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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 127 records · Page 7

Large Scale and Multi-Alloy Rocket Engine Component Development using Various Metal Additive Manufacturing Techniques

The NASA Marshall Space Flight Center (MSFC) has been involved with various forms of metallic additive manufacturing (AM) for use in liquid rocket engine component design, development, and testing since 2010. These AM techniques have been demonstrated to significantly reduce hardware cost, shorten fabrication schedules, increase reliability by reducing the number of joints, and improve hardware performance by allowing fabrication of designs not feasible by conventional means. The focus at the NASA MSFC for these metal additive manufacturing techniques include laser powder-bed fusion (L-PBF), blown powder directed energy deposition (DED), arc-based deposition, and Laser Wire Direct Closeout (LWDC). A variety of components have been evaluated and tested including thrust chamber injectors, injector components such as faceplates, regeneratively-cooled combustion chambers, regeneratively-cooled nozzles, gas generator and preburner hardware, and augmented spark igniters. To support these component applications in harsh environments, NASA has advanced a variety of “standard” additive manufacturing alloys such as those in the superalloy-family and also evolved new alloys including GRCop-84, GRCop-42, NASA HR-1, and JBK-75. The purpose of this presentation is to discuss the various component programs at the NASA MSFC using AM to develop, fabricate, and test combustion devices hardware and the evolution of the new additive alloys. One of these projects that will be highlighted is Rapid Analysis and Manufacturing Propulsion Technology (RAMPT), which includes new process development for large scale AM components, multi-metallic AM components, including unique component designs using additive manufacturing. Additional information will be provided on the development of other components, hot-fire testing, post-processing of AM techniques including surface enhancements (polishing) techniques, material and process characterization, future development programs, and dissemination of data to industry partners.

Additive Manufacturing↗

Additively manufacturing high-temperature aluminum alloy for automotive engine pistons

The purpose of the project was to evaluate DuAlumin-3D, an ORNL designed Al alloy, for additive manufacturing of high-performance automotive components. The project consisted of additively manufacturing a cylindrical block of representative material which was then heat treated before machining into test coupons. Testing included tensile tests as a function of temperature, high-cycle fatigue testing as a function of temperature, density and elastic modulus measurements, and thermophysical property measurements. Fractography was also performed on failed high-cycle fatigue specimens. The results were compared against benchmark AM Al alloys and current high-performance conventionally manufactured alloys. Overall, the DuAlumin-3D material outperformed the incumbent materials in mechanical properties, especially at elevated temperatures, while maintaining broadly similar thermophysical properties. The results of this study support further maturation of the material for additive manufacturing of high-performance automotive components.

36 MATERIALS SCIENCE↗

EBF3 Design and Sustainability Considerations

Electron beam freeform fabrication (EBF3) is a cross-cutting technology for producing structural metal parts using an electron beam and wire feed in a layer-additive fashion. This process was developed by researchers at NASA Langley to specifically address needs for aerospace applications. Additive manufacturing technologies like EBF3 enable efficient design of materials and structures by tailoring microstructures and chemistries at the local level to improve performance at the global level. Additive manufacturing also facilitates design freedom by integrating assemblies into complex single-piece components, eliminating flanges, fasteners and joints, resulting in reduced size and mass. These same efficiencies that permit new design paradigms also lend themselves to supportability and sustainability. Long duration space missions will require a high degree of self-sustainability. EBF3 is a candidate technology being developed to allow astronauts to conduct repairs and fabricate new components and tools on demand, with efficient use of feedstock materials and energy.

Taminger, Karen M. B.↗

Viability of Additively Manufactured Electrodes for Lithium-Ion Batteries

As the global economy becomes increasingly electrified, the demand for batteries and energy storage is expected to rise significantly, particularly in the transportation and electricity sectors. Lithium-ion batteries (LIBs) are currently the most advanced and widely used technology in this field. Traditionally, LIBs are manufactured using simple 2D planar geometries to maximize production efficiency and minimize costs. However, this approach limits energy density due to the restricted design flexibility of the electrodes. Additive manufacturing (AM) offers a promising solution to enhance the energy density and efficiency of LIBs by enabling the design of architectures that reduce diffusive losses and allow for a greater amount of active material to be incorporated within the same device footprint, thereby minimizing the use of inactive materials. Different AM techniques come with their own set of limitations, including printing speed, material compatibility, and scale, which must be considered when designing electrodes. Scalable and cost-effective methods are particularly important for electric vehicle batteries, while achieving higher energy densities in microbatteries is crucial for the miniaturization of wearable electronics and medical devices. Here, in this study, we simulate various 3D porous electrode designs for LIBs using graphite and nickel manganese cobalt oxide (NMC) electrodes. These designs are selected to represent structures that could be produced using different AM techniques, such as direct ink writing, fused deposition modeling, and stereolithography. Our results indicate that at higher charging rates and increased areal mass loading, 3D structures can outperform traditional 2D electrodes, although the benefits may diminish with more complex designs that are harder to manufacture. The observed gains in energy density are attributed to improved electrode utilization and reduced diffusive energy losses. This comprehensive analysis of structure–performance relationships will provide valuable insights to guide future research on 3D designs, material selection, and AM techniques for additively manufactured battery electrodes.

25 ENERGY STORAGE↗

Lessons learned for composite structures

Lessons learned for composite structures are presented in three technology areas: materials, manufacturing, and design. In addition, future challenges for composite structures are presented. Composite materials have long gestation periods from the developmental stage to fully matured production status. Many examples exist of unsuccessful attempts to accelerate this gestation period. Experience has shown that technology transition of a new material system to fully matured production status is time consuming, involves risk, is expensive and should not be undertaken lightly. The future challenges for composite materials require an intensification of the science based approach to material development, extension of the vendor/customer interaction process to include all engineering disciplines of the end user, reduced material costs because they are a significant factor in overall part cost, and improved batch-to-batch pre-preg physical property control. Historical manufacturing lessons learned are presented using current in-service production structure as examples. Most producibility problems for these structures can be traced to their sequential engineering design. This caused an excessive emphasis on design-to-weight and schedule at the expense of design-to-cost. This resulted in expensive performance originated designs, which required costly tooling and led to non-producible parts. Historically these problems have been allowed to persist throughout the production run. The current/future approach for the production of affordable composite structures mandates concurrent engineering design where equal emphasis is placed on product and process design. Design for simplified assembly is also emphasized, since assembly costs account for a major portion of total airframe costs. The future challenge for composite manufacturing is, therefore, to utilize concurrent engineering in conjunction with automated manufacturing techniques to build affordable composite structures. Composite design experience has shown that significant weight savings have been achieved, outstanding fatigue and corrosion resistance have been demonstrated, and in-service performance has been very successful. Currently no structural design show stoppers exist for composite structures. A major lesson learned is that the full scale static test is the key test for composites, since it is the primary structural 'hot spot' indicator. The major durability issue is supportability of thin skinned structure. Impact damage has been identified as the most significant issue for the damage tolerance control of composite structures. However, delaminations induced during assembly operations have demonstrated a significant nuisance value. The future challenges for composite structures are threefold. Firstly, composite airframe weight fraction should increase to 60 percent. At the same time, the cost of composite structures must be reduced by 50 percent to attain the goal of affordability. To support these challenges it is essential to develop lower cost materials and processes.

Whitehead, R. S.↗

Overall Cooling Effectiveness of Internally Cooled Additively Manufactured Blades

Power generation gas turbine blades must utilize highly effective cooling schemes to withstand moderate heat loads for long operating times. Prior work indicates that gas turbines in the 5-10 MW range primarily utilize internal cooling to prevent further increase of aerodynamic losses that result from film cooling, but few studies focus solely on internal cooling. In this study, three additively manufactured internal cooling designs were tested in the 50 percent span section of the National Experimental Turbine (NExT) blade: a baseline cooling design with pin-fin arrays and rib turbulators, a double wall design with impingement jets and serpentine channels, and an incremental impingement design. The designs were tested in a high-speed linear cascade at exit Reynolds numbers ranging from 700,000 to 1,400,000 at an exit Mach of 0.8. In addition, freestream turbulence and build angle effects on cooling performance were studied.

gas turbine blades↗

Database Design Strategies for Coordinated Simulation and Testing in Additive Manufacturing

The qualification and certification (Q&C) process presents a significant challenge for widespread adoption of additive manufacturing (AM) materials and processes for aerospace applications. A relational database framework will be presented as a tool for data curation of coordinated experimental and computational materials modeling research activities. A comparison of relational and hierarchical data structures in this domain will be emphasized through the evolution of a database design strategy. This framework’s mission is to support the advancement of computational materials-informed Q&C by providing the necessary data infrastructure to trace reliability and reproducibility measures through unified AM materials simulation and experimental testing. FAIR (findable, accessible, interoperable, and reusable) data will be highlighted as a necessary precursor for automation of specific actions, which ultimately reduces the time and expense burden for Q&C. The discussion will be mostly limited to back-end design elements, though a few front-end user experience examples will also be shared.

Qualification↗

Additive Manufacturing of Multifunctional Components Using High Density Carbon Nanotube Yarn Filaments

Additive manufacturing allows for design freedom and part complexity not currently attainable using traditional manufacturing technologies. Fused Filament Fabrication (FFF), for example, can yield novel component geometries and functionalities because the method provides a high level of control over material placement and processing conditions. This is achievable by extrusion of a preprocessed filament feedstock material along a predetermined path. However if fabrication of a multifunctional part relies only on conventional filament materials, it will require a different material for each unique functionality printed into the part. Carbon nanotubes (CNTs) are an attractive material for many applications due to their high specific strength as well as good electrical and thermal conductivity. The presence of this set of properties in a single material presents an opportunity to use one material to achieve multifunctionality in an additively manufactured part. This paper describes a recently developed method for processing continuous CNT yarn filaments into three-dimensional articles, and summarizes the mechanical, electrical, and sensing performance of the components fabricated in this way.

Gardner, John M.↗

Investigating Fast Scanning Calorimetry and Differential Scanning Calorimetry as Screening Tools for Thermoset Polymer Material Compatibility with Laser-Based Powder Bed Fusion

As additive manufacturing (AM) technology has developed and progressed, a constant topic of research in the area is expanding the library of materials to be used with these techniques. Among AM methods that utilize polymers, laser-based powder bed fusion (PBF-LB) has preferentially used thermoplastic polymers as its starting materials, but the deposition and material joining method employed in PBF-LB may also be compatible with powdered thermoset polymer precursors as feedstocks. To assess the compatibility of candidate thermosetting polymers and PBF-LB, characterization techniques and protocols that link fundamental material behavior to material behavior in the processing environment are needed. Therefore, the objectives of this work are to compare the curing behavior measured with two different calorimetry techniques that can operate in different heating rate regimes, differential scanning calorimetry (DSC) and fast scanning calorimetry (FSC), and to assess the capabilities of these techniques to act as materials screening tools for PBF-LB. A commercial polyester powder coating is used as a model material to evaluate the potential of obtaining complimentary information for material screening through a combination of calorimetry methods, and its non-isothermal curing behavior is measured at heating rates between 5 °C/min and 7500 °C/min. Curing exotherms are observed with both calorimetry techniques, and comparing the enthalpy associated with curing shows that incomplete curing occurs at higher heating rates, with relative conversion values of approximately 30%. The curing data are fit with two isoconversional models, Friedman and Starink, which show a reduced activation energy at higher heating rates as well, signifying a lower barrier to curing at the conditions used in the FSC experiments. Overall, the results of this work indicate that using these two calorimetry techniques as tiered screening tools can provide valuable information about how curing may proceed in PBF-LB and inform materials selection and design activities for additive manufacturing.

36 MATERIALS SCIENCE↗

Decarbonizing nitrogen fertilizer production via the electrochemical nitrogen oxidation reaction

Nitric acid is an important commodity chemical with extensive applications in both agricultural and industrial sectors. However, current production methods involve a combination of the Haber–Bosch and Ostwald processes, which are both energy and carbon emission intensive. The electrochemical nitrogen oxidation reaction (NOR) to produce nitric acid or nitrates shows great potential as an environmentally friendly method for producing fertilizers under mild conditions. The key to progress in this field lies in understanding the fundamental mechanistic insights and establishing robust experimental methods, which is essential for the efficient design and synthesis of electrocatalysts for NOR. Additionally, poor gas mass transport in conventional electrochemical reactors at present lead to lower NOR activity, thereby limiting the progress in this field. In this work, we present a synergistic computational and experimental approach to map out the potential chemical and electrochemical steps and determine the energetics on PtO 2 catalyst to gain mechanistic insights into NOR. Here, this study marks the first attempt to perform NOR in a vapor-fed reactor designed using advanced (additive) manufacturing. The vapor-fed reactor significantly improved the N 2 mass transport to the catalyst, allowing us to report the highest rate for nitrate production to date at 3.3 μmol cm -2 h -1 at 2.01 V vs RHE.

30 DIRECT ENERGY CONVERSION↗

Denoising diffusion probabilistic models for generative alloy design

Inverse material design is an extremely challenging optimization task made difficult by, in part, the highly nonlinear relationship linking performance with composition. Quantitative approaches have improved significantly owing to advances in high throughput experimentation and computational thermodynamics. However, existing physics-based tools are mostly forward models; input a chemistry and obtain a prediction. More recently the materials community has leveraged advances in the machine learning community to establish novel inverse design frameworks. Very recently denoising diffusion probabilistic models have been shown to be extremely powerful generators producing synthetic data of various modalities e.g. images, text, audio, tables, etc.. In this work a novel framework for alloy design and optimization is proposed leveraging these class of models. Five key generative tasks are demonstrated (1) unconditional generation (2) composition conditioned generation (3) property conditioned generation (4) multi-feedstock conditioned generation and (5) generative optimization. These methods were tested on three case studies: high entropy alloy design, superalloy binder jet additive manufacturing, and in-situ dual-feedstock wire-arc additive manufacturing. Results indicate that the established models are extremely flexible, expressive, and robust. The architecture’s flexibility and training procedure empower the model to learn complex intra-compositional and composition-property relationships. Furthermore, the probabilistic nature of these models makes them well suited for addressing solution non-uniqueness and tackling uncertainty quantification tasks. While the fidelity and quantity of the underlying training data is paramount, we envision that future alloy design frameworks will make extensive use of these kinds of machine learning models as “search” tools bolstering the utility of experimental and computational approaches.

36 MATERIALS SCIENCE↗

Computational Study of Additively Manufactured Internally Cooled Airfoils for Industrial Gas Turbine Applications

Internal cooling features such as pin-fins, impingement jets, and rib-turbulators are necessary to keep turbine components cool, but if sufficiently advanced can potentially also eliminate the need for film cooling on turbine blades particularly in industrial gas turbines where temperatures are not extreme. Furthermore, by leveraging additive manufacturing, other advanced designs such as lattice and incremental impingement configurations are possible and have recently been experimentally tested. While the performance of such configurations has been quantified through means of overall cooling effectiveness, it is not as clear why certain designs were better than others, or what the mechanisms were behind the observed external cooling patterns. The purpose of this study was to computationally analyze different advanced turbine blade internal cooling designs previously tested by the National Energy Technology Laboratory.

CFD↗

2020 Budget Request for the DOE Computational Science Graduate Fellowship (CSGF) Grant

The Department of Energy Computational Science Graduate Fellowship (DOE CSGF) is essential for addressing the increasingly complex national workforce demands stemming from the growth of computational science and engineering challenges. Computational science and engineering (CSE) takes a multidisciplinary approach that utilizes scientific computing to tackle practical problems and provide technical tools across the spectrum of scientific discovery. The DOE CSGF specifically highlights high-performance computing (HPC) as a critical enabling technology in CSE, driving advancements in science and engineering that are vital to both the DOE and the broader economy. Over the past half-century, HPC has been an essential tool for DOE’s success. During this period, important missions, such as nuclear stockpile stewardship, have turned to HPC as an essential technology. Entire science disciplines have been transformed through the augmentation of scientific observation via HPC. At government laboratories, academic institutions, and in industry, DOE CSGF alumni are helping push traditional HPC boundaries while contributing to discoveries in high-energy physics, quantum information systems, fusion-reactor design, machine learning, additive manufacturing, nano materials for next-generation batteries and transistors, and advanced nuclear reactor modeling. In addition, HPC is used to address national health needs that will eventually point to cures both by helping cancer researchers manage and analyze huge troves of data, by simulating biological mechanisms, and by accelerating drug development. A 2023 report from the ASCAC Subcommittee on American Competitiveness and Innovation to the ASCR office, “Can the United States Maintain Its Leadership in High-Performance Computing?” says of the Program, “The CSGF program provides a barometer for disciplines that will be of interest to future DOE computing. Computational biology, machine learning, and quantum computing are among the subjects that began to swell in the ranks of CSGF applicants before the labs were hiring as high a percentage of employees in these categories.” The explosion of scientific and technological data has heightened the demand for advanced high-performance computing (HPC) to transform these data into meaningful scientific insights. As access to vast amounts of data increases, the fields of Machine Learning and Artificial Intelligence are experiencing a resurgence, enhancing the established practices of computational modeling and simulation. In its September 2020 subcommittee report on "AI/ML, Data Intensive Science, and High-Performance Computing," the DOE Advanced Scientific Computing Advisory Committee (ASCAC) specifically called for a fellowship program to train computational and data scientists to address exascale and data-intensive computing challenges. This integration of empirical and theoretical modeling will increasingly guide federal policymakers in making decisions that impact American society and future generations. It demands a workforce of highly skilled and intellectually agile computational scientists capable of navigating the rapid advancements in scientific computing within the DOE National Laboratory research environment. The DOE CSGF program has consistently addressed this critical need.

97 MATHEMATICS AND COMPUTING↗

Crew Exploration Vehicle Environmental Control and Life Support Development Status

The Orion Crew Exploration Vehicle (CEV) is the first crew transport vehicle to be developed by the National Aeronautics and Space Administration (NASA) in the last thirty years. The CEV is currently being developed to transport the crew safely from the Earth to the Moon and back again. This year, the vehicle focused on building the Orion Flight Test 1 (OFT1) vehicle to be launched in 2013. The development of the Orion Environmental Control and Life Support (ECLS) System, focused on the components which are on OFT1 which includes pressure control and active thermal control systems, is progressing through the design stage into manufacturing. Additional development work was done to keep the remaining component progressing towards implementation. This paper covers the Orion ECLS development from April 2010 to April 2011.

Lewis, John F.↗

Multi Purpose Crew Vehicle Environmental Control and Life Support Development Status

The Orion Multi Purpose Crew Vehicle (MPCV) is the first crew transport vehicle to be developed by the National Aeronautics and Space Administration (NASA) in the last thirty years. Orion is currently being developed to transport the crew safely from the Earth beyond Earth orbit. This year, the vehicle focused on building the Orion Flight Test 1 (OFT1) vehicle to be launched in 2013. The development of the Orion Environmental Control and Life Support (ECLS) System, focused on the components which are on OFT1 which includes pressure control and active thermal control systems, is progressing through the design stage into manufacturing. Additional development work was done to keep the remaining component progressing towards implementation for a flight test in 2017. This paper covers the Orion ECLS development from April 2011 to April 2012.

Lewis, John F.↗

Orion Multi Purpose Crew Vehicle Environmental Control and Life Support Development Status

The Orion Multi Purpose Crew Vehicle (MPCV) is the first crew transport vehicle to be developed by the National Aeronautics and Space Administration (NASA) in the last thirty years. Orion is currently being developed to transport the crew safely from the Earth beyond Earth orbit. This year, the vehicle focused on building the Exploration Flight Test 1 (EFT1) vehicle to be launched in 2014. The development of the Orion Environmental Control and Life Support (ECLS) System, focused on the components which are on EFT1 which includes pressure control and active thermal control systems, is progressing through the design stage into manufacturing. Additional development work was done to keep the remaining component progressing towards implementation for a flight tests in 2017 and in 2020. This paper covers the Orion ECLS development from April 2011 to April 2012.

Lewis, John F.↗

Electron Beam Freeform Fabrication of Titanium Alloy Gradient Structures

Historically, the structural optimization of aerospace components has been done through geometric methods. A monolithic material is chosen based on the best compromise between the competing design limiting criteria. Then the structure is geometrically optimized to give the best overall performance using the single material chosen. Functionally graded materials offer the potential to further improve structural efficiency by allowing the material composition and/or microstructural features to spatially vary within a single structure. Thus, local properties could be tailored to the local design limiting criteria. Additive manufacturing techniques enable the fabrication of such graded materials and structures. This paper presents the results of a graded material study using two titanium alloys processed using electron beam freeform fabrication, an additive manufacturing process. The results show that the two alloys uniformly mix at various ratios and the resultant static tensile properties of the mixed alloys behave according to rule-of-mixtures. Additionally, the crack growth behavior across an abrupt change from one alloy to the other shows no discontinuity and the crack smoothly transitions from one crack growth regime into another.

Brice, Craig A.↗