Engineering topics
Publications and source records attributed to Kulkarni, Anand.
Conference Presentation at TMS 2024 entitled "Property-Microstructure Evaluation of L-PBF Ni-based Superalloy Candidates for Industrial Gas Turbine (IGT) Fuel Injectors"
To realize the full capability of additively manufactured components in complex energy systems, it is imperative to minimize early component failures during development phases and during operation. Traditional field feedback timelines and offline inspection protocols significantly reduce the design-manufacturing iteration times. To address this specific question, the project developed and demonstrated a method for the integration of sensors into complex components through additive manufacturing. The team used gas turbine engines as a platform, which meets the need of both power generation and propulsion and offer opportunities for cost reductions and efficiency increases. The innovation of this intelligent integration of sensors into complex components uniquely customized to address questions of integrity and durability for additively manufactured components. With real-time sensing data from additively manufactured components, turbine manufacturers will realize higher efficiencies, reduced component failures, and a 30-50% acceleration in product deployment of high efficiency gas turbine components due to a faster reduction in component risk assessment under actual operating conditions. This is a transformative shift towards a data-driven design and qualification of additively manufactured gas turbine components. To directly integrate sensors into additively manufactured components with all the complexities of actual hardware, powder bed fusion (direct metal laser sintering) and laser metal deposition technologies was developed. Validation took take place in two university laboratories both of which contain actual engine hardware and closely simulate a gas turbine prior to demonstrating the technology in a turbine development test. Indeed, two major technologies from this research cold impact turbine systems in the near future: (1) higher efficiency materials and designs enabled by additive manufacturing with 50% faster design to manufacturing cycle time, to enable faster time-to-market targets; and (2) integration of sensors into additively manufactured components enabling broad health and condition based prognostics for faster component and engine risk reduction.
Oral Presentation entitled Materials Evaluation of Additively Manufactured Fuel Injector Candidates at 2023 UTSR and Advanced Turbines Program Review
Abstract By leveraging the additive manufacturing (AM) platform, development time and costs for turbine component testing can be reduced relative to traditional investment casting. Surface roughness is a key characteristic of the additive manufacturing process that can impact flow, heat transfer, and mechanical integrity of printed components. There are multiple design and build considerations that result in variability in surface roughness, especially when additively fabricating complicated three-dimensional vanes and internal cooling passages. This study characterizes the surface roughness of internal cooling passages, vanes, and flat external surface samples made using additive manufacturing, specifically the direct metal laser sintering process. The samples were manufactured with various wall thicknesses, layer thicknesses, build locations, build directions, and on different AM machines. A combination of computed tomography scanning and optical profilometry was used to evaluate surface roughness levels. The data indicate that the dominant factors in roughness for a given layer thickness are a function of wall thickness, build location, and build direction.
Many additive manufacturing (AM) reference standards for build quality verification concentrate primarily on external features. In contrast, EPRI proposes a pair of AM reference blocks that feature only internal and embedded forms. This report presents, collates, and discusses quantitative nondestructive evaluation (NDE) results from various techniques, including visual testing (VT), radiographic testing (RT), conventional ultrasonic testing (UT), and full matrix capture/total focusing method (FMC/TFM) scanning. The blocks are intended, as part of a larger series of blocks, to evaluate build quality and the relative performance of different NDE techniques in detecting various features. The limits of detectability and the closeness of the as-built shape to the intended form for certain features are quantified, facilitating direct comparison. Upon analysis of the results of this testing, it was found that FMC/TFM was consistently superior in detection, followed by conventional UT, then VT, and lastly RT.
This report presents qualitative results of ultrasonic full matrix capture/total focusing method (FMC/TFM) scanning of two series of blocks, additively manufactured by powder bed fusion, containing a variety of internal features and structures that would not be achievable by conventional manufacturing techniques. The purpose of the first series of additively manufactured (AM) blocks was to explore the possibility of building calibration blocks for FMC/TFM ultrasonic testing (UT). It was confirmed that AM is a suitable candidate for generation of unusual and novel reflector forms, such as rotating slots, purposely embedded voids, and tapering holes, and that FMC/TFM was very capable of characterizing them. The intended use of the second series of AM blocks was as UT reference blocks to characterize the AM process quality or the interrogating UT technique. The larger block in this series was scanned from multiple faces, using multiple UT methods (conventional UT and FMC/TFM) and X-ray computed tomography for comparative purposes. The performance of each method was quantified by a metric corresponding to the detection limit of each feature, and the quantitative results are discussed.
The overall Science-based Acceleration of the Full Value Stream for Metal Additive Manufacturing (AM): Expedited Powder Development and Additive Manufacturing Deployment (“X-P4AM”) project objective is to drastically reduce the time-to-market barriers for new additive alloys of interest in automotive and aerospace applications, through computational alloy design with rapid screening and down- selection via synthesis of candidate alloys with rapid solidification. The project will also refine the technology in high pressure gas atomization to improve the production of commercial quantities of selected powders with high powder yields and enhanced powder quality. Production of modified nickel-based superalloys and a Ni-containing alloy based on a high entropy composition, enhanced powder production methods, and optimized AM build parameterization provided critical steps in widespread adoption of AM technology for aerospace applications, in this case. The individual backgrounds and capabilities of the Parties are ideally suited to the successful execution of this work. The included work enhanced the Contractors’ AM capabilities, a core competency of the Contractors, and develop a close working relationship with the Participant in the areas of nickel-based powder superalloys and custom alloys and their end use.
Superheater tubes are critical boiler components that operate at relatively higher temperatures and pressure. Amongst the primary concerns for these tubes is the deposition of ash particles on the tube surface, leading to the reduced thickness of the tube due to material corrosion, consequently causing early creep failure of the component. In this research, a novel tube design has been proposed which resembles a teardrop or ogive shape to reduce the drag and concurrently improve the creep life of the superheater tubes. To administer the practicality of novel tubes, metal additive manufacturing (AM), for instance, laser-powder bed fusion (L-PBF), has been proposed. These unconventional designs were assessed and compared with the baseline circular tube design for mechanical design requirements (hoop stress and creep life) and the particle and flue gas flow characteristics around the differently shaped tubes. A thermomechanical finite element (FE) analysis was performed for hoop stress calculations. This study also emphasizes on effect of circumferential thermal variation on hoop stress distribution in tubes. Therefore, a detailed two-dimensional (2D) thermal simulation has been performed to report the circumferential thermal variation on the tube. A computational fluid dynamics (CFD) analysis coupled with particle tracing was performed for gas flow visualization and particle tracing around the proposed shapes and baseline circular-shaped tube design. The Schlieren optic setup was built and leveraged for qualitative validation of the proposed design. The complete design methodology established in the paper shows teardrop-shaped tubes better in terms of drag and creep life in contrast to the circular-shaped tube.
Additive manufacturing has the potential to revolutionize industrial hardware and unlock efficiency gains through the fabrication of geometries and architectures not possible by conventional processing. Wire Arc Additive manufacturing (WAAM) process is a class of directed energy deposition process enabling higher build rate and allowing custom wire feedstock allowing spatial variation of microstructure. The larger spot size and lower speed creates a larger melt pool, reducing residual stress and often time creating directional/columnar microstructure for Ni-superalloy. The use of flexible platform provides freedom in deposition strategy, which can accommodate complex substrates, including feature addition onto existing structures, non-flat layers, and repair methods. However, the certification of the final component needs to match the strength requirement. Hence, the quality of the component produced is stringently monitored to avoid buildup of residual stress, cracks, porosity and to reduce detrimental segregated phases commonly observed during alloy solidification. Simulation plays a huge role in predicting the melt pool dimension and can be used to optimize the process parameter. Similar development is also required to perform physics-based modeling of microstructural development in WAAM that can predict the microstructural features during solidification and can be used to optimize the process more effectively. To move toward this goal, Raytheon Technologies Research Center together with Siemens worked to create a set of computational tools to control the process parameters, enable on-line measurements and acquisition with feedback to the optimized process parameters, and eventually track material evolution through each step of the additive process. Computational fluid dynamics is used for accurate prediction and calibration of the thermal field during WAAM process. and phase field models for microstructure evolution as a function of processing parameters to establish a connection between additive parameters and the final microstructure. Here we report cellular automata (CA) model development to predict the dendritic microstructure evolution with surface and bulk nuclei for single track and multiple layers. The CA model was developed to account for secondary element addition and predict segregation, local melting, and latent heat release as well as prediction of Euler angles from orientation information and validated against experiments. This framework was utilized to tailor spatially-varying composition in a part by appropriately controlling the microstructure evolution during the additive process. Functionally graded Haynes 282 alloy with high Cr content at the surface was tested for oxidation and mechanical properties. An advanced physics-based reaction-diffusion model predicting the simultaneous creation of chromium oxide and alumina is developed and validated to extend life expectancy of the WAAM manufactured high temperature part. A machine-learning data-driven framework establishing the process-structure relationship from a dataset of real microstructure images and corresponding process history data has been developed and implemented in the NX Siemens design system. The digital twin configuration along with the tool path generation enabled prediction of WAAM component buildup time and the techno-economic analysis provided a favorable option for all 4 cases with 15-40% cost reduction.