Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Additively 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 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Investigate the height dependency of the micro-/defect-structure and mechanical properties of additively manufactured AlF357 aluminum alloy

When the laser powder bed fusion (L-PBF) additive manufacturing method is employed to build parts with increased heights, there is a possibility that defects are increased in part. This study investigates the effect of build height on the micro-/defect-structure and, consequently, the mechanical properties of L-PBF AlF357, an Al-Si-Mg alloy family. Tall vertical cylinders of 316 mm with 15 mm diameter were fabricated and cut into specimens at different heights. Although not much difference is observed in the microstructure (grain size and morphology), the defects' size and population slightly vary with height. Nonetheless, the tensile properties of the L-PBF AlF357 are found to be independent of height. This is ascribed to the approximately identical microstructure and marginal difference in the defect's size and distribution along the heights.

Laser powder bed fusion (L-PBF)↗
DOE OSTI2021

Optimal toolpath generation system and method for additively manufactured composite materials

The present disclosure relates to a system for optimizing an additive manufacturing (AM) process. The system may use a printing component for using a material to form a component in a layer-by-layer process. An electronic controller may control movement of one of the printing component or a substrate on which the component is being formed, in a manner to optimize a toolpath for the printing component as each layer of the component is formed. Optimization operations are performed using an optimization subsystem which enables manufacturability constraints, as well as optimized toolpaths for each layer of the component, to be defined using contours of a level-set function. The level-set function may be used to define the optimized toolpaths within a fixed, predetermined grid, and the optimized toolpaths then used to generate suitable code for controlling movement of the printing component relative to the substrate to create the part or structure in a layer-by-layer process, using the optimized toolpaths.

Lewicki, James↗
DOE OSTI2021

Additive manufacturing powder spreading technology to mitigate surface defects

A laser powder bed fusion additive manufacturing system having a powder dispenser that provides powder layers on a build platform; a laser fusion system that fuses the powder layers, wherein spatter particles are produce on the powder layers; and a powder bed sweeping system that sweeps the spatter particles from the powder layers. The powder bed sweeping system includes a brush that has bristles that contact the spatter particles and sweeps the spatter particles from the powder layers.

Khairallah, Saad A.↗
DOE OSTI2023

Use of latent metathesis polymerization systems for additive manufacturing

The invention is directed to latent metathesis-active resin compositions and additive manufacturing approaches. The latent metathesis-active compositions comprise at least one latent metathesis catalyst, at least one curable metathesis-active monomer, and optional fillers, photosensitizers, and/or a secondary monomer resin system for dual-cure. A method comprises extruding a latent metathesis-active resin from a dispensing apparatus and spatially triggering a ring-opening metathesis polymerization by directed irradiation with light or directed application of a thermal stimuli for direct-ink write printing of objects. Another method uses a latent metathesis-active resin for vat photopolymerization and stereolithographic printing of objects.

Appelhans, Leah↗
DOE OSTI2026

Exploring the tempering behaviour of additively manufactured high-alloy tool steel using synchrotron X-ray and neutron techniques

Post-processing heat treatment provides a critical pathway toward the commercialisation of additively manufactured (AM) S390 high-speed steel, which is a representative high-alloy tool steel employed in precision manufacturing, offering up to 1.5 times longer tool life and over 20% higher cutting speeds compared to conventional grades. In this study, the phase evolution of AM S390 steel during heat treatment, with particular emphasis on carbide precipitation behaviour, was systematically investigated using a combination of synchrotron X-ray and neutron techniques. The metastable M2C carbides were found to dissolve during austenitisation, while the stable primary carbides MC and M6C experienced coarsening with an average size increase of about 60 nm after just 2 min of tempering. Moreover, the austenite lattice parameters reduced from 3.618 to 3.608 Å within the first 10 min of tempering, suggesting carbon depletion in the steel matrix was likely associated with the formation of secondary carbides. This interpretation was substantiated by small-angle scattering results, which revealed the presence of nanoscale precipitates with a volume fraction of 3.1% after 60 min of tempering. These microstructural evolutions collectively accounted for the observed peak hardness of 921 HV. Furthermore, a comparative analysis of synchrotron and neutron small-angle scattering data highlighted the complementary strengths of each technique, offering critical insight into their suitability for characterising nanoscale features in AM high-alloy steels.

Synchrotron X-ray diffraction↗
NASA NTRSDate not supplied

Uncertainty Reduction With Multi-Model Monte Carlo for Crystal Plasticity Simulations of Additively Manufactured Metals

In this work, multi-model Monte Carlo estimators are developed to reduce uncertainty in quantities of interest (QoIs) extracted from crystal plasticity simulations of additively manufactured (AM) metals. A significant concern in AM parts is uncertainty in mechanical properties caused in part by complex microstructures that arise from the AM process. Quantifying uncertainty in microstructure-sensitive behavior using experiments alone is costly, especially when mechanical allowables must be established. Quantitative relationships among microstructure, micromechanical metrics like slip accumulation, crack initiation, and failure are also difficult to capture with limited experiments. Crystal plasticity material models instead enable computational prediction of micromechanical stress and strain fields given a discretized microstructure. However, high-fidelity finely discretized crystal plasticity simulations are computationally expensive, while lower-fidelity models are less accurate and generally biased, making uncertainty quantification and reduction computationally difficult as well. Multi-model Monte Carlo methods leverage correlations between high- and low-fidelity models to produce unbiased estimators for QoIs with reduced uncertainty relative to standard Monte Carlo. Crystal plasticity QoIs considered in this work include yield strength and the mean and extreme values of micromechanical fields that are relevant to crack initiation. Multi-model Monte Carlo estimators are developed for each individual QoI and several groups of QoIs. The results of this work establish relationships among model correlations, sample allocation, and uncertainty reduction for different combinations of QoIs and demonstrate a trend of less uncertainty reduction as QoIs become more sensitive to local microstructure. Limitations from using pilot samples to estimate model covariances and train low-fidelity models are also addressed. The uncertainty reduction achieved by multi-model Monte Carlo is an important step toward using computational mechanics models to predict microstructure-sensitive crack initiation and failure in AM parts.

uncertainty quantification↗
DOE OSTI2024

Multiscale and Machine Learning Modeling for Process-informed Microstructure Prediction in Additively Manufactured Materials Using MALAMUTE

Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy, aims to develop and qualify additively-manufactured materials for nuclear applications. The key challenges to these efforts are the microstructural variabilities observed on the AM products and their impact on the properties and performance of the material in extreme environments. AMMT is using a combination of high-through-put experimental and modeling techniques to accelerate the qualification efforts. Conventionally, in-situ and ex-situ characterizations and testing are performed to correlate different aspects of the AM process to the final product and its performance. However, adopting a trial-and-error approach to experimentally evaluate the vast range of process parameters required to capture the microstructural variabilities is cost-prohibitive. Modeling and simulation provide a comparatively inexpensive way to understand and correlate the microstructural evolution to the processing conditions. The modeling and simulation work-packages within the AMMT program aims to use physics-based and machine learning modeling capabilities to develop a digital twin for AM that can correlate the process conditions to the final product and establish a process-structure-property-performance (PSPP) correlation for AM materials. The melting and subsequent solidification that occurs during the AM process is a complex phenomenon that requires multiscale multiphysics analysis. Idaho National Laboratory’s (INL) Multiphysics Object-Oriented Simulation Environment (MOOSE), specifically the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) software, provides an ideal platform for developing the multiphysics multiscale model to explore the intricacies of the microstructural evolution during the AM processes within a single framework. Furthermore, given that such full-fidelity simulations can be computationally intensive, reduced order models are necessary to explore the PSPP space for AM materials in an efficient, reliable, and cost-effective way. This work package focuses on understanding the role of process variabilities on the various microstructural characteristics of the AM materials. Microstructures unique to AM materials, such as compositional micro-heterogeneity and dislocation cells, are of particular interest here since they can influence the creep properties and radiation performance. In fiscal year (FY) 24, we significantly advanced upon our work in the last fiscal year, both on physics-based and ML models. The alloy solidification model available in MOOSE has been extended to incorporate the thermodynamic properties and free energy relevant to 316SS. The model demonstrates the Cr segregation that occurs during solidifcation. It is demonstrated that rate of solidification and solute segregation is primarily influence by the cooling rate dictating the level of freezing. This work captures the microstructural variabilities at the subgrain level that are often missing in the part-scale models. With an aim to connect the microstructural evolution model to realistic process conditions, a reduced order model is developed for predicting the thermal conditions around meltpool from high-fidelity process simulations. Furthermore, machine learning approach is used to accelerate the temperature prediction during the AM process. In the following years, MALAMUTE will be used to connect different aspects of the models and quantitatively predict the microstructural evolution. The developed ML-based surrogate model will consider the process conditions as the input to predict the microstructural features in a cost-effective way. The generated microstructures can be used by other work packages under AMMT to evaluate the properties and environmental response of the material at the mesoscale. Thus, this work help identify the key microstructural features at the subgrain level that are significant in property/performance prediction of the AM products. This work will provide inputs to the large-scale process variability models to reevaluate and validate assumptions/simplifications made in the part-scale models. Furthermore, through active learning this work will help identify the data need from both modeling and experimental sides for development of a robust digital twin for AM.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Additive manufacturing of a metastable high entropy alloy: Metastability engineered microstructural control via process variable driven elemental segregation

Compositional paradigm shift in high entropy alloys (HEAs) provided new opportunities for microstructural engineering, whereas process control during laser powder bed fusion (LPBF) additive manufacturing (AM) enable fine microstructure tailoring. Metastability engineering in transformation induced plasticity (TRIP) HEAs by addition of minor alloying elements is an attractive strategy for fine microstructural tuning. This study explored in detail the microstructural evolution during LPBF AM of a metastable Fe 40 Mn 20 Co 20 Cr 15 Si 5 (at.%) dual phase HEA (CS-HEA). LPBF processing window for CS-HEA was established based on quantitative analysis and experiments. Based on melt pool overlap lack of fusion pores were observed at lower energy densities (J) of $\textit{J}$ ≤ 31.25 J/mm 3 and key-hole formation by melt pool destabilization in case of $\textit{J}$ ≥ 75 J/mm 3 . The microstructure of CS-HEA consists of metastable FCC-γ and HCP-ε phases; LPBF process parameters governed the final phase fraction in the alloy which has been correlated to metastability alteration of the high temperature γ phase. Final microstructural engineering was devised by LPBF process control which enabled cooling rate manipulation to guide Mn and Si segregation at the cell boundaries, thereby controlling the matrix metastability and final phase fraction. Additionally, high resolution transmission electron microscopy (TEM) revealed disparity in stacking fault morphology in CS-HEA with LPBF process variable alterations associated with local variations in chemical composition and stacking fault energy. Further, the phase evolution with process parameters also affected the nanomechanical behavior of the alloy.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Mesoscale Modeling of Dislocation Cell Structure Evolution and Radiation-Induced Segregation in Additively Manufactured Austenitic Stainless Steel

Structural alloys under irradiation develop radiation-induced segregation (RIS) at point defect sinks, which lead to undesired changes in the alloy's properties. Additively manufactured austenitic stainless steels are expected to yield a distinct response to irradiation damage owing to their unique as-printed dislocation cell structure. In this talk, we present the development of a mesoscale model for dislocation cell structure evolution coupled with RIS using the MOOSE framework. The evolution of network dislocations within spatially distinct cells and cell walls are modeled using climb-mediated edge annihilation and generation processes. Starting with initial microstructures of as-printed non-equilibrium segregations at dislocation cell walls, our 2D and 3D simulations explore the effects of irradiation temperature, dose rate, dislocation sink bias, and specimen thickness on microstructure evolution. The results will be compared against experimental characterizations of in-situ and ex-situ ion-irradiated samples, and the implications of evolving cell structure on irradiation damage response will be discussed.

additive manufacturing↗
DOE OSTI2020

Current challenges and potential directions towards precision microscale additive manufacturing – Part III: Energy induced deposition and hybrid electrochemical processes

The Part III of the four-part series of articles discusses the challenges and opportunities in microscale additive manufacturing processes, specifically focusing on energy-induced deposition and electrochemical processes. Compared to the direct ink write (DIW) and laser-based processes, the energy-induced deposition methods can fabricate high-resolution, high aspect ratio and complex parts, while the hybrid electrochemical process can be used to fabricate complex parts using a wide range of conductive and photoactive materials. However, the volumetric throughput of these processes is lower than their DIW and laser-based counterparts. The processes that have been explored in this process are Focused-ion Beam Induced Deposition (FIBID), Laser Chemical Vapor Deposition (LCVD), Menicus-confined Electrodeposition (MCED) and Laser-Enabled Electrochemical Printing (LECP). The range of processable materials, feature-size resolution, geometry and volumetric throughput are used as factors to evaluate the current state-of-the-art for these processes. Finally, novel approaches have been proposed in the article to address these challenges associated with microscale AM processes.

42 ENGINEERING↗
DOE OSTI2023

Additively Manufactured Strain Sensing for Nuclear Reactor Applications

Real-time monitoring of materials in harsh environments is a crucial technique towards reducing innovation time in nuclear systems. The successful measurement of real time, in-situ strain measurements during nuclear reactor operation requires innovative sensing solutions, including novel sensing strategies as well as advanced sensor design, manufacturing, and materials selection. In this paper, we will discuss two primary strategies for in-situ strain measurement strategies: additively manufactured (AM) capacitive strain gauges (CSGs) and digital image correlation (DIC). Current commercial strain gauges have limited applications in reactors due to the harsh operating conditions and non-trivial attachment strategies (i.e., welding, epoxy-adhesive) that can affect both the sensing performance and the underlying substrate under testing. AM CSGs are a viable solution as they have a low profile, low hysteresis, and wireless sensing integration capabilities that will enhance nuclear sensing technologies. In this work, the mechanical and thermal performance of the AM CSGs were tested up to 300 °C using ASTM standardized testing procedures to simulate the temperatures found in existing light water reactors. The AM CSGs had a similar performance across multiple samples which correlates to analytical models. This work leads towards the development of CSGs designed for higher temperatures and additional environmental factors found in Generation-IV reactors. Non-contact sensors, such as DIC, offer a less destructive way to measure deformation of materials when compared to alternative methods of in-situ strain determination, such as weldable strain gauges. However, DIC requires high contrast surfaces, which often relies on the implementation of artificial patterns. Using traditional splatter techniques to fabricate these patterns have limitations, including poor surface adhesion and reproducibility. In this work, AM fabrication techniques were implemented to avoid such limitations. Accordingly, aerosol jet printing (AJP) was used to print small scale periodic patterns of silver on stainless steel and aluminum tensile specimens. DIC was employed to monitor strain (up to 1100 µe) during temperature cycling from 23-600 °C. The results validated the use of AJP to better control pattern parameters for small fields of view applications at high temperatures.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Advances in high-pressure and high-temperature heat exchangers: Innovations via additive manufacturing and their applications

This paper provides a comprehensive overview of technological developments and applications for high-pressure and high-temperature (HPHT) heat exchangers produced through additive manufacturing (AM) techniques. As the demand for high-efficiency energy systems has been rising, the role of heat exchangers for thermal management and transport is becoming increasingly crucial. In this context, AM has emerged as a promising manufacturing solution to address the challenges posed by higher operating temperatures and/or pressures. This paper delves into three primary areas: the exploration of HPHT regimes supported by conventional heat exchangers, the impact of AM processes on thermal transport devices, and the discussion focused on HPHT heat exchangers produced via AM. The study examines the traditional manufacturing processes, materials, structures and geometries, and limitations of the commonly used heat exchangers for HPHT applications. Furthermore, it highlights the potential of AM in optimizing HPHT heat exchanger design, by reviewing studies that enable uniform flow distribution, minimization of fouling, and thermo-hydraulic performance augmentation without compromising structural stability. While addressing the limitations of cost, size, and other constraints, this study offers insights into the possibilities of AM in revolutionizing HPHT heat exchanger technology. The goal has been to fill the gap in literature by summarizing key studies, findings, and limitations, presenting a detailed examination, and proposing new areas for research. In conclusion, this review contributes to a deeper understanding of AM’s role in advancing HPHT heat exchangers for future energy systems.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Spatially resolved phase transformation mapping in 410 stainless steel during additive manufacturing visualized via real-time infrared data

Here, in this study, we demonstrate that spatially resolved cooling curves derived from real-time infrared (IR) thermography during additive manufacturing (AM) can capture spatial variations in phase transformation temperatures through cooling curve analysis (CCA). Using this approach, we show that during laser hot-wire deposition of 410 stainless steel (410SS), the martensite start temperature (M s ) evolves dynamically throughout the build. The M s temperature is spatially nonuniform, ranging from 185 °C to 348 °C, with the lowest values toward the build center and higher values toward the upper region of the deposit. In the lower portion of the build, no M s inflection is detected via CCA, consistent with transformation occurring earlier during thermal cycling followed by tempering during subsequent thermal cycles. These trends in M s are corroborated by characterizing the microstructure by electron backscatter diffraction (EBSD). Traditionally, M s is assumed to be constant, and a single interpass temperature is applied during both deposition and residual stress modeling. Our results demonstrate that IR-derived cooling curves provide a route to spatially and temporally resolved transformation temperature tracking for dynamic interpass control and improved residual-stress modeling.

Additive manufacturing↗
NASA NTRS2020

In-Situ Alloying of GRCop-42 via Additive Manufacturing: Precipitate Analysis

In situ alloying of elemental Cu, Cr, and Nb to form GRCop-42 (Cu-4at. % Cr-2at. % Nb)using laser powder bed fusion (LPBF) additive manufacturing (AM) was successful. Evaluation of the in situ alloyed GRCop-42(ISGRCop-42) was conducted using phase extraction to explore the effects of AM process conditions on the formation of Cr2Nb precipitates from elemental powders. It was found that ISGRCop-42successfully and repeatedly formed Cr2Nb at a yield as high as 89%of potential Cr2Nbcontent. Initial work shows that powder preparation was the most influential factor in alloying success, followed by laser power.

Additive Manufacturing↗
NASA NTRSDate not supplied

Maturation of Additive Manufactured Aerospace Alloys and Development of Mechanical and Thermophysical Properties for Space Applications

The National Aeronautics and Space Administration (NASA) has been involved in the development and maturation of metal additive manufacturing (AM) for space applications since the late 2000’s. Several efforts have focused on the understanding of AM processes through design optimization, component fabrication, material characterization, testing, standards development, and infusion into propulsion development for flight applications. NASA and partners have matured commonly used aerospace alloys from various alloy families (Nickel, Steel, Iron, Aluminum, and Titanium) and AM processes. An extensive effort has been ongoing between NASA, industry partners, and academia to complete detailed AM process and heat treatment characterization, in addition to generating temperature-dependent mechanical and thermophysical properties. This presentation highlights the characterization and property results using laser powder bed fusion (L-PBF) and laser powder directed energy deposition (LP-DED) processes among various alloys. In addition to commonly used alloys, there is a need for ongoing AM optimized alloys using integrated computational materials engineering (ICME) and process development for high performance applications. The applications targeted are launch vehicles, liquid rocket engines, advanced propulsion systems, advanced power systems, and in-space propulsion with high heat fluxes, high pressure, and that utilize propellants such as hydrogen, which can degrade alloys. This presentation will also discuss some of the ongoing novel alloy development and maturation using AM for use in these harsh environments, such as GRCop-42, GRCop-84, NASA HR-1, and C-103. The results from these processes have demonstrated that AM can enable rapid development and new AM optimized alloys can yield higher performance. These alloys have undergone modeling, fundamental metallurgical evaluations, heat treatment studies, and microstructure characterization and mechanical testing campaigns. This, combined with direct application-specific component fabrication and hot-fire testing, can enable the increase of the Technology Readiness Level (TRL) through high duty-cycle testing. This presentation provides a background and overview of these various common and AM-enabled alloys and processing developments including the initial effort related to metallurgical, mechanical, and thermophysical property studies. It also covers the latest advancement in the parallel component development, hot-fire testing, and future developments for these alloys.

Additive Manufacturing↗
DOE OSTI2023

Life cycle cost, energy, and carbon emissions of molds for precast concrete: Exploring the impacts of material choices and additive manufacturing

Molds for precast concrete are commonly used to create simple- to complex-shaped concrete products away from construction sites. These molds are often handmade from wood; however, additively manufacturing (AM, or 3D printing) fiber-reinforced polymer composites is an advantageous alternative, producing significantly more durable, highly complex molds faster, but likely at a higher cost. Here, this study explores the impact of material and production variables on the cost, energy, and carbon emissions of employing composite AM molds over the full lifecycle. The case study employed techno-economic and life cycle assessments to show that using wood flour–poly(lactic acid) or recycled carbon fiber–acrylonitrile butadiene styrene for AM molds can be less expensive than conventional wood molds, especially when considering use phase costs. While wood molds have the least environmental impacts due to wood's higher biogenic carbon sequestration and minimal processing, optimizing AM designs could reduce energy demand, carbon emissions, and cost.

36 MATERIALS SCIENCE↗
DOE OSTI2020

High-Energy X-ray Tomographic Analysis of Precursor Metal Powders (Ti-6Al-4V) Used for Additive Manufacturing

We utilized high-energy x-ray tomography to characterize Ti-6Al-4V metal powders (both as-received and recycled) used in powder-bed additive manufacturing process. The image processing workflow was developed to process and analyze large amount of data objectively by computer program. The distribution of size and shape of the metal particles as well as defect (mainly porosity) inside the particles was analyzed with the statistical representation and resolution in micrometer. The result revealed that circular-shaped porosity with various sizes could be embedded in the powder particles. These porosities could potentially be transferred to the 3D printed part and critically affect the mechanical performance of the component. The present study shows the effectiveness of characterizing metal powders using x-ray imaging techniques where sufficient number of particles can be sampled within tens of minutes with a minimum sample preparation and high accuracy. Clear structural differences in the as-received and recycled powders were delineated that helps in determining the feasibility of using the recycled powders.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Rethinking production of machine tool bases: Polymer additive manufacturing and concrete

Cast iron and steel weldments are the most common machine tool base elements. However, both construction methods have associated disadvantages for domestic machine tool manufacturers. Here, this paper documents the investigation of an alternative method for machine tool base production using concrete to fill an additively manufactured polymer mold, where the motion components are attached to the concrete base after the initial concrete curing. Modal testing results for a three-axis, vertical spindle prototype indicate high damping and stiffness can be achieved using the concrete base construction. Advantages are reduced cost and lead time compared to traditional methods.

Additive manufacturing↗