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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Unified Software Architecture for Advanced Materials and Manufacturing Technologies Data Management and Processing: FY 2023 Multidimensional Data Correlation Platform

This report details the various digital manufacturing activities ongoing at ORNL as part of the Advanced Materials and Manufacturing Technologies (AMMT) program. The AMMT program is exploring a data-driven approach to demonstrate the use of AM for the fabrication of components for nuclear applications, with the goal of providing a greater understanding of manufacturing quality outcomes that would pave the way toward the development of standards for certification and qualification. The objective of this work package is to establish a digital manufacturing discipline common to all participants of the AMMT program to improve the performance, reliability, and lifetime of nuclear components. As part of this effort, we will develop a unified software architecture for AMMT data management and processing, deploy the digital platform across AMMT participants’ facilities, and generate pedigreed datasets in a common format across multiple labs and facilities. To this end, the MDDC work package has focused on three activities during FY23. First, the MDF Digital Tool was overhauled to better serve the needs of the AMMT program. Next, multiple laser powder bed fusion (L-PBF) systems at the MDF were upgraded to a common sensor package for collecting comparable in situ data across machines. Finally, various improvements relevant to the AMMT program were implemented in the ORNL-developed software tool, Peregrine. This report marks the completion of FY23 milestone M3CR-22OR0403051: Report Describing the Architecture of the Digital Platform to Support AMMT Activities.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Novel Hot Gas Components for Gas Turbine Engines Enabled by Materials and Additive Manufacturing Process Development

Additive Manufacturing (AM), also known as 3D printing, has emerged as a manufacturing method that enables new design freedom for gas turbine engine manufacturers. However, the material selection for AM processable high-temperature super alloys is currently limited. Additionally, the heat transfer performance of AM enabled micro-cooling architectures is not yet well understood. Accordingly, in support of advanced manufacturing and engine performance development, Oak Ridge National Laboratory (ORNL)and Solar Turbines (Solar) conducted a multidisciplinary project to generate both AM super alloy material properties data and micro-channel performance data for two AM super alloys. The data supported the design and analysis of an internally cooled turbine hot section AM tip shoe component. This data was used to analytically predict the reduction in operating temperature of a gas turbine tip shoe. The work concluded that the cooling flow required to cool the tip shoe can be tuned to suit the efficiency improvements desired in an industrial gas turbine.

36 MATERIALS SCIENCE↗
DOE OSTI2024

On the Corrosion Response of Novel Heat Exchangers Manufactured by Casting of Al-Ce-Mg Alloy

Developing low-cost and durable heat exchangers is critical for next-generation heating, ventilation, air conditioning, and refrigeration systems. The emerging requirement to minimize the total refrigerant charge inventory while ensuring a uniform distribution of refrigerant has led to the deployment of advanced manufacturing strategies. At the same time, corrosion is a longstanding issue for metal components, especially those used in heat exchanger (HX) applications. In this study, Al-Ce-Mg alloy-based HXs have been investigated. The corrosion resistance of HXs prototype manufactured by the casting process has been examined and the potential of a new manufacturing approach has been explored to meet the requirements of emerging needs.

Brechtl, Jamieson↗
DOE OSTI2022

Techno‐economic, environmental, and social measurement of clean energy technology supply chains

Abstract In addition to the criteria of reliability and cost, clean energy technologies, such as wind, solar, and batteries, need to strive to a higher standard of environmental and societal benefit along their entire supply chain. This means additional performance metrics for these technologies should be considered, such as embodied energy, embodied carbon, recycled content and recyclability, environmental impact of material sourcing, impact on land and ecosystems, materials recovery at end of life, and production through quality nonexploitive jobs with community benefit. Many commercial and emerging energy technologies have not yet been explicitly evaluated based on these environmental and social performance metrics, which presents multiple opportunities for researchers and analysts. In this paper, we review the importance and current limitations of techno‐economic and life‐cycle assessment models for research design and manufacturing decisions. We explore emerging manufacturing modeling options that could improve environmental and social performance and how they could be used to help guide research. Even with the deployment of low‐carbon energy‐generation technologies, the future of a successful clean energy transition requires collaboration between researchers, advanced manufacturers, independent standards and tracking organizations, local communities, and national governments, to ensure the financial, environmental, and social sustainability of the entire supply and manufacturing process of energy technologies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

The role of ferrites in wireless charging systems for electric vehicles

This review examines the critical role of magnetic ceramic ferrites in wireless charging systems (WCS) for electric vehicles (EVs). With the increasing shift towards electrifying motor vehicles, advanced charging systems are needed to optimize EV range and performance. Magnetic materials are vital in WCS, as they act as a coupler that enhances power transfer. However, design limitations in weight and size motivate the need for systems tailored to meet a range of specifications. Additionally, ferrite systems can be tailored by altering composition, microstructure, and processing. Furthermore, this review examines advanced manufacturing techniques for improved ferrite design and identifies future directions for ferrite core research to meet future WCS needs.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Project DarkStar: Vision for LLNL in 2030

DarkStar was a Strategic Initiative (FY2021-FY2024) to investigate applications of Artificial Intelligence (AI) and Machine Learning (ML) to scientific problems of complex hydrodynamics, shockwave physics and energetic materials. The research focused on physics and engineering design as a process that can be tremendously accelerated through merging AI with advanced physics simulation on exascale-class platforms, and to experimentally validate this revolutionary new approach through dynamic materials campaigns. A central thread of scientific inquiry was in the application of AI to enable human understanding of how to control hydrodynamic instability (which has impacts to areas such as inertial confinement fusion) via engineering features and time-dependent sources. Motivated by an unfinished line of research started by Dr. Johnny von Neumann, AI-enabled simulation approaches were developed that allowed DarkStar researchers to uncover several ground-breaking discoveries regarding hydrodynamic instability, including how to completely suppress Richtmyer-Meshkov instability (RMI). These S&T discoveries, along with other advances, have shown the way for an entirely new approach to time-dependent problems known as inverse design – the idea that complex systems can be developed directly from a final state that is to be achieved and resolve the initial design via satisfying several constraints simultaneously via AI/ML. Through experimental campaigns conducted across a wide range of facilities in the NNSA complex (the High Explosive Application Facility at LLNL, the Dynamic Compression Sector/Advanced Photon Source at Argonne National Lab, and Special Technologies Laboratory at MSTS) the radical new AI/ML approach to engineering complex material dynamics was verified, establishing a new field of study within the realm of shock physics. As advanced manufacturing capabilities continue to develop, the great importance of inverse design as a means to apply that technology effectively for NNSA missions will feature prominently over this decade. DarkStar has positioned NNSA as a world-leader in this newly emerging cross-disciplinary area of AI methods for advanced physics simulation and pioneered multiple novel approaches that have enabled the broader scientific community. By allowing us to see past the horizon, to 2030 and beyond, DarkStar has illuminated the vast potential of AI/ML to impact a wide range of new national security missions and, consequently, multiple areas of further research have already emerged across the NNSA and DOD complex.

42 ENGINEERING↗
DOE OSTI2021

Numerical study to predict the effect of surface roughness on the thermal and hydraulic performance of additively manufactured heat exchangers

Heat exchangers are used in many industries to transfer thermal energy between two or more objects with an associated thermal and hydraulic performance indicated by thermal effectiveness and pressure drop respectively. Many investigations have aimed to enhance the thermal effectiveness of heat exchangers by introducing turbulent flow inducers that increase the heat transfer rate at the expense of increasing pressure drop. Flow inducers like surface roughness can be controlled with advanced manufacturing methods like additive manufacturing for heat exchanger production. Selecting and manufacturing an optimal surface roughness for heat exchangers requires a more comprehensive approach that accounts for the surface roughness effect on the thermal and hydraulic performance of a sample. Since fabricating samples with additive manufacturing to a desired surface roughness can be an extensive experimental process, this study will fundamentally investigate the effect of surface roughness on the thermal and velocity boundary layers for various surface roughness profiles with physics-based computational modeling. To accurately model the surface roughness effect on thermohydraulic performance, correlations like roughness ratio, friction factor, and Nusselt number are investigated. This study expects to indicate correlations for different flow regimes which can successfully predict the effect of surface roughness on thermohydraulic performance. Results generated from modeling surface roughness effect with unique correlations are then compared to experimental data obtained from literature for validation. The results of this study will provide insight to understand the thermal fluid physics associated with surface roughness and design guidelines for heat exchangers produced with additive manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Electricity use in big area additive manufacturing of fiber-reinforced polymer composites

In recent years, additive manufacturing (AM), especially large-format additive manufacturing (LFAM), has gained momentum in the manufacturing industry. While LFAM offers benefits over conventional manufacturing processes, such as minimizing material waste and providing vast geometric freedom, assessing its sustainability remains challenging due to limited data, particularly on energy consumption. Most existing data pertain to small-scale or desktop AM and are not directly applicable to LFAM. In this study, we conducted real-time measurements of electricity usage for a type of LFAM known as big area additive manufacturing (BAAM), which typically uses fiber-reinforced polymer pellets as feedstock. We collected electricity usage data from fifteen printing jobs over two months in an industrial production setting. These data fill the existing gap and can be reused to enhance the community’s understanding of LFAM electricity usage, support further research, and promote sustainable development in advanced manufacturing technologies.

ecology↗
DOE OSTI2024

Design of robot grippers for binder jet products handling

Dimension accuracy, damage minimization, and defect detection are essential in manufacturing processes, especially additive manufacturing. These types of challenges may arise either during the manufacture of a product or its use. The repeatability of the process is vital in additive manufacturing systems. However, human users may lose concentration and, thus, would be a great alternative as an assistant. Depending on the nature of work, a robot’s fingers might vary, for example, mechanical, electrical, vacuum, two-fingers, and three-fingers. In addition, the end effector plays a vital role in picking up an object in the advanced manufacturing process. However, inbuilt robotic fingers may not be appropriate in different production environments. In this research presented here considering metal binder jet additive manufacturing, the two-finger end- effectors are proposed design, analysis, and experiment to pick up an object after completing the production process from a specific location. The final designs were further printed by using a 3D metal printer and installed in the existing robotic systems. These new designs are used successfully to hold the object from the specific location by reducing the contact force that was not possible with the previously installed end effector's finger. In addition, a numerical study was conducted in order to compare the flowability of the geometric shape of finger's free areas.

42 ENGINEERING↗
DOE OSTI2021

Materials for Harsh Environments

The 2020 Materials for Harsh Service Conditions (M4HSC) Workshop was coordinated by three different U.S. Department of Energy (DOE) Offices: the Advanced Manufacturing Office (AMO), the Office of Fossil Energy (FE), and the Office of Nuclear Energy (NE). The event was held virtually October 27–30, 2020. The workshop brought together stakeholders from academia, industry, national laboratories, and DOE offices to identify the opportunities (paths for obtaining desirable goals), challenges (actionable tasks taken up along these paths), barriers (obstacles impeding advancement along the paths), and research and development (R&D) needs for enabling development of technology readiness level (TRL) 3–6 materials and materials systems, as well as their advancement into widespread commercial application.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Directed Energy Deposition Process Modeling, Validation, and Process-Informed Optimization

The directed energy deposition (DED) process, one of the most popular additive manufacturing techniques in use today, involves various complex physical mechanisms that are not yet well understood. In this regard, computational tools show promise for elucidating the manufacturing process and enabling nondestructive performance evaluations of manufactured parts. To better control and optimize the DED process?thereby improving the manufactured product? the present work develops and demonstrates a novel artificial intelligence (AI)-based process control and optimization technique. Specifically, a geometry-free thermo-mechanical model with adaptive subdomain construction is developed to accurately capture the material?s thermo-mechanical response under cyclical reheating and high cooling rates [1]. The model is demonstrated and validated with experimental measurements, in light of various geometries and processing parameters. Moreover, based on this thermo-mechanical model, a physics-informed reduced-order model is developed to enable quick predictions of the temperature field at every time step. Furthermore, an AI-based controller is developed that can adapt to the ever-changing system states by automatically adjusting the manufacturing process parameters. This entire work is based on the open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) [2] and its recent integration with Libtorch (the C++ frontend of PyTorch [3]). The combined development of the adaptive material deposition scheme, thermo-mechanical model, associated reduced-order model, and AI-based process controller carries great potential for improving advanced manufacturing processes.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Transport Affordable Clean Hydrogen Energy via Existing Pipeline Infrastructure (CRADA 573)

Our Nation’s vast network of oil pipelines span over 230,000 miles connecting remote energy producing regions to distant markets. The COVID-19 pandemic’s influence on oil prices intensified technical and economic vulnerabilities afflicting the Trans-Alaska Pipeline System (TAPS, operating below 25% capacity) that may soon resurface as energy demand shifts to low carbon sources. Through the opportunity afforded by the Arctic Advanced Manufacturing Program, I’ve toured the great State of Alaska learning about its culture, unique energy challenges, business ecosystem, research institutions, and regulatory agencies. With encouragement and support from dedicated Alaskans and my professional mentors, I’ve founded Mighty Pipeline for the purpose of developing and commercializing proprietary technology and hardware to convert oil pipelines into clean hydrogen energy transmission systems. Leveraging the advanced technical capabilities of Pacific Northwest National Laboratory, we’ve demonstrated proof-of-concept (TRL = 3) and are seeking pre-pilot development project opportunities to conduct hardware and system level tests. If we successfully achieve technical and regulatory milestones, Mighty Pipeline’s technology could be available to help facilitate bulk clean hydrogen energy export this decade.

08 HYDROGEN↗
DOE OSTI2020

Tribal Colleges and Universities/Advanced Manufacturing Network Initiative (Q3 FY2020 Progress Report)

The National Nuclear Security Agency (NNSA) initiated the Minority Serving Institution Partnership Plan (MSIPP) to 1) align investments in a university capacity and workforce development with the NNSA mission to develop the needed skills and talent for NNSA's enduring technical workforce at the laboratories and production plants, and 2) to enhance research and education at under-represented colleges and universities. Out of this effort, MSIPP launched a new consortium in early FY17 focused on Tribal Colleges and Universities (TCUs) known as the Advanced Manufacturing Network Initiative (AMNI). This consortium has been extended for FY20 and FY21. The following report summarizes the status update during this quarter.

42 ENGINEERING↗
DOE OSTI2020

Tribal Colleges and Universities/Advanced Manufacturing Network Initiative (Q4 FY2020 Progress Report)

The National Nuclear Security Agency (NNSA) initiated the Minority Serving Institution Partnership Plan (MSIPP) to 1) align investments in a university capacity and workforce development with the NNSA mission to develop the needed skills and talent for NNSA’s enduring technical workforce at the laboratories and production plants, and 2) to enhance research and education at under-represented colleges and universities. Out of this effort, MSIPP launched a new consortium in early FY17 focused on Tribal Colleges and Universities (TCUs) known as the Advanced Manufacturing Network Initiative (AMNI). This consortium has been extended for FY20 and FY21. The following report summarizes the status update during this quarter.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2021

Tribal Colleges and Universities/Advanced Manufacturing Network Initiative (Phase II) (Q1 FY2021 Progress Report)

The National Nuclear Security Agency (NNSA) initiated the Minority Serving Institution Partnership Plan (MSIPP) to 1) align investments in a university capacity and workforce development with the NNSA mission to develop the needed skills and talent for NNSA’s enduring technical workforce at the laboratories and production plants, and 2) to enhance research and education at under-represented colleges and universities. Out of this effort, MSIPP launched a new consortium in early FY17 focused on Tribal Colleges and Universities (TCUs) known as the Advanced Manufacturing Network Initiative (AMNI). This consortium has been extended for FY20 and FY21. The following report summarizes the status update during this quarter.

42 ENGINEERING↗
DOE OSTI2021

Tribal Colleges and Universities/Advanced Manufacturing Network Initiative Phase II Sandia Technical Assistance (Q2 FY2021 Progress Report)

The National Nuclear Security Agency (NNSA) initiated the Minority Serving Institution Partnership Plan (MSIPP) to 1) align investments in a university capacity and workforce development with the NNSA mission to develop the needed skills and talent for NNSA’s enduring technical workforce at the laboratories and production plants, and 2) to enhance research and education at under-represented colleges and universities. Out of this effort, MSIPP launched a new consortium in early FY17 focused on Tribal Colleges and Universities (TCUs) known as the Advanced Manufacturing Network Initiative (AMNI). This consortium has been extended for FY20 and FY21. The following report summarizes the status update during this quarter.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Tribal Colleges and Universities/Advanced Manufacturing Network Initiative Phase II Sandia Technical Assistance FY21 Q3 Progress Report

The National Nuclear Security Agency (NNSA) initiated the Minority Serving Institution Partnership Plan (MSIPP) to 1) align investments in a university capacity and workforce development with the NNSA mission to develop the needed skills and talent for NNSA’s enduring technical workforce at the laboratories and production plants, and 2) to enhance research and education at under-represented colleges and universities. Out of this effort, MSIPP launched a new consortium in early FY17 focused on Tribal Colleges and Universities (TCUs) known as the Advanced Manufacturing Network Initiative (AMNI). This consortium has been extended for FY20 and FY21. The following report summarizes the status update during this quarter.

42 ENGINEERING↗
DOE OSTI2021

Tribal Colleges and Universities/Advanced Manufacturing Network Initiative: Phase II Sandia Technical Assistance (FY21 Q4 Progress Report)

The National Nuclear Security Agency (NNSA) initiated the Minority Serving Institution Partnership Plan (MSIPP) 1) to align investments in a university capacity and workforce development with the NNSA mission to develop the needed skills and talent for NNSA’s enduring technical workforce at the laboratories and production plants, and 2) to enhance research and education at under-represented colleges and universities. Out of this effort, MSIPP launched a new consortium in early FY17 focused on Tribal Colleges and Universities (TCUs) known as the Advanced Manufacturing Network Initiative (AMNI). This consortium has been extended for FY20 and FY21. The following report summarizes the status update during this quarter.

42 ENGINEERING↗