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At least 451 records · Page 25

NASA Efforts to Explore Additively Manufactured Thermal Protection Systems

Development of the thermal protection system (TPS) needed to protect external and internal surfaces during launch, ascent, cruise, and reentry, is a very specialized field with expertise developed over seven decades and has enabled successful robotic as well as human exploration. Well known examples are: 1) the ablative heatshield that protected Apollo Astronauts during reentry in 1960’s, 2) reusable TPS used on the Space Shuttle Orbiter, which is now sought after by commercial space industry, and 3) hot structures, such as Carbon-Carbon and other high temperature materials needed to operate control surfaces and sharp leading edges during hypervelocity flight. TPS function demands fail-safe design to ensure mission success. One TPS does not fit all, and each application requires a unique material along with manufacturing and integration approach. TPS mass is a key metric. A robust but inefficient TPS reduces payload mass. Mission- and domain-unique TPS development and flight certification efforts have been expensive with long lead times. As a result, there are limited TPS choices with high cost. For future commercial efforts to be successful, the ability to rapidly develop TPS, based on specific needs and at a lower cost, without compromising either mass efficiency or functionality is necessary. NASA is looking into this. Additive manufacturing (AM) techniques have shown their utility in making complex parts and, through automation, the potential to reduce cost and schedule in some applications. The promise of additive manufacturing to TPS, while exciting, is unexplored. In the past several years, NASA has made exploratory investments in internal development as well as in small business and universities through SBIR and STTR programs. In addition, NASA is bringing together the TPS as well as Additive Manufacturing communities to explore approaches to prioritize focus areas for broad benefits. The very first “Additively Manufactured Thermal Protection System Workshop,” to be held at NASA Johnson Space Center in Houston at the end of March of this year, is the culmination of a year-long effort to engage the research, development, and user communities involved in both TPS as well as additive manufacturing. The workshop participants include representatives from large and small commercial space industry, DoD, Federally Funded Research and Development Centers, University Researchers and NASA personnel. The proposed talk will highlight future TPS needs of both emerging commercial and Government interests, NASA’s development efforts in additively manufactured TPS, and the findings and recommendations from the first AM TPS Workshop.

Ethiraj Venkatapathy↗

Understanding structure-processing relationships in metal additive manufacturing via featurization of microstructural images

Understanding and predicting accurate property-structure-processing relationships for additively manufactured components is important for both forward and inverse design of robust, reliable parts and assemblies. While direct mapping of process parameters to properties is sometimes plausible, it is often rendered difficult due to poor microstructural control. Exploring the direct relationship between processing conditions and microstructural features can thus provide significant physical insights and aid the overall design process. Here, in this study, we develop an automated high-throughput framework to simulate an uncertainty-aware additive manufacturing (AM) process, characterize microstructural images, and extract meaningful features/descriptors. A kinetic Monte Carlo (KMC) based model of the AM process is used to simulate microstructural evolution for a diverse set of experimentally relevant processing conditions. We perform a parametric study to explore the relationship between microstructural features and processing conditions. Our results indicate that a many-to-one mapping can exist between processing conditions and typical descriptors; therefore, multiple descriptors are thus necessary to unambiguously represent microstructural images. Our work provides crucial quantitative and qualitative in-formation that would aid in the selection of features for microstructural images. Featurized microstructures could then be utilized to build data-driven models for predictive control of microstructures and thereby properties of additively manufactured components.

36 MATERIALS SCIENCE↗

Robot-based Additive Manufacturing of Lego-type Modular Molds for Wind Blades

The objective of this project is to reduce the cost and lead time of horizontal wind turbine blade mold tooling and blade transportation, while maintaining the highest standards of blade quality. The solution involves a smart-design family of modular molds that are easily transportable to fabrication sites near the place of service. Key innovations include the use of additive manufacturing (AM) to integrate conformal thermal management channels, offering enhanced control over the thermal profiles tailored to specific blade materials. This approach enables in-situ quality assurance during mold fabrication, significantly improves mold life, and allows for reuse across multiple production cycles. Ultimately, the solution aims to optimize both tooling and transportation costs, contributing to the scalability of wind turbine blade production. A significant barrier to scaling up the production of large wind turbine blades lies in the high costs associated with tooling and the transportation of blades. Traditional molds are expensive, bulky, and difficult to transport, adding considerable lead time and cost to the overall manufacturing process. Additionally, transporting blades to distant locations for final assembly further exacerbates these challenges. The project aims to address these inefficiencies by demonstrating a modularized, additive-manufactured mold that meets all necessary blade specification requirements, specifically for blade lengths between 120m and 150m.

17 WIND ENERGY↗

Wire Arc Additive Manufacturing of Lightweight High Pressure Die Casting Tooling

Oak Ridge National Laboratory (ORNL) and Mercury Marine partnered to develop and test methods for additively manufactured tooling for aluminum die casting applications under CRADA agreement NFE- 20-08193. Tooling is the largest capital expense for high production casting projects. The lead time for tooling is often measured in months with a typical project taking 9-12 months to realize Production Part Approval Process (PPAP) ready die cast samples. This project demonstrated the technical viability of rapidly produced steel components for high pressure die casting tooling via Wire Arc Additive Manufacturing (WAAM). A 410 stainless steel tool was redesigned and optimized with conformal cooling channels and additively manufactured. The finished tool was tested and used to produce over 4000 parts, which well surpassed expectations. A secondary objective was to evaluate the durability of multi-material additively manufactured (AM) components with conformal cooling. A large multi-material tool (H13 and 410SSNiMo) was manufactured using the same methods showing potential reductions in used material and cost. However, the H13 section sustained material cracking. Further analysis showed that the potential cause was the CTE mismatch of the two materials at higher temperatures. It is also suggested that the material mix can be used if the steel processing temperature does not exceed 600 ˚C. This project has shown high potential for using the WAAM technology for creating AM parts for aluminum dies casting. However, the multi-material approach requires extended study and tests.

36 MATERIALS SCIENCE↗

Impact of Powder Supply Variation on Mechanical Properties for Additive Manufacture of Alloy 718

The Additive Manufacturing Structural Integrity Initiative (AMSII) examined how a number of different Alloy 718 powder lots can create variation in microstructure and mechanical properties in parts fabricated using Laser Powder Bed Fusion. Being a common alloy, Alloy 718 powder can be found in a variety of compositions, fabrication techniques, and powder size distribution. Sixteen virgin powders, and three recycled powders were used to build samples for microstructure analysis, fatigue and tensile testing. The major impacts of the different powders manifested in variations in the microstructure, such as minor phases and grain size variation. There were corresponding variations in mechanical properties. A down-selection of powders were chosen for additional analysis, and a powder recyclability study was completed to look at the effect of reused powder.

Alloy 718↗

Fracture Control for Additive Manufactured Spacecraft Structures

Final Paper is attached. This paper discusses how the intent of current NASA fracture control requirements may be applied to "fracture critical" additive manufactured spacecraft hardware. Fracture control is a multi-discipline design and certification methodology that is applied in order to mitigate catastrophic failure of structures resulting from growth of an undetected crack-like defect. The methodology is defined in existing spacecraft standards and is required by NASA on all human-rated space structures. Recently, standards have been published by NASA to define materials and processes requirements for certain metallic additive manufactured hardware, but procedures for fracture control implementation on additive manufactured parts are not yet addressed in detail in any standard or guidance document.The discussion contained herein is necessary at this time as new guidance in this area should be founded collaboratively by the technical community at large including industry, academia, and government. Three Fracture Control Certification Methods are proposed for discussion. Additionally, a concept for "Design for AM fracture control" is introduced. The goals of this paper are to further expose the need for maturing additive manufacturing fracture control guidance in the spacecraft industry and to generate discussion on what this guidance should consist of.

McElroy, Mark↗

Impact of controlled prewetting on part formation in binder jet additive manufacturing

Binder jetting is an additive manufacturing process that bonds powder through selectively depositing binder by inkjet printing. The part is then extracted and densified by sintering and/or infiltration. The process offers low costs and fast build rates, but properties can be poor due to residual porosity after sintering. The inkjet printing process may contribute to this residual porosity by creating large pores. The droplet kinetic energy ejects some powder particles from the bed and rearranges others. Particle ejection and rearrangement are theorized to create porous regions in binder-jetted parts. In this work, small amounts of moisture are added to the spread powder before printing and the impact on part formation, part properties, and printing parameters measured with varied droplet spacing, droplet velocity, and print frequency. Moisture is added by applying an atomized fluid mixture to the powder between layer spreading and binder printing. The fluid mixture partially evaporates but leaves a stable residue to increase cohesion and enhance imbibition. Moisture addition to the powder increases the range of droplet spacings for line formation while reducing particle ejection, powder rearrangement, and balling in layer and multilayer parts. Excessive moisture addition decreases the effective saturation of printed lines, but saturation in 3D parts is less impacted. Increased surface roughness in the first few layers of a print was also mitigated with prewetting. Finally, high-speed X-ray imaging verified prewetting reduction in particle ejection and rearrangement.

36 MATERIALS SCIENCE↗

Investigating Marine Environmental Degradation of Additive Manufacturing Materials for Renewable Energy Applications

Marine renewable energy is a relatively young industry where there is a great need for rapid prototyping in design-build-test campaigns to quickly mature groundbreaking technologies. Additive manufacturing has an important role to play in the industry; however, little information is available to marine energy developers to help inform them on which additive manufacturing materials are appropriate for highly loaded structures in harsh marine environments. This paper presents an initial study on the mechanical characterization of polymeric additive manufacturing materials and the degradation effects due to the marine environment. Ultem 9085, acrylonitrile styrene acrylate, and chopped carbon-filled nylon, as well as continuous carbon and glass fiber-reinforced nylon were chosen for this study. Samples were manufactured to perform a variety of tension, shear, and compression mechanical characterization tests on the materials. Half of the samples were conditioned in Pacific Ocean water for approximately 6 months at the Pacific Northwest National Laboratory's Marine and Coastal Research Laboratory before being returned for mechanical characterization. The mechanical testing results showed that the Ultem 9085 and acrylonitrile styrene acrylate materials experienced little to no degradation in stiffness or strength after exposure to the marine environment. On the other hand, the nylon-based materials suffered significant stiffness and strength degradation (over 50% in some cases) after environmental conditioning. Ultimately, these data sets should serve as starting points to allow marine renewable energy developers to make informed additive manufacturing material choices for their prototype deployments.

additive manufacturing↗

CALPHAD Models to Guide Refractory Alloys Additive Manufacturing: In-Situ Compounds Formation, Nanoparticles, and Impurities Considerations

This technical memorandum (TM) seeks to model and discuss aspects of nanoparticle and micrometer-scale particle or ‘microparticle’ inclusions in refractory metal alloy manufacturing, via a currently used additive manufacturing (AM) method that results in equivalent wt.% addition of dissolved elements in the melt pool composition and subsequent formation of nanometer-scale MC and MO inclusions. Additionally, the authors begin to consider the effects of oxygen (O), a ubiquitous impurity, in AM; and seek to understand a combined optimization of alloying, nano- and micro strengthening and refinement, elemental additions, and even in-situ compounds and alloys species formation. To gain insights, this TM focuses on a pair of refractory alloys currently of interest to NASA: tungsten-rhenium-tantalum carbide (with O impurities) (W-Re-TaC(-O)) and tungsten-rhenium-tantalum-carbon (with O impurities) (W-Re-Ta-C(-O)), which are processed via powder bed fusion (PBF)-SLM.

ICME integrated computational materials engineerin↗

Performance of Compact Pulsed Thermal Imaging System for In-Service Applications. Pulsed thermal tomography nondestructive examination of additively manufactured reactor materials and components

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of complex topology nuclear reactor parts from high-strength corrosion resistance alloys, such as stainless steel and Inconel. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process, which has the capability of melting metallic powder and net shaping the structures with relatively high precision. Some of the challenges with using LPBF method for nuclear manufacturing include the possibility of introducing pores into metallic structures. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures due to creep in high temperature nuclear reactor environment. Currently, there exist limited capabilities to evaluate actual AM structures nondestructively. Pulsed Thermography (PT) imaging provides a capability for non-destructive evaluation (NDE) of sub-surface defects in arbitrary size structures. The PT method is based on recording material surface temperature transients with infrared (IR) camera following thermal pulse delivered on material surface with flash light. The PT method has advantages for NDE of actual AM structures because the method involves one-sided non-contact measurements and fast processing of large sample areas captured in one image. The data cube of PT measurements consists of surface temperature taken at sequential time intervals T(x,y,t). Material defects can be detected either by analyzing the thermograms T(x,y,t) data cube, or by using thermal tomography (TT) algorithm to obtain 3D spatial reconstruction of thermal effusivity e(x,y,z). To reduce the cost and enable in-service NDE in spatially constrained environment, it is highly desirable to develop PT with compact and inexpensive IR camera. Following initial qualification of an AM component for deployment in a nuclear reactor, a compact PT system can also be used for in-service nondestructive evaluation (NDE) applications. However, data cube obtained with PT based on compact IR camera suffers from strong thermal noises and loss of features due to relatively low sampling rate. In this report we describe two unsupervised machine learning (ML) algorithms for enhancement of PT images obtained with compact IR camera. In one approach, we introduce Sparse Coding Discrete Cosine Transform (SC/DCT) algorithm to remove additive white Gaussian noise (AWGN) from spatial thermal effusivity reconstructions. In another approach we introduce a Spatial Temporal Denoised Thermal Source Separation (STDTSS) ML algorithm to process thermograms. The STDTSS algorithm consists of spatial and temporal denoising using Gaussian and Savitzky–Golay filtering, followed by the matrix decomposition using Principal Component Analysis (PCA), and Independent Component Analysis (ICA) to automatically detect flaws. In the work described in this report, we constructed a compact PT system using a relatively small and low-cost FLIR A65 camera, consisting on uncooled microbolometer detector. Performance of SC/DCT algorithm was demonstrated on enhancing TT images of Inconel 718 AM plate. Performance of the STDTSS methods was investigated using thermography data obtained from imaging stainless steel 316L specimens produced with LPBF method with imprinted calibrated porosity defects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A quality-agnostic combinatoric cost estimation model for large-format directed energy deposition metal additive manufacturing

Directed energy deposition (DED) additive manufacturing (AM) processes are amenable to synergistic combination into multi-process AM systems due to similar requirements for automation and energy sources. This work analyzes the economic performance of such DED AM systems from a quality-agnostic combinatoric standpoint with a model that calculates lowest-cost system combinations based on part geometry and process performance metrics. Common DED AM systems research focuses on a single process and does not consider the process, system, and application in the context of all possible system combinations (e.g., the combined set of process selection(s), motion system(s), and process hardware), leading to limited applicability of the resulting DED AM systems to cost-sensitive components such as those found in energy generation applications. The model developed herein incorporates the capital, material, and energy costs associated with DED AM system combinations into a predictive tool for estimating part and system cost, the output of which is intended to guide deployment of finite research and development resources towards DED AM system combinations with the lowest costs and greatest likelihood of economic impact. The DED AM systems identified by this framework may enable domestic production of the large conventionally cast and forged components necessary for energy generation.

Shanafield, Alexandra [ORNL]↗

PTT System Design and Data Analysis for Improved Performance: Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components

Additive manufacturing (AM, or 3D printing) for commercial nuclear energy applications is an emerging method for cost-efficient manufacturing aimed at replacing aging nuclear reactor parts and reducing costs for new construction. Because of the geometry of metallic structures of interest for nuclear applications, which consist of planar primitives with no symmetry of revolution, limited options are available for non-destructive evaluation (NDE) either during or post manufacturing. Known material flaws in AM include low density regions consisting of non-sintered powder, which have to be detected to ensure the safety of long-term performance nuclear reactor components. As a solution to NDE of AM, we are developing pulsed thermal tomography (PTT) models and depth inversion algorithms for 3D imaging. PTT has many advantages because the method is non-contact and allows for in-service, NDE of AM nuclear reactor parts. By analyzing transients of surface temperature response due to internal thermal resistances, one can obtain 3D reconstructions of material effusively using a unique inversion algorithm developed at Argonne. This study investigates the limits of PTT capability in detection of defects in metallic plates using COMSOL numerical modeling of heat transfer. Defects are modeled as cylindrical flat bottom holes (FBH), which is a common model of calibrated material flaws in thermal tomography experiments. Materials considered in this study include stainless steel 316 (SS316), stainless steel 304 (SS304), and Inconel 718. Theoretical analyses were conducted to validate inversion of simulated PTT data with COMSOL for a plate. Subsequently, 3D reconstructions were performed on COMSOL simulations for FBH, revealing a decrease in spatial resolution over depth due to thermal diffusion. The results of this study show that the performance of the inversion algorithm for detecting smaller defects depends strongly on the depth of the defect as well as the incident heat flux. The size of detectable defect was estimated by fitting a Gaussian function to surface temperature profile. The criteria for detectability was taken as 20mK noise equivalent temperature difference (NETD), which is currently the sensitivity limit of high-performance infrared cameras. It was determined through computer simulations that the smallest detectable FBH in SS316 has a 50µm diameter and is located 0.5mm below the plate surface.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Artificial Intelligence for Multiphysics Nuclear Design Optimization with Additive Manufacturing

The geometric flexibility of additively manufactured metals and ceramics generates a very large and open design space that requires advanced modeling and simulation tools for physics simulations and the rigorous definition of design problems. This effort deploys artificial intelligence (AI) and machine learning (ML) algorithms to understand the design space, evaluate potential designs, and more efficiently generate optimized results. The Transformational Challenge Reactor (TCR) program is leveraging advances in several scientific areas—including materials, manufacturing, sensors and control systems, data analytics, and high-fidelity modeling and simulation—to accelerate the design, manufacturing, qualification, and deployment of advanced nuclear energy systems. Through a manufacturing-informed design approach, the TCR program seeks to integrate digital data for rapid nuclear innovation; accelerate the adoption of advances in manufacturing, materials, and computational sciences for nuclear applications; and dramatically reduce deployment costs and timelines for new nuclear reactor technologies. This report documents efforts under the TCR program to leverage advanced modeling and simulation techniques driven by AI/ML algorithms on high-performance computing (HPC) systems to yield more optimized TCR core designs. A multiphysics ML surrogate model was developed to run on the HPC architectures. The surrogate model is trained on high-fidelity simulation data of coupled neutronics and thermofluidics and is used to quickly evaluate thousands of candidate core designs in parallel, which drives the evolution of the cooling channel shapes to minimize temperature peaking and material stress. Outcomes from these activities provide design information and feedback into the core design efforts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Application of Machine Learning to Monitor Metal Powder-Bed Fusion Additive Manufacturing Processes

The use of additive manufacturing (AM) is increasing for high-value, critical applications across a range of disparate industries. This article presents a discussion of high-valued engineering components predominantly used in the aerospace and medical industries. Applications involving metal AM, including methods to identify pores and voids in AM materials, are the focus. The article reviews flaw formation in laser-based powder-bed fusion, summarizes sensors used for in situ process monitoring, and outlines advances made with in situ process-monitoring data to detect AM process flaws. It reviews investigations of ML-based strategies, identifies challenges and research opportunities, and presents strategies for assessing anomaly detection performance.

Reutzel, Edward W.↗

Computational Process Modeling for Additive Manufacturing (OSU)

Powder-Bed Additive Manufacturing (AM) through Direct Metal Laser Sintering (DMLS) or Selective Laser Melting (SLM) is being used by NASA and the Aerospace industry to "print" parts that traditionally are very complex, high cost, or long schedule lead items. The process spreads a thin layer of metal powder over a build platform, then melts the powder in a series of welds in a desired shape. The next layer of powder is applied, and the process is repeated until layer-by-layer, a very complex part can be built. This reduces cost and schedule by eliminating very complex tooling and processes traditionally used in aerospace component manufacturing. To use the process to print end-use items, NASA seeks to understand SLM material well enough to develop a method of qualifying parts for space flight operation. Traditionally, a new material process takes many years and high investment to generate statistical databases and experiential knowledge, but computational modeling can truncate the schedule and cost -many experiments can be run quickly in a model, which would take years and a high material cost to run empirically. This project seeks to optimize material build parameters with reduced time and cost through modeling.

Bagg, Stacey↗

Feasibility Study to Dissolve Additively Manufactured Inconel 718 Support Structures

Additive manufacture (AM) component design face constrains due to support structure removal. Interior passages or delicate geometries require supports yet cannot be removed without compromising the design or complicating post-processing. A process was developed to dissolve metal AM supports where a sensitizing agent is applied post-build. During stress relief the sensitizing agent diffuses into the surface and alters the chemical composition of the top 100 to 200 μm. During an electrochemical dissolution process the sensitized region is susceptible to corrosion/dissolution and the etching reaction self-terminates once the sensitized region is dissolved. Support thickness varies from 80 to 200 μm, resulting in total dissolution or sufficiently weakened to facilitate removal. The objective of this project was to demonstrate a support structure dissolution process for IN718 components built using AM and to characterize the impact on mechanical properties, microstructure, and surface finish.

Omar R Mireles↗

Foil-based additive manufacturing system and method

An additive manufacturing system, method of manufacturing, and fabricated part. The system uses a material joining laser system to join together foil sheets to form a metal part. The material joining laser system can be configured to join adjacent foil sheets together in a substantially uniform manner. The manufacturing system also includes a material removal system that removes material from selected locations of the foil sheets to shape the foil sheets to correspond with selective slices of the part. The material removal system can be a laser system, such as a laser system configured to remove material from a foil sheet without removing material from an underlying layer. One embodiment involves the manufacture of amorphous alloy components.

Tsai, Hai-Lung↗

Low density syntactic foams via material extrusion additive manufacturing

An ink formulation for additive manufacturing of low density syntactic foams is described. The ink formulation can include a thermoset resin, a curing agent suitable for use with the thermoset resin, a plurality of hollow spheres, such as glass microballoons, one or more solvents, and one or more non-hollow, viscosity modifying filler. Also described are a method of preparing the ink formulation, a method of preparing three-dimensional objects comprising low density syntactic foams, and the three-dimensional objects prepared thereby.

Compton, Brett Gibson↗