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SMR Containment Cable and Electrical Penetration Assembly System
GAIN Project CRADA Number NFE-21-08839, entitled “SMR Containment Cable and EPA System” was initiated by the partnership of Oak Ridge National Laboratory (ORNL) and Engineered Solutions Group (ESG) to test an ESG-designed Electrical Penetration Assembly and Containment Cabling System Qualified for not only SMR technologies, but also Advanced Reactors design. An Electrical Penetration Assembly (EPA) is a component used to allow electrical power and signal conductors as well as optical fiber through the nuclear reactor’s containment structure while maintaining a pressure barrier. The EPA ensures the containment's integrity both during the normal operation and also accident conditions by providing a sealed passage for power and signals. This project was undertaken to fill the equipment gap of EPA and Cabling Systems that require much more severe environmental requirements than legacy plant applications present due to their smaller containment volumes that result in high energy densities compared to legacy designs. This high energy density results in severe accident environments and also more severe normal operating conditions.This document describes cost effective approaches to qualify a unique EPA for Small Modular Reactor (SMR) technologies as legacy LWR EPA technologies will likely have inherent material performance insufficiencies. The DBA profiles for SMRs (and some Advanced Reactor Technologies) are more severe than the legacy qualification requirements making the design of the qualification testing system challenging as the temperatures and pressures can approach the limits permitted by ASME Pressure Vessel Code, as well as accident temperatures exceeding the capability of polymeric gaskets and dielectrics. Small Modular Reactors are designed to have, as the name suggests, modularity which implies sized for factory fabrication and subsequent assembly at the power plant site. SMR containment is much smaller than a legacy Light Water Reactor containment. The containment walls are likely to be comprised of stainless steel. Qualifying Electrical Penetration Assemblies (EPAs) through these steel vessels are of interest in this work. Methods are presented here that discuss critical safety and cost effectiveness for these SMR EPA’s test systems.
Perceived Conflicts of Systems Engineering in Early-Stage Research and Development 1
Early Systems Research and Development (ESR&D) is one of the most crucial phases in the product development process. It both blends and blurs the lines between science and engineering, and requires a risk-based, disciplined, and graded approach to effectively manage scope, cost, and complexity of the final product. Many leaders, program managers, and scientists are unwilling to involve systems engineering because of the perception that systems engineering is heavily process oriented, adds unnecessary costs, and should be applied only to mature technologies. The value of systems engineering as applied to ESR&D is unclear to these key individuals. The unfortunate result is that system engineering is not applied to ESR&D. This results in R&D efforts that may have solved the wrong problem, selected the wrong architecture, require technical rework, have difficulty transitioning later maturity levels, and result in higher R&D costs and extended development timelines. This work discusses the difficulty of introducing systems engineering to the research and early development process and their inclination perspectives of researchers, engineers, and managers. The article shall offer potential means to manage the cultural transformation of early adoption of right-sized systems engineering in ESR&D and reverse the attitudinal positions.
Alteration of pool boiling heat transfer on metallic surfaces by in situ oxidation
The critical heat flux during pool boiling has been investigated for a range of applications including electrical power generation and thermal management. Reported experimental CHF values during pool boiling of water on flat metallic surfaces, however, show a large discrepancy across studies. Here, we address this discrepancy in CHF values by accounting for oxidation of metallic surfaces during boiling. We studied the effect of in situ oxidation on flat Cu and Ni surfaces by changing the duration that samples were held in saturated water before conducting boiling experiments. The morphology and chemical composition of surfaces after the boiling experiments were analyzed by atomic force microscopy and X-ray photoelectron spectroscopy, respectively. Cu surfaces showed gradually increasing CHF values as the duration in saturated water increased, which could be attributed to the increase in roughness due to the formation of Cu 2 O nanostructures. Conversely, Ni surfaces showed relatively stable CHF and morphology as a nearly flat layer of NiO formed, with one exception: formation of a highly wetting hydroxide, Ni(OH) 2 , on a Ni coupon held in saturated water for 24 h resulted in a uniquely high CHF value, signifying the importance of surface chemistry in addition to morphology. Finally, the fundamental mechanisms resulting in the wide spread of CHF values on metallic surfaces elucidated in this work will lead to more accurate estimation of CHF as well as a deeper mechanistic understanding of CHF values on engineered surfaces.
Device response principles and the impact on energy resolution of epitaxial quantum dot scintillators with monolithic photodetector integration
Abstract Epitaxial quantum dot (QD) scintillator crystals with picosecond-scale timing and high light yield have been created for medical imaging, high energy physics and national security applications. Monolithic photodetector (PD) integration enables the sensing of photons generated within the waveguiding crystal and allows a wide range of scintillator-photodetector coupling geometries. Until recently, these doubly novel devices have suffered from complex, high variance responses to monoenergetic sources which significantly reduces their precision and accuracy. The principles governing the overall device response have now been discerned and embodied by an expression derived within a geometrical optics framework which considers optical properties, surface roughness and photodetector coupling geometry. Response variation due to these factors was sufficiently reduced to obtain material-related energy resolution values of 2.4% with alpha particles. These findings place energy resolution alongside luminescence timescale, photon yield, and radiation hardness as outstanding properties of these engineered materials.
Impact of Random Spatial Fluctuation in Non-Uniform Crystalline Phases on the Device Variation of Ferroelectric FET
In this work, a comprehensive study of random spatial fluctuation of the ferroelectric (FE) phase and dielectric (DE) phase in FeFETs is conducted to understand its impact on device variation. It is found that: i) there exists a certain DE percentage threshold that below which the increase of the DE phase does not significantly impact the device memory window and variation and only above which evident device degradation can be observed; ii) increasing the DE phase increases the variation in the memory window and the coercive field distribution further exacerbates the variation, hence degrading the sensing margin; iii) decreasing the number of grains degrades the device variation, which calls for further grain size engineering for variation suppression.
Retaining Systems Engineering Model Meaning Through Transformation: Demo 2
Digital engineering strategies typically assume that digital engineering models interoperate seamlessly across the multiple different engineering modeling software applications involved, such as model- based systems engineering (MBSE), mechanical computer-aided design (MCAD), electrical computer-aided design (ECAD), and other engineering modeling applications. The presumption is that the data schema in these modeling software applications are structured in the familiar flat- tabular schema like any other software application. Engineering domain-specific applications (e.g., systems, mechanical, electrical, simulation) are typically designed to solve domain-specific problems, necessarily excluding explicit representations of non-domain information to help the engineer focus on the domain problems (system definition, design, simulation). Such exclusions become problematic in inter-domain information exchange. The obvious assumptions of one domain might not be so obvious to experts in another domain. Ambiguity in domain-specific language can erode the ability to enable different domain modeling applications to interoperate, unless the underlying language is understood and used as the basis for translation from one application to another. The engineering modeling software application industry has struggled for decades to enable these applications to interoperate. Industry standards have been developed, but they have not unified the industry. Why is this? The authors assert that the industry has relied on traditional database integration methods. The basic issue prohibiting successful application integration then is that traditional database-driven integration does not consider the distinct languages of each domain. An engineering models meaning is expressed through the underlying language of that engineering domain. In essence, traditional integration methods do not retain the semantic context (meaning) of the model. The basis of this research stems from the widely held assumption that systems engineering models are (or can be) structured according to the underlying semantic ontology of the model. This assumption can be imagined from two thoughts. 1) Digital systems engineering models are often represented using graph theory (the graph of a complex systems model can contain millions of nodes and edges). When examining the nodes one at a time and following the outbound edges of each node one by one, one can end up with rudimentary statements about the model (i.e., node A relates to node B), as in a semantic graph. 2) Likewise, from the study of natural languages, a sentence can be structured into unambiguous triples of subject-predicate-object within formal and highly expressive semantic ontologies. The rudimentary statements about a systems model discerned with graph theory closely mimic the triples used in the ontologies that try to structure natural languages. In other words, a systems models semantic graph can be (or is) structured into an ontology. Additionally, it is well established in industry that through natural language processing (NLP), which provides the means to create language structures, that computers can interpret ontological graphs. Therefore, the authors hypothesized that if the integrity of the underlying semantic structure of a systems model is retained, the contextual meaning of the model is retained. By structuring system models into the triples of the underlying ontology during the transformation from one MBSE application to another, the authors have provided a proof of the concept that the meaning of a system model can be retained during transformation. The authors assert that this is the missing ingredient in effective systems model-to-model interoperability. ACKNOWLEDGEMENTS The authors would like to thank the FY19 Model Interoperability team members who provided a solid foundation for the FY20 team to leverage: John McCloud, for the work he did to guide us toward the right use of technology that will appropriately discover and manipulate ontologies. Carlos Tafoya, for the work he did to develop an application programming interface (API)/Adapter that would export ontology-based data from GENESYS. Peter Chandler, for the work he did to architect our overall integration solution, with an eye toward the future that would influence a large-scale federated production-level systems engineering digital model ecosystem.
Report on Properties and Microstructure of 3D Printed Inc-718
The report presents the microstructure and mechanical properties of 3D printed Inconel 718 to assess its potential use as a structural material for the Transformation Challenge Reactor (TCR). The structural components near the outlet of the core will experience significant neutron fluxes and outlet coolant temperatures from the hot standby temperature of 300°C to nearly 550°C at the center of the part. These components must support the core in appropriate loading conditions and require structural analysis at relevant temperatures. Strong spatial and chemical heterogeneity was found in as-built (ASB) Inconel 718. Three heat treatments were designed and conducted to simplify the microstructure and determine how each precipitating phase contributed to the overall strength. Baseline mechanical properties were measured from uniaxial tensile tests on subsize SS-J2 specimens at room temperature and at elevated temperatures of 300, 450, and 600°C. Microstructure electron microscopy was performed on ASB Inconel 718 and heat treated to correlate the observed mechanical properties with nanoscale features. Homogenization of the microstructure led to a highly ductile Inconel with lower strength compared with wrought Inconel 718. The tensile properties of additively manufactured 718 using a standard ASTMrecommended heat treatment were consistent with literature and with the ASTM for the properties of this alloy. A higher fraction of the δ phase led to shorter uniform elongation without altering other engineering properties.
MST e-News Fall 2021
The society’s highly competitive Bronze Medal—only two were awarded—recognizes ASM members who are in early-career positions for their significant contributions in the field of materials science and engineering through technical content and service to ASM and the materials science profession.
AOI-2, A Novel Access Control Blockchain Paradigm for Cybersecure Sensor Infrastructure in Fossil Power Generation Systems
Fossil power generation systems are increasingly vulnerable to attack from both cybercriminals as well as internal threats. These vulnerabilities demand that emerging technologies such as blockchains be utilized to secure the data involved in the information flows within the Supervisory Control and Data Acquisition (SCADA) systems of the fossil power generation plants. The publicly accessible blockchain protocols, although secure, are visible to everyone. Even private blockchains currently are unable to support different levels of access to different participants, which is a critical requirement for the existing SCADA systems running the power plants. In light of the above, novel blockchain protocols that are specifically adapted to fossil power generation environments need to be developed in order to achieve the goal of cybersecure sensor networks. In this work, we address this question by creating a novel blockchain technology, namely smart private ledger, for cybersecure communication within the fossil power generation systems. A lab-scale sensor network consisting of strain and temperature sensors is constructed to develop the ledger. The technology has hierarchical access control which is compatible with the existing SCADA systems in fossil power plants. The sensor data is used with cryptographic digital signatures and secret sharing protocols within the nodes of the blockchain technology. The research results will lead to cybersecurity for machine-to-machine interactions, infrastructure for secure data logging for sensors, decentralized data storage, and second-layer technologies for high volume machine-to-machine interactions in the power plants. The work aims to largely address the concerns for the security of distributed sensor networks in such systems that can be compromised by insider threats and by cybercriminals. The research has led to the training of the next generation of engineers and scientists in the important areas of sensor engineering and blockchain technology.
Uncertainty Quantification for Component Modeling Using the Discrete-Direct Approach
Threaded fastener behavior can be an important aspect of complex component and system behavior, but there is no one-size-fits-all finite element analysis technique. Proper modeling of threaded fastener joints requires careful consideration of many details, from test setup and data acquisition to constitutive modeling and uncertainty quantification approaches. This report details analysis of a “mini-radax” bolted-joint exemplar where a Discrete-Direct uncertainty quantification approach is employed to evaluate margin of the component. The mini-radax geometry is tested to failure on a drop table, and single-coupon tests of individual fasteners serve as foundational data for the analysis. Analysis predictions complement the test data well and provide additional context for engineering decision-making.
Effect of Split-Injection Strategies on Engine Performance and Emissions under Cold-Start Operation
The recently concluded partnership for advancing combustion engines (PACE) was a US Department of Energy consortium involving multiple national laboratories focused on addressing key efficiency and emission barriers in light-duty engines. Generation of detailed experimental data and modeling capabilities to understand and predict cold-start behavior was a major pillar in this program. Cold-start, as defined by the time between first engine crank and three-way catalyst light-off, is responsible for a large percentage of NOx, unburned hydrocarbon, and particulate matter emissions in light-duty engines. Minimizing emissions during cold-start is a trade-off between achieving faster three-way catalyst light-off, and engine out emissions during that period. In this study, engine performance, emissions, and catalyst warmup potential were monitored while the engine was operated using a single direct injection (baseline case) as well as a two-way-equal-split direct injection strategy. These injection strategies were analyzed at a range of cold-start-operation relevant retarded spark timings of up to 25 degrees after top dead center of firing (dATDCf). A stoichiometric 2-bar NIMEP steady-state condition was used for all cases to simulate cold-start operation. Significant improvement in engine stability was observed with the two-way-split injection strategy at the retarded spark timings allowing for up to 2.5x increase in exhaust heat rate when engine operation is stability constrained. Similar fuel-loss-to-oil trends with exhaust heat rate were observed for both single and two-way-split injection strategies. However, the two-way split injection was observed to produce higher NOx emissions per unit exhaust heat rate. A single data point run with three-way-split direct injection at a very retarded spark-timing of 30 dATDCf pointed to further improvements in engine stability and reduction in fuel-loss-to-oil as compared to single injection strategy. Engine stability decreased as spark timing was initially retarded with a single injection but was observed to plateau and stabilize beyond spark timing of 10 dATDCf. Finally, for the two-way-split-injection strategy, retarding the start of injection (SOI) timing of the second injection led to a decrease in engine stability as well as an increase in soot emissions.
ASNF Engineering Scale Drying Experiment System Operability Functional Requirements
This checklist specifies the functional requirements for the drying system installed at Holtec International under the scope of INL Contract # 215725, in collaboration with University of South Carolina under INL Contract Number 207046, consistent with the parameters described in INL/EXT-19-56017, Aluminum-clad Spent Nuclear Fuel Engineering Scale Drying Experiment Design. Completion of the ASNF Engineering Scale Drying Experiment Acceptance Criteria for Fabricated Items, INL/MIS-20-58551, is a prerequisite.
Fort Saint Vrain Fuel Handling Tool Modernization- Intern Poster
This poster presents the modernization of a crane tool for handling spent nuclear fuel from Fort St. Vrain, involving some reverse engineering and structural analysis.
NeuroSEM: A hybrid framework for simulating multiphysics problems by coupling PINNs and spectral elements
Multiphysics problems that are characterized by complex interactions among fluid dynamics, heat transfer, structural mechanics, and electromagnetics, are inherently challenging due to their coupled nature. While experimental data on certain state variables may be available, integrating these data with numerical solvers remains a significant challenge. Physics-informed neural networks (PINNs) have shown promising results in various engineering disciplines, particularly in handling noisy data and solving inverse problems in partial differential equations (PDEs). However, their effectiveness in forecasting nonlinear phenomena in multiphysics regimes, particularly involving turbulence, is yet to be fully established. Here, this study introduces NeuroSEM, a hybrid framework integrating PINNs with the highfidelity Spectral Element Method (SEM) solver, Nektar++. NeuroSEM leverages the strengths of both PINNs and SEM, providing robust solutions for multiphysics problems. PINNs are trained to assimilate data and model physical phenomena in specific subdomains, which are then integrated into the Nektar++ solver. We demonstrate the efficiency and accuracy of NeuroSEM for thermal convection in cavity flow and flow past a cylinder. The framework effectively handles data assimilation by addressing those subdomains and state variables where the data is available. We applied NeuroSEM to the Rayleigh-B´enard convection system, including cases with missing thermal boundary conditions and noisy datasets. Finally, we applied the proposed NeuroSEM framework to real particle image velocimetry (PIV) data to capture flow patterns characterized by horseshoe vortical structures. Our results indicate that NeuroSEM accurately models the physical phenomena and assimilates the data within the specified subdomains. The framework’s plug-and-play nature facilitates its extension to other multiphysics or multiscale problems. Furthermore, NeuroSEM is optimized for efficient execution on emerging integrated GPU-CPU architectures. This hybrid approach enhances the accuracy and efficiency of simulations, making it a powerful tool for tackling complex engineering challenges in various scientific domains.
Long-range cooperative resonances in rare-earth ion arrays inside photonic resonators
Engineering arrays of active optical centers to control the interaction Hamiltonian between light and matter has been the subject of intense research recently. Collective interaction of atomic arrays with optical photons can give rise to directionally enhanced absorption or emission, which enables engineering of broadband and strong atom-photon interfaces. Here, we report on the observation of long-range cooperative resonances in an array of rare-earth ions controllably implanted into a solid-state lithium niobate micro-ring resonator. We show that cooperative effects can be observed in an ordered ion array extended far beyond the light’s wavelength. We observe enhanced emission from both cavity-induced Purcell enhancement and array-induced collective resonances at cryogenic temperatures. Engineering collective resonances as a paradigm for enhanced light-matter interactions can enable suppression of free-space spontaneous emission. The multi-functionality of lithium niobate hosting rare-earth ions can open possibilities of quantum photonic device engineering for scalable and multiplexed quantum networks.