Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “large scale additive manufacturing”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Joining technique for in-oven/autoclave molds manufactured by large scale polymer additive manufacturing

Large scale additive manufacturing (AM) of fiber-reinforced polymer composites has gained traction in the mold and die community over the last decade, largely due to reduced material cost and lead time. However, limitations in mold size remain present due to printer volume constraints and costs associated with large format machines. Here, this paper describes a method for producing additively manufactured polymer molds in segments with an O-ring joint design, which can be machined and subsequently assembled for autoclave applications. The developed joining mechanism allows for maintaining the vacuum integrity during the cure cycle while accounting for the anisotropic nature of the additively manufactured polymer molds. Over a range of tested temperatures, 20–200 °C, the multi-part mold joining design was able to achieve full vacuum of ∼73.7 cmHg (29 inchHg) and maintain a vacuum integrity with vacuum losses less than 1.5 cmHg/5min (0.6 inchHg).

Joining↗
DOE OSTI2020

Characterizing material transitions in large-scale Additive Manufacturing

Integrating Multiple Materials (MM) into large-scale Additive Manufacturing (AM) is a key for various industrial applications wishing to incorporate site-specific properties into geometrically complex designs that are difficult to manufacture with traditional techniques. Printing with multiple materials is typically accomplished by using layers as natural material boundaries, but having the capability to switch between materials within a single layer without pausing would further expand MM possibilities. This study used Cincinnati Incorporated’s Big Area Additive Manufacturing (BAAM) system to explore material transitions with a novel dual-hopper that enables in-situ material blending of a pelletized feedstock. Constructing MM and functionally graded material (FGM) structures requires depositing a specific material composition at a specific geometric location to achieve a desired performance. Furthermore, accurately implementing this with the BAAM’s blended extrusion system requires a thorough understanding of the transition between distinct material compositions. This study characterizes a step-change transition between neat acrylonitrile butadiene styrene (ABS) and carbon fiber-reinforced ABS. Three distinct techniques were compared for analyzing the fiber content, and the transition zone between materials was characterized as a function of transition direction. The transition process was consistent to within 0.7 wt% carbon fiber variation between different layers and prints. The transition between materials was found to be directionally dependent, with ABS to CF/ABS having a transition length of 3.5 m compared to 3.2 m for CF/ABS to ABS. Furthermore, the transition from Material A to Material B was found to be repeatable with a possible variance in transition length of 0.3 m.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Large-scale additive manufacturing of self-heating molds

Large-scale material extrusion additive manufacturing technology is becoming the new mainstream technology for scaled-up composite mold and die applications. This paradigm shift in composite processing technology is primarily driven by out-of-autoclave tooling applications, in which fiber reinforced composite molds with scaled-up sizes and embedded heating elements are attractive. The present research describes the design, manufacturing, and testing of self-heating composite molds fabricated via a large-scale pellet extrusion 3D printing machine with an integrated wire co-extrusion tool. Polycarbonate (PC) composites reinforced with carbon fiber (PC/CF; 20 wt.%) and glass fiber (PC/GF; 20 wt.%) were used to fabricate mold parts. Joule heating thermal test results showed that uniform temperatures (~100 °C) were achieved for both PC/CF and PC/GF mold surfaces, using a custom-made feedback control power supply and infrared thermography. Mechanical characterizations, including tensile and flexural testing were performed on the wire-embedded and un-wired PC/CF and PC/GF base specimens to investigate the impact of the fiber reinforcement as well as the embedded wires. In the direction of extrusion, the ultimate tensile stress of PC/CF was 105 MPa, and that of PC/GF was 73 MPa, while the neat PC value was 64 MPa. Inner-bead voids and interfacial gaps were observed and characterized via optical and scanning electron microscopy. The embedded wires and inner bead impacted the mechanical properties of the composites. Furthermore, the stiffness of the wire-embedded mold was still satisfactory, proving that the technology can be used to fabricate additively manufactured out-of-oven/autoclave molds.

36 MATERIALS SCIENCE↗
DOE OSTI2020

HYBRID MANUFACTURING TECHNIQUE USING LARGE-SCALE ADDITIVE MANUFACTURING AND COMPRESSION MOLDING FOR HIGH PERFORMANCE COMPOSITES

Additive Manufacturing (AM) or 3-D printing has moved from small-scale prototypes to large-scale functional structures. With the introduction of large-scale 3D printers into the market a new industry has been born. For the first time, we are presenting the idea of preparing large-scale 3-D printed β-stage preforms to be used in traditional compression molding (CM) manufacturing technique to prepare final functional structures. Short carbon fiber (CF) reinforced material acrylonitrile butadiene Styrene i.e. ABS with 20% CF is used in present work. It is shown that highly aligned 3D printed short carbon fiber composite maintains its orientation after compression molding. A sandwich panel is prepared to show the capability to prepare complicated parts by integrating AM and CM. Interphase of the prepared dissimilar material is also studied using SEM. Samples prepared using AM-CM integration showed 11% and 79 % improvement in tensile strength and tensile modulus respectively compared to the traditional extrusion compression molding (ECM) process.

Kumar, Vipin↗
DOE OSTI2025

Genesis of a novel high-rate composite manufacturing process using large-scale additive manufacturing – compression molding (AM-CM) system: Possibilities and limitations

Oak Ridge National Laboratory (ORNL) has developed a highly automated manufacturing process for thermoplastic composites that combines the benefits of Additive Manufacturing and Compression Molding (AM-CM) to produce high-performance functional composite structures at automotive production rates. Here, the AM-CM process creates highly precise preforms by additively placing extruded fiber-filled polymers (with controlled fiber orientations and multi-material configurations) in the desired mold location before undergoing a secondary compression molding process immediately before the preform cools down. Preforms can be in the form of short, long-chopped, or continuous fiber-filled thermoplastic polymers (e.g., CF/GF-filled ABS, PC, LM-PAEK, etc.). The AM-CM process combines the benefits of controlled fiber alignment, that is only achievable in AM-printed parts with the classical CM process, which eliminates porosity and good surface finish. A preform created using AM-CM can integrate various materials to enable additional architectural functionalities, including over-molding, selective stiffening, and the incorporation of electrically or thermally conductive channels. All these advantages come with a fast part production cycle time. The AM-CM process can manufacture multi-material, multi-functional parts in under 3 min, starting from raw material (pellets) to the final product. The novel AM-CM process offers superior microstructural control and enhanced multi-functionality previously unattainable with any other traditional high-rate thermoplastic composite manufacturing method. This work covers the manufacturing concept, system development, materials and applications of AM-CM process in detail.

Kumar, Vipin [Oak Ridge National Laboratory (ORNL)↗
DOE OSTI2024

In-Process Monitoring and Structural Health Monitoring of Large-Scale Additive Manufacturing Using Acoustic Emission Technique

ORNL collaborated with MISTRAS Group, Inc. to investigate acoustic emission (AE) as a structural health monitoring (SHM) method for large-scale additive manufacturing (AM). Large-scale AM is being adapted as method of producing large structures in a short lead time and cost-effective way. With the growing advancement in AM techniques and application, machine monitoring and part qualification is highly needed. There has been leading research focused on the manufacturing, feedstock material but minimum research on the SHM, defect detection, and nondestructive evaluation (NDE) for AM. Scanning large structure using conventional nondestructive testing (NDT) techniques, such as ultrasound or X-ray, and searching for potential defects can be very time consuming, challenging and cost prohibitive. AE is a passive technique that can be used to monitor and locate defect progression in large structure by distributing group of sensors around the part. This project utilized AE technique and system manufactured/designed by MISTRAS Group to monitor large-scale AM equipment (i.e. Big Area Additive Manufacturing (BAAM) system located at the Oak Ridge National Laboratory – Manufacturing Demonstration Facility (ORNL-MDF) and the printed parts it produces. The AE system provided valuable insight on defect development/progression during and post-printing process.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Investigating the effect of different shielding gas mixtures on microstructure and mechanical properties of 410 stainless steel fabricated via large scale additive manufacturing

Metal Big Area Additive Manufacturing (mBAAM) offers the potential to fabricate large scale tools at high deposition rates (15 lb/h+). 410 martensitic steel is a potential tooling material, owing to its low cost, good machinability and reasonable printability. During the mBAAM process, the shielding gas can have a significant impact on the material properties as well as the process cost. Therefore, the current study aims to understand the effect of different shielding gas mixtures on large-scale additive manufacturing of 410 martensitic stainless steel. We show that an argon mixture with 3% nitrogen gas produced the best performance in terms of maximum hardness and tensile strength, with much less scatter in tensile strength. He-Ar-CO 2 or tri-mix shielded samples showed a low tensile strength with wide scatter, due to stabilized delta ferrite in microstructure during printing. Both tri-mix and Ar-CO 2 shielded samples showed slightly higher porosity. Thus, we recommend the use of argon-3% nitrogen as a shielding gas mixture for processing 410 steel for tool applications, based on the relatively low cost of this gas mixture and the resulting higher hardness, higher dimensional stability, and lower porosity.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Reducing warpage in a hybrid large-scale additive manufacturing and compression molding process

In recent years, a hybrid manufacturing process, developed by combining extrusion-based large-scale additive manufacturing (AM) and compression molding (CM) techniques, has shown promising outcomes for producing structurally functional parts. The process can be used with both short fiber-reinforced composites and neat polymers and hence, even multi-material parts can be manufactured easily. This process offers the advantages of structural enhancement by having a desired fiber orientation using a large-scale AM process, as well as rapid manufacturing capability using a CM process. In the large-scale AM process, the alignment of fibers in the deposition direction enables significant improvement in the mechanical properties of the manufactured parts. However, the anisotropy resulting from the directional arrangement of fibers also introduces challenges related to warpage in the produced parts. This study aims to identify the causes of warpage and propose strategies to mitigate it. The research involves the use of preforms manufactured through the large-scale AM, which are then combined with the neat resin for CM manufacturing. A finite element-based numerical simulation model is developed, employing a sequentially coupled thermomechanical approach. Through a parametric study using the simulation models, optimization of printing direction and preform geometry is performed to minimize warpage. This contributes to the advancement and wider adoption of AM/CM hybrid manufacturing to produce structurally functional parts.

Jo, Eonyeon↗
DOE OSTI2023

Using Large-Scale Additive Manufacturing for Wind Turbine Blade Core Structures

This report describes the techno-economic potential of using additive manufacturing technologies to design large wind turbine blade structures. After considering all additive technologies, the authors identified large-scale, polymer-based, material extrusion as the three-dimensional (3D) printing technology best suited to meet modern wind turbine blade manufacturing costs, cycle times, and geometric scale. Due to the lower structural performance requirements and the opportunity to reduce resin uptake mass penalties within the blade, the core material within the sandwich composite sections of the wind turbine blade is established as a logical entry point into advanced wind turbine blade manufacturing.

17 WIND ENERGY↗
DOE OSTI2022

THE DESIGN OF LAYER TIME OPTIMIZATION IN LARGE SCALE ADDITIVE MANUFACTURING WITH FIBER REINFORCED POLYMER COMPOSITES

In this study, we have developed a method to optimize a layer deposition time (a.k.a. layer time) for large-scale additive manufacturing (AM) via physics-based simulations. A long layer time leads to an over-cooled surface on which a new layer is deposited, and therefore, it may result in a weak bonding or debonding between layers, cracking, or warping. A short layer time leads to a high temperature of the structure due to insufficient cooling, and therefore, the structure may not be stiff enough and may collapse during manufacturing. Therefore, it is important to estimate the optimal layer time in additive manufacturing for a high-quality product. The temperature of a top layer right before deposition is recommended to be slightly higher than the glass temperature of the material. A temperature cooling was approximated to an exponential function of time, and the optimized layer time was obtained based on a target temperature while maintaining a minimal printing time. The material used is carbon fiber-reinforced polycarbonate (CF/PC), and the large-scale deposition system used is LSAM TM from Thermwood Corporation. Three different layer time cases were used for experiments, and a series of thermal images were obtained via an infra-red (IR) camera during the entire AM processes. AM process simulations were performed using a finite element method and the temperature profiles from the simulation were in good agreement with those from experiments. The layer time optimization was performed based on the temperature profiles from the simulations. A layer temperature with the optimal layer time was confirmed as the target temperature through simulation.

Jo, Eonyeon↗
DOE OSTI2021

Supervisory control and health monitoring framework for large-scale additive manufacturing systems. Final CRADA report

ORNL worked with National Instruments (NI) to develop a large-scale, complex additive manufacturing (AM) systems framework for remote health monitoring and supervisory control. We found the framework, based on the Lincoln Electric Metal AM system located at ORNL’s MDF, capable of controlling the process, leading to improved part quality and digital twin creation.

42 ENGINEERING↗
DOE OSTI2021

Kinematics of a Cable-Driven Robotic Platform for Large-Scale Additive Manufacturing

Concrete additive manufacturing (AM) is a growing field of research. However, on-site, large-scale concrete additive manufacturing requires motion platforms that are difficult to implement with conventional rigid-link robotic systems. This article presents a new kinematic arrangement for a deployable cable-driven robot intended for on-site AM. The kinematics of this robot are examined to determine if they meet the requirements for this application, the wrench feasible workspace (WFW) is examined, and the physical implementation of a prototype is also presented. Data collected from the physical implementation of the proposed system are analyzed, and the results support its suitability for the intended application. The success of this system demonstrates that this kinematic arrangement is promising for future deployable AM systems.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Layer Time Control for Large Scale Additive Manufacturing Using High Performance Computing

This work proposes to optimize an additive manufacturing AM process to reduce energy and printing cost. The polymer AM process is inherently dependent on the time-temperature history of each layer to maintain geometric tolerances and mechanical integrity. Our preliminary study shows that regression-based layer time control model using thermal images could result in up to 30% build time reduction for simple geometries. This proposed work would use high-performance computing (HPC) to couple the data-driven model with thermal simulation for better predicting layer temperature profiles, improving throughput of large-scale additive manufacturing, and reducing its energy cost. We have developed a method to optimize a layer deposition time (a.k.a. layer time) for large-scale AM via physics-based simulations. A long layer time leads to an over-cooled surface on which a new layer is deposited, and therefore, it may result in a weak bonding or debonding between layers, cracking, or warping. A short layer time leads to a high temperature of the structure due to insufficient cooling, and therefore, the structure may not be stiff enough and may collapse during manufacturing. Therefore, it is important to estimate the optimal layer time in additive manufacturing for a high-quality product. The temperature of a top layer right before deposition is recommended to be slightly higher than the glass temperature of the material. A temperature cooling was approximated to an exponential function of time, and the optimized layer time was obtained based on a target temperature while maintaining a minimal printing time. The material used is carbon fiber-reinforced polycarbonate (CF/PC), and the large-scale deposition system used is LSAM TM from Thermwood Corporation. Three different layer time cases were used for experiments, and a series of thermal images were obtained via an infra-red (IR) camera during the entire AM processes. AM process simulations were performed using a finite element method and the temperature profiles from the simulation were in good agreements with those from experiments. The layer time optimization was performed based on the temperature profiles from the simulations. A layer temperature with the optimal layer time was confirmed as the target temperature through simulation. In addition to the development of a layer time optimization method, we have developed a numerical framework for AM simulation with element activations in sync with toolpath, based on an open source finite element framework, DEAL.II. A major portion of this work was presented at SAMPE 2022 Conference and Exhibition on May 2022, and published in Proceedings of SAMPE 2022.

42 ENGINEERING↗
DOE OSTI2022

Large-Scale Additive Manufacturing of Silicon Carbide with Process Monitoring

This report summarizes new capabilities in additive manufacturing (AM) of large-scale silicon carbide (SiC) components under the Advanced Materials and Manufacturing Technologies (AMMT) program. SiC is a promising material that is being considered for many advanced reactor designs due to its high temperature strength, radiation tolerance, minimal neutron absorption, and oxidation resistance [1-8]. One of the primary limitations to using SiC as an in-core structural material is the inability to fabricate large SiC components with complex geometries. While under the former Transformational Challenge Reactor (TCR) program, ceramic AM systems at the Oak Ridge National Laboratory (ORNL) were limited in the quantity and overall size achievable for producing ceramic AM components. To address this, ORNL has improved its infrastructure for binder jet and chemical vapor infiltration (CVI) processes with cutting-edge equipment coming online in a newly renovated laboratory space capable of producing larger components and higher throughput without compromise on part size. This report details the laboratory renovation progress, focusing specifically on the DesktopMetal (formerly ExOne) X25Pro binder jet, a large scale CVI furnace, and the added functionality of a software tool called Peregrine for quality assurance and control purposes.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Dual Material System for Polymer Large Scale Additive Manufacturing

Big Area Additive Manufacturing (BAAM) technology allows for manufacturing of large-scale objects with a potential to reduce energy embedded in products, reduce or eliminate energy necessary for transportation of goods along with reducing the lead time and cost in some cases. Over the last few years, Oak Ridge National Laboratory (ORNL) has been focusing on large-scale printing of single material systems, typically un-reinforced or short fiber reinforced polymers, in order to address needs in stiffness-limited applications. This paper describes the development of a multi-material large-scale AM system through a collaboration with Cincinnati Inc. and Performance Feed Screw Inc. Modifications to the Big Area Additive Manufacturing (BAAM) system includes a new extruder design to accommodate a dual feed system, an expanded two-dryer system with a capacity of 273 kg/dryer, and a system that is capable of mixing pelletized materials up to 60Kg/hr. This article highlights the advantages and limitations of the multi-material system as well as potential applications.

Smith, Tyler↗
DOE OSTI2023

In-Situ Monitoring Assisted Large-Scale Additive Manufacturing of Mild Steel and 316L Alloys for Nuclear Application

The Advanced Materials and Manufacturing Technologies (AMMT) Program is aimed at developing cross-cutting technologies in support of a broad range of nuclear reactor parts, and to maintain U.S. leadership in materials and manufacturing technologies for nuclear energy applications. The overarching vision of the AMMT program is to accelerate the development, qualification, demonstration and deployment of advanced materials and manufacturing technologies to enable reliable and economical nuclear energy. One of its three goals is to target big challenges and game-changing technologies, to realize the mission and vision of AMMT program. Based on this context, this multi-year work package focuses on understanding the current state of large-scale additive manufacturing (AM) technology for the deposition of 316L stainless steel materials for final components and mild steel for use in nuclear manufacturing processes. The targeted AM modality is directed energy deposition (DED), capable of fabricating components on the size scale of meters including valves, pumps, impellers. etc. that are challenging or difficult to source, especially when developing new systems or replacing obsolete components. Accordingly, the current writeup aims at providing a baseline literature survey on structure-property relationships in mild steel and 316L alloys. Also, information on preliminary trials to date involving these two alloys show tremendous potential of printing parts having complex geometry and thin- walled structures, such as nuclear valve and Hot isostatic Press (HIP) can, using wire based (Wire Arc Additive Manufacturing and Hybrid Additive Manufacturing) as well as blown powder DED machines. All of this is aimed towards (i) demonstrating the ability to fabricate large components for pressure boundary applications relevant to the nuclear community and nuclear manufacturing technology, and (ii) understanding the effect of different manufacturing technology on AM can production and post HIPed material for nuclear applications. Another target of this writeup is to compile various in-situ monitoring tools that have been incorporated for different DED AM modalities, in order to understand process variability during the entire fabrication process. This can be correlated with processing-structure-property response surfaces and would add confidence around process quality verification and ultimately component certification for nuclear applications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Anisotropic thermal behavior of extrusion-based large scale additively manufactured carbon-fiber reinforced thermoplastic structures

Large format additive manufacturing (AM) enables rapid manufacturing of large parts and structures with minimum waste in material and energy. Extrusion-based AM deposition processes provide parts with highly anisotropic thermal properties, which are not typically reflected in textbook values for these materials. In order to develop accurate models that describe the directionally dependent thermal behavior of these materials in processing and service, accurate measurements of specific heat capacity and thermal conductivity are required. Here, this work characterizes, documents, and analyzes the effect of the anisotropic nature of the extrusion-based deposition process on the specific heat capacity and thermal conductivity of the resulting AM products. All measurements were made over a temperature range of 20–180°C using the transient plane source technique, also referred to as the hot disk technique. Three of the most commonly used large format AM feedstock materials that utilize carbon fiber reinforcement were examined in this work: acrylonitrile butadiene styrene, polyphenylene sulfide and polyphenylsulfone. Finally, these findings can serve as a thermal design/process guideline for future large format AM applications.

36 MATERIALS SCIENCE↗