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At least 1,243 records · Page 69

AGR-5/6/7 Thermal Model with Non-uniform Gas Gaps

Fuel compact temperatures are a crucial factor in assessing the irradiation performance of tri-structural isotropic fuel particles. In the absence of direct measurement, fuel compact temperatures were calculated using a three-dimensional finite element thermal model, which is subject to simulation uncertainty. The most dominant factor in the uncertainty of calculated fuel temperatures is the gas gap uncertainty due to the nub-to-shell clearance caused by a design error of AGR-5/6/7 capsules. The thermal model was revised to examine the most probable graphite offset position for six different days during the irradiation for Capsules 1 and 2. The analysis varied the offset distance and azimuthal direction at both the top and bottom of the holder. The best-fit offset was estimated based on the minimum root mean square error of the residuals (measured minus calculated) for the operational thermocouples (TCs). From these results, the following conclusions were made: (1) The holder offsets led to slightly lower average temperatures but wider temperature variations (lower minimum and higher peak fuel temperatures) for both Capsule 1 and Capsule 2. (2) During earlier cycles (162A–164B), when numerous TCs were still operational, the best-fit offset distance varied over a specific range for both the top and bottom ([0.002–0.0035 in.] for Capsule 1 and [0.003-0.004 in] for Capsule 2). In contrast, the offset azimuthal direction varied widely, especially for the offset at the bottom of the Capsule 1 holder. This is because holder movement was somewhat constrained at the top of Capsule 1 by the TC leads running through the capsule head and into the holder and by the through tubes in Capsule 2, but the Capsule 1 bottom did not have this type of constraint. (3) During later cycles, when all TCs failed, applying the maximum possible offset of 0.006 in. to the northwest direction for both the top and bottom resulted in a calculated peak fuel temperature of 1557? in Capsule 1 (i.e., a 135? increase from 1422? with zero offset on September 20, 2019 (166A)); the maximum offset of 0.0068 in. to the south for both top and bottom resulted in a calculated peak fuel temperature of 1110°C in Capsule 2 on April 20, 2020 (i.e., a 116? increase from 994? with zero offset (168A)). High peak fuel temperatures in Capsule 1 during Cycle 166A could be the cause of massive particle failure near the end of this cycle. (4) Even though the highest temperature at the tip of Type-N TCs, such as TC-1-7, slightly exceeded 1000?, the temperature along the TC wire reached as high as 1335? assuming an offset of 0.006 in. in the northwest of Capsule 1 holder near the end of Cycle 166A. This temperature significantly exceeds the temperature threshold at which TC degradation is expected to occur, ultimately contributing to considerable particle failures in Capsule 1. For eight Type-N TCs in Capsule 2, the peak TC line temperature was much lower (i.e., 1029°C for TC-2-5), assuming maximum offset of 00068 in. to the south during cycle 168A.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

AGR-5/6/7 Thermal Model with Non-uniform Gas Gaps

Fuel compact temperatures are a crucial factor in assessing the irradiation performance of tri-structural isotropic fuel particles. In the absence of direct measurement, fuel compact temperatures were calculated using a three-dimensional finite element thermal model, which is subject to simulation uncertainty. The most dominant factor in the uncertainty of calculated fuel temperatures is the gas gap uncertainty due to the nub-to-shell clearance caused by a design error of AGR-5/6/7 capsules. The thermal model was revised to examine the most probable graphite offset position for six different days during the irradiation for Capsules 1 and 2. The analysis varied the offset distance and azimuthal direction at both the top and bottom of the holder. The best-fit offset was estimated based on the minimum root mean square error of the residuals (measured minus calculated) for the operational thermocouples (TCs). From these results, the following conclusions were made: (1) The holder offsets led to slightly lower average temperatures but wider temperature variations (lower minimum and higher peak fuel temperatures) for both Capsule 1 and Capsule 2. (2) During earlier cycles (162A–164B), when numerous TCs were still operational, the best-fit offset distance varied over a specific range for both the top and bottom ([0.002–0.0035 in.] for Capsule 1 and [0.003-0.004 in] for Capsule 2). In contrast, the offset azimuthal direction varied widely, especially for the offset at the bottom of the Capsule 1 holder. This is because holder movement was somewhat constrained at the top of Capsule 1 by the TC leads running through the capsule head and into the holder and by the through tubes in Capsule 2, but the Capsule 1 bottom did not have this type of constraint. (3) During later cycles, when all TCs failed, applying the maximum possible offset of 0.006 in. to the northwest direction for both the top and bottom resulted in a calculated peak fuel temperature of 1557? in Capsule 1 (i.e., a 135? increase from 1422? with zero offset on September 20, 2019 (166A)); the maximum offset of 0.0068 in. to the south for both top and bottom resulted in a calculated peak fuel temperature of 1110°C in Capsule 2 on April 20, 2020 (i.e., a 116? increase from 994? with zero offset (168A)). High peak fuel temperatures in Capsule 1 during Cycle 166A could be the cause of massive particle failure near the end of this cycle. (4) Even though the highest temperature at the tip of Type-N TCs, such as TC-1-7, slightly exceeded 1000?, the temperature along the TC wire reached as high as 1335? assuming an offset of 0.006 in. in the northwest of Capsule 1 holder near the end of Cycle 166A. This temperature significantly exceeds the temperature threshold at which TC degradation is expected to occur, ultimately contributing to considerable particle failures in Capsule 1. For eight Type-N TCs in Capsule 2, the peak TC line temperature was much lower (i.e., 1029°C for TC-2-5), assuming maximum offset of 00068 in. to the south during cycle 168A.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Utilizing Commercial Submersible Mixer Pumps for Sludge Removal in Savannah River Site's Tank 26 - 20289

The Savannah River Site (SRS) Liquid Waste System (LWS) safely manages, stores, treats, and dispositions liquid radioactive waste. The LWS consists of 51 underground waste storage tanks (eight of which are operationally closed and filled with grout), waste evaporators, treatment facilities, and solidification facilities, known as the Defense Waste Processing Facility (DWPF) and Saltstone Production Facility (SPF). One of the waste storage tanks, Tank 26, was placed into service in 1980 as an F Tank Farm (FTF) Evaporator Feed Tank. From 1980 to 2013, Tank 26 received F Canyon receipts and dilute supernate that was then transferred to the 242-16F FTF Evaporator for volume reduction. In 2013, the steam tube bundle failed in the FTF Evaporator, and the decision was made not to repair/resume evaporator operation. During operation of Tank 26, solids built up to a level of 2.03 m in the tank with a volume of 1062.9 kL. Due to the evaporator failure and subsequent shutdown, the solids in Tank 26 were selected to feed Sludge Batch 10, which is collected and prepped prior to being sent to DWPF for final disposition. To accomplish solids removal, Commercial Submersible Mixer Pumps (CSMPs) were selected to slurry the solids in preparation to be sent to Tank 51. Four CSMPs were installed in Tank 26 with each one installed in a separate quadrant of Tank 26. This work would mark the first deployment of CSMPs in an SRS waste tank. The CSMPs were developed in response to operational issues from previous mixing pumps and budgetary constraints. The CSMPs use the concept of modifying commercially available equipment for nuclear waste applications. The CSMPs consist of a 230-horsepower submersible mixing pump (manufactured by GPM, Inc.) joined to a mast fabricated at SRS. For this application, Savannah River Remediation (SRR) design services was challenged to provide a mast design that required no steel superstructure support system on top of Tank 26. Also, SRR design services provided a simplified Tank 26 riser interface that did not require extensive machine parts to adjust height of the suction screen of the CSMP within the tank. Other design improvements include no requirements for tank top radiation monitors and no requirements for flushing of the CSMPs during startup/shutdown operations. The CSMPs were operated at an initial height of 2.29 m above the Tank 26 bottom for 10 days. After sludge sounding, the CSMPs were lowered to a height of 1.52 m with no issues due to proper work planning and the simplified riser interface. With the CSMPs lowered to a level of 1.52 meters above the tank bottom, the CSMPs were operated for 12 days and another sounding was performed. The sounding level came back matching the disturbance depth results of the first pump run. Chemistry samples were analyzed while the tank was left to settle. The analysis revealed enough weight percent solids to provide good feed to Sludge Batch 10. Also, the results revealed the supernate within the mixture would provide good salt solution feed to Salt Waste Processing Facility (SWPF) Salt Batch 3. So, the plan was modified to let the disturbed solids settle and decant the salt solution for addition to SWPF Salt Batch 3. Then water will be added back to Tank 26, and the CSMPs run in order to wash the solids to decrease settling time prior to being sent to Tank 51 for Sludge Batch 10. Utilizing CSMPs for waste removal in an SRS Tank has provided a cost-effective means for further waste removal efforts. In addition, the CSMPs are easier to operate by utilizing a robust and simplified design. The CSMPs performed quite well with no process shutdown or delays during operation. As a result, CSMPs are integral to the future of removing radioactive waste from storage tanks at SRS. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Machine Learning and Economic Models to Enable Risk-Informed Condition Based Maintenance of a Nuclear Plant Asset

The primary objective of this research is to address challenges in the implementation of risk-informed, condition-based predictive maintenance (PdM), which reduces operating costs while still maintaining the safety and reliability of commercial nuclear power plants (NPPs). To achieve the objective, risk models are being developed by taking advantage of advancements in data analytics, deep learning, machine learning (ML), and artificial intelligence (AI). The notable outcomes presented in the report include ? Development of a ML models using heterogeneous plant process and vibration data collected at different spatial and temporal resolutions from the Salem?s CWS to diagnose a circulating water pump (CWP) failure based on salient fault signatures. The developed diagnostic models are extendable to other faults associated with CWPs and CWP motors given associated fault signatures. ? Development of a natural language processing (NLP) technique to automatically classify the WO data into different categories. The developed NLP technique was validated on independent WO data. This automates the tedious and time-consuming activity of mining and classifying WOs by subject matter experts. ? Estimation of mean time between downtime (i.e., time duration between time instances when 1 or more CWPs are not available) and developed an approach to establish reliability of CWS components using unstructured WO data along with CWS plant process data. ? Formulation of economic model based on Markov chain models. The parameters of associated with the transition rate between different states of Markov chain models were estimated using WO data. The economic model formulation and discussion captures both time-independent and time-dependent parameter variation, leading to risk-informed decision-making.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Development of a BlueCRAB/MELCOR Framework for Supporting Realistic Mechanistic Source Term Calculations in Microreactors

Efforts are currently underway to deploy microreactor modeling and simulation tools to better support vendors and regulatory authorities in submitting and reviewing licensing applications. In particular, the Nuclear Regulatory Commission is expected to rely on the Comprehensive Reactor Analysis Bundle (BlueCRAB) multiphysics toolset in performing design- and beyond-design-basis accident analyses. In addition, the Nuclear Regulatory Commission has been using the MELCOR code to estimate mechanistic source terms during accidents. As MELCOR relies on isotopic inventory and reactor temperature/power evolution profiles during accident conditions—all of which can theoretically be obtained from BlueCRAB—the ultimate goal of this activity is to establish a common BlueCRAB-MELCOR framework. However, prior to the present research, BlueCRAB had never been used to calculate such quantities of interest at the full-core level. While there are many Monte Carlo (MC) codes capable of computing such quantities of interest, they are unable to readily account for multiphysics feedback. BlueCRAB allows for the coupling of different physics codes together to perform multiphysics-informed calculations. Therefore, the purpose of this fiscal year 2023 work is to investigate the feasibility and challenges of performing such calculations within BlueCRAB so as to generate the data that MELCOR relies on. To demonstrate the methodology, the proposed workflow was applied to a prototypical heat pipe-cooled microreactor model. To predict isotopic concentrations (taking into account the ac- cumulation of fission products during operation), the necessary microscopic cross sections were generated via OpenMC and tabulated with respect to temperature and burnup. Next, a recently developed capability in Griffin (the reactor physics application in BlueCRAB) was used to convert the OpenMC output format into the ISOXML format used by Griffin. A multiphysics microscopic depletion calculation that involved performing a coupled full-core, heterogeneous neutron trans- port and thermal calculation at each depletion step was conducted to deplete the core to end of life (EOL) conditions so as to provide both isotopics and the initial condition for the transient calculation. Following a brief null-transient to verify that the initial condition had been properly restarted and was indeed in thermal equilibrium, a heat pipe failure transient was simulated. Thus, the entire workflow of using BlueCRAB to generate MELCOR inputs, from cross-section generation to producing isotopic inventory and power/temperature evolution profiles during transients, is demonstrated. This report also details the identified gaps in the workflow and how they were (for the most part) addressed. Future work should focus on directly including MEL- COR into the workflow by performing a MELCOR calculation using the BlueCRAB-generated input data. In addition, the heat pipe reactor design should be improved so as to reflect more prototypical burnup characteristics at EOL.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Performance of Compact Pulsed Thermal Imaging System for In-Service Applications. Pulsed thermal tomography nondestructive examination of additively manufactured reactor materials and components

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of complex topology nuclear reactor parts from high-strength corrosion resistance alloys, such as stainless steel and Inconel. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process, which has the capability of melting metallic powder and net shaping the structures with relatively high precision. Some of the challenges with using LPBF method for nuclear manufacturing include the possibility of introducing pores into metallic structures. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures due to creep in high temperature nuclear reactor environment. Currently, there exist limited capabilities to evaluate actual AM structures nondestructively. Pulsed Thermography (PT) imaging provides a capability for non-destructive evaluation (NDE) of sub-surface defects in arbitrary size structures. The PT method is based on recording material surface temperature transients with infrared (IR) camera following thermal pulse delivered on material surface with flash light. The PT method has advantages for NDE of actual AM structures because the method involves one-sided non-contact measurements and fast processing of large sample areas captured in one image. The data cube of PT measurements consists of surface temperature taken at sequential time intervals T(x,y,t). Material defects can be detected either by analyzing the thermograms T(x,y,t) data cube, or by using thermal tomography (TT) algorithm to obtain 3D spatial reconstruction of thermal effusivity e(x,y,z). To reduce the cost and enable in-service NDE in spatially constrained environment, it is highly desirable to develop PT with compact and inexpensive IR camera. Following initial qualification of an AM component for deployment in a nuclear reactor, a compact PT system can also be used for in-service nondestructive evaluation (NDE) applications. However, data cube obtained with PT based on compact IR camera suffers from strong thermal noises and loss of features due to relatively low sampling rate. In this report we describe two unsupervised machine learning (ML) algorithms for enhancement of PT images obtained with compact IR camera. In one approach, we introduce Sparse Coding Discrete Cosine Transform (SC/DCT) algorithm to remove additive white Gaussian noise (AWGN) from spatial thermal effusivity reconstructions. In another approach we introduce a Spatial Temporal Denoised Thermal Source Separation (STDTSS) ML algorithm to process thermograms. The STDTSS algorithm consists of spatial and temporal denoising using Gaussian and Savitzky–Golay filtering, followed by the matrix decomposition using Principal Component Analysis (PCA), and Independent Component Analysis (ICA) to automatically detect flaws. In the work described in this report, we constructed a compact PT system using a relatively small and low-cost FLIR A65 camera, consisting on uncooled microbolometer detector. Performance of SC/DCT algorithm was demonstrated on enhancing TT images of Inconel 718 AM plate. Performance of the STDTSS methods was investigated using thermography data obtained from imaging stainless steel 316L specimens produced with LPBF method with imprinted calibrated porosity defects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Mechanical Properties of Permanent Foaming Fixatives for Deactivation and Decommissioning Activities

DOE-EM have identified an operational requirement for a fixative that can immobilize and/or encapsulate residual contamination in 3D void volumes (pipes, gloveboxes, waste containers, etc.) during D and D activities. Failure to safely and effectively immobilize residual contamination can: Put workers at risk, Contaminate the public and environment, Drive up operational costs. Commercial-off-the-shelf (COTS) polyurethane (PU) foams is one possible solution and is currently being investigated in collaboration with Savannah River National Lab (SRNL). Mechanical property testing will dictate how well PU foams can withstand physical stressors outlined in safety documents while immobilizing residual contamination. Results can provide a performance criteria for Section 5 of ASTM E3191: Standard Specification for Permanent Foaming Fixatives Used to Mitigate Spread of Radioactive Contamination. Polyurethanes consists of repeating units of urethanes which are produced from an exothermic reaction between a polyol (an alcohol with two or more hydroxyl groups in a molecule) and an isocyanate [2]. PUs consists of 3D cells that are formed by a blowing agent which is normally water. Water interacting with the isocyanate creates carbon dioxide and urea which contributes to cells' growth and expansion. The cross-linking between the polyol and isocyanate solidify the cell faces and walls. Micro scale properties that can influence mechanical properties include: Relative density (ratio between density of cellular material and density of the solid of which the cell walls are made of). Cells connectivity between edges and faces, and number of cells contact neighbors [3]. Whether a foam is open-celled or closed-celled. Closed-celled foams have a thin membrane that encloses each cell which can contribute to the stiffness of the foam. Incorporating fillers in the PU matrix like carbon-based nanoparticles in the form of expandable graphite (EG) can increase the thermal and mechanical performance [4]. When exposed to heat, EG produces a char layer that prevents heat and oxygen transfer which is known as intumescing. Mechanical performance is dependent on amount of EG loading since the cell sizes are linearly dependent on it. Overall, the rigid foams (I-R2) proved superior. SEM Analysis: I-R2 had the most consistent spherical sizes (average cell diameter: 489 μm), which enhance the relative density the most [5]. Tensile Testing Results: I-R2 experienced the largest breaking load (103.65 lbf) and stress (289.42 psi). I-R2 also had a higher Young's Modulus compared to R1 (2.99 ksi to 2.09 ksi). Compression Testing Results: I-R2 had the highest stress at 80% deflection (360.67 psi), load (1387.48 lbf) and modulus (3.92 ksi)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Second Annual Progress Report on Correlation Between Microstructure and Mechanical Properties of Neutron-Irradiated Ferritic-Martensitic and Austenitic Steels

Ferritic-martensitic steels G92-2b (an optimized Grade 92 heat), NF616 and T91, and austenitic stainless steel 800H and its Grain Boundary Engineering (GBE)-treated version 800H-TMP (ThermoMechanical Processing) were irradiated in the High Flux Isotope Reactor (HFIR) of Oak Ridge National Laboratory (ORNL) and the Advanced Test Reactor (ATR) of Idaho National Laboratory (INL). Selected G92-2b samples were irradiated up to 14.66 dpa in the HFIR at two temperature ranges: 400–496.7°C and 683.3– 720°C. NF616 and T91 were irradiated in the ATR up to 8.16 dpa with the irradiation temperatures ranged from 241°C to 447.5°C. Alloy 800H and 800H-TMP samples were irradiated in both the HFIR and the ATR. Selected 800H and 800H-TMP samples had HFIR irradiation to 1.28 dpa at 580°C and ATR irradiation up to 9.12 dpa at 359°C to 431°C. Vickers hardness measurements, fractography, and microstructural characterization were performed on the selected samples in the Low Activation Materials Design and Analysis (LAMDA) laboratory. Radiation-hardening of G92-2b was observed at the lower doses and lower irradiation temperatures (400- 496.7°C), with GB03 (0.52 dpa at 400°C) and GB04 (7.44 dpa at ~490°C) showing ~12% and ~8% hardening, respectively. Softening by ~14% was observed for GB05 (14.66 dpa at 496.7°C). Radiationsoftening of G92-2b was more prevalent at the higher irradiation temperatures (683.3-~720°C), with GB10 (0.46 dpa at 683.3°C), GB11 (7.44 dpa at ~720°C), and GB12 (14.63 dpa at ~720°C) showing ~8%, ~8%, and ~40% softening, respectively. Radiation-hardening of NF616 and T91 was observed with the hardness increased by ~37% to ~65% depending on the irradiation doses and irradiation temperatures. Within the studied irradiation conditions of NF616 and T91, samples with a higher dose had a larger hardness after irradiation. All the tested alloy 800H and 800H-TMP samples in this work showed radiation-hardening by ~96±7% to ~152±10%. Alloy 800H-TMP tended to have slightly smaller radiation-hardening than alloy 800H. The fractography results of G92-2b sample GB03, GB10, and GB11, together with the previously characterized fractography of GB04, GB05, and GB12, indicated that the ductility of G92-2b was maintained up to 14.66 dpa at the lower irradiation temperatures of 400-496.7°C, while some loss of ductility (less necking) was observed for higher doses at the higher irradiation temperatures of 683.3-720°C. This agrees with the previously reported tensile test results of G92-2b, where the elongation of G92-2b was reduced at higher doses at the higher irradiation temperatures. Dimple sizes increased at higher doses, which are more evident at the higher irradiation temperatures of 683.3-~720°C. The fractography of NF616 sample D2 (2.96 dpa at 291.5°C), D4 (5.91 dpa at 359°C), and D6 (8.16 dpa at 431°C) indicated loss of ductility with negligible necking for sample D2, while ductile failure for samples D4 and D6. Fractography of alloy 800H and 800H-TMP samples in various irradiation conditions showed ductile failure with obvious necking. Dimples were observed, with some of them containing large Ti-rich particles, in all the 800H/800H-TMP samples. Electron backscatter diffraction characterization of GB12 indicated the recovery of the lath structure, which was generally replaced by an equiaxed grain structure. Transmission electron microscopy (TEM) characterization showed the presence of frequent M 23 C 6 (M = primarily Cr), MX (M = primarily V), spherical Nb(C,N) precipitates, and occasional Laves phase precipitates in the G92-2b samples. MX precipitates with sizes of 20-30 nm were observed at boundaries of smaller grains, indicating the pinning effect of the V-rich precipitates. The lath structure recovery was more evident at the higher irradiation temperatures (683.3-~720°C), with decreased densities of line dislocations and M23C6 precipitates. The irradiated T91 (TA04) showed the growth of M23C6 precipitates to 101 ± 40 nm from the initial 68 ± 22 nm in the unirradiated condition. Dislocation loops of both {100} and {111} types were present in TA04. TEM characterization was also performed on the irradiated 800H (N4, N5, N6, and AR2) and 800H-TMP (P4, P5, P6, and HG1). Accumulation of M 23 C 6 precipitates at grain boundaries was observed in all the xii 800H/800H-TMP samples, and the presence of Ti(C,N) precipitates at grain boundaries and in the matrix was observed in the irradiated 800H-TMP. Some Ti(C,N) precipitates are embedded in the M 23 C 6 precipitates, maintaining specific orientation relationships between the precipitates and between the precipitate and matrix. In addition, nanoscale Si-rich clusters were observed in the matrix of all the 800H/800H-TMP samples, with EDS Si maps tending to have a lower contrast in 800H-TMP samples. Atom probe tomography was conducted on the same samples, supported by a Rapid Turnaround Examination project under Nuclear Science User Facilities. The results are being analyzed to be integrated with the TEM results for a confident description of the γ’ precipitates. Dislocation loops also formed in all the 800H/800H-TMP samples. The density and the average size of dislocation loops were quantified to be in the order of 10 22 – 10 23 m -3 and 11.7 – 15.9 nm, respectively, in the ATR-irradiated 800H/800H-TMP samples. The loop densities in irradiated 800H were higher than that in irradiated 800H-TMP under the same irradiation conditions. Further systematic data analyses, together with some complementary experiments, will be pursued for these samples to foster peer-reviewed journal article publications.

36 MATERIALS SCIENCE↗

Unsupervised Process Anomaly Detection and Identification Using the Leave-One-Variable-Out Approach

Automated anomaly detection and identification can signal equipment issues and pinpoint causes in large-scale industrial systems. For systems with limited failure history, unsupervised machine learning methods can be utilized as they do not require past failures. This study introduces the leave-one-variable-out (LOVO) model, which masks one variable at a time to predict the others, learning underlying process correlations. Detection performance was assessed with synthetic and experimental data, while identification performance used only synthetic data due to its ability to generate labeled anomaly types. For detection using synthetic data, the LOVO model generally outperformed comparative models; while using experimental data, the comparative methods outperformed the LOVO model. However, the comparative methods required selecting a latent size, and these conclusions pertain to using the optimal size. In practice, it would not be feasible to always select the optimal value, and incorrect selections impacted performance. In contrast, the LOVO model does not require a latent space. For identification using synthetic data, the LOVO model was slightly outperformed in interpretability and repeatability but still demonstrated impressive results. These outcomes suggest that the LOVO model is an effective model and may be more easily implemented without the challenging tuning process of selecting a latent size.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Considerations regarding the Use of Computer Vision Machine Learning in Safety-Related or Risk-Significant Applications in Nuclear Power Plants

With the advancements made to date in the field of artificial intelligence (AI), significant potential exists to utilize AI capabilities for nuclear power plant (NPP) applications. AI can replicate human decision making and it is usually faster and more accurate than humans. For implementations that impact critical NPP applications (e.g., safety-related or non-safety systems that potentially affect overall plant risk), a deeper safety analysis of the AI methods is necessary. AI applied to NPP operations could resemble the use of digital I&C (DI&C) because such applications involve digital computer hardware and custom-designed software that input plant data, execute complex software algorithms, and output the results to a system or licensed human operator to potentially provoke an action. For AI methods to be compliant with current safety requirements for DI&C, AI compatibility must be evaluated, and AI-related gaps may exist that prevent the prompt deployment of AI in NPPs. This effort aims to evaluate how example AI technologies align with the DI&C safety framework, and discusses how they could be analyzed, modeled, tested, and validated in a manner similar to typical DI&C technologies. Because AI is a broad field that encompasses areas such as machine learning (ML), natural language processing, and computer vision, this research focused on a subset of methods categorized as the computer vision ML (CVML) methods. This report explores two CVML use cases, gauge reading and fire watch, considered relevant to the DI&C standards, as they could play a safety-critical role. For the gauge reading use case, a CVML-enabled technology that can read gauges at oblique angles is utilized. For the fire watch use case, a CVML-enabled technology is utilized that migrates fire watch from a manual (human) approach to automated fire detection. These use cases are mainly intended to give context to the CVML system discussion. This effort assumes the worst-case scenario, with the CVML system being used to replace a safety-related or risk-significant system, thus requiring evaluation. Evaluating CVML against most of the relevant safety requirements for DI&C yielded several CVML-specific considerations due to the uniqueness of its characteristics in comparison with typical DI&C systems. For example, CVML models often employ commonly used (open-source) datasets, and it is not always possible to determine the level of overlap among open-source datasets. Therefore, the independence of the developed CVML models when demonstrating diversity is questionable, therefore creating vulnerability to common cause failure (CCF). The design verification process is also impacted since the data overlap could result in overestimation of the software validation and verification (V&V) performance results. Section 2 of this report evaluates a list of the identified CVML-specific characteristics and discusses the resulting considerations and potential solutions in the context of each referenced requirement. A summation is provided in Section 3. This report is not to be used as a guideline. It was developed to identify and consider issues in the implementation of ML technologies used to augment activities that may have a bearing on plant operation. The report draws parallels to the use of DI&C technologies, for which many standards are available to guide their use in nuclear plant operation. It considers the technologies and some of the potential implications of their use in safety-related applications but is not intended to address regulatory or licensing related issues.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Techno-Economic Impact of Diesel Fuel, Labor, and Interest Rates on Bulk-Format and Round Bale Logistics Expenses for Switchgrass

Highlights System-wide sensitivity of bulk-format and round bale logistics responded to different degrees of expense inputs. Biomass size-reduction expenses for bulk-format were consistently less than round-bale chopping. Stack/reclaim operations with high-density-capacity equipment for bulk-format were the highest expenses. Clean-sheet design of stacker/reclaimer and self-compacting bulk trailer may significantly reduce expenses. Abstract . Deterministic cost analyses were conducted for a harvest, storage, preprocessing, and supply system providing 371,870 dry Mg (dMg) year-1 of milled switchgrass (SG) to a biorefinery from 21,929 ha of production fields within 72 km of the biorefinery. Varied input costs of diesel fuel, labor, and interest rate were input into a highly detailed cost analysis for bulk-format and baseline round bale logistics. These operational input factors, potentially reflecting an evolving economic climate or paradigm shift, were examined to provide insight into the cost to deliver preprocessed biomass feedstock for centralized commercial-scale conversions. Total annual costs per dry unit of SG were determined for all combinations of diesel fuel prices of $0.53 L-1, $0.92 L-1, and $1.32 L-1; total labor costs of $20.00 h-1, $28.85 h-1, and $40.00 h-1 singly and uniformly applied across all labor inputs; and three representative interest rates of 6%, 8%, and 12%. Increases in total cost most depended on increases in diesel fuel cost, followed by labor rate, and finally interest rate. Increases in fuel costs from $0.53 L-1 to $1.32 L-1 yielded a total cost increase of about $11.56 dMg-1 and $13.36 dMg-1 for bulk-format and round bale logistics, respectively, for all combinations of labor and interest rates. The overall increase in labor rate ($20.00 h-1 to $40.85 h-1) resulted in increased total costs of about $10.32 dMg-1 for bulk-format logistics and $9.94 dMg-1 for round bale logistics for all fuel and interest rates. The overall increase in interest rate (6% to 12%) resulted in increased total costs of about $6.72 dMg-1 for bulk-format logistics and $4.21 dMg-1 for round bale logistics for all fuel and labor rates. Increases in total costs for combined increases in fuel cost, labor rate, and interest rate were $28.60 dMg-1 and $27.48 dMg-1, yielding maximum total costs of $87.87 dMg-1 and $86.53 dMg-1 for bulk-format and round bale logistics, respectively. Costs were determined for existing equipment systems, including novel use of waste compaction and ejector semi-trailers. The highest potential for cost reductions may require clean-sheet equipment designs specifically tailored for SG, such as forage harvesters that direct-cut standing SG, mobilized stacker-reclaimer technology to not inhibit stack-area footprint, self-compacting ejector trailer technology, and bale grinding technology incorporating controlled mass feeding and shear failure elements. Keywords: Bales, Bioenergy, Bulk-format, Densification, Field chop, Logistics, Transportation

Agriculture↗

Modeling and experimental validation of a W f /W-fabrication by chemical vapor deposition and infiltration

Tungsten (W) has a unique combination of excellent thermal properties, low sputter yield, low hydrogen retention, and acceptable activation. Therefore, W is presently the main candidate for the first wall material in future fusion devices. However, its intrinsic brittleness and its further embrittlement during operation bears the risk of a sudden and catastrophic component failure. As a countermeasure, tungsten fiber-reinforced tungsten (W f /W) with extrinsic toughening is being developed. A possible synthesis route is chemical vapor deposition (CVD) using heated W fabrics as substrate. The challenge is that the growing CVD-W can isolate domains from precursor access leading to strength-reducing pores. To deepen the process understanding and to optimize the CVD parameters, models were developed with COMSOL Multiphysics and validated experimentally. W deposition rate equations as function of the temperature and the partial pressures of the precursors H 2 and WF 6 were experimentally validated in previous work. In the present article, these equations are applied to obtain partial pressures within the CVD reactor. The results are taken as input for transient simulations in the microscale, in which W coatings, growing onto multiple adjacent W fibers, were simulated via mesh deformation and remeshing. The surface-to-surface contact of the W coatings and the corresponding potential pore formation were simulated by implementing sophisticated deposition rate stop conditions. Within the measuring uncertainties of ≃ ±1%, the models are validated successfully by experimental comparison regarding the deposition rate, pore structure, and relative densities ranging from 0.6 to 0.9.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High compressive energy absorption and shape recovery behavior of additively manufactured textile-inspired cylindrical braided metamaterials

Mechanical metamaterials (MMs) are engineered structures with unique mechanical properties that arise from their unique spatial arrangement or lattice-like structure. The most commonly designed MMs such as honeycomb and re-entrant auxetics are prone to failure at the sharp corners and weak joints due to the increased stress concentration under deformation. To mitigate this challenge, braided MM structures involving intertwining threads of nylon—forming curved unit cells—have been studied. These textile-inspired cylindrical braided metamaterials (CBMMs) with contrasting unit cells, namely diamond and regular CBMMs, were fabricated by 3D printing. The layer-by-layer deposited structure built by fused filament fabrication delivered an assembly of overlapped threads that are fused at the contact point. To understand deformation behavior of these MMs, finite element models were developed for various load scenarios including quasi-static compression, cyclic and creep loads at room temperature. Stress distribution, deformation mechanisms, and failure modes were analyzed and validated by experiments to analyze the geometries and associated performance. The diamond CBMMs showed stress softening at 30 % compressive strain, withstanding a load of ∼440 N, whereas the regular CBMMs at 50 % strain experienced ∼250 N. The diamond CBMMs delivered higher creep resistance under sustained load and better energy absorption under cyclic loading than the regular CBMMs. The latter, however, exhibited 94 % shape recovery in contrast to 88 % recovery in former prototype during their first cyclic load. In conclusion, this study helps design mechanical lightweight devices that endure significant sustained load and exhibit enhanced energy absorption and shape recovery characteristics in cyclic loading.

Creep↗

The Uranium-Containing and Thorium-Containing Anions Studied by Photoelectron Spectroscopy

An in-depth knowledge of actinide chemistry is fundamental to many aspects of nuclear science and technology, including the synthesis and processing of materials and the remediation of waste disposal sites. Among the actinides, the chemical bonding behaviors of actinium and thorium resemble those of the transition metals; the 5f-electrons of protactinium, uranium, neptunium, and plutonium often play important roles in their bonding; and among the still heavier elements, their bonding tends to mimic the lanthanide elements in terms of electron shielding and their f-electron contributions. Bonding that involves 5f-electrons, however, is especially important, in part because of the significance of uranium and plutonium, but also because these elements are among the few where f-electron participation in bonding is relatively common. This work focused on studying uranium-containing and thorium-containing anions in the gas phase using negative ion photoelectron spectroscopy. Since this technique directly probed valence electrons, it was uniquely positioned to address open questions regarding molecular bonding and electron configurations. A particularly important issue concerned how bonding in actinide-containing molecules was affected by modifications to their actinide atoms’ environment, i.e., due to their interaction with ligands. A closely related question was how actinide atoms’ suborbitals were qualitatively reordered and their energies quantitatively shifted as a result of their ligated environments. These were especially relevant issues in regard to uranium due to it having multiple possible oxidation states (OS) and the potential for 5f electron participation in bonding. The effects of ligands on oxidation states and 5f-orbital energies in uranium bonding was expected to be pronounced. Both ligands and excess electrons were seen as probes of actinide atoms within actinide-containing molecules. Our strategy for advancing knowledge of chemical bonding in the actinide-containing species utilized the synergy between experiments and theory, where in some cases experimental results validated theory and where in others computational results assisted in interpreting experiments. Calculations on actinide systems are terrifically challenging due to large spin-orbit interactions, relativistic effects, and just the sheer number of electrons involved. Even in the simplest species, e.g., U and U2, the most sophisticated, modern calculations carried out by the most experienced theorists often only approximate experimentally-measured values, such as electron affinities. For theory to provide confident predictions that can be used to solve real problems it needed an iterative and ultimately corrective mechanism by which its methods can develop further. Experiments can be used to identify when theory has failed; whereupon the subsequent process of using the experiment-theory interplay can be used to find the cause of the failure. Upon fixing it in one case, different test species can be proposed and studied by the experiment-theory combination to determine whether the problem has been corrected. Thus, experiments not only measure the values of molecular properties, they also provide navigational 3 beacons that keep computations off the reefs in an otherwise dark sea with few reference points. Experimental measurements in the actinide field are not only important, they are in actuality essential to computational progress. While it was not always possible to compare the theoreticallydetermined quantity of interest directly with the same experimentally-measured observable, it was usually possible to compare consequential properties that are both calculable and measurable. In the work completed here electron affinities and electronic state spacings were often sensitive consequential parameters. Reasonable agreement between measured and computational values signaled that a calculation that was very likely to be on-track. We had established collaborative relationships with five computational groups, all of which have expertise in computational actinide chemistry. Their PI’s are L. Cheng, D. Dixon, L. Gagliardi, K. Peterson, and B. Vlaisavljevich. Our close interaction with our theory partners led to us suggesting systems to them and them to us. This reciprocal interaction between our experimental and their computational results was among the most important strengths of this work and was a thread woven throughout. Even though anion photoelectron spectroscopic studies are conducted on anions, much of the information that they provide, pertains to the electronic structure of the neutral counterparts of those anions; among these are electron affinities and electronically excited state spacings. Our experimental tools included several specialized ion sources for forming the anionic species of interest, a mass spectrometer for identifying and mass-selecting them, and an anion photoelectron spectrometer for determining their electron affinities (EA) and characterizing the electronic states of the selected anions’ neutral counterparts. Anion photoelectron spectroscopy is conducted by crossing a mass-selected beam of anions with a fixed-frequency laser beam and energy-analyzing the resultant photodetached electrons. The photodetachment process is governed by the energyconserving relationship: hν = EBE + EKE, where hν is the photon’s energy, EBE is the electron binding (photodetachment transition) energy, and EKE is the electron’s kinetic energy. In our apparatus mass-selection is accomplished via time-of-flight mass spectrometry (TOF-MS), electron energy analysis is achieved with either a magnetic bottle or by velocity mapped imaging. Photodetachment of electrons from anions is implemented via either Nd:YAG or excimer lasers. The photodetachment transition energy, i.e., the EBE, between the ground vibrational and electronic state of an anion and the ground vibrational and electronic state of that anion’s neutral counterpart is the adiabatic electron affinity (EA) of that neutral molecule. Likewise, photodetachment transitions between the ground vibrational and electronic state of an anion and the various electronically-excited states of that anion’s corresponding neutral map the electronic spectrum of that neutral species, i.e., the spectral spacings in the photoelectron spectrum are a mirror image of the neutral’s electronic spectrum. It was, of course, crucial to be able to form the anionic species of interest. There, we had a particularly broad field of anion sources from which to choose. These included several variants of pulsed laser vaporization (LV), laser photoemission, infrared desorption plus photoemission, pulsed arc discharge (PACIS), electrospray ionization (ESI), and Rydberg electron transfer (RET). Each of these anion sources were readily combined with, i.e., connected to, the anion photoelectron spectroscopic portion of our apparatus as described above. Among the sources that utilize lasers, visible light for LV sources as well as IR for desorption sources are provided by Nd:YAG lasers. Ultraviolet photons are provided by both Nd:YAG and excimer lasers, whereas the excitation wavelengths for RET experiments come from two Nd:YAG-pumped dye lasers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modeling of fluid injection-induced fault reactivation using coupled fluid flow and mechanical interface model

The present study is aimed at developing a numerical model to reproduce coupled hydro-mechanical processes associated with fault reactivation by fluid injection in low permeability rock, as part of the DECOVALEX-2019 project Task B. We proposed a modeling approach for simulating the processes using the TOUGH-FLAC simulator, and modeled a fault reactivation experiment conducted at Mont Terri Rock Laboratory in Switzerland. The first step of the study involved benchmark calculations considering a simplified fault plane and geometry. Fluid flow along a fault was modeled using elements of aperture-sized thickness on the basis of Darcy's law and the cubic law in TOUGH2, whereas the mechanical behavior of a single fault was represented by zero-thickness interface elements in FLAC3D upon which a slip and/or separation is allowed. A methodology to connect a TOUGH2 volume element to a FLAC3D interface element was developed for handling the hydro-mechanical interactions on the fault during fluid injection. Two different fault models for describing the evolutions of hydraulic aperture by elastic fracture opening and failure-induced aperture increase were considered in the benchmark calculations. In the coupling process, the changes in geometrical features and hydrological properties induced by mechanical deformation were continuously updated. The transient responses of the fault and host rock to stepwise pressurization were examined during the simulation. The hydro-mechanical behavior, including the injection flow rate, pressure distribution around the borehole, stress conditions, and displacements in normal and shear directions were monitored in the surrounding rock and along the fault. The results of benchmark calculations suggest that the developed model reasonably represents the hydro-mechanical behavior of a fault and the surrounding rock. This modeling approach was applied to the fault reactivation experiment of the Mont Terri Rock Laboratory. In this interpretive modeling, a parametric study was conducted to examine the effects of input parameters regarding in situ stress and fault properties on the hydro-mechanical responses of the fault to water injection. Then, an optimal parameter set to reproduce the field experiment results was chosen by trial-and-error. The injection flow rate and pressure response during fault reactivation closely matched those obtained at the site, which indicates the capability of the model to appropriately capture the progressive pathway evolution during fault reactivation tests at the site. Finally, the anchor displacements were overestimated by the model, but a fair agreement was obtained in terms of the order of magnitude and the variation tendency.

58 GEOSCIENCES↗

Design, Deployment, and Characterization of the World’s First Flexible Large Power Transformer

GE Research and its partner Prolec GE have designed, built and deployed in the field the world’s first flexible power transformer. The flexible power transformer is a transmission class 3-phase autotransformer configurable in impedance and in voltage which allows it to serve as a universal spare for multiple units in a given fleet. However, the key innovation in this new concept is the online adjustable leakage impedance which allows the transformer to change its impedance without interrupting the transmission line operation. The flexible power transformer can be designed with up to three low voltage transmission class ratings and up to 12 impedance values changeable both online and offline. This report provides an overview of the design, manufacturing, testing, and commissioning of the 165kV, 60MVA prototype built including the results of the field performance validation tests. The prototype was specified in collaboration with Cooperative Energy, the utility host. It was designed and tested in the factory according to IEEE standard C57.12.00 and followed all protocols for transportation, installation, and commissioning of a power transformer. In addition to the prototype, a flexible protection system capable of automatically adjusting its settings upon the transformer impedance was also developed and deployed in the for testing and validation. On September 3, 2021 the prototype was energized in Cooperative Energy’s substation in Columbia, Mississippi to become the world’s first flexible power transformer in operation. Its performances and impact on the grid operation were demonstrated through different field tests. Results obtained confirm that the impedance of the flexible transformer can be varied under load through its full range, from 4.3% to 9.3%, without adverse impacts on the line operation, the protection system, the transformer stability and health condition. Results also proved that the flexible transformer is very effective in controlling power transfer through the line or load sharing between units operating in parallel. Indeed, it was proven that higher impedances decrease the thruput power of the transformer while lower impedances increase it. Up to 26MW was controllable on a line loading of 45MVA. It was also possible to demonstrate that the variation of the transformer impedance has no effect on the circulating current between units in parallel, except a minor transient during the impedance change. It was also proven that the flexible protection relay can update its protection settings automatically when the impedance change was detected. The prototype has operated continuously for more than 12 months now with a peak load exceeding 50MVA corresponding to >80% of its ONAN power rating. No alarm, trip or sign of failure has been reported by the utility. In addition to the development and deployment of the flexible transformer prototype, investigations were carried out on new nanodielectric fluids to replace the mineral oil used in power transformers with the goal of reducing their footprint and weight. The key parameters that were targeted for improvement included the breakdown voltage to reduce clearances between windings and tank hence the footprint; viscosity and thermal conductivity to increase the cooling efficiency and therefore to reduce the winding material. Several nanodielectric mixtures with mineral oil including with alumina (Al2O3), titania (TiO2) and Borum Nitrate (BN) with different surfactants have been analyzed and tested. Unfortunately, despite encouraging results no nanofluid candidate has been found viable to replace mineral oil. With the formulations tested, breakdown voltages are generally similar to mineral oil at lower particle contents and worse at higher particle contents. Viscosity appreciably increased at particles concertation over 2 wt% and thermal conductivity increased slightly at 5wt% and appears to be 10-15% higher at 10 wt% particle content. It is recommended to continue investigations to find solutions that can help increase the power density of future flexible power transformers. Flexible power transformers can significantly help the future power grid by providing more flexibility and resiliency. Indeed, by providing voltage and impedance flexibility, flexible power transformers reduce the need for multiple spares, hence inventory costs for utilities. With their online controllable impedance, they can provide support to the grid and help manage short-circuit currents, power flow, line congestion, and grid stability which will become more important with higher penetrations of intermittent renewable resources. During the field validation tests, it was demonstrated that up to 26MW was controllable on a line loading of 45MVA when the transformer impedance was varied from its minimum to its maximum range. Also, with the impedance range, the short-circuit currents could be reduced by up to 38% at the load side of the transformer. With its controllable impedance, flexible transformers can be used in future strategies of grid resilience to help better prepare the grid to face forecasted severe events including storms, heat waves and contingencies. The flexible power transformers can also find role in other applications including high voltage transmission cables such as offshore wind farms where solutions for energizing the cables and managing the reactive power are of critical importance. The designed flexible power transformer is now fully validated and ready for commercialization. Further analysis on the benefits of flexible power transformers for grid stability and short-circuit management including current limiting capability, reclosure and line restoration, control of inrush current, sizing of flexible AC components (FACTS) would help its rapid adoption by the industry.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Role of reinforcement learning for risk-based robust control of cyber-physical energy systems

Critical infrastructures such as cyber-physical energy systems (CPS-E) integrate information flow and physical operations that are vulnerable to natural and targeted failures. Safe, secure, and reliable operation and control of CPS-E is critical to ensure societal well-being and economic prosperity. Automated control is key for real-time operations and may be mathematically cast as a sequential decision-making problem under uncertainty. Emergence of data-driven techniques for decision making under uncertainty, such as reinforcement learning (RL), have led to promising advances for addressing sequential decision-making problems for risk-based robust CPS-E control. However, existing research challenges include understanding the applicability of RL methods across diverse CPS-E applications, addressing the effect of risk preferences across multiple RL methods, and development of open-source domain-aware simulation environments for RL experimentation within a CPS-E context. This article systematically analyzes the applicability of four types of RL methods (model-free, model-based, hybrid model-free and model-based, and hierarchical) for risk-based robust CPS-E control. Problem features and solution stability for the RL methods are also discussed. We demonstrate and compare the performance of multiple RL methods under different risk specifications (risk-averse, risk-neutral, and risk-seeking) through the development and application of an open-source simulation environment. Motivating numerical simulation examples include representative single-zone and multizone building control use cases. Finally, six key insights for future research and broader adoption of RL methods are identified, with specific emphasis on problem features, algorithmic explainability, and solution stability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Mechanical Loads on Spent Nuclear Fuel in the General 30 cm Package Drop Scenario

The U.S. Department of Energy Office of Nuclear Energy (DOE-NE) Spent Fuel and Waste Science & Technology (SFWST) research program is guided by the high-level goal of closing prioritized knowledge gaps related to spent nuclear fuel (SNF) storage and transportation, which are summarized by Saltzstein et al. (2020). One of the high-priority knowledge gaps is the identification and quantification of mechanical loads that are expected to affect SNF during normal conditions of transportation and storage to inform the range of physical SNF test programs. This report uses modeling and analysis methods to estimate the mechanical loads on spent nuclear fuel (SNF) in the general 30 cm package drop scenario. The drop scenario assumes impact limiters are in place in the transportation configuration and the impact surface is perfectly rigid. The goal of this analysis is to consider the universe of potential mechanical loading conditions that can happen to SNF and present the results in a manner that is useful for materials testing, decision making, and regulatory rule making purposes. This study uses validated finite element models and methods to perform a broad parametric study of key variables that can affect the mechanical loads on SNF during a hypothetical package free drop scenario. Physical drop test data from a cask and fuel assembly drop test campaign is the basis for model validation. Additionally, the results of the parametric study are used to inform a damage model, which uses multiple nonlinear regression to estimate the relationships between input variables and output response. The parametric finite element analyses consider thousands of input variable combinations, while the damage model estimates millions of combinations. The breadth of this study provides confidence that the potential range of mechanical loads that SNF might experience during the general 30 cm package drop scenario are characterized well enough to consider this knowledge gap closed. While this report documents the overall peak values calculated in this study, the 95 th percentile values, the histograms, and the observed trends are equally important. This study covered a large range of SNF temperatures, room temperature to 300°C, and burnups, 10 GWd/MTU to 62 GWd/MTU. Each temperature and burnup combination has a different cladding yield strain, so it is more meaningful to summarize the calculated cladding strain response as its factor of safety, which is defined relative to the yield strain. The factor of safety is calculated as the yield strain divided by the peak cladding strain. A factor of safety greater than unity indicates that the cladding remains below yield, whereas a value less than unity is indicative of plastic deformation. In all cases of this study a safety factor over 1.0 was calculated, although in the most limiting case at 300°C the safety factor was only 1.01, which suggests that yielding could occur when additional loads like rod internal pressure are included. When the temperature is restricted to 200°C the limiting safety factor increases to 1.28, which has significant margin to accommodate internal pressure and potential local cladding defects that could cause a local stress concentration. An important trend in the calculated fuel rod mechanical loads is that the 2 nd highest loaded fuel rod in an assembly tends to be significantly lower than the highest loaded rod. The implication is that even if one rod in an assembly experiences a failure the loads would have to be significantly higher to cause two or more rods to fail.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗