Electric field-assisted embedding of fiber optic sensors in structural materials for structural health monitoring
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Engineering topics
Publications and source records attributed to Zhang, Xinchang.
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This report details the design, fabrication, and testing of surveillance test articles aimed at assessing material damage in reactor-relevant environments for effective degradation management. Two types of surveillance test articles with reduced sizes were developed based on design algorithms and finite element modeling: welded design and interlocking design. A furnace heating setup was adopted to apply multiple thermal cyclic loading profiles on the test articles with a temperature range of 500°C - 700°C, while the strain response was monitored using a digital image correlation technique. The testing results demonstrated the successful capturing of expected strain range for welded design while machining tolerance should be improved to engage strain coupling in the interlocking design. Mid-term (500 hours) and long-term (1500 hours) cyclic tests were conducted on welded test articles. A constant strain range of ~0.6% was observed at the specimen with testing under 500 hours, while a gradual decrease of strain at specimen was observed after 500 hours. Non-destructive evaluation through X-ray computed tomography confirmed the microcracks in the welds at specimen-driver joints after cyclic test that caused the strain change. Creep testing of the specimen after long-term cyclic test revealed a short creep life than expected. A multi-profile cyclic test was also conducted on a test article and demonstrated consistent strain response under different temperature ramp rates. The report also briefly discussed the challenges and future research efforts to advance test article development for material surveillance.
This study investigated the microstructural characteristics and mechanical behavior of diffusion welded nickel-based Alloy 617 obtained by electric field-assisted sintering (EFAS) using various parameters. The interfacial microstructure exhibited different characteristics including good grain boundary (GB) migration across the interface in the samples diffusion-welded at 1100 °C and a flat interface in the samples joined at 1000 °C and 1050 °C. The interface consisted of fine Al 2 O 3 oxides, while precipitation of interfacial M 23 C 6 carbides was not observed. Grain boundaries migrated across the Al 2 O 3 oxides, leaving these oxides within the grains. Graded grain size was observed, with grain coarsening being more significant near the sample surface due to the temperature gradient induced by EFAS. Tensile testing revealed that the specimens fractured in the matrix away from the interface, indicting strong diffusion-welded joints. Further, the peak tensile strength of 807 MPa was obtained in the samples welded at 1000 °C due to minimal grain growth. The materials obtained at 1100 °C exhibited reduced tensile strength but improved ductility. Strain maps revealed by digital image correlation showed alternating high and low strain segments in the samples produced at 1000 °C and 1050 °C, indicating that the flat interfaces with no GB migration were less ductile compared to the matrix. A greater strain uniformity was observed along the bond interfaces with improved GB migration. The hardness reduced near the sample surfaces due to enlarged grains induced by temperature gradient. This study demonstrates that GB migration and enhanced mechanical strength can be achieved in diffusion-welded Alloy 617.
The Electric Field Assisted Sintering (EFAS) technique was used for embedding the fibers, involving rapid heating via an electric current and pressure, reducing fiber exposure to high temperatures. Stainless steel guide tubes were inserted at the fiber-matrix junctions to prevent fiber breakage during the sintering process. The study varied key EFAS parameters—temperature (800°C to 980°C), pressure (40-50 MPa), and hold time (5-10 minutes)—to assess how they influenced fiber embedding. After embedding, the fibers were inspected using optical frequency domain reflectometry (OFDR) to evaluate optical losses and strain along the fiber length. The OFDR scans confirmed that the fibers remained intact, and subsequent transmission tests demonstrated no macroscopic fractures. The embedded samples were also analyzed using scanning electron microscopy (SEM) and X-ray computed tomography (CT) scans. These tests confirmed good bonding between the fiber and matrix with no cracking, though some porosity was present in samples fabricated at lower temperatures. At higher temperatures (980°C), the fiber-matrix bonding was continuous and defect-free, with metal coatings aiding in the bonding process. Elemental analysis showed interdiffusion between the fiber coatings and matrix materials, particularly between the gold coating and stainless steel. Helium leak tests revealed that lower sintering temperatures resulted in matrix porosity, causing leaks, but samples fabricated at 980°C were leak-tight.
This slide deck presents the research results in embedding fiber optic sensors in structural materials. Fiber optic sensors were embedded in stainless steel and nickel via electric field assisted sintering. The embedded sensors were evaluated in terms of fiber integrity, fiber-matrix bonding, fiber functionality, mechanical properties, and machinability.
Additive Manufacturing (AM) is a transformative manufacturing technology enabling direct fabrication of complex parts layer-by-layer from 3D modeling data. Among AM applications, the fabrication of Functionally Graded Materials (FGMs) has significant importance due to the potential to enhance component performance across several industries. FGMs are manufactured with a gradient composition transition between dissimilar materials, enabling the design of new materials with location-dependent mechanical and physical properties. This study presents a comprehensive review of published literature pertaining to the implementation of Machine Learning (ML) techniques in AM, with an emphasis on ML-based methods for optimizing FGMs fabrication processes. Through an extensive survey of the literature, this review article explores the role of ML in addressing the inherent challenges in FGMs fabrication and encompasses parameter optimization, defect detection, and real-time monitoring. The article also provides a discussion of future research directions and challenges in employing ML-based methods in the AM fabrication of FGMs.
Directed energy deposition (DED) is gaining widespread acceptance in various industrial applications since its unique manufacturing features allow the DED to print metallic parts with very complex geometries. However, DED inevitably generates a lot of internal pores which can limit the widespread applications of the DED technique. The current studies on DED porosity are mostly focused on analyzing pores’ bulk-scale influences on mechanical properties and performances. Since DED pores have a micro-scale existence, with dimensions ranging from a few microns to several hundred microns, it is fundamental to explore the pores’ influences on the micro-scale, including local mechanical properties, residual stress, and grains near pores. However, this important research direction has been neglected. The objective of this work is to fill the above gap in DED porosity research and acquire a fundamental understanding of the role of porosity on a microscopic scale. The authors used nanoindentation approaches to investigate internal pores’ effects on mechanical properties and residual stress in local regions surrounding the pores. In addition, the grains near pores were observed through EBSD, and simulated with the Kinetic Monte Carlo model. The research findings can be provided for DED researchers and industrial practitioners as technical guidance. Most importantly, the research results can work as a good reference for tracing the source of bulk-scale mechanical performances and properties of DED parts with internal pores.
The advanced non-light water reactor designs (Gen IV reactors), including molten salt/ very high temperature/ sodium-cooled and lead-cooled fast reactors, typically operate at higher temperatures and more extreme radiation conditions than light water reactors. An intrinsic part of the deployment and progress of Gen IV reactor designs is selecting the most suitable structural material for a specific application. Additive manufacturing (AM), a fairly new process of making physical, three-dimensional objects from a computer design file, is going to completely change the way of design, build and certify nuclear systems. It offers a range of opportunities to produce complex geometries from existing materials, offers new routes for processing of previously difficult to process materials, allows for design of new high-performance materials, and finally facilitates hybridization of dissimilar materials. This emerging technology has successfully produced cars, wind turbine blade molds and even live cells. It could also open up big opportunities for the nuclear industry to quickly deploy technologies at a fraction of the cost. So far, AM techniques have been preliminarily applied in the field of nuclear reactors, including the classical parts such as the pressure vessel of a small reactor with 508-III steel, the bottom nozzle of a fuel assembly with 304L steel, the fuel cladding with zirconium alloy and the integrated impeller of a pump and the multi-channel valve body with 316L steel [6,7]. The AM applications for operating nuclear reactors started in auxiliary plant components and have slowly migrated to metallic reactors and core components, but many of these are not safety critical components. Although many parts used for nuclear reactors have been fabricated by AM techniques, practical applications in engineering are still a long way off due to the uncertainty factors focused on the processing, material properties, analysis methods and application standards, which feeds the safety and life-cycle of the nuclear reactor. Due to rapid, repeated heating and cooling during production, a high dislocation density was present in the AM material. This microstructure feature is unstable at elevated temperature while high temperature is one of the typical operation environments for nuclear reactors. Thus, it is important to understand the thermal effect on the microstructure of AM material. The objectives of this study are to investigate the effect of heat treatment on the microstructure and mechanical properties of 316L stainless steel produced by laser powder bed fusion additive manufacturing, and to determine an appropriate heat treatment practice that will be applied to the lightweight AM lattice-structured material with the same chemistry. The heat treatment study consisted of annealing the samples at a temperature range of 800 to 1200 oC with a 50 oC increment for different times (1-24 hours), followed by vacuum or air cooling. Microstructural characterization was carried out by Scanning Electron Microscope (SEM). Grain size and crystallographic orientation were investigated by Electron Backscatter Diffraction (EBSD). Vickers hardness tests with a 0.5 kg load were employed to determine the hardness of samples after different heat treatments. After heat treatment, the random crystallographic orientation was preserved, and the volume fraction of high-angle grain boundaries (grain boundary misorientation =15 oC) remained the same. The dislocation density decreased with annealing temperature due to recovery. The fine subgrain structures in the as-printed specimen were quite stable up to 1200 oC. Minimal recrystallization was observed up to 1200 oC. Recrystallization initiated only after 8.5 hours at 1200 oC. The SEM images did not show obvious dependence of microstructure on cooling rate. The hardness of the specimens decreased with increasing annealing temperature as a result of the decrease in dislocation density. It is interesting to note that the AM material showed very similar hardness to the wrought material when annealing at similar temperature, although the microstructures are very different. Annealing at 1050 oC for 1 hour followed by air cooling was selected as the heat treatment procedure for the lattice designed lightweight AM 316L material.
This presentation details the efforts toward developing material surveillance test article designs to support materials surveillance technology development for advanced reactors.