with efforts ranging from its complete removal to willful addition. It was shown that controlled amounts of water can be beneficial, as it not only enhances the physicochemical properties of these electrolytes but also has no significant detrimental effects on their electrochemical stability. Despite these advantages, there is still limited understanding of how water interacts with DES systems at the molecular level. This study examines the water activity in ethylene glycol and glycerol, as well as their binary mixtures with choline chloride to form the DESs ethaline and glyceline, respectively. In this work, we show that the high electrochemical stability of glyceline is related to its lower water activity compared to ethaline and can be attributed to the robust H-bonding network formed by the three hydroxyl groups of glycerol. Its 3D H-bond network effectively integrates water molecules within its solvent structure, reducing degradation and maintaining stability at higher water contents. The deviations from the ideal Raoult's law behavior are reflected in the water activity and activity coefficients, which highlight the intricate H-bond interactions within DES-water mixtures. Water acts like a lubricant within the more viscous DES mixtures without being detrimental to their electrochemical performance. The presented results emphasize the necessity of customizing DES-water compositions to enhance their performance as electrolytes, especially in flow battery applications where electrochemical stability, ionic conductivity, and fluidity are of utmost importance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Phenome‐to‐genome insights for evaluating root system architecture in field studies of maize

Abstract Understanding the genetic basis of root system architecture (RSA) in crops requires innovative approaches that enable both high‐throughput and precise phenotyping in field conditions. In this study, we evaluated multiple phenotyping and analytical frameworks for quantifying RSA in mature, field‐grown maize in three field experiments. We used forward and reverse genetic approaches to evaluate >1700 maize root crowns, including a diversity panel, a biparental mapping population, and maize mutant and wild‐type alleles at two known RSA genes,DEEPER ROOTING 1(DRO1) andRootless1(Rt1). We show the utility of increasing the dimensionality of traditional two‐dimensional (2D) techniques, referred to as the “2D multi‐view” method, to improve the capture of whole root system information for mapping genetic variation influencing RSA. Comparison of univariate and multivariate genome‐wide association study (GWAS) approaches revealed that multivariate traits were effective at dissecting complex RSA phenotypes and identifying pleiotropic quantitative trait loci (QTLs). Overall, three‐dimensional (3D) root models generated from X‐ray computed tomography and digital phenotyping captured a larger proportion of RSA trait variations compared to other methods of root phenotyping, as evidenced by both genome‐wide and single‐gene analyses. Among the individual root traits, root pulling force emerged as a highly heritable estimate of RSA that identified the largest number of shared QTLs with 3D phenotypes. Our study shows that integrating complementary phenotyping technologies helps to provide a more comprehensive understanding of the genetic architecture of RSA in field‐grown maize.

Genetics & Heredity↗
DOE OSTI2025

Stimulated Raman Scattering Microscopy: Real-Time In-Situ Physical and Chemical Characterization of Reverse Osmosis Desalination Membrane Scaling

We introduce a stimulated Raman scattering (SRS) methodology designed for rapid, real-time, and in situ monitoring of RO membrane scaling adapted for bench-scale desalination flow cells. The methodology can provide new insights into membrane scaling dynamics by offering time-resolved reflection imaging of inorganic crystal growth, coupled with chemical identification from Raman spectral data. These capabilities allow for direct local measurement of the membrane surface area covered by different scalants as well as an approximation of the scalant volume using three-dimensional, integrated Raman intensity. The 2D and 3D SRS results obtained from CaSO 4 scaling experiments are compared to and are in reasonable agreement with those provided by confocal microscopy. The real-time physical and chemical characterization capabilities presented here could be extended to study combinations of inorganic, organic, and biological fouling. Overall, the SRS methodology represents an advancement in real-time sensing of membrane fouling that offers the potential for improved operation, lower cost, and more resilient RO membrane systems for sustainable water management.

42 ENGINEERING↗
DOE OSTI2024

Additive manufacturing of LiCoO 2 electrodes via vat photopolymerization for lithium ion batteries

Additive manufacturing has the potential to revolutionize the fabrication of lithium-ion batteries for a diversity of applications including in portable, biomedical, aerospace, and the transportation fields. Standard commercial batteries consist of stacked layers of various components (current collectors, cathode, anode, separator and electrolyte) in a two-dimensional manner. By leveraging the latest advances in additive manufacturing and computer-aided design, an improved geometric and electrochemical configuration of these batteries can maximize energy efficiency while allowing design optimization to reduce dead space for a given application. In this work, a composite UV photosensitive resin was prepared and used as feedstock in a vat photopolymerization system. The resin was loaded with LiCoO 2 acting as electrochemically active material for the cathode of a lithium-ion battery, and was further improved with the addition of conductivity-enhancing carbonaceous additives. Challenges to additive manufacturing arise from the opacity and high viscosity of the composite nature of these electrochemically-active resins, which cause light refraction during selective UV curing. Subsequently, items were printed and subjected to a thermal post-processing step to obtain an adequate compromise between electrochemical performance and mechanical integrity. Both sintered and green state 3D printed cathodes were assembled into half-cell lithium-ion batteries using lithium metal as a reference and counter electrode. Electrochemical cycling of these batteries yielded satisfactory results approaching commercial LiCoO 2 cathodes’ performance, with the potential advantages of additive manufacturing – high surface area anode–cathode configurations for power performance as well as shape conformability.

25 ENERGY STORAGE↗
DOE OSTI2025

Robotic Assembly of SRF Cavity Pair

Superconducting Radio Frequency (SRF) cavities for particle accelerators require tight tolerances, ultrahigh vacuum, and strict cleanliness during assembly. As in the semiconductor industry, defects such as particles and residues are deleterious to performance, possibly rendering a cavity unfit for use. This problem is addressed primarily through cleanroom assembly during sensitive steps and rigorous chemical processing to prevent and remove such defects. Human workers are often the largest source of contamination, even with proper gowning and practices. The semiconductor industry has long integrated robots in cleanroom operation, but this has not occurred for SRF cavity production; SRF cavities, unlike wafers, are complex shapes, require more hands-on mechanical assembly, and are low-volume production items. At Jefferson Laboratory, a co-operative robot (cobot) has been setup to overcome these problems. Cobots are safe for use alongside human workers and can integrate new tools such as a 3D camera part detection and gripper for item manipulation. Therefore, cobots represent a promising avenue for reducing particulate generated during a variety of assembly tasks. A mockup of a cavity pair and coupler was setup and the cobot programmed to automatically pick up the coupler and place on the mating cavity flange. Particle counting methods were setup to measure human vs cobot assembly particulate generation inside a cavity mockup. Other potential uses will be discussed for further improving SRF cavity assembly steps, where a cobot can replace or assist a human operator, and what potential gains are expected.

Duzik, Adam [Thomas Jefferson National Accelerator↗
NASA NTRS1990

Robotics technology discipline

Viewgraphs on robotics technology discipline for Space Station Freedom are presented. Topics covered include: mechanisms; sensors; systems engineering processes for integrated robotics; man/machine cooperative control; 3D-real-time machine perception; multiple arm redundancy control; manipulator control from a movable base; multi-agent reasoning; and surfacing evolution technologies.

Montemerlo, Melvin D.↗
NASA NTRS2009

Coastal Online Analysis and Synthesis Tool 2.0 (COAST)

The Coastal Online Assessment and Synthesis Tool (COAST) 3D geobrowser has been developed to integrate disparate coastal datasets from NASA and other sources into a desktop tool that provides new data visualization and analysis capabilities for coastal researchers, managers, and residents. It is built upon the widely used NASA-developed open source World Wind geobrowser from NASA Ames (Patrick Hogan et al.) .Net and C# version is used for development. It is leveraged off of World Wind community shared code samples and COAST 2.0 enhancement direction is based on Coastal science community feedback and needs assessment (GOMA). The main objective is to empower the user to bring more user-meaningful data into multi-layered, multi-temporal spatial context.

Brown, Richard B.↗
NASA NTRS2012

Parametric Deformation of Discrete Geometry for Aerodynamic Shape Design

We present a versatile discrete geometry manipulation platform for aerospace vehicle shape optimization. The platform is based on the geometry kernel of an open-source modeling tool called Blender and offers access to four parametric deformation techniques: lattice, cage-based, skeletal, and direct manipulation. Custom deformation methods are implemented as plugins, and the kernel is controlled through a scripting interface. Surface sensitivities are provided to support gradient-based optimization. The platform architecture allows the use of geometry pipelines, where multiple modelers are used in sequence, enabling manipulation difficult or impossible to achieve with a constructive modeler or deformer alone. We implement an intuitive custom deformation method in which a set of surface points serve as the design variables and user-specified constraints are intrinsically satisfied. We test our geometry platform on several design examples using an aerodynamic design framework based on Cartesian grids. We examine inverse airfoil design and shape matching and perform lift-constrained drag minimization on an airfoil with thickness constraints. A transport wing-fuselage integration problem demonstrates the approach in 3D. In a final example, our platform is pipelined with a constructive modeler to parabolically sweep a wingtip while applying a 1-G loading deformation across the wingspan. This work is an important first step towards the larger goal of leveraging the investment of the graphics industry to improve the state-of-the-art in aerospace geometry tools.

Anderson, George R.↗
NASA NTRSDate not supplied

Autonomous Measurement of Electrochemical Redox Couples for In-Situ Characterization of Enceladus Plume Samples

A 3D-printed microfluidic electrochemical cell with integrated electrodes was developed to demonstrate autonomous in-situ electrochemical characterization of terrestrial seawater samples. The system is designed to extend the capabilities of the 2008 Phoenix Lander’s Wet Chemistry Laboratory (WCL) that analyzed the soluble chemistry of the Martian soil, by miniaturizing its fluidic architecture for analysis of µL-volume samples as expected from an Enceladus fly-by mission. The microfluidic device has a total fluid volume of 48 µL and includes dual channels each populated with 7 electrodes. Measurement of pH was measured using an iridium oxide electrode. Cyclic voltammetry with Au, Pt, and glassy carbon working electrodes was used to measure redox couples in synthetic seawater that contained inorganic and bio-organic molecules. Glassy carbon was found to have minimal risk of interference from constituents of synthetic seawater when measuring molecular organic redox species; however, care must be used to prevent interference due to potential oxidation or dissolution in the case of Au working electrodes. A completely autonomous end-to-end run including sample delivery was performed, to demonstrate the feasibility of microfluidic-based cyclic voltammetry measurements for in-situ characterization of redox couples in Ocean World samples.

Planetary Instruments↗
DOE OSTI2022

Gas-mapping 3D imager measurement techniques and method of data processing

Measurement approaches and data analysis methods are disclosed for combining 3D topographic data with spatially-registered gas concentration data to increase the efficiency of gas monitoring and leak detection tasks. Here, the metric for efficiency is defined as reducing the measurement time required to achieve the detection, or non-detection, of a gas leak with a desired confidence level. Methods are presented for localizing and quantifying detected gas leaks. Particular attention is paid to the combination of 3D spatial data with path-integrated gas concentration measurements acquired using remote gas sensing technologies, as this data can be used to determine the path-averaged gas concentration between the sensor and points in the measurement scene. Path-averaged gas concentration data is useful for finding and quantifying localized regions of elevated (or anomalous) gas concentration making it ideal for a variety of applications including: oil and gas pipeline monitoring, facility leak and emissions monitoring, and environmental monitoring.

Thorpe, Michael↗
DOE OSTI2022

Implementing Spatio-Temporal 3D-Convolution Neural Networks and UAV Time Series Imagery to Better Predict Lodging Damage in Sorghum

Unmanned aerial vehicle (UAV)-based remote sensing is gaining momentum in a variety of agricultural and environmental applications. Very-high-resolution remote sensing image sets collected repeatedly throughout a crop growing season are becoming increasingly common. Analytical methods able to learn from both spatial and time dimensions of the data may allow for an improved estimation of crop traits, as well as the effects of genetics and the environment on these traits. Multispectral and geometric time series imagery was collected by UAV on 11 dates, along with ground-truth data, in a field trial of 866 genetically diverse biomass sorghum accessions. We compared the performance of Convolution Neural Network (CNN) architectures that used image data from single dates (two spatial dimensions, 2D) versus multiple dates (two spatial dimensions + temporal dimension, 3D) to estimate lodging detection and severity. Lodging was detected with 3D-CNN analysis of time series imagery with 0.88 accuracy, 0.92 Precision, and 0.83 Recall. This outperformed the best 2D-CNN on a single date with 0.85 accuracy, 0.84 Precision, and 0.76 Recall. The variation in lodging severity was estimated by the best 3D-CNN analysis with 9.4% mean absolute error (MAE), 11.9% root mean square error (RMSE), and goodness-of-fit (R2) of 0.76. This was a significant improvement over the best 2D-CNN analysis with 11.84% MAE, 14.91% RMSE, and 0.63 R2. The success of the improved 3D-CNN analysis approach depended on the inclusion of “before and after” data, i.e., images collected on dates before and after the lodging event. The integration of geometric and spectral features with 3D-CNN architecture was also key to the improved assessment of lodging severity, which is an important and difficult-to-assess phenomenon in bioenergy feedstocks such as biomass sorghum. This demonstrates that spatio-temporal CNN architectures based on UAV time series imagery have significant potential to enhance plant phenotyping capabilities in crop breeding and Precision agriculture applications.

3D-convolution neural networks↗