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At least 415 records · Page 23

Calculation of the Phenix end-of-life test in natural circulation with the CATHARE code

The Inst. of Radiological Protection and Nuclear Safety (IRSN) acts as technical support to French public authorities. As such, IRSN is in charge of safety assessment of operating and under construction reactors, as well as future projects. In this framework, one current objective of IRSN is to evaluate the ability and accuracy of numerical tools to foresee consequences of accidents. One of the advantages pointed up for fast reactors cooled by heavy liquid metal is the possibility of decay heat removal based on natural convection. The promotion of this passive cooling mode in future safety demonstrations will involve the use of adapted and validated numerical codes. After the final shutdown of the Phenix sodium cooled fast reactor in 2009, a set of tests covering different areas was conducted for code validation, including a natural circulation test in the primary circuit. Experimental data were issued by CEA to organize a benchmark exercise in the frame of an IAEA Coordinated Research Project (CRP), with the objective to assess the system-codes capability in simulating the thermal-hydraulics behavior of sodium cooled fast reactors in such accidental conditions. IRSN participated to this benchmark with the CATHARE code. This code, co-developed by CEA, EDF, AREVA and IRSN and widely used for PWR safety studies, was recently extended for sodium applications. This paper presents the CATHARE modeling of the Phenix primary circuit and the results obtained. A relatively good agreement was found with available measurements considering the experimental uncertainties. This work stressed the local aspects of phenomena occurring during the natural convection establishment and the limits of a 0D/1D approach. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

COVID-19 Exposure Assessment Tool (CEAT): Exposure quantification based on ventilation, infection prevalence, group characteristics, and behavior

The coronavirus disease 2019 (COVID-19) Exposure Assessment Tool (CEAT) allows users to compare respiratory relative risk to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) for various scenarios, providing understanding of how combinations of protective measures affect risk. CEAT incorporates mechanistic, stochastic, and epidemiological factors including the (i) emission rate of virus, (ii) viral aerosol degradation and removal, (iii) duration of activity/exposure, (iv) inhalation rates, (v) ventilation rates (indoors/outdoors), (vi) volume of indoor space, (vii) filtration, (viii) mask use and effectiveness, (ix) distance between people (taking into account both near-field and far-field effects of proximity), (x) group size, (xi) current infection rates by variant, (xii) prevalence of infection and immunity in the community, (xiii) vaccination rates, and (xiv) implementation of COVID-19 testing procedures. CEAT applied to published studies of COVID-19 transmission events demonstrates the model’s accuracy. We also show how health and safety professionals at NASA Ames Research Center used CEAT to manage potential risks posed by SARS-CoV-2 exposures.

60 APPLIED LIFE SCIENCES↗

Experimental and Computational Analysis of NEAMS Pebble Bed Reactors

The Advanced High-Temperature Pebble Bed Reactor concept leverages a particle-based fuel format consisting of discrete spherical graphite pebbles arrayed in a packed bed architecture. Thermal regulation achieved via flow of gas (e.g., helium) or liquid (e.g., molten salt) coolants through the void spaces between pebbles in the bed (characteristic pebble diameters: ~ 6 cm, gas cooled; ~ 3 cm, liquid cooled). This design is of interest owing to inherent advantages including passive safety features and highly efficient heat transfer characteristics that enable high power densities to be achieved. Fully leveraging these advantages requires a fundamental understanding of the complex coolant flow structure within the pebble-shaped fuel bed. Unfortunately, complexities associated with non-invasively probing the micro-scale flow phenomena within the complex network of void spaces between pebbles have hindered efforts to characterize the underlying transport phenomena. Without this fundamental foundation, it becomes challenging to rationally construct macroscopic transport models based upon volume averages of micro-scale parameters that accurately capture the observed flow behavior. Consequently, this lack of fundamental knowledge has limited previous work to coarse comparisons between theory and extremely limited experimental data. Moreover, these comparisons have been made only in terms of integral or macroscopic results. Therefore, multipoint measurements with a high level of spatial and temporal resolution are critically needed to fully map the complex flow patterns and to provide data at high spatial density to permit accurate volume averaging in the pebble bed. For this project, we performed a coordinated experimental and computational effort to quantitatively map the full-field velocity and temperature fields in the interstitial spaces within the pebble bed. The major accomplishments of this project included the important knowledge acquired for the flow mixing and heat transfer in the interstitial pore scales, the effects of flow mixing in the near-wall and far-wall regions, and the by-pass flows of pebble bed systems. The produced high-resolution experimental data (not broadly available in existing literature) were then used for the numerical studies enabling the refinement and validation of standard simulation tools (Nek5000).

42 ENGINEERING↗

Anomaly Detection in Flight Operational Data Using Deep Learning

In this session, we demonstrate two recently developed deep learning models for anomaly detection in flight operational data by the Data Sciences Group at NASA Ames Research Center. The first model is Convolutional Variational Auto-Encoder (CVAE) [1], which is an unsupervised deep encoder-decoder model, designed specifically for finding anomalies in heterogeneous multivariate time series data. We will demonstrate its application to finding anomalies in streaming data from NASA’s Digital Information Platform’s Fuser source. CVAE identifies data instances that are not representative of expected nominal behavior as anomalous. Since it is an unsupervised approach, the flagged anomalies will need to be reviewed by the subject matter experts (SMEs) for validation and labeling and is designed to assist with vulnerability discovery within Safety Monitoring System programs. The second model is Robust and Explainable Semi-supervised Anomaly Detection (RESAD) model [2], which builds on CVAE to allow learning from both minimally labeled data (previously reviewed by the SMEs) as well as majority unlabeled data. RESAD takes advantage of graph theoretic techniques to propagate the labels from the labeled data to the unlabeled data based on a pre-defined similarity metric and structures the learned feature space from flight time-series so that data of the same class would cluster tightly together. This model characteristic is enabled by training with an augmented loss function and allows learning of a more informative feature space for down-stream tasks such as search and active learning. We demonstrate RESAD using data from the NASA DASHlink project [3].

anomaly detection↗

Graded approach for assessing digital system failure susceptibilities - 305

Owner/operators of nuclear plants must be able to identify and assess susceptibilities to digital system failures and unintended behaviors that could lead to plant system malfunctions, including common-cause failures (CCFs) of multiple controlled components that may impact overall plant safety. Nuclear plant designers and regulators often assess and manage potential failure modes by assuming the failure occurs and showing by analysis that the results are acceptable. In 2016 EPRI published a guideline on Methods for Assuring Safety and Dependability when Applying Digital Instrumentation and Control Systems (EPRI 3002005326), which takes a more holistic approach that considers digital system failure modes from the perspective of their impact on plant risk and includes a graded approach based on safety significance. This paper describes that graded approach. The methodology in EPRI 3002005326 systematically identifies potential I and C vulnerabilities that could lead to significant malfunctions of controlled components and systems, including common-cause failures (CCF), and discusses in detail methods to protect against them. It considers both preventive measures that reduce the likelihood of failures, and plant systems and features that mitigate the effects of component failures and misbehaviors. Coping analysis is then performed as appropriate to provide additional assurance of protection. The safety significance based graded approach is an important feature in that it can help users focus attention on overall plant safety, including potentially risk-significant scenarios that might not be considered in traditional safety analyses. The purpose is to help the user ensure that modifications to the I and C that could potentially be safety significant are treated appropriately and at the same time not waste valuable resources on excessive protection against changes that have little or no impact on safety. The graded approach allows the design engineer to tailor the rigor of the preventive, limiting, and mitigative measures commensurately with the effects the I and C modification has on overall plant safety. The graded approach focuses on safety significance impact, which is effectively a qualitative measure of the potential change in safety (or risk) caused by a proposed I and C modification, as compared to the I and C that is being replaced. Safety significance impact should not be confused with importance to safety or risk significance. It is possible that an upgrade to safety-related and/or risk-significant I and C systems may have little or no safety significant impact and vice versa. The approach considers three factors that influence the impact on safety significance of a proposed I and C modification: context, likelihood of failure, and consequences of failure. The most significant of the three factors is context - what the I and C is connected to, both directly and indirectly, including its potential effects on plant systems that respond to transients or accidents. The graded approach is particularly helpful in assessing potential CCFs resulting from digital I and C failures, and shows why the most problematic CCFs will be those that can affect multiple plant systems. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Unveiling the High‐Voltage Reactivity and Gas Evolution With Aluminum‐Based Chloride and Oxychloride Catholytes in Solid‐State Sodium Batteries

All-solid-state sodium batteries (ASSBs) employing halide solid electrolytes (SEs) offer a cost-effective and energy-dense alternative to conventional liquid electrolyte systems. However, their high voltage (>4 V vs. Na/Na + ) performance remains limited by interfacial instability between the cathode active material (CAM) and the SE. We present here the electrochemical and interfacial behaviors of crystalline NaAlCl 4 and amorphous sodium–aluminum–oxychloride (NACO) SEs when combined with NaNi 0.5 Mn 0.5 O 2 cathode. While oxygen incorporation in NACO enhances ionic conductivity by nearly three orders of magnitude relative to NaAlCl 4 , it does not improve high-voltage cycling stability. Cells employing NACO exhibit accelerated capacity fade, increased cell impedance growth, and intrinsic oxygen evolution above 4.5 V vs. Na 3 Sn, as revealed by operando electrochemical mass spectrometry. In contrast, the NaAlCl 4 -based cells show no detectable gas release, underscoring their superior high-voltage stability and safety. Time-of-flight secondary-ion mass spectrometry confirms the formation of Al─O and Ni/Mn─Cl species, respectively, in the SE and CAM, indicating redox-driven anion exchange that contributes to kinetic hindrance of high-voltage phase transitions. The findings establish that while oxygen incorporation enhances ionic transport, it can compromise interfacial stability, suggesting pure chloride SEs may offer a more robust and intrinsically safer pathway for developing high-energy ASSBs.

25 ENERGY STORAGE↗

Thermal Hydraulics Safety Analyses of TRIGA Reactor Upon Fuel Reconfiguration

Safety analyses of the Training, Research, Isotope, General Atomics (TRIGA) reactor at Kansas State University(KSU) is performed using thermal hydraulic simulations based on changes to reactivity or the volumetric heat generation rate due to changes in the positioning of the enriched fuel elements in the reactor core. If the reactivity or neutronics parameters are known, then they can be used to simulate the thermal energy state of the material which is crucial to assess the safety of the nuclear fuel inside a nuclear reactor. Several thermal hydraulics models and codes have been developed in the past to assess reactor safety. RELAP (Reactor Excursion and Leak Analysis Program) is one such tool widely used throughout the world for safety analyses. Although RELAP is considered a reliable tool by regulators, vendors, and operators, it lacks the numerical fidelity provided by 3-D computational fluid dynamics (CFD) models. This work involves the critical task of assessing safety of a research reactor upon fuel reconfiguration based on models developed in RELAP and comparing them with a commercially available 3-D CFD program. The TRIGA Mark-II reactor, designed by General Atomics and located at Kansas State University, is a class of small pool type inherently safe research reactor licensed to operate at steady state power of up to 1.25 MW. It has a cylindrical core measuring 0.45 meters diametrically and 0.38 meters axially positioned in a tank measuring 1.98 meters diametrically and 6.25 meters axially. It has uranium zirconium hydride (UZrH) fuel rods housed in stainless steel cladding material arranged in five concentric rings (B,C,D,E and F rings, in that order, moving outwards from the center). TRIGA fuel is nominally 20% enriched, but the reactivity of the fuel can be changed by using burnable poisons (not used at KSU), or by varying the total weight percent of uranium in the UZrH fuel meat. The TRIGA reactor is designed to be an inherently safe reactor and is designed to be cooled by natural convection. Thus it is of paramount importance to avoid the film boiling regime; failing to do so will subject the fuel to severe conditions, possibly resulting in its failure due to fuel/clad interactions. A high DNBR ratio is a primary consideration in the reactor core design and thus any modification in the core should ensure that this criteria is always met. In order to fully utilize the capabilities of KSU TRIGA reactor facility, it should be operated at its full capacity, i.e. 1.25 MW, which requires increasing the fuel loading in some of the E- and F-ring elements from 8.5% U (nominal) to 12.0% U (nominal). Only four elements are to be switched to 12% loading, causing local power peaking in these elements. The degree of power peaking to be expected in these 12%-loaded fuel elements was calculated based on a detailed MCNP (Monte Carlo N-Particle code) model of the reactor core. Some preliminary results of the calculations are presented in this paper based on changes in peaking factors and power levels. To predict reactor thermal behavior, axial changes in the peaking factors obtained from MCNP models were used to calculate volumetric energy density functions for a single channel one dimensional RELAP model and a three dimensional COMSOL model of the TRIGA MARK-II reactor. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Superior metal storage behavior of Zn-containing porous carbon nanostructures for Na and Li metal batteries

Na and Li metals are ideal anodes for high-energy rechargeable batteries. However, their poor coulombic efficiency and the associated safety issues due to dendritic metal deposition and large volume changes during metallic plating/stripping are the major causes that persistently hinder their practical energy-storage applications. Herein, Zn-containing carbon nanostructures derived from typical zeolitic imidazolate framework-8 (ZIF-8) are proposed as advanced metal anode materials for both Na and Li metal batteries. In this study; the three-dimensional interconnected porous surfaces confine metallic Na and Li within the nanostructures, filling the carbon scaffold, and covering the electrode surface to form stable solid electrolyte interphases. Based on the metal nucleation and growth results obtained through various electrochemical tests, Zn incorporation and pore morphology have been revealed to be the key factors that regulate the metal nucleation and metallic plating/stripping during cycling. Thus, the incorporation of Zn in the closed pores of a carbon nanostructure improves the cycle performance, even in carbonate electrolytes, and produces stable Na and Li metallic anodes for next-generation rechargeable batteries.

25 ENERGY STORAGE↗

Feedback-Based Fault-Tolerant and Health-Adaptive Optimal Charging of Batteries

The key technology barriers that hinder the growth of Electric Vehicles (EVs) are long charging time, the shorter life-time of EV batteries, and battery safety. Specifically, EV charging protocols have significant effects on battery lifetime and safety. If not charged properly, the battery could end up with shorter life, and more importantly, improper charging can cause battery faults leading to catastrophic failures. To overcome these barriers, we propose a closed-loop feedback based approach, that enables real-time optimal fast charging protocol adaptation to battery health and possess active diagnostic capabilities in the sense that, during charging, it detects real-time faults and takes corrective action to mitigate such fault effects. We utilize battery electrical-thermal model, explicit battery capacity and power fade aging models, and thermal fault model to capture battery behavior. In conjunction with the models, we adopt linear quadratic optimal control techniques to realize the feedback-based control algorithm. Simulation studies are presented to illustrate the effectiveness of the proposed scheme.

batteries↗

Characterization of high thermal conductivity fuel surrogates before and after ion irradiation

High thermal conductivity nuclear fuels offer important potential advantages over traditional oxide-based fuels such as higher burnup, reduction in fission gas release, and better overall safety of the system. One proposed approach to high thermal conductivity fuels utilizes high thermal conductivity nonfissile additives with UO 2 fuel to lower the fuel operating temperature and thereby take advantage of the highly favorable radiation resistance of UO 2 at lower operating temperatures. However, differential swelling in the matrix and high conductivity additive phases during high dose irradiation could lead to internal cracking and poor performance. In the current study, ceria (CeO 2 ) and zirconia (ZrO 2 ) surrogate matrices were used to model UO2 behavior. Additives of 10 vol. % Al 2 O 3 or SiC in the form of short fibers or platelets were used for the high conductivity second phase. The nuclear fuel surrogates were sintered to achieve densities greater than 93% of the ideal values. Scanning electron microscopy (SEM) imaging and X-ray diffraction confirmed the uniform distribution of the second phase and that no intermetallic second phase was formed during sintering. The thermal conductivity of the sintered samples was measured from 50 °C to 900 °C and confirmed the desirable increase compared to pure CeO 2 /ZrO 2 pellets. Samples were irradiated with 20 MeV Ni 6+ ions at midrange doses ranging from 1 to 15 displacements per atom (dpa) and temperatures from 300 °C to 700 °C. Post irradiation characterization revealed a good stability of the samples at low to medium doses with matrix lattice parameter swelling of < 0.14 % but showed a significant microstructural deterioration and decrease of the mechanical properties at 15 dpa.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Lessons Learned—Fluoride Exposure and Response

Laboratory research can expose workers to a wide variety of chemical hazards. Researchers must not only take personal responsibility for their safety but also inevitably rely on coworkers to also work safely. The foundations for protocols, requirements, and behaviors come from our history and lessons learned from others. For that reason, here, a recent incident is examined in which a researcher suffered hydrofluoric acid (HF) burns while working with an inorganic digestion mixture of aqueous HF (8%) and nitric acid (HNO 3 , 58%). HF education is critical for workers because delays in treatment, improper treatment, and delay of symptoms are all factors in unfavorable outcomes in case reports. Furthermore, while the potential severity of the incident was elevated due to bypassed engineered controls and lack of proper personal protective equipment, only minor injuries were sustained. We discuss the results of a causal analysis of the incident that revealed areas of improvement in protocols, personal protective equipment, and emergency response that could help prevent similar accidents from occurring. We also present simple improvements that anyone can implement to reduce the potential consequences of an accident, based upon our lessons learned.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Surface Characterization of Nanoparticles: Critical Needs and Significant Challenges.

There is a growing recognition that nanoparticles and other nanostructured materials are sometimes inadequately characterized and that this may limit or even invalidate some of the conclusions regarding particle properties and behavior. A number of international organizations are working to establish the essential measurement requirements that enable adequate understanding of nanoparticle properties for both technological applications and for environmental health issues. Our research on the interaction of iron metal-core oxide-shell nanoparticles with environmental contaminants and studies of the behaviors of ceria nanoparticles, with a variety of medical, catalysis and energy applications, have highlighted a number of common nanoparticle characterization challenges that have not been fully recognized by parts of the research community. This short review outlines some of these characterization challenges based on our research observations and using other results reported in the literature. Issues highlighted include: 1) the importance of surfaces and surface characterization, 2) nanoparticles are often not created equal - subtle differences in synthesis and processing can have large impacts; 3) nanoparticles frequently change with time having lifetime implications for products and complicating understanding of health and safety impacts; 4) the high sensitivity of nanoparticles to their environment complicates characterization and applications in many ways; 5) nanoparticles are highly unstable and easily altered (damaged) during analysis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Scaling of thermal stratification in outlet plena of SFRs with gallium as a surrogate fluid

Due to its high thermal diffusivity, liquid sodium can develop thermally stratified regions in the hot and cold pools of SFRs under certain off normal operating conditions. The temperature gradients in the fluid give rise to mixed convection flow in which flow velocities result both from pressure gradients and from volume forces induced by density gradients. High thermal diffusivity and low momentum diffusivity leads to reduced thermal mixing and enhanced stratification. Thermal stratification, if not looked carefully in the design, can lead to severe consequences in normal operation with forced coolant circulation and during off-normal natural circulation. The resulting hydraulic and thermal loads can cause the failure modes in structures and components critical for reactor safety. Thermal stratification in the SFR pools can lead to thermal fatigue, which can lead to structural and material failure, or pose serious concerns for the reactor safety. In addition to thermo-structural issues, the reactivity changes are significantly impacted due to density or temperature driven movement of liquid sodium. Temperature changes or gradients in the Upper Instrumentation Structures (UIS) of SFRs can lead to thermal contraction, a case that can lead to positive reactivity insertion after core shut-down. The motivation of this work is to design a scaled down experimental facility which can generate high fidelity data for thermal stratification physics to validate 3-dimensional (3D) Computational Fluid Dynamics (CFD) models. These validated CFD codes can be used to improve the 1-dimensional (1D) system level codes such as SAS4A/SASSYS-1 which are currently not capable of simulating thermal stratification accurately. These improvements in 1D system level SAS4A/SASSYS-1 codes can significantly improve the safety analyses and design of SFRs. The GaTE facility outlet plenum model is designed based on physics based similarities. Thermal stratification physics is governed primarily by the Richardson numbers (Ri). The expected low flow rates during off-normal conditions can lead to a high degree of thermal stratification in the outlet plenum with a corresponding Ri = 530. Therefore, the inlet flow velocities and inlet hydraulic diameter for the gallium coolant entering the test vessel are required to achieve same Ri. The design of test vessel in GaTE facility is finalized to a 1/20. scale outlet plenum height of the ABTR. This design of the test facility will allow the decoupling of the thermal stratification physics at low flow rates with the transient natural circulation. In other words, it will enable effective control to study thermal stratification at very low flow rates. Numerical studies are conducted with a 3D CFD code to examine the thermal behavior of the selected test design. Simulation results show that thermal gradients are present only in the vertical or axial direction which are similar to the behavior reported in previous studies on full scale SFR models. Future work will involve the experimental studies using the GaTE facility with the high fidelity instrumentation.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

LOCA and LOFA Safety Margin Analysis for U-10Mo Monolithic LEU Fuel Conversion of the MURR{sup R} Reactor

The University of Missouri Research Reactor (MURR{sup R}) is a multi-disciplinary research and education facility providing a broad range of analytical and irradiation services to the research community and the commercial sector. The source of neutrons for the experimental facilities of MURR{sup R} is a compact 10 MW core fueled with highly-enriched uranium (HEU) fuel. The continued presence of HEU fuel in civilian installations such as research and test reactors poses a threat to national and international security. Therefore, most research and test reactors, both domestic and international, have started a program of conversion to the use of low-enriched uranium (LEU) fuel. MURR{sup R} is one of five U.S. high-performance research and test reactors (USHPRRs) that are actively collaborating with the U.S. National Nuclear Security Agency (NNSA) Office of Material Management and Minimization (M3) to develop a suitable LEU fuel replacement for the currently required HEU fuel. A new type of high-density LEU fuel based on an alloy of uranium and molybdenum is currently undergoing qualification testing, and is expected to allow the conversion of all USHPRRs. As a part of the LEU conversion of MURR{sup R}, an analysis of core behavior under a set of accident conditions for a core fueled with an LEU monolithic alloy of uranium and 10 wt% molybdenum (U-10Mo) has been conducted. This paper presents the newest results for the loss-of-coolant accidents (LOCAs) and loss-of-flow accidents (LOFAs). Other classes of accidents have also been investigated but were not included here. Namely, reactivity insertion accidents (RIAs), fuel failure during operations accidents (FFAs), and fuel handling accidents (FHAs)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Radiation Effects on High Thermal Conductivity Fuels (Final Scientific Report)

High thermal conductivity nuclear fuels offer important potential advantages over traditional oxide-based fuels such as higher burnup, reduction in fission gas release, and better overall safety of the reactor system. One interesting approach to high thermal conductivity fuels utilizes high thermal conductivity nonfissile additives to UO 2 fuel to lower the fuel operating temperature and thereby take advantage of the highly favorable radiation resistance of UO 2 at lower operating temperatures. However, differential swelling between the matrix and high conductivity additive phases during high dose irradiation could lead to internal cracking and poor performance. In the current study, ceria (CeO 2 ) and zirconia (ZrO 2 ) surrogate matrices were used to model UO 2 behavior. Al 2 O 3 or SiC in the form of nanoscale powder or platelets, respectively, were used for the high conductivity second phase. The nuclear fuel surrogates were sintered to achieve densities greater than 93% of the ideal values. Scanning electron microscopy (SEM) imaging and X-ray diffraction confirmed the uniform distribution of the second phase and that no intermetallic second phase was formed during sintering. The thermal conductivity of the sintered samples was measured from 50°C to 900°C and revealed an important increase compared to pure CeO2 and ZrO2 pellets. Samples were irradiated with 20 MeV Ni6+ ions at midrange doses ranging from 1 to 15 displacements per atom (dpa) and temperatures from 300°C to 700°C. Post irradiation characterization revealed a good stability of the samples at low to medium doses (1 to 5 dpa) but showed a significant microstructural deterioration and decrease of the mechanical properties at 15 dpa. Although microcracking is not observed at the interface between the matrix and high conductivity phase for any investigated irradiation condition, the strength degradation at 15 dpa suggests that these high thermal conductivity fuel forms may not be suitable for high burnup applications in current or proposed fission reactors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Runtime Monitoring for Unmanned Aerospace Systems with Neural Network Components

AI components (e.g., Deep Neural Networks) are increasingly used in unmanned Aerospace systems for safety-relevant applications. Rigorous Verification and Validation methods for such components are still in their infancy and thus, monitoring of the AI's behavior during runtime is essential. In this paper, we will present a runtime-monitoring architecture, which combines the advanced statistical analysis framework SYSAI (System Analysis using Statistical AI) with temporal and probabilistic runtime monitoring carried out by R2U2 (Realizable, Responsive, and Unobtrusive Unit). Learned statistical models of complex systems with AI components are produced by the SYSAI framework and provide detailed information to enable the R2U2 runtime monitor to efficiently perform advanced safety and performance checks in nominal and off-nominal conditions. We will present initial results of our tool set and architecture on a case study, a DNN-based autonomous centerline tracking system (ACT).

Yuning He↗

QMU as an Approach to Strengthening the Predictive Capabilities of Complex Models

Complex systems are made up of multiple interdependent parts, and the behavior of the entire system cannot always be directly inferred from the behavior of the individual parts. They are nonlinear and system responses are not necessarily additive. Examples of complex systems include energy, cyber and telecommunication infrastructures, human and animal social structures, and biological structures such as cells. To meet the goals of infrastructure development, maintenance, and protection for cyber-related complex systems, novel modeling and simulation technology is needed. Sandia has shown success using M&S in the nuclear weapons (NW) program. However, complex systems represent a significant challenge and relative departure from the classical M&S exercises, and many of the scientific and mathematical M&S processes must be re-envisioned. Specifically, in the NW program, requirements and acceptable margins for performance, resilience, and security are well-defined and given quantitatively from the start. The Quantification of Margins and Uncertainties (QMU) process helps to assess whether or not these safety, reliability and performance requirements have been met after a system has been developed. In this sense, QMU is used as a sort of check that requirements have been met once the development process is completed. In contrast, performance requirements and margins may not have been defined a priori for many complex systems, (i.e. the Internet, electrical distribution grids, etc.), particularly not in quantitative terms. This project addresses this fundamental difference by investigating the use of QMU at the start of the design process for complex systems. Three major tasks were completed. First, the characteristics of the cyber infrastructure problem were collected and considered in the context of QMU-based tools. Second, UQ methodologies for the quantification of model discrepancies were considered in the context of statistical models of cyber activity. Third, Bayesian methods for optimal testing in the QMU framework were developed. This completion of this project represent an increased understanding of how to apply and use the QMU process as a means for improving model predictions of the behavior of complex systems.

Gray, Genetha Anne↗

Damage Assessment of Creep Tested and Thermally Aged Metallic Alloys Using Acousto-Ultrasonics

In recent years emphasis has been placed on the early detection of material changes experienced in turbine powerplant components. During the scheduled overhaul of a turbine, the current techniques of examination of various hot section components aim to find flaws such as cracks, wear, and erosion, as well as excessive deformations. Thus far, these localized damage modes have been detected with satisfactory results. However, the techniques used to find these flaws provide no information on life until the flaws are actually detected. Major improvements in damage assessment, safety, as well as more accurate life prediction could be achieved if nondestructive evaluation (NDE) techniques could be utilized to sense material changes that occur prior to the localized defects mentioned. Because of elevated temperatures and excessive stresses, turbine components may experience creep behavior. As a result, it is desirable to monitor and access the current condition of such components. Research at the NASA Glenn Research Center involves developing and utilizing an NDE technique that discloses distributed material changes that occur prior to the localized damage detected by the current methods of inspection. In a recent study, creep processes in a nickel-base alloy were the life-limiting condition of interest, and the NDE technique was acousto-ultrasonics (AU). AU is an NDE technique that utilizes two ultrasonic transducers to interrogate the condition of a test specimen. The sending transducer introduces an ultrasonic pulse at a point on the surface of the specimen while a receiving transducer detects the signal after it has passed through the material. The goal of the method is to correlate certain parameters of the detected waveform to characteristics of the material between the two transducers. Here, the waveform parameter of interest is the attenuation due to internal damping for which information is being garnered from the frequency domain. The parameters utilized to indirectly quantify the attenuation are the ultrasonic decay rate as well as various moments of the frequency power spectrum. A new, user-friendly, graphical interface AU system was developed at NASA Glenn. This system is an all-inclusive, multifunction system that controls the sending and receiving ultrasonic transducers as well as all posttest signal analysis. The system's postprocessing software calculates the multiple parameters used to study the material of interest.

Gyekenyesi, Andrew L.↗