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At least 1,585 records · Page 88
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Size Effects on Laser Powder Bed Fusion and Laser Powder Directed Energy Deposition GRCop-42 Alloy

Additive manufacturing (AM) plays a significant role in the fabrication of regeneratively cooled rocket engine combustion chambers, where internal channels are used to transport high pressure propellants to keep the engine from overheating. Cooling channels are designed with thin walls between the cooling and combustion sides, experiencing high thermal and mechanical stresses from large temperature gradients and internal pressures. Hence, selecting materials suited for this environment and maintaining a high-quality processing for this critical application is of utmost importance. GRCop-alloys (Cu-Cr-Nb) were developed as an ideal material for combustion chambers due to its high conductivity and high strength at temperature, being employed as a structural member for the hotwall with excellent heat transfer capabilities. GRCop-42 (Cu, 4 at% Cr, 2 at% Nb) has significantly matured using the Laser Powder Bed Fusion (L-PBF) process through microstructure, mechanical and thermophysical properties and evaluations using hot-fire testing. Additionally, Laser Powder Directed Energy Deposition (LP-DED) has demonstrated successful deposition and geometry samples using GRCop-42. While the maturation in properties has focused on bulk material properties from standard test specimens, these cannot be extrapolated to be used in thin walls, as different features (i.e., microstructure, porosity, and surface texture) have a greater effect on thin walls, especially on AM structures built using L-PBF and LP-DED. This presentation provides an overview of the effects introduced by reducing the thickness on the fabrication, microstructure, surface metrology and subsequent mechanical properties of GRCop-42 using L-PBF and LP-DED as well as future work planned for this research.

Gabriel Demeneghi↗
NASA NTRSDate not supplied

Towards A Flexible Data Fusion Tool Incorporating Model, Satellite, Regulatory Monitor and Low-Cost Sensor Data for Air Quality Estimation and Forecasting

Air quality managers, researchers, and concerned community scientists around the world have a variety of sources for air quality information, ranging from traditional regulatory monitoring networks and atmospheric chemistry models to remote sensing data products and low-cost sensor networks. However, the ability to incorporate data from these disparate sources and synthesize a comprehensive overview of the local air quality situation remains a considerable barrier for many end-users. This presentation will outline a tool, currently in development, which will address this need using a flexible data fusion approach. The tool will make use of air quality forecast model outputs (primarily from the NASA GEOS-CF composition forecast modeling system), satellite remote sensing data (from instruments including MODIS, VIIRS, TROPOMI, plus TEMPO for the US when available), and in-situ data from official regulatory and/or low-cost networks where these are available. The ability to incorporate data from low-cost sensor networks will be a key feature of the tool; it will make use of other available data sources to calibrate the low-cost sensor data on a regional scale, then use these calibrated low-cost sensor data for localized updating to resolve finer-scale air quality patterns. Development of this tool is taking place with the help of national and international partners and end-user groups, coordinated through the US EPA and the United Nations Environment Programme (UNEP). The tool is being developed on the Google Earth Engine cloud computing platform to facilitate integration of diverse data sources and free access by a broad community of end-users. Stewardship of the tool will be passed to US EPA and UNEP to support future activities with end-users in the US and around the world, and the tool itself will remain freely accessible. We hope that this tool will lower the barrier to entry for various user groups worldwide, including community scientists, who struggle to integrate disparate data sources to gain insight into their local air quality situations. This presentation will cover the early stages of the development of the tool, including the underlying methods and some pilot case studies in integrating low-cost sensor data.

global models↗
NASA NTRSDate not supplied

Fusion of Hyperspectral Sounder Products Via Spectral Fingerprinting Methodology

Satellite based measurements of top-of-atmosphere (TOA) spectral radiances in the infrared (IR) region have been in existence for almost two decades and are expected to be continued in the following decades. The data from multiple hyper-spectral IR sounders can therefore be combined to build a long-term data record to further global scale climate trend research. Challenges associated with the fusion of data from different sensors come from the stability and consistency requirement on the climate record. The direct radiance observations from different sounders need to be homogenized by reconciling the differences in calibration, spectral response function (SRF), and spatial-temporal sampling. When geophysical variables derived from radiances measured by different sounders are combined to form long-term climate records, the impacts of any inconsistencies between overlapping measurements on the retrieval must be carefully assessed in order to estimate the uncertainty of the corresponding climate anomalies/trends derived. This paper presents a novel climate fingerprinting methodology and establishes a rigorously-defined inverse relationship that allows us to efficiently evaluate the change in essential climate variables from the change in spectral radiances measured in prescribed spatial and temporal averaging scales. The inverse spectral fingerprinting relationship is constructed based on a unified spectral kernel scheme, providing a direct means for quantifying the potential discontinuity in the derived climate anomalies due to inconsistencies between overlapping measurements. We show in this paper a sample application of using the spectral fingerprinting scheme to derive long-term, global-scale surface temperatures from the Climate Hyperspectral Infrared Radiance Product (CHIRP) and quantify the inter-satellite biases.

Wan Wu↗
NASA NTRS2020

Continuity of A Global, Satellite-Based Terrestrial Primary Productivity Dataset in the VIIRS Era Achieved With Model-Data Fusion

The NASA Terra and Aqua satellites have been successfully operating for over two decades and have far exceeded their original 5‐year design life. However, the era of NASA’s Earth Observing System (EOS) may be coming to a close as early as 2023. We conducted a comprehensive calibration and validation of the MODIS MOD17 product [1,2] and the potential for continuity of multi‐decadal ecosystem gross primary productivity (GPP) and annual net primary productivity (NPP), using data from the Visible Infrared Imaging Radiometer Suite (VIIRS) sensors aboard Suomi NPP and NOAA‐20. We combined an 18‐year record of eddy covariance flux tower measurements with hundreds of field measurements of NPP from the Oak Ridge National Laboratories Multi‐Biome collection to benchmark MODIS MOD17 Collection 6.1 (C61) and to develop the first terrestrial productivity estimates from VIIRS. Plant traits from the literature and the global TRY database [3,4] provide strong priors for identifying model parameters in a Bayesian model‐data fusion. As MODIS‐like observations are still needed for global environmental applications, the new VIIRS VNP17 product has the potential to extend these continuous estimates of global, terrestrial primary productivity beyond 2030.

K. Arthur Endsley↗
NASA NTRSDate not supplied

Data Fusion and Mining Techniques to Map Water Use and Drought across Spatial and Temporal Scales

As the world’s water resources come under increasing tension due to dual stressors of climate change and population growth, accurate knowledge of water consumption through evapotranspiration (ET) over a range in spatial scales will be critical in developing adaptation strategies. Remote sensing methods for monitoring consumptive water use (e.g, ET) are becoming increasingly important, especially in areas of significant water and food insecurity. One method to estimate ET from satellite-based methods, the Atmosphere Land Exchange Inverse (ALEXI) model uses the change in mid-morning land surface temperature to estimate the partitioning of sensible and latent heat fluxes which are then used to estimate daily ET. This presentation will outline several recent enhancements to the ALEXI modeling system, with a focus on global ET and drought monitoring. Until recently, ALEXI has been limited to areas with high resolution temporal sampling of geostationary sensors. The use of geostationary sensors makes global mapping a complicated process, especially for real-time applications, as data from as many as five different sensors are required to be ingested and harmonized to create a global mosaic. However, our research team has developed a new and novel method of using twice-daily observations from polar-orbiting sensors such as MODIS and VIIRS to estimate the mid-morning rise in LST that is used to drive the energy balance estimations within ALEXI. This allows the method to be applied globally using a single sensor (in this case, initially MODIS with a planned transition to VIIRS) rather than a global compositing of all available geostationary data. Other advantages of this new method include the higher spatial resolution provided by MODIS and VIIRS and the increased sampling at high latitudes where oblique view angles limit the utility of geostationary sensors. This presentation will focus on global applications for mapping water use and drought using data mining and data fusion across spatial scales extending from 5-km to 30-m “field-scale” estimates.

Christopher Hain↗
NASA NTRSDate not supplied

Heat Treatment Optimization of Laser Powder Bed Fusion Additive Manufacture C103

Laser Powder Bed Fusion (L-PBF) and Laser Powder Directed Energy Deposition (LP-DED) additive manufacture C103 is in development for propulsion applications that operate under extreme environments. The standard post-process heat treatment has called for vacuum stress relief, however, depending on the application or certification requirements hot isostatic press (HIP) may be required. Although C103 density responds well to HIP the associated grain growth results in a reduction in mechanical properties. An investigation was conducted to look at the potential benefit of leveraging HIP followed by rapid cooling to minimize grain growth. A series of heat treatment schedules varying temperature and pressure were conducted followed by microstructural and mechanical characterization.

Additive Manufacturing↗
NASA NTRSDate not supplied

Air Quality Data Fusion with Sensors, Satellites, and Models

Poor air quality is a major global public health concern, which is only projected to get worse in coming years. A comprehensive understanding of current and potential future air quality and its key drivers spanning from local to global scales is needed to tackle this important problem. This presentation will outline the sources of information that we use to understand air quality, including ground-based measurements, satellites, and models. After giving an overview of these data sources and outlining their strengths and limitations, we will take a look at how they can be used together to give us a better picture of air quality locally and globally with data fusion techniques.

Carl Malings↗
NASA NTRSDate not supplied

Distributed Visual Sensing and Fusion for Advanced Air Mobility

Surveillance solutions for Advanced and Urban Air Mobility frameworks are a key factor to enable safe operations of highly automated aircraft in the civil airspace. To design solutions suitable for all types of aircraft, non-cooperative sensors can be used, though many challenges arise when the small dimensions of the vehicles and their proximity to the ground during low-altitude missions are considered. A distributed sensing concept can be efficiently applied to address these challenges by exploiting multiple sensors within a surveillance network. This paper proposes a strategy to fuse the information collected by three ground-fixed cameras within a network of multiple distributed sensors and is tested with during experimental flight tests. The solution exploits standalone tracking estimates of each camera within a fusion center that performs triangulation and three-dimensional tracking. This approach is tested in a scenario involving two small UAVs flying at low altitude. The paper deals with the challenges of associating the two objects from independent and unrelated tracks to achieve robust triangulation, which produces meter-level mean errors with respect to GNSS-based ground truth.

Federica Vitiello↗
NASA NTRSDate not supplied

A Novel Framework for Multi-Path Data Fusion in Earth Observation and New Observing Strategies: Applications to Predicting Forest Canopy Height

Exponential growth of data from Earth Observation (EO) assets has necessitated the development of sophisticated methods for data interpretation and management. NASA’s New Observing Strategy (NOS) approach aims to coordinate operations among complex heterogenous systems of constellations, requiring advanced Artificial Intelligence and Machine Learning (AI/ML) techniques. Despite significant advancements in AI/ML across various domains, the EO and machine learning for satellite (SatML) fields remain fragmented, often relying on adapted techniques rather than domain-specific solutions. We present a novel end-to-end data fusion framework tailored specifically for EO and SatML, addressing this gap by facilitating rapid development of AI/ML applications. This framework, called, Multimodal Earth Observation Workflow for Machine Learning (MEOW-ML), sup- ports the entire AI/ML lifecycle, from dataset manipulation, to model training, evaluation, and logging, and is designed to expedite the development of next-generation NOS deployments and SOTA in EO. We apply our framework to predict canopy height model (CHM) derived from lidar data. We integrate multiple data modalities through a hierarchical, multi-path model architecture, effectively identifying and leveraging the unique strengths of each data source to enhance predictive accuracy. Our experiments demonstrate that the multi-path architecture outperforms traditional single-path models and provides significant advantages in both accuracy and computational efficiency.

Mark Moussa↗
NASA NTRSDate not supplied

Uncertainty Quantification and Sensitivity Analysis in Process-Structure-Property Simulations for Laser Powder Bed Fusion Additive Manufacturing

Process variations and process-induced defects like porosity cause significant uncertainty in the microstructure and mechanical behavior of additively manufactured metals. Establishing process-structure-property (PSP) relationships and quantifying uncertainty using experiments alone is costly, especially for structural applications where mechanical allowables must be established for qualification and certification. This work presents a PSP simulation framework for laser powder bed fusion with a focus on uncertainty quantification through probabilistic calibration and multi-fidelity uncertainty propagation. Motivated by phenomenological input parameters related to grain nucleation and growth that are difficult to characterize, a global sensitivity analysis (GSA) is completed. Through GSA, the most important input parameters are identified based on their influence on the statistical distributions of microstructural metrics that influence mechanical behavior, including grain size, morphology, and crystallographic texture. The results provide insight on what experiments are necessary to quantify and control PSP uncertainties, particularly those associated with the more challenging input parameters.

additive manufacturing↗
NASA NTRSDate not supplied

Development of Laser Powder Bed Fusion NASA HR-2 for Hydrogen Sensitive Liquid Rocket Engine Applications

The National Aeronautics and Space Administration (NASA) has been involved in the development and maturation of metal additive manufacturing (AM) for space applications since the late 2000s. AM has provided new design and manufacturing opportunities to reduce cost and schedule, consolidate parts, and optimize performance. Laser Powder Bed Fusion (L-PBF) is one of the most commonly used AM processes to fabricate components of complex shape requiring fine feature resolution. Due to exposure to high-pressure gaseous hydrogen, mechanical property degradation caused by hydrogen environment embrittlement (HEE) is a critical concern for many materials in liquid hydrogen propulsion systems. NASA has identified the need to develop and advance new materials in unique engine applications using liquid hydrogen as a propellant. One such material being developed at NASA Marshall Space Flight Center is L-PBF NASA HR-2 (Hydrogen Resistant-2), a high-strength Fe-Ni-based superalloy resistant to HEE. The chemistry of NASA HR-2 was formulated to meet requirements for key liquid rocket engine (LRE) components that operate in high-pressure hydrogen environments. Initial development and material characterization found that NASA HR-2 has excellent L-PBF printability, and its microstructure evolves well after heat treatment. This new alloy has undergone fundamental metallurgical evaluations, heat treatment studies, detailed microstructure characterization, and mechanical testing across a range of temperatures. Tensile testing was performed in a pressurized gaseous hydrogen (GH2) environment to assess its resistance to HEE. L-PBF NASA HR-2 has an average yield stress of 95 ksi, an ultimate tensile stress of 165 ksi, and a very high fracture elongation of 34 - 36% when tested in a high-pressure (5 ksi) hydrogen environment. The tensile property data confirms hydrogen has little influence on HR-2’s ductility, strength, and fracture behavior. L-PBF NASA HR-2 is a promising option for many hydrogen-sensitive LRE components that require exceptional resistance to HEE. This paper will provide an overview of the L-PBF process development, material characterization, mechanical and thermophysical properties, and LRE hardware development for NASA HR-2.

Po S Chen↗
DOE OSTI2021

Experiment Based Superposition Thermal Modeling of Laser Powder Bed Fusion

This paper evaluates experiment-based superposition thermal modeling for Laser Powder Bed Fusion (LPBF) with a pulsed laser. An analytical pulsed laser thermal model establishes the modeling procedure. The framework inverts a powder bed’s single pulse temperature response from experimental spatiotemporal Short-Wave Infrared (SWIR) camera data. Superimposing this response along a scan path simulates multi-pulse LPBF. Results show the experimentally informed superposition model rapidly and accurately predicts a layer’s temperature history. The model has applications in correction of thermally driven LPBF errors and in-situ part qualification.

Lough, Cody↗
DOE OSTI2021

Electron Beam Powder Bed Fusion Additive Manufacturing of Refractory Metals

The processing of refractory metals via additive manufacturing (AM) presents an opportunity to fabricatecomponents not possible through traditional powder metallurgy techniques. However, processing via AM isextremely challenging and there exist a host of technological limitations still unaddressed. Molybdenumand tungsten are two materials of particular interest for nuclear energy generation applications. Themajority of existing work on the processing of these materials is focused on laser powder bed fusion whereasa smaller body of work exists for electron beam melting AM. In general, material with acceptable densitycan be obtained via both routes however cracking is much more difficult to mitigate against. Strongcrystallographic fiber textures have been observed across a range of refractory systems. In this work wepresent our recent findings on electron beam melting AM of pure tungsten and molybdenum. Wedemonstrate that defect-free material can be obtained in both systems with appropriate processing. Strongbuild direction crystallographic texture fibers are observed in both systems. In molybdenum the fibertexture has direct impact on the resulting tensile behavior. These results demonstrate that electron beamAM is a suitable technology for processing these difficult to fabricate materials.

Fernandez-Zelaia, Patxi↗
DOE OSTI2023

Fundamentals of Polymer Crystallization in Laser Powder Bed Fusion for New Material Screening

Although laser powder bed fusion (PBF/LB) was one of the first industrially viable additive manufacturing (AM) methods for end-use part production, polyamides remain grossly dominant at both the commercial- and researchscale. The research community continues to develop and refine “rapid screening” methods for evaluating the suitability of a new polymer for PBF/LB. The so-called “SLS Process Window,” which is the difference between melting and crystallization temperature measured at 10 K min-1 as originally outlined in the patent literature, is perhaps the most often reported screening method. Although perhaps appropriate as part of a larger study, the simplistic guidelines put forth by the “SLS Process Window” are not sufficiently scientifically rigorous to understand how crystallization kinetics affects successful 3D printing. The common understanding of the SLS Process Window omits details from published theories of polymer crystallization. as evidenced by published assumptions and methods in PBF/LB process modeling papers. The authors explain polymer crystallization in the PBF/LB process context and propose replacing the “process window” with crystallization halftime and physical gelation for new material screening. These measurements better represent behavior critical for ensuring a lengthy coexistence of solid powder and molten polymer affecting warp-free parts.

CHATHAM, CAMDEN A.↗
DOE OSTI2025

Airport Delay Prediction with Temporal Fusion Transformers

Since flight delay hurts passengers, airlines, and airports, its prediction becomes crucial for the decision-making of all stakeholders in the aviation industry and thus has been attempted by various previous research. However, previous delay predictions are often categorical and at a highly aggregated level. To improve that, this study proposes to apply the novel Temporal Fusion Transformer model and predict numerical airport arrival delays at quarter hour level for U.S. top 30 airports. Inputs to our model include airport demand and capacity forecasts, historic airport operation efficiency information, airport wind and visibility conditions, as well as en-route weather and traffic conditions. The results show that our model achieves satisfactory performance measured by small prediction errors on the test set. In addition, the interpretability analysis of the model outputs identifies the important input factors for delay prediction.

Liu, Ke [University of California Berkeley]↗
DOE OSTI2024

Fusion proteins useful for modifying terpenes

The present invention provides for a fusion protein comprising: (a) a terpene synthase (TS), or a homolog thereof, (b) a peptide linker, and (c) a P450 enzyme, or a homolog thereof.

Lee, Taek Soon↗
DOE OSTI2024

System and method for large-area pulsed laser melting of metallic powder in a laser powder bed fusion application

The present disclosure relates to systems and methods for performing large area laser powder bed fusion (LBPF) to form a plurality of layers of a 3D part in a layer-by-layer fashion using meltable powder particles. In one implementation the system makes use of a first light source, which may be a diode laser subsystem, for generating a first light pulse of a first duration. The first light is used to preheat a substrate underneath a new layer of powder particles, wherein the substrate is formed from a previously fused quantity of the powder particles. A second light source, which may be a pulse laser, generates a second light pulse subsequent to the first light pulse. The second light pulse has a second duration shorter than the first duration by a factor of at least about 10, and fully melts the new layer of powder particles in addition to the substrate, to achieve a smooth printed layer. The wavelength of the first light pulse also differs from a wavelength of the second light pulse.

Khairallah, Saad A.↗
DOE OSTI2021

Diii-D Research Advancing The Physics Basis For Optimizing The Tokamak Approach To Fusion Energy

DIII-D physics research addresses critical challenges for operation of ITER and the next generation of fusion energy devices. This is done through a focus on innovations to provide solutions for high performance long pulse operation, coupled with fundamental plasma physics understanding and model validation, to drive scenario development by integrating high performance core and boundary plasmas. Substantial increases in off-axis current drive efficiency from an innovative top launch system for EC power, and in pressure broadening for Alfven eigenmode control from a co-/counter-Ip steerable off-axis neutral beam, all improve the prospects for optimization of future long pulse/steady state high performance tokamak operation. Fundamental studies into the modes that drive the evolution of the pedestal pressure profile and electron vs. ion heat flux validate predictive models of pedestal recovery after ELMs. Understanding the physics mechanisms of ELM control and density pumpout by 3D magnetic perturbation fields leads to confident predictions for ITER and future devices. Validated modeling of high-Z shattered pellet injection for disruption mitigation, runaway electron dissipation, and techniques for disruption prediction and avoidance including machine learning, give confidence in handling disruptivity for future devices. With this physics understanding and suite of actuators, a high poloidal beta optimized-core scenario with an internal transport barrier that projects nearly to Q=10 in ITER at 9 MA was coupled to a detached divertor, and a near Super H-mode optimized-pedestal scenario with co-Ip beam injection, was coupled to a radiative divertor. The Hybrid core scenario was achieved directly, without the need for internal flux pumping, using off-axis current drive actuators, and a controller to avoid mode locking and disruptions in the ITER baseline scenario, based on plasma response to probing 3D fields, was demonstrated. Finally innovative tokamak operation using a negative triangularity shape showed many attractive features for future pilot plant operation.

Fenstermacher, M.↗