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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Effect of toolpath in large-format additive manufacturing with bio-derived composites

There has been growing interest in integrating bio-derived composites into Large-format additive manufacturing (LFAM) feedstocks to reduce the use of petroleum-derived materials and reduce the overall carbon footprint of LFAM. However, these materials present unique challenges during manufacturing due to their variability, which can lead to unintended deformations and failures attributable to suboptimal process conditions. While numerical modelling has been extensively employed to simulate numerous manufacturing processes, its application in LFAM with bio-derived composites remains limited. This study addresses this gap by systematically developing a numerical model to simulate the LFAM process using bio-based materials, specifically wood fiber-reinforced polylactic acid (PLA/WF). Experimental investigations were conducted to characterise the thermal and mechanical properties of additively manufactured PLA/WF specimens. Numerical simulations were performed to predict temperature profiles and deformations during LFAM. The effect of varying infill patterns, internal structures, and tool paths on the temperature distribution and deformation of printed parts was explored using the developed model. This article aims to advance the utilisation of bio-derived composites in LFAM systems and provide a comprehensive understanding of the LFAM process. The findings offer valuable insights for optimising process parameters and enhancing the performance of LFAM with bio-based composites.

Large-format additive manufacturing↗
DOE OSTI2024

Advanced multimaterial shape optimization methods as applied to advanced manufacturing of wind turbine generators

Abstract Currently, many utility‐scale wind turbine generator original equipment manufacturers are dependent on imported rare earth permanent magnets, which are susceptible to market risks from cost instability. To lower the production costs of these generators and stay competitive in the market, several small wind manufacturers are pursuing continuous improvements to both generator design and manufacturing. However, traditional design and manufacturing methods have yielded marginal improvements in wind power performance. This work presents novel methods to redesign a baseline 15‐kW wind turbine generator with reduced rare‐earth permanent magnets by leveraging cutting‐edge three‐dimensional (3D) printed polymer‐bonded permanent magnets and steel. Symmetric, asymmetric, and multimaterial‐magnet parametrization methods are introduced for shape optimization. We extend the symmetric and asymmetric methods to the back iron in the stator to further investigate the impact and opportunities for performance improvements with lesser active materials. We employ a design‐of‐experiments approach with parametric computer‐aided design for shape generation and evaluate different designs by magneto‐thermal modeling and finite‐element analysis. We use adaptive sampling technique to identify better performing designs with lesser magnet mass, higher efficiency, and lower cogging torque when compared with the baseline generator. Asymmetric pole designs resulted in a magnet mass in the range of 4.77–5.37 kg, which was 27%–35% lighter than the baseline generator, suggesting that a new design freedom exists that can be enabled by advanced manufacturing, such as 3D printing. Shaping the back iron in the stator resulted in material savings in electrical steel of up to 14.62 kg, which was 20% lighter than the baseline stator. We conducted a structural analysis to evaluate an optimized asymmetric rotor design from the point of view of mechanical integrity and air‐gap stiffness. The magnetically optimal shape profile was shown as having a positive impact on the radial stiffness, and an optimal solution was discovered to reduce the structural mass by nearly 30 kg, which was 29% lighter than the baseline.

17 WIND ENERGY↗
DOE OSTI2023

Characterization of Fe-6Si Soft Magnetic Alloy Produced by Laser-Directed Energy Deposition Additive Manufacturing

Abstract Commercial electrical steels, Fe-Si alloys with < 4 wt.% Si, are inexpensive and efficient materials for electrical power conversion. Further efficiency improvements require increasing the silicon concentration to 6 wt.%, at which point the material becomes brittle and difficult to form by conventional rolling and sheet fabrication methods. Additive manufacturing stands to overcome challenges with commercial manufacturing techniques by leveraging near-net-shape fabrication. The wide array of process conditions provides additive manufacturing with increased flexibility, enabling control over the microstructure and mechanical properties. This work explores the microstructures and magnetic properties of ring-shaped Fe-Si alloys produced using concentric and cross-hatch tool paths on a laser-directed energy deposition additive manufacturing system. Concentric-built samples exhibit elongated grain structures while cross-hatch-built samples comprise lower aspect ratio grain structures. Thermal finite element analysis simulations model the stress conditions produced by the different scan path geometries. Microhardness measurements probe the mechanical properties as a function of anneal temperature, providing a qualitative understanding of the intergranular defect density. Soft magnetic properties measured under quasistatic and AC conditions show frequency- and microstructure-dependent coercivity and permeability. Finally, analysis of the core loss quantifies how the build strategies and thermal treatments influence efficiency in electrical power conversion applications. Understanding the influences of scan path geometry and thermal treatment provides a pathway towards application of additively manufactured soft magnetic materials.

Adamczyk, Jesse M.↗
DOE OSTI2022

Data Mining and Visualization of High-Dimensional ICME Data for Additive Manufacturing

Integrated computational materials engineering (ICME) methods combining CALPHAD with process-based simulations can produce rich, high-dimensional data for alloy and process design. In ICME methods for metallurgical applications, the visualization and interpretation of such high-dimensional data has previously been through heat maps represented in 2 or 3 dimensions. While such an approach is ideal when one variable is varied at a time, in the case of high-dimensional data with multiple variables varied simultaneously, as is the case in additive manufacturing, interpreting the trends through two- or three-dimensional heat maps becomes challenging. Here, we propose a strategy of mixed visual data mining and quantitative analysis for high-dimensional metallurgical and process data using high-throughput thermodynamic calculations. Two case studies show the application of the proposed approach. The first case study investigated the effects of feedstock chemistry on the δ ferrite formation in 316L stainless steel powders used for binder jet additive manufacturing. The second case study linked Scheil–Gulliver calculations to a process model for dissimilar joining of aluminum alloys 5356 and 6111 during laser hot-wire additive manufacturing. Both cases contained thousands of calculated data points, showcasing the utility of visual data analysis through parallel coordinate plotting, Pearson correlation coefficient matrices, and scatter matrices compared to traditional process maps. These visualization techniques can be extended to many additive manufacturing problems to capture process–structure–property relationships for additively manufactured components.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Validation Data for Benchmarking Wire Arc Additive Manufacturing Process Simulations

Residual stresses cause geometric distortion and affect mechanical performance of additively manufactured structures, yet they are notoriously difficult to assess and predict. Distortion (warpage) can drive parts outside dimensional tolerance limits, leading to part rejection or rework. For parts that meet tolerance, locked-in residual stress fields can affect structural integrity during operation, particularly subcritical cracking by fatigue, creep, or corrosion. This work develops benchmark data for a common additive manufacturing process (Wire Arc Additive Manufacturing) that can be applied for calibration and validation of physical process models that predict residual stress fields. The work includes design of two different samples of differing geometry, detailed manufacturing records for a set of physical samples, and an extensive set of residual stress measurement data developed using two diverse techniques (the contour method and neutron diffraction). An initial application of the work is also reported, where a modeling challenge was issued to secure residual stress model predictions from two independent laboratories that were blind to residual stress measurement data. These initial blind residual stress predictions show significant discrepancies relative to the measurement data, illustrating the potential value of the underlying validation data. An open repository for this work, including the sample designs, manufacturing process records, and the residual stress data, is also provided for future application in non-blind validation efforts.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Additive Manufacturing in the Nuclear Reactor Industry

This article discusses the application of additive manufacturing in the nuclear reactor industry.Additive manufacturing for nuclear applications increased significantly in the late 2010s due to rapid progress in technology, particularly with methods using metals and ceramics.Because these manufacturing technologies are uniquely data-rich, they allow for an advanced understanding of materials, and they offer the potential to predict part performance based on build data. The inherent characteristics of additive manufacturing technologies allow for rapid prototyping and geometric freedom, making it possible to implement an accelerated agile design process for advanced nuclear reactor applications. Predictive high-fidelity multiphysics simulations are crucial to fully leverage this geometric flexibility. Qualification and regulator acceptance ultimately determine the breadth and scope of applications for these technologies. The US Department of Energy Office of Nuclear Energy Transformational Challenge Reactor program integrates many of these elements to accelerate the deployment of additive manufacturing technologies to industry.

Betzler, Benjamin↗
DOE OSTI2022

Laser diagnostics to characterize the in-flame growth of platinum nanoparticles manufactured by the reactive spray deposition technology

Reactive Spray Deposition Technology (RSDT) is an atmospheric pressure, flame-based advanced manufacturing method used to fabricate Membrane Electrode Assemblies (MEAs) for proton exchange fuel cells and water electrolyzers. RSDT combines the flame synthesis of catalyst nanoparticles and their deposition onto the membrane in one step. The properties of the synthesized nanoparticles, such as their Size Distribution Function (SDF), determine the manufactured electrodes’ performance, which can be evaluated when the deposition is complete via ex-situ characterization of the products. Efforts to improve RSDT for manufacturing state-of-the-art MEAs can be significantly enhanced with integrated laser diagnostics that enable in situ measurement of the synthesized catalyst nanoparticles. This paper reports the implementation of laser diagnostics in an RSDT facility and evaluates their potential to assist the manufacturing process. Laser Light Scattering (LS) and Laser-Induced Incandescence (LII) measurements are performed in the oxygen-rich zone of the flame at various distances from the flame fuel jet nozzle downstream of its luminous region. The measurements quantitatively track the evolution in size and volume fraction of platinum-based nanoparticles in two flames that yield different catalytic properties in the manufactured electrodes. The profiles of the measured nanoparticles’ volume fraction along the flame axis can be estimated a priori so that the average nanoparticle sizes can be measured in quasi-real time via LS. Nanoparticles experience an extremely slow growth rate while being convected at distances from 150 nm to 300 nm from the fuel nozzle. Complementary characterizations of the synthesized nanoparticles are performed ex-situ via High-Angle Annular Darkfield Scanning Transmission Electron Microscopy (HAADF-STEM) image analyses of samples collected on grids at a fixed distance from the fuel jet nozzle. Comparing the results from laser and microscopy techniques not only cross-validates the findings but also provides the parameters to infer the bimodal SDF in-situ and yields evidence that the coagulation efficiency of the synthesized nanoparticles has extremely low values in the investigated zone of the flames.

Rayleigh Light Scattering (LS)↗
DOE OSTI2023

Recyclability of additively manufactured bio-based composites

As the flexibility, efficiency, and application space of additive manufacturing continues to grow, many have begun to investigate more sustainable feedstocks as well as options for the end of life of additively manufactured parts. This study examines the effects of mechanical recycling on additively manufactured parts from bio-based feedstock. Here, articles were printed on the Big Area Additive Manufacturing (BAAM) system at the Oak Ridge National Laboratory using poly (lactic acid)/wood flour (PLA/WF) pellets. These parts were shredded and granulated, and the granulate was fed directly back into the BAAM system for re-printing, skipping the costly and energy-intensive steps of extrusion and pelletization. The chemical, mechanical, thermal, and rheological changes to PLA/WF before and after recycling were investigated. Additionally, the energy savings from directly printing granulate on the BAAM system without extrusion and pelletization is reported. It is shown that PLA/WF is an excellent candidate for recycling of large format additively manufactured parts, and value of these parts can be reclaimed while saving cost and energy through mechanical recycling.

42 ENGINEERING↗
DOE OSTI2023

Silicon carbide fiber manufacturing: Cost and technology

Significant advances have been made in the past decade concerning silicon carbide fiber manufacturing methods resulting in near-stoichiometric small-diameter fibers that meet the property requirements for most of the ceramic matrix composites (CMC) and nuclear applications. The manufacturing cost, however, remained prohibitively high, preventing the use of it in different applications requiring much lower cost. Silicon carbide (SiC) fiber reinforced CMC is dominated by the cost of SiC fiber which comprises more than 50 % of the finished part cost. Here, this article provides insight into the SiC fiber manufacturing costs and highlights the need for an alternative SiC fiber precursor and manufacturing method. Analysis of the existing polycarbosilane (PCS)-based SiC fiber manufacturing shows that the crosslinking (curing) and raw material preparation steps are high-cost steps that need lower cost options. Alternative SiC fiber precursor should be sought for lowering the cost of SiC fibers.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A techno-economic framework for comparing conventionally and additively manufactured parts for geothermal applications

Geothermal reservoir characterization, construction, and operations are technology-intensive activities that contribute significantly to the cost of delivering renewable electricity. The technologies involved, such as downhole tools and drilling equipment, are similar to those used in oil and gas exploration and production must often be adapted for use in the corrosive, high-temperature geothermal reservoir environment. Low production volume of geothermal tools presents a major challenge in meeting the industry's technology needs. Production of specialized tools for geothermal subsurface applications is often cost-prohibitive. Reduced inventory of subsurface well construction, characterization, and production tools causes geothermal reservoir development efficiency and sophistication to lag behind that of the oil and gas industry. Advances in additive manufacturing provide opportunities to advance geothermal technology while reducing lead time and costs associated with production of low-volume, complex parts. Additionally, this paper performs an initial techno-economic analysis comparing the cost of conventional production techniques and additive manufacturing for geothermal downhole applications. An analysis of representative downhole tools is used to create a framework for estimating fabrication costs of subtractive and additive techniques, including post-print machining required to meet final tolerances. The framework is used to explore several manufacturing scenarios and identify the dominant factors driving manufacturing time and cost. The current feasibility of additive manufacturing for geothermal downhole tool applications is assessed and issues for future development to better meet the needs of the geothermal industry are identified.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Cold spray manufacturing of oxide-dispersion strengthened (ODS) steels using gas-atomized and ball-milled 14YWT powders

The cold spray deposition process has been investigated for the manufacture of 14YWT oxide-dispersion strengthened (ODS) steel, a nanostructured ferritic alloy (NFA), using gas-atomized and ball-milled feedstock powders. Cold spraying of the gas-atomized powder resulted in a thick dense deposit, but annealing them above 900 °C induced grain growth and heterogeneous precipitation of nanoparticles, thus resulting in lower hardness (~ 170 HV) compared to 14YWT ODS steel manufactured by the conventional method. The ball-milled powder (Fe-14Cr-3W-0.4Ti-0.2Y-0.125O) was cryomilled in liquid N 2 to achieve small particle sizes followed by annealing in a H 2 /Ar environment at 1000 °C and 1100 °C to reduce the hardness from ~ 8 GPa to ~ 5 GPa. Both smaller particle sizes and lower hardness of annealed powders made them amenable to the cold spray deposition process, resulting in thick and dense deposits, while retaining the favorable fully solutionized microstructure of the ball-milled powders. The microstructure of the as-deposited ODS exhibited very fine grain sizes (50–250 nm) with a uniform dispersion of Y-Ti-O nanoprecipitates in the ferritic steel matrix. The hardness values of the cold spray deposits using the powders annealed at 1000 °C and 1100 °C was 770 HV and 496 HV, respectively. Post-heat treatment of the as-deposited material up to 1100 °C showed a high-density microstructure with uniformly dispersed nanoscale oxide particles. The hardness of the annealed deposits up to 1000 °C had a notably higher hardness than bulk 14YWT ODS steel manufactured by conventional methods. The study demonstrates that cold spray deposition of the microstructurally-tailored feedstock powders can be used to successfully manufacture ODS steel with microstructure and properties comparable to those produced by the conventional methods, while providing for an attractive option for the more rapid and cost-effective manufacturing of ODS steel cladding tubes.

14YWT↗
DOE OSTI2022

Strong yet ductile nanolamellar high-entropy alloys by additive manufacturing

Additive manufacturing produces net-shaped components layer by layer for engineering applications. The additive manufacture of metal alloys by laser powder bed fusion (L-PBF) involves large temperature gradients and rapid cooling, which enables microstructural refinement at the nanoscale to achieve high strength. However, high-strength nanostructured alloys produced by laser additive manufacturing often have limited ductility. In this work, we use L-PBF to print dual-phase nanolamellar high-entropy alloys (HEAs) of AlCoCrFeNi 2.1 that exhibit a combination of a high yield strength of about 1.3 gigapascals and a large uniform elongation of about 14 percent, which surpasses those of other state-of-the-art additively manufactured metal alloys. The high yield strength stems from the strong strengthening effects of the dual-phase structures that consist of alternating face-centred cubic and body-centred cubic nanolamellae; the body-centred cubic nanolamellae exhibit higher strengths and higher hardening rates than the face-centred cubic nanolamellae. The large tensile ductility arises owing to the high work-hardening capability of the as-printed hierarchical microstructures in the form of dual-phase nanolamellae embedded in microscale eutectic colonies, which have nearly random orientations to promote isotropic mechanical properties. The mechanistic insights into the deformation behaviour of additively manufactured HEAs have broad implications for the development of hierarchical, dual- and multi-phase, nanostructured alloys with exceptional mechanical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Advanced electrode processing for lithium-ion battery manufacturing

Lithium-ion batteries (LIBs) need to be manufactured at speed and scale for their use in electric vehicles and devices. However, LIB electrode manufacturing via conventional wet slurry processing is energy-intensive and costly, challenging the goal to achieve sustainable, affordable and facile manufacturing of high-performance LIBs. Here, in this Review, we discuss advanced electrode processing routes (dry processing, radiation curing processing, advanced wet processing and 3D-printing processing) that could reduce energy usage and material waste. Maxwell-type dry processing is a scalable alternative to conventional processing and has relatively low manufacturing cost and energy consumption. Radiation curing processing could enable high-throughput manufacturing, but binder selection is limited to certain radiation curable chemistries. 3D-printing processing can produce electrodes with diverse architectures and improved rate performance, but scalability is yet to be demonstrated. 3D-printing processing is good for special applications where throughput and cost can be compromised for performance.

25 ENERGY STORAGE↗
DOE OSTI2025

Tailoring additive manufacturing to optimize dynamic properties in 316L stainless steel

With the advent of additive manufacturing, manipulation of typical microstructural elements such as grain size, texture, and defect densities is now possible at a faster time scale. While the processing–structure–property relationship in additive manufactured metals has been well studied over the past decade, little work has been done in understanding how this process affects the dynamic behavior of materials. We postulate that additive manufacturing can be used to alter the material microstructure and used to enhance its dynamic strength. In this work, 316L stainless steel (SS) was manufactured via selected laser melting and its microstructure was altered through changing build parameters like laser power, speed, and hatch spacing systematically. These samples were then subjected to spall recovery experiments to measure the spall strength and quantify the amount of damage as a function of build parameters. By mapping the spall strength as a function of build parameters, this work demonstrated that indeed additive manufacturing can be used to tailor the spall strength of 316L SS. This work also determined the optimum build parameters (laser power=195W; scanning speed=1083mm/s; hatch spacing=0.09mm; layer thickness=0.02mm) to obtain the highest spall strength and the least amount of total damage in 316L SS. Microstructural characterization of the pre- and post-mortem samples revealed that increased grain average misorientation and textural index were the main driving force behind this higher spall strength. This work aims to enhance microstructural engineering techniques to design materials with greater resistance to dynamic shock loading.

36 MATERIALS SCIENCE↗
DOE OSTI2025

New Era Towards Autonomous Additive Manufacturing: A Review of Recent Trends and Future Perspectives

Abstract The Additive Manufacturing (AM) landscape has significantly transformed in alignment with Industry 4.0 principles, primarily driven by the integration of Artificial Intelligence (AI) and Digital Twin (DT). However, current Intelligent Additive Manufacturing (IAM) systems face limitations such as fragmented AI tool usage and suboptimal human-machine interaction (HMI). This paper reviews existing IAM solutions, emphasizing control, monitoring, process autonomy, and end-to-end integration, and identifies key limitations, such as the absence of a high-level controller for global decision-making. To address these gaps, we propose a transition from IAM to Autonomous Additive Manufacturing (AAM), featuring a hierarchical framework with four integrated layers: knowledge, generative solution, operational, and cognitive. In the cognitive layer, AI agents notably enable machines to independently observe, analyze, plan, and execute operations that traditionally require human intervention. These capabilities streamline production processes and expand the possibilities for innovation, particularly in sectors like in-space manufacturing (ISM). Additionally, this paper discusses the role of AI in self-optimization and lifelong learning, positing that the future of AM will be characterized by a symbiotic relationship between human expertise and advanced autonomy, fostering a more adaptive, resilient manufacturing ecosystem.

Fan, Haolin↗
DOE OSTI2025

Treatment of antibiotic-manufacturing wastewater enriches for Aeromonas veronii, a zoonotic antibiotic-resistant emerging pathogen

Antibiotic-manufacturing wastewater treatment plants primarily target chemical pollutants, but their processes may select for antibiotic-resistant pathogens and antibiotic resistance genes. Leveraging the combined strengths of deep metagenomic sequencing, 16S rRNA gene sequencing, quantitative polymerase chain reaction, and bacterial culturing, we investigated bacterial communities and antibiotic resistomes across eleven treatment units in a full-scale antibiotic-manufacturing wastewater treatment plant processing wastewater from a β-lactam manufacturing facility. Both bacterial communities and antibiotic resistance gene compositions varied across the treatment units, but were associated. Certain antibiotic resistance gene persisted through treatment, either carried by identical bacterial species, or linked to mobile genetic elements in different species. Despite the satisfactory performance in chemical removal, this plant continuously enriched zoonotic antibiotic-resistant Aeromonas veronii (an emerging pathogen responsible for substantial economic losses in aquaculture and human health) from influent to effluent, probably due to prolonged β-lactam selection pressure and aquatic nature of A. veronii. This enrichment resulted in a significantly higher abundance of A. veronii than other aquatic samples worldwide. Furthermore, the closest evolutionary relative to the retrieved A. veronii was an isolate obtained from the stool of a local diarrhea patient. These findings highlighted a substantial public health risk posed by antibiotic-manufacturing wastewater treatment, underlining its potential role in enriching and disseminating zoonotic antibiotic-resistant pathogens. Beyond chemical monitoring, enhanced surveillance of antibiotic-resistant pathogens and antibiotic resistance genes is needed in effluent discharge standard for antibiotic-manufacturing wastewater treatment plants.

Wang, Xingshuo↗
DOE OSTI2022

Optimizing Multi-Robot Placements for Wire Arc Additive Manufacturing

Wire arc additive manufacturing is a metal additive manufacturing process in which the material is deposited using arc welding technology. It is gaining popularity due to high material deposition rates and faster build time. It is en-abled using robotic manipulators and can build relatively large-scale parts faster when compared with other metal additive manufacturing processes. However, the size of the large-scale parts is limited by the size of the industrial manipulator being used for the process. This limitation is overcome by using a fixed configuration multi-robot cell in which manipulators work cooperatively to build large-scale parts quickly. A fixed multi-robot cell with closely spaced industrial manipulators has high flexibility, but it restricts the part size that can be built. If the manipulators are spread out, the cell loses its flexibility but can build relatively larger parts. This issue can be avoided by using larger size manipulators, which are expensive, or by moving the modest size manipulators based on the part geometries. This paper presents a novel algorithm to generate multi-robot placements for different part geometries to be built using wire arc additive manufacturing. Furthermore, the algorithm hierarchically optimizes the build time and the inverse kinematics consistency in robot paths to improve the process efficiency and part quality. We compare the results with fixed multi-robot cells and provide insights to users to make an informed decision on whether to use a fixed or a flexible multi-robot cell for wire arc additive manufacturing.

Bhatt, Prahar↗
DOE OSTI2021

Convection in Scaled Turbine Internal Cooling Passages With Additive Manufacturing Roughness

Abstract Additive manufacturing processes, such as direct metal laser sintering (DMLS), enable the creation of novel turbine cooling internal passages and systems. However, the DMLS method produces a significant and unique surface roughness. Previous work in scaled passages analyzed pressure losses and friction factors associated with the rough surfaces, as well as investigated the velocity profiles and turbulent flow characteristics within the passage. In this study, the heat transfer characteristics of scaled additively manufactured surfaces were measured using infrared (IR) thermography. Roughness panels were CNC machined from plates of aluminum 6061 to create near isothermal roughness elements when heated. Fluid resistance differences between the aluminum roughness panels and roughness panels constructed from ABS plastic using the same roughness patterns from McClain et al. (2020, “Flow in a Simulated Turbine Blade Cooling Channel With Spatially Varying Roughness Caused by Additive Manufacturing Orientation,” ASME Turbo Expo 2020, Turbomachinery Technical Conference and Exposition, Virtual Conference, Sept. 21–25, GT2020-16069) were investigated. Finally, the overall thermal performance enhancements and friction losses were assessed through the calculation of surface averaged “global thermal performance” ratios. The global thermal performance characterizations indicate results in-line with those found for traditional commercial roughness and slightly below traditional internal passage convection enhancement methods such as swirl chambers, dimples, and ribs. The passages investigated in this study do not include compressibility effects or the long-wavelength artifacts and channel geometric deviations observed by Wildgoose et al. (2020, “Impact of Additive Manufacturing on Internal Cooling Channels with Varying Diameters and Build Directions,” ASME Turbo Expo 2020, Turbomachinery Technical Conference and Exposition, Virtual Conference, Sept. 21–25, GT2020-15049). However, the results of this study indicate that, based on the roughness augmentation alone, artificial convective cooling enhancers such as turbulators or dimples may still be required for additively manufactured turbine component cooling.

Engineering↗