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At least 91 records · Page 5

Embedding of Fiber Optic Sensors in Stainless Steel for Sensing in Harsh Environments

Structural health monitoring is critical for components working in harsh environments to assess their safety and integrity. This can be realized with advanced sensors, such as fiber optic sensors, embedded in these components. Recent studies have used ultrasonic consolidation (UC) and laser-based additive manufacturing (AM) techniques to embed fiber optic sensors in metals. However, sensor embedding using these techniques has been challenging, with gaps and voids around the embedded fiber. Successful embedding of fiber optic sensors requires good contact between the fiber and the matrix to eliminate potential gas/liquid leaks in critical systems such as in nuclear and aerospace services. Defect-free fiber/matrix bond is also essential for accurate measurement of parameters of interest, such as temperature and strain. This study developed a novel fiber embedding technique based on electric field-assisted sintering (EFAS). Sapphire optical fibers with diameters of 125 µm and 250 µm were embedded in stainless steel (SS) 316L using EFAS. The embedding was completed by sintering SS 316L powders at a pressure of 50MPa, hold time of 5 min, and temperatures of 1000°C, 1100°C, and 1200°C. Joule heating mechanism during EFAS enabled rapid sintering of the SS 316L powder with resulting sample densities over 99%. Microscopy analysis performed on the cross-sections revealed a defect-free bond between the embedded fiber and SS 316L. The good integrity of the embedded fiber was evidenced by optical transmittance measurement. Optical attenuation of the fiber before and after embedment was examined in the near-infrared region. Scanning electron microscopy was employed to investigate the grain morphology of SS 316L near the embedded fiber. Hardness distribution in the sintered part was also investigated to study the effect of the embedded fiber on the mechanical properties of the as-fabricated component. The results indicated that EFAS was able to embed fiber in SS with good fiber functionality and part quality.

36 - MATERIALS SCIENCE↗

Embedded metallized optical fibers for high temperature applications

Embedding fiber optics in metal components could enable new capabilities such as active monitoring of spatially distributed strain. Ultrasonic additive manufacturing is a suitable technique for embedding fiber optics because it allows fibers to be embedded in metals without melting and without the use of epoxy. However, for harsh environments that could have high temperatures or high radiation doses, traditional polymer-coated fibers cannot survive for extended periods of time. This work demonstrates successful embedding of commercially available copper-, nickel-, and aluminum-coated fibers into aluminum without any observable damage to the fiber. Copper-coated fibers embedded in copper show adequate light transmission, although residual strain could not be resolved. With further processing improvements, fibers embedded in copper or other high-temperature materials could enable even higher temperature operation. Optical transmission and spatially distributed strain were measured in the fibers embedded in aluminum. Measurements were taken after embedding and during heating to temperatures greater than 500 °C. Within the embedded region, both the copper- and aluminum-coated fibers showed strain that matched the expected strain in the surrounding aluminum matrix during heating. This suggests a strong interfacial bond strength that exceeds the maximum estimated fiber strain of 1.2% (871 MPa tensile stress). Furthermore this demonstration of embedded fibers that can survive high temperatures and remain bonded to the metal matrix is the first step toward embedded fiber optic sensors for harsh environment applications.

36 MATERIALS SCIENCE↗

Exact density functional and wave function embedding schemes based on orbital localization

Exact schemes for the embedding of density functional theory (DFT) and wave function theory (WFT) methods into lower-level DFT or WFT approaches are introduced utilizing orbital localization. First, a simple modification of the projector-based embedding scheme of Manby and co-workers [J. Chem. Phys. 140, 18A507 (2014)] is proposed. We also use localized orbitals to partition the system, but instead of augmenting the Fock operator with a somewhat arbitrary level-shift projector we solve the Huzinaga-equation, which strictly enforces the Pauli exclusion principle. Second, the embedding of WFT methods in local correlation approaches is studied. Since the latter methods split up the system into local domains, very simple embedding theories can be defined if the domains of the active subsystem and the environment are treated at a different level. The considered embedding schemes are benchmarked for reaction energies and compared to quantum mechanics (QM)/molecular mechanics (MM) and vacuum embedding. We conclude that for DFT-in-DFT embedding, the Huzinaga-equation-based scheme is more efficient than the other approaches, but QM/MM or even simple vacuum embedding is still competitive in particular cases. Concerning the embedding of wave function methods, the clear winner is the embedding of WFT into low-level local correlation approaches, and WFT-in-DFT embedding can only be more advantageous if a non-hybrid density functional is employed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Embedded Sensor Development in Metallic Structures for the Transformational Challenge Reactor

The ability to make minimally intrusive measurements of process conditions has tremendous potential for improving system performance and control in applications such as nuclear power generation. Towards this end, emerging and evolving advanced manufacturing methods, such as additive manufacturing, present new opportunities for more seamlessly integrating sensing with structure. This technical report summarizes the progress of work performed to assess the feasibility of embedding commercial off-the-shelf (COTS) sensors in a metallic reactor core using advanced manufacturing methods. The progress of four research and development tasks are documented: 1) A survey of COTS sensors for nuclear applications that are candidates for embedded fabrication, 2) Development of a conceptual framework for investigating the feasibility of sensor embedment, 3) Definition of structural geometries and other characteristics that will represent compelling proof-of-concept, and 4) Preliminary prototyping of embedded sensors. For the purposes of this initial study, nuclear grade K-type thermocouples were selected for investigation of embedment methodologies. This sensor was selected as an initial candidate because it represents one of the simplest sensor configurations that can provide useful process information. A selective laser melting (SLM) additive manufacturing process was used to fabricate structures with complexity representative of the core design of the transformational challenge reactor (TCR) and methods were developed to embed a thermocouple with a complex two-dimensional routing path. There are many challenges associated with embedding sensors during the additive manufacturing process including securing the sensor in the structure, relocating the part in the additive machine if using a “pick and place” sensor placement method, mitigating the potential for powder contamination, optimizing energy deposition parameters to build as closely as possible around the sensor path and improve structural integrity of the part, and tuning energy deposition to mitigate thermally induced warpage of the sensor and part as well as potential for damaging the sensing device. Preliminary results indicate that it is feasible to integrate the sensor while minimally compromising the structural integrity of the part and preserving sensor performance. This first phase of this work focused on developing a workflow for embedding sensors and controlling energy deposition during the additive manufacturing process to better understand the build characteristics around the sensor. Future work will perform more in-depth characterization of prototype parts using X-ray computed tomography and scanning electron microscopy to better understand fabricated structures, performance testing of embedded sensors in high temperature environments, adding new embedded measurement modalities, embedding devices with dissimilar materials in contact with additive powders, and the development of methods for embedding sensors with three-dimensional routing paths.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

In situ embedment of type K sheathed thermocouples with directed energy deposition

Advanced nuclear reactor systems require new technologies for heat transfer and system monitoring. Additive manufacturing (AM) offers the design flexibility to allow in-situ sensor embedment through smart manufacturing for real-time monitoring, and performance of these systems. Here, this study focuses on experiments investigating the feasibility of in-situ sensor embedment using directed energy deposition (DED). Type K thermocouples are embedded into 316L stainless steel (SS) samples using two different configurations (e.g., exposed and embedded tips) and two designs (e.g., flush to substrate) within an AM base. Embedded sensor samples are analyzed via in-situ measurements and high-temperature performance validation tests at 350ºC and 900ºC. Temperature performance results at both temperature tests show good agreement with manufacturer specifications proving that these sensors could still capture accurate temperature readings after in-situ embedment during DED processing. An additional optimization experiment was conducted on the exposed tip configuration using a surrogate thermocouple to improve tolerances and the embedment process. Results improved tolerances, lower porosity, smaller gaps between the sensor and base, and better junction contact for the sensor. Although further optimization of this embedment strategy is necessary to improve the structural stability and tolerances within the component, this research strategy provides a proof-of-feasibility for DED embedment with commercial sheathed thermocouples. This research provides early impact on embedment of sensor for multiple materials and complex geometric components..

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Benchmarking an Embedded Adaptive Sampling Configuration Interaction Method for Surface Reactions: H 2 Desorption from and CH 4 Dissociation on Cu(111)

Embedded (emb-) correlated wavefunction (CW) theory enables accurate assessments of both ground- and excited-state reaction mechanisms involved in heterogeneous catalysis. Embedded multireference second-order perturbation theory (emb-MRPT2) based on reference wavefunctions generated via embedded complete active space self-consistent field (emb-CASSCF) theory is currently state-of-the-art. However, the factorial scaling of CASSCF limits the size of active space and the complexity of systems that can be studied. In this work, we assess the efficacy of an alternative CW method, adaptive sampling configuration interaction (ASCI)–which enables large active spaces to be used–for studying surface reactions. We couple ASCI with density functional embedding theory (DFET) and benchmark its performance for two reactions: H 2 desorption from and CH 4 dissociation on the Cu(111) surface. Unlike embedded complete active space second-order perturbation theory (emb-CASPT2) that accurately reproduces a measured H 2 desorption barrier, embedded ASCI, using a very large active space (though one that still comprises a small portion of the full set of orbitals) fails to do so. Adding an extra correlation term from embedded Møller–Plesset second-order perturbation theory (emb-MP2) improves the desorption barrier and endothermicity predictions. Thus, the inaccuracy of embedded ASCI comes from the missing dynamic correlation from the many other electrons and orbitals not included in the active space. For CH 4 dissociation, again embedded ASCI overestimates the dissociation barrier compared to emb-CASPT2 predictions. Adding dynamic correlation from emb-MP2 helps correct the barrier. However, this composite approach suffers from double counting of correlation within embedded ASCI followed by emb-MP2 calculations. We therefore conclude that the state-of-the-art emb-MRPT2 based on reference wavefunctions generated via emb-CASSCF remains the method of choice for studying surface reactions. emb-ASCI is useful when large active spaces beyond the limit of emb-CASSCF are essential, such as to study complex surface reactions with significant multiconfigurational character (static correlation) but weak dynamic correlation.

08 HYDROGEN↗

Replacing non-biomedical concepts improves embedding of biomedical concepts

Embeddings are semantically meaningful representations of words in a vector space, commonly used to enhance downstream machine learning applications. Traditional biomedical embedding techniques often replace all synonymous words representing biological or medical concepts with a unique token, ensuring consistent representation and improving embedding quality. However, the potential impact of replacing non-biomedical concept synonyms has received less attention. Embedding approaches often employ concept replacement to replace concepts that span multiple words, such as non-small-cell lung carcinoma, with a single concept identifier (e.g., D002289). Also, all synonyms of each concept are merged into the same identifier. Here, we additionally leveraged WordNet to identify and replace sets of non-biomedical synonyms with their most common representatives. This combined approach aimed to reduce embedding noise from non-biomedical terms while preserving the integrity of biomedical concept representations. We applied this method to 1,055 biomedical concept sets representing molecular signatures or medical categories and assessed the mean pairwise distance of embeddings with and without non-biomedical synonym replacement. A smaller mean pairwise distance was interpreted as greater intra-cluster coherence and higher embedding quality. Embeddings were generated using the Word2Vec algorithm applied to a corpus of 10 million PubMed abstracts. Our results demonstrate that the addition of non-biomedical synonym replacement reduced the mean intra-cluster distance by an average of 8%, suggesting that this complementary approach enhances embedding quality. Future work will assess its applicability to other embedding techniques and downstream tasks. Python code implementing this method is provided under an open-source license.

algorithms↗

Embedding Sensors in 3D Printed Metal Structures

The Transformational Challenge Reactor (TCR) program is leveraging recent advances in modeling and simulation, materials, and additive manufacturing (AM) technologies to design a modern nuclear reactor. Some of the main TCR technologies include in situ monitoring and the integration of sensors during the manufacturing of quality-significant nuclear reactor components. This report describes the general procedure and process optimization for embedding sensors within generic stainless steel 316 (SS316) components using laser powder bed fusion (LPBF). A more detailed, quality-significant test plan and supporting procedures are available upon request (ORNL/TM-2021/2127). LPBF involves the use of a scanning laser to selectively melt regions of a powder bed, additively building a part layer by layer. This report describes the LPBF processing technique and discusses the effects of LPBF processing parameters on the success of the sensor embedding process. Experiments used machined cavities in the form of channels in an SS316 base for the sensors to lay in while material is additively built over the top, thereby embedding them in an SS316 matrix. A preliminary investigation involved using empty SS316 sheaths as surrogates to explore the effects of various LPBF processing parameters and the dimensional requirements of the machined channels. Microstructural investigations showed that a smaller channel width/depth combination closer to the sensor’s diameter was best for the embedding process. After the desired parameters were selected, Type-K thermocouples were embedded and evaluated post-embedding using nondestructive thermal testing, as well as destructive sectioning and microscopy. Post-build characterization showed that the thermocouples were well-bonded to the SS316 matrix and were fully functional after embedding. During thermal testing to temperatures up to 500 °C, the embedded thermocouples read consistently with one another and deviated only slightly from the readings of a nonembedded thermocouple located within the furnace. This slight discrepancy was most likely due to differences in the thermal time constants for a nonembedded thermocouple vs. a thermocouple embedded in a solid SS316 block. The results presented in this report will serve as the foundation for future work that will focus on embedding sensors in relevant TCR reactor components and eventually testing those components under neutron irradiation.

36 MATERIALS SCIENCE↗

EFFECT OF INCLINED WAVES ON DEEPLY EMBEDDED NUCLEAR FACILITIES

Several conceptual designs for advanced reactors show that most if not all of the structure is embedded in the soil. Consequently, analysis techniques that have been verified and validated for the analysis of light water reactors on surface foundations may not be directly applicable to deeply embedded reactors. Specifically two effects that may change the in-structure response (ISR) of embedded facilities are: (i) the effect of the kinematic interaction becomes more prominent as the embedment depth increases; (ii) non-vertically propagating waves, which are usually not considered for surface-founded facilities, may be more important for deeply embedded facilities. A preliminary study is presented in this article to understand the response of embedded nuclear facilities to non-vertically propagating seismic waves. The inclined wave field is generated from source-to-site simulations using representative earthquake faults with different dip angles. The embedment depth of the nuclear containment facility is also varied to obtain a better understanding of the effect of embedment. This analysis of the soil-structure ensemble is conducted using the application called Multi-hazard Analysis for STOchastic time-DOmaiN phenomena (MASTODON), developed on top of Idaho National Lab’s open source MOOSE finite element framework. The Domain Reduction Method implemented in MASTODON to incorporate the seismic excitation within the region of interest is verified and then used to reduce the computational effort in analyzing this problem. Preliminary analysis using linear soil and structure material properties and tied contact between the soil and structure indicate that embedding the nuclear facility reduces significantly the response of the structure in all the earthquake scenarios considered.

42 ENGINEERING↗