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DOE OSTI2014

Data-Driven Benchmarking of Building Energy Efficiency Utilizing Statistical Frontier Models

Frontier methods quantify the energy efficiency of buildings by forming an efficient frontier (best-practice technology) and by comparing all buildings against that frontier. Because energy consumption fluctuates over time, the efficiency scores are stochastic random variables. Existing applications of frontier methods in energy efficiency either treat efficiency scores as deterministic values or estimate their uncertainty by resampling from one set of measurements. Availability of smart meter data (repeated measurements of energy consumption of buildings) enables using actual data to estimate the uncertainty in efficiency scores. Additionally, existing applications assume a linear form for an efficient frontier; i.e.,they assume that the best-practice technology scales up and down proportionally with building characteristics. However, previous research shows that buildings are nonlinear systems. This paper proposes a statistical method called stochastic energy efficiency frontier (SEEF) to estimate a bias-corrected efficiency score and its confidence intervals from measured data. The paper proposes an algorithm to specify the functional form of the frontier, identify the probability distribution of the efficiency score of each building using measured data, and rank buildings based on their energy efficiency. To illustrate the power of SEEF, this paper presents the results from applying SEEF on a smart meter data set of 307 residential buildings in the United States. SEEF efficiency scores are used to rank individual buildings based on energy efficiency, to compare subpopulations of buildings, and to identify irregular behavior of buildings across different time-of-use periods. SEEF is an improvement to the energy-intensity method (comparing kWh/sq.ft.): whereas SEEF identifies efficient buildings across the entire spectrum of building sizes, the energy-intensity method showed bias toward smaller buildings. The results of this research are expected to assist researchers and practitioners compare and rank (i.e.,benchmark) buildings more robustly and over a wider range of building types and sizes. Eventually, doing so is expected to result in improved resource allocation in energy-efficiency programs.

Kavousian, A↗

DOE OSTI2015

Modeling of two-storey precast school building using Ruaumoko 2D program

The long-distant earthquake loading from Sumatra and Java Island had caused some slight damages to precast and reinforced concrete buildings in West Malaysia such as cracks on wall panels, columns and beams. Subsequently, the safety of existing precast concrete building is needed to be analyzed because these buildings were designed using BS 8110 which did not include the seismic loading in the design. Thus, this paper emphasizes on the seismic performance and dynamic behavior of precast school building constructed in Malaysia under three selected past earthquakes excitations ; El Centro 1940 North-South, El Centro East-West components and San Fernando 1971 using RUAUMOKO 2D program. This program is fully utilized by using prototype precast school model and dynamic non-linear time history analysis. From the results, it can be concluded that two-storey precast school building has experienced severe damage and partial collapse especially at beam-column joint under San Fernando and El Centro North-South Earthquake as its exceeds the allowable inter-storey drift and displacement as specified in Eurocode 8. The San Fernando earthquake has produced a massive destruction to the precast building under viscous damping, ξ = 5% and this building has generated maximum building displacement of 435mm, maximum building drift of 0.68% and maximum bending moment at 8458kNm.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2018

Center for Extended Magnetohydrodynamic Modeling (CEMM), Final Technical Report for UW-Madison Engineering Physics

The Center for Extended Magnetohydrodynamic Modeling (CEMM) focused on the further development, verification, validation, and application of two scientific computation programs, the NIMROD and M3D-C1 codes, for modeling macroscopic dynamics in magnetized plasma. Both NIMROD and M3D-C1 solve the mathematical equations that model two-fluid 3D magnetohydrodynamic (MHD). They are designed and optimized to be efficient and accurate for toroidal confinement physics calculations. The effort improved the fidelity of the physics models, the realism of the treatment of the surrounding vessel, coils, and other structures, the accuracy and efficiency of the algorithms, and the ability to scale calculations to thousands of processors in order to take advantage of leading-edge computers. The primary application areas of Resonant Magnetic Perturbations (RMP), Edge Harmonic Oscillations (EHO), Edge Localized Modes (ELMs), Disruption Studies, Sawteeth and Stationary States, and Kinetic MHD and Neoclassical Tearing Modes (NTM) are of concern for the international ITER experiment, which is under construction in France. The effort by the UW-Madison Engineering Physics component of CEMM improved the numerical methods in the NIMROD code with respect to modeling MHD interchange and two-fluid effects. It also improved the algorithm for solving large algebraic systems to enhance NIMROD's computational performance when running the code in parallel on increasing numbers of processor cores. The modeling efforts included a study of the nonlinear evolution of ballooning, and the findings were supported by analytical theory and computation. Numerical MHD modeling also examined the influences of two-fluid effects on ELMs and RMPs, where "two-fluid" refers to separation of electron dynamics from ion dynamics. Another related aspect considered the effects of a localized layer of electrical current density near the edge of the plasma confinement region. Two-fluid effects on resonant reconnecting instabilities were verified and applied to computations of sawtooth and drift-tearing dynamics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2018

AOI [3]: Smart Refractory Sensor Systems for Wireless Monitoring of Temperature, Health, and Degradation of Slagging Gasifiers

The objective of the work was to develop refractory “smart bricks”, which would contain embedded temperature, strain/stress, and spallation sensors throughout the volume of highchromia (-Cr 2 O 3 ) refractory brick. The proposed work included work to interconnect the sensors to the reactor exterior, where the sensor signals may be processed by low-power electronics and transmitted wirelessly to a central processing hub. The data processing and wireless transmitter hardware was specifically designed to be isolated (with low power consumption) and to be adaptable to future implementation of energy-harvesting strategies for extended life. Finally, the collected data was incorporated into a model to estimate refractory degradation, a technique that could help monitor the health of the refractory in real-time. The long-term goal of this program was to demonstrate high-temperature, wireless sensor arrays for in situ three-dimensional (3-D) refractory monitoring or mapping for slagging gasification systems. The research was in collaboration with HarbisonWalker International (HWI) Technology Center in West Mifflin, PA. HWI is a leading developer and manufacturer of ceramic refractory products for high-temperature applications. The work completed focused on the following areas: 1) Investigation of the chemical stability, microstructural evolution, grain growth kinetics, degree of homogeneity (quantitative image analysis), and electrical properties of refractory oxide-silicide composites at temperatures between 750-1450ºC; 2) Fabrication of silicide-alumina composite and oxide thermocouples and thermistor preforms and the development of techniques to embed them into high-chromia refractory bricks to form “smart bricks”; 3) Utilization of commercial off-the-shelf discrete components to prototype circuits for interfacing between smart brick sensors and the wireless sensor network. The prototypes were then used to design an integrated circuit for thermistor, thermocouple, and capacitive-based smart brick sensor interfacing; 4) Interfacing of the smart bricks with embedded sensors with wireless motes thus yielding a complete signal chain. This end-to-end data collection system was tested on a furnace heated to 1350°C; 5) Development of a slag penetration model and a nonlinear unknown input filter for the data from the embedded sensors for estimating temperature and extent of slag penetration.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

Approximating Trajectory Constraints With Machine Learning – Microgrid Islanding With Frequency Constraints

Here, we introduce deep earning aided constraint encoding to tackle the frequency-constraint microgrid scheduling problem. The nonlinear function between system operating condition and frequency nadir is approximated by using a neural network, which admits an exact mixed-integer formulation (MIP). This formulation is then integrated with the scheduling problem to encode the frequency constraint. With the stronger representation power of the neural network, the resulting commands can ensure adequate frequency response in a realistic setting in addition to islanding success. The proposed method is validated on a modified 33-node system. Successful islanding with a secure response is simulated under the scheduled commands using a detailed three-phase model in Simulink. The advantages of our model are particularly remarkable when the inertia emulation functions from wind turbine generators are considered.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2015

Light Water Reactor Sustainability Program Advanced Seismic Soil Structure Modeling

Risk calculations should focus on providing best estimate results, and associated insights, for evaluation and decision-making. Specifically, seismic probabilistic risk assessments (SPRAs) are intended to provide best estimates of the various combinations of structural and equipment failures that can lead to a seismic induced core damage event. However, in some instances the current SPRA approach has large uncertainties, and potentially masks other important events (for instance, it was not the seismic motions that caused the Fukushima core melt events, but the tsunami ingress into the facility). SPRA’s are performed by convolving the seismic hazard (this is the estimate of all likely damaging earthquakes at the site of interest) with the seismic fragility (the conditional probability of failure of a structure, system, or component given the occurrence of earthquake ground motion). In this calculation, there are three main pieces to seismic risk quantification, 1) seismic hazard and nuclear power plants (NPPs) response to the hazard, 2) fragility or capacity of structures, systems and components (SSC), and 3) systems analysis. Two areas where NLSSI effects may be important in SPRA calculations are, 1) when calculating in-structure response at the area of interest, and 2) calculation of seismic fragilities (current fragility calculations assume a lognormal distribution for probability of failure of components). Some important effects when using NLSSI in the SPRA calculation process include, 1) gapping and sliding, 2) inclined seismic waves coupled with gapping and sliding of foundations atop soil, 3) inclined seismic waves coupled with gapping and sliding of deeply embedded structures, 4) soil dilatancy, 5) soil liquefaction, 6) surface waves, 7) buoyancy, 8) concrete cracking and 9) seismic isolation The focus of the research task presented here-in is on implementation of NLSSI into the SPRA calculation process when calculating in-structure response at the area of interest. The specific nonlinear soil behavior included in the NLSSI calculation presented in this report is gapping and sliding. Other NLSSI effects are not included in the calculation. The results presented in this report document initial model runs in the linear and nonlinear analysis process. Final comparisons between traditional and advanced SPRA will be presented in the September 30th deliverable.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Size effects on thermo-mechanical performance of U-10Mo monolithic fuel plates

Monolithic fuel is a fuel form that is considered for the conversion of high performance research reactors. This plate-type fuel consists of a high density U-Mo fuel in monolithic form that is sandwiched between zirconium diffusion barriers, and encapsulated in an aluminum cladding. To date, large number of plates have been irradiated with satisfactory perforamce. The program is now moving into the qualification phase, a predecessor to the timely conversion of the target reactors. It must be shown that the fuel system meets the safety standards and performs well in reactor. The requirement to satisfactory irradiation performance under normal operating conditions is primarily demonstrated by a successful testing. Since each reactor employs distinct fuel plate geometries for various consideration with unique plate design features and attributes, a single “generic” plate geometry capturing all of the extremities is not achievable. Furthermore, testing all these geometric and irradiation parameters on a large size plate is not practical. Therefore, a smaller, “down-scaled” versions of fuel plates, are often employed for experimental purposes. This limitation consequently requires much more cautious performance evaluations, as thermal and mechanical response of a plate with certain geometry may not be representative for a plate with a different geometry. To investigate if plate size has any effects on irradiation performance, the plates with various geometric dimensions were parametrically evaluated. In particular, length and width of the plates were varied between the bounding values. Temperature, deformation, stress values were comparatively evaluated. The results have indicated that effects of geometric ratios and plate size variations in length and width directions are insignificant. However, wider plates could become more prone to a warping-type deformation, if there are nonlinearities.

42 ENGINEERING↗

DOE OSTI2019

Size effects on thermo-mechanical performance of U-10Mo monolithic fuel plates

42 ENGINEERING↗

DOE OSTI2023

MODELING A SPENT NUCLEAR FUEL CASK SEISMIC TEST

The US Department of Energy Spent Fuel and Waste Science and Technology (SFWST) program is planning to conduct a series of full-scale shake table tests to simulate hypothetical earthquake conditions and record the response of surrogate spent nuclear fuel (SNF) assemblies in a canister dry storage system mockup. The shake table motions will represent a range of hypothetical earthquake conditions at hypothetical locations in the continental US to generally define the range of mechanical loads that SNF can be expected to experience during extended dry storage periods. The earthquake conditions will represent seismic hazards in the 2,000-to-20,000-year return period range. The test will use instrumented pressurized water reactor fuel assemblies with surrogate mass inside the fuel rods instead of radioactive fuel pellets. Dummy assemblies with similar mass and dimensions to actual fuel assemblies will occupy the rest of the fuel assembly locations in a SNF canister that holds 32 fuel assemblies. The canister will be located inside a mockup vertical concrete cask. Instrumentation will record the motion of the major components of the complex dynamic system, and strain gauges will be used to record the cladding strain at select locations. Preparations for the test require modeling predictions to identify the range of response of the system and to help select specific earthquake cases to be simulated on the shake table from a large set of potential cases. This paper describes the pretest nonlinear finite element modeling efforts that have been completed to date, including cask system level modeling and fuel assembly modeling in LS-DYNA. The cask system level models are critical for anticipating sliding or tipping of an unanchored cask during the test. The fuel assembly model is needed to estimate the range of cladding strain response and fuel assembly structural response to be expected during the test and cladding strain measurements will be key metrics for model validation and the development of modeling best practices after the test is concluded.

Klymyshyn, Nicholas A.↗

DOE OSTI2018

Load Mitigation on Floating Offshore Wind Turbines with Advanced Controls and Tuned Mass Dampers

General Electric, the National Renewable Energy Laboratory (NREL), the University of Massachusetts Amherst (UMass), and Glosten have recently completed a US Department of Energy (DOE)-funded research program to study technologies for mitigating loads on floating offshore wind turbines through the use of advanced turbine controls and tuned mass dampers (TMDs). The analysis was based upon the Glosten PelaStar tension leg platform (TLP) with GE Haliade 150 turbine, a system developed in a previous front end engineering design (FEED) study funded by the Energy Technology Institute (ETI) in the UK. The platform was designed for the WaveHub wave energy research site, with a mean water depth of 59-m. Loads were analyzed by running time-domain simulations in four 50-year return period (50-YRP) ultimate load state (ULS) conditions and 77 fatigue load state (FLS) environmental conditions. In 50-YRP conditions advanced controls are not active. The influence of TMDs on ULS loads have been reported previously (Park et al. [2]). In FLS conditions advanced controls and TMDs afford dramatic reductions in fatigue damage, offering the potential of significant savings in tower structural requirements. Simulations in turbine idling conditions were run in OrcaFlex, and simulations in operating conditions were run in FAST. Simulations were run with a baseline turbine controller, representative of the current state of the art, and an advanced controller developed by NREL to use collective and individual blade pitch control to maintain rotor speed and reduce tower loads. UMass developed a number of TMD types, with varying system configurations, including passive nonlinear dampers and semi-actively controlled dampers with an inverse velocity groundhook control algorithm. Loads and accelerations in FLS conditions were evaluated on the basis of damage equivalent loads (DELs), and fatigue damage was computed by Miner's summations of stress cycles at the tower base. To study sensitivity to water depth, loads were analyzed at both the 59-m WaveHub depth and a more commercially realistic depth of 100 m. TMDs reduce fatigue damage at the tower-column interface flange by up to 52% in 59-m water depth and up to 28% in 100 m water depth. Advanced controls reduce fatigue damage at the tower-column flange by up to 22% in 59-m water depth and up to 40% in 100 m water depth. The most effective load-mitigation strategy is combining advanced controls with TMDs. This strategy affords a 71% reduction in fatigue damage in both 59-m and 100-m water depths.

17 WIND ENERGY↗

DOE OSTI2019

Redox transistors for neuromorphic computing

Efficiency bottlenecks inherent to conventional computing in executing neural algorithms have spurred the development of novel devices capable of “in-memory” computing. Commonly known as “memristors,” a variety of device concepts including conducting bridge, vacancy filament, phase change, and other types have been proposed as promising elements in artificial neural networks for executing inference and learning algorithms. In this article, we review the recent advances in memristor technology for neuromorphic computing and discuss strategies for addressing the most significant performance challenges, including nonlinearity, high read/write currents, and endurance. As an alternative to two-terminal memristors, we introduce the three-terminal electrochemical memory based on the redox transistor (RT), which uses a gate to tune the redox state of the channel. Decoupling the “read” and “write” operations using a third terminal and storage of information as a charge-compensated redox reaction in the bulk of the transistor enables high-density information storage. These properties enable low-energy operation without compromising analog performance and nonvolatility. Finally, we discuss the RT operating mechanisms using organic and inorganic materials, approaches for array integration, and prospects for achieving the device density and switching speeds necessary to make electrochemical memory competitive with established digital technology.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Novel, Middle and Long Wave Infrared Laser Sources For Accelerator Applications

The main accomplishment during Years 2020-2024 of the DOE Accelerator Stewardship Program is proof-of-principle demonstration of amplification of an ultrashort 10 µm seed pulse in a multiatmosphere CO 2 laser optically pumped by nanosecond pulses of either a ~4.3 µm Fe:ZnSe laser or a 2.8 µm electro-optically (EO) Q-switched Er: Laser. This has been accomplished at the UCLA Neptune Laboratory by using about 100 mJ, ~100 ns long pulses generated by the pump laser built for this purpose by the UAB team. Implementation of EO Q-switching regime in the solid-state Er:laser system made possible nanosecond synchronization between the pump pulse and the 0.5 ps seed pulse produced by a commercial Ti:sapphire laser based mid-IR OPA/DFG. The injection mode-locking regime realized in a compact Mult atmosphere 3 Hz CO 2 -He regenerative amplifier enabled generation of a train of ultrashort pulses separated by the cavity round-trip time of ~3.2 ns. The measured gain lifetime of ~1 µs at a total pressure of ~12-15 atm indicates that lifetime of the upper laser level is a critical limiting factor in designing high-pressure CO 2 amplifiers. A single picosecond 10 mm pulse with an energy 0.1-0.2 mJ was extracted from the amplifier’s cavity using an ultrafast Ge semiconductor switch whose reflectivity was photo-induced by a femtosecond 800 nm pulse. For direct amplification regime, nonlinear absorption in Ge at 10 mm at GW/cm 2 intensities limited the extracted energy. Therefore, the generated energy could be further increased by minimizing losses in the switch and optimizing the cavity mode size. Based on the obtained data in collaboration with BNL colleagues, we have designed a high-pressure CO 2 amplifier to be used as a preamplifier for the future experiments at the ATF BNL. The latter work is the subject of funding availability.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Bayesian Monte Carlo Evaluation of Imperfect (n, 233 U) Data and Model

Conventional nuclear data evaluation methods using generalized linear least squares make the following assumptions: prior and posterior probability distribution functions (PDFs) of all model parameters and data are normal (Gaussian); the linear approximation is sufficiently accurate to minimize the cost function (even for nonlinear models); the model (e.g., of neutron cross section) and experimental data (including covariance data) are without defect and prior PDFs of parameters and measured data are known perfectly. Neglect of covariance between model parameters and measured data in conventional evaluations contributes to imperfections. These assumptions are inherent to the generalized linear least squares minimization method commonly used for resolved resonance region neutron cross section evaluations but are often not justified due to the presence of non-normal PDFs, nonlinear models (e.g., R-matrix formalism), and inherent imperfections in data and models (e.g., imperfect covariance data). Here, these assumptions are removed in a mathematical framework of Bayes’ theorem, which is implemented using the Metropolis-Hastings Monte Carlo method. Most importantly, new parameters are introduced to parameterize discrepancies between the theoretical model and measured data to quantify judgement about discrepancies or imperfections in a reproducible manner. An evaluation of 233U in the eV region using the ENDF-B/VIII.0 library and transmission data (Guber et al.) is presented, and posterior parameters are compared to those obtained by conventional evaluation methods. This example illustrates the effects of removing the most harmful assumption: that of model-data perfection.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

A Hybrid AI/ML and Computational Mechanics Based Approach for Time-Series State and Fatigue Life Estimation of Nuclear Reactor Components

Environmental fatigue modeling is a complex problem due to multiple failure modes and their intermixing. The failure modes are function of various underlying causes in addition to the corrosive effect of reactor coolant environment. Some of the major causes are time-dependence of material associated with cyclic loading, load sequence effect associated with random/variable amplitude loading, effect of strain amplitude and rates, effect of varying temperature (along both temporal and spatial directions) and the effect of mean strain and stress. The nonlinear intermixing of failure modes associated with above mentioned causing parameters makes the environmental fatigue modeling is a challenging task. Because of this challenge, fatigue is traditionally being modeled based on experimental data. However, test based empirical approach often requires hundreds of fatigue tests to model the above-mentioned intermixing failure causes even for a single material system. The problem is further exaggerated for reactor component made from multi-material systems such as made from both carbon and stainless-steel base metals and their similar and dissimilar metal welds. With the difficulty of conducting hundreds of fatigue tests to capture the above-mentioned intermixing failure causes, fatigue modeling approaches often depends on empirical models based on limited available test data such as available through ASME code and NUREG 6909. However, these limited test-data-based models may not be enough to accurately predict the life of reactor components. Accurate prediction of life of reactor component would become a necessity, particularly when the license of the reactors to be extended for long-term-operation (LTO) that is for well beyond its original design life of 40 years. The requirement of extending the license of reactor under LTO requires hundreds of fatigue tests to be conducted to understand the mechanism associated with the above-mentioned interdependent failure causes. However, conducting large number of fatigue tests is not a feasibility due to the cost involved. To address this issues Argonne National Laboratory (ANL) with the sponsorship of DOE Light Water Reactor Sustainability (LWRS) program trying to develop a hybrid predictive modeling approach. This is based on limited experiment-data, Artificial-intelligence (AI) – Machine-Learning (ML) - Deep-Learning (DL) based techniques and Multiphysics-computational-mechanics based modeling tools. The hybrid approach not-only can improve the accuracy of the existing stress analysis and fatigue modeling approach but also can reduce the over-dependency on test-based approach. Towards this goal following are some of the major contributions based on ANL’s FY-20 environmental fatigue modeling activities: 1) A cyclic plasticity material model database for 82/182 dissimilar metal weld, which can be readily shared with US nuclear industry and regulatory agency on request. 2) A well validated analytical modeling methodology to perform cycle-by-cycle stress prediction under both constant amplitude fatigue loading and variable amplitude fatigue loading (with load-sequence effect). 3) An AI/ML/DL based methodology to predict unmeasurable cyclic strain based on other available sensor signals. This type of approach can be used for estimating strain in real reactor components from other sensor readings. 4) An AI/ML based approach to improve the US capability on environmental fatigue testing. This is by improving ANL’s existing environmental fatigue testing capacity to conduct ASME required strain-controlled tests (by controlling strain amplitudes and its rate), while not measuring the strain (due to the difficulty of placing an extensometer in a narrow autoclave in a PWR-water-test system). 5) A simulation and experiment based probabilistic modeling methodology for time-series fatigue state and life estimation of reactor metal such as dissimilar metal weld.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2011

Near Field Modeling Of Spe1 Experiment And Prediction Of The Second Source Physics Experiments (SPE2)

Motion along joints and fractures in the rock has been proposed as one of the sources of near-source shear wave generation, and demonstrating the validity of this hypothesis is a focal scientific objective of the source physics experimental campaign in the Climax Stock granitic outcrop. A modeling effort has been undertaken by LLNL to complement the experimental campaign, and over the long term provide a validated computation capability for the nuclear explosion monitoring community. The approach involves performing the near-field nonlinear modeling with hydrodynamic codes (e.g., GEODYN, GEODYN-L), and the far-field seismic propagation with an elastic wave propagation code (e.g., WPP). the codes will be coupled together to provide a comprehensive source-to-sensor modeling capability. The technical approach involves pre-test predictions of each of the SPE experiments using their state of the art modeling capabilities, followed by code improvements to alleviate deficiencies identified in the pre-test predictions. This spiral development cycle wherein simulations are used to guide experimental design and the data from the experiment used to improve the models is the most effective approach to enable a transition from the descriptive phenomenological models in current use to the predictive, hybrid physics models needed for a science-based modeling capability for nuclear explosion monitoring. The objective of this report is to describe initial results of non-linear motion predictions of the first two SPE shots in the Climax Stock: a 220-lb shot at a depth of 180 ft (SPE No.1), and a 2570-lb shot at a depth of 150 ft (SPE No.2). The simulations were performed using the LLNL ensemble granite model, a model developed to match velocity and displacement attenuation from HARDHAT, PILE DRIVER, and SHOAL, as well as Russian and French nuclear test data in granitic rocks. This model represents the state of the art modeling capabilities as they existed when the SPE campaign was launched in 2010, and the simulation results presented here will establish a baseline that will be used for gauging progress as planned modeling improvements are implemented during the remainder of the SPE program. The initial simulations were performed under 2D axisymmetric conditions assuming the geologic medium to be a homogeneous half space. However, logging data obtained from the emplacement hole reveal two major faults that intersect the borehole at two different depth intervals (NSTec report, 2011) and four major joint sets. To evaluate the effect of these discrete structures on the wave forms generated they have performed 2D and 3D analysis with a Lagrangian hydrocode, GEODYN-L that shares the same material models with GEODYN but can explicitly take joints and fault into consideration. They discuss results obtained using these two different approaches in this report.

58 GEOSCIENCES↗

DOE OSTI2014

Redwing: A MOOSE application for coupling MPACT and BISON

Fuel performance and whole core neutron transport programs are often used to analyze fuel behavior as it is depleted in a reactor. For fuel performance programs, internal models provide the local intra-pin power density, fast neutron flux, burnup, and fission rate density, which are needed for a fuel performance analysis. The fuel performance internal models have a number of limitations. These include effects on the intra-pin power distribution by nearby assembly elements, such as water channels and control rods, and the further limitation of applicability to a specified fuel type such as low enriched UO2. In addition, whole core neutron transport codes need an accurate intra-pin temperature distribution in order to calculate neutron cross sections. Fuel performance simulations are able to model the intra-pin fuel displacement as the fuel expands and densifies. These displacements must be accurately modeled in order to capture the eventual mechanical contact of the fuel and the clad; the correct radial gap width is needed for an accurate calculation of the temperature distribution of the fuel rod. Redwing is a MOOSE-based application that enables coupling between MPACT and BISON for transport and fuel performance coupling. MPACT is a 3D neutron transport and reactor core simulator based on the method of characteristics (MOC). The development of MPACT began at the University of Michigan (UM) and now is under the joint development of ORNL and UM as part of the DOE CASL Simulation Hub. MPACT is able to model the effects of local assembly elements and is able calculate intra-pin quantities such as the local power density on a volumetric mesh for any fuel type. BISON is a fuel performance application of Multi-physics Object Oriented Simulation Environment (MOOSE), which is under development at Idaho National Laboratory. BISON is able to solve the nonlinearly coupled mechanical deformation and heat transfer finite element equations that model a fuel element as it is depleted in a nuclear reactor. Redwing couples BISON and MPACT in a single application. Redwing maps and transfers the individual intra-pin quantities such as fission rate density, power density, and fast neutron flux from the MPACT volumetric mesh to the individual BISON finite element meshes. For a two-way coupling Redwing maps and transfers the individual pin temperature field and axially dependent coolant densities from the BISON mesh to the MPACT volumetric mesh. Details of the mapping are given. Redwing advances the simulation with the MPACT solution for each depletion time step and then advances the multiple BISON simulations for fuel performance calculations. Sub-cycle advancement can be applied to the individual BISON simulations and allows multiple time steps to be applied to the fuel performance simulations. Currently, only loose coupling where data from a previous time step is applied to the current time step is performed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

RTN-056: Study of the Photon Transfer Curve in the CCD detectors of the Vera C. Rubin Observatory

The RECA internship program provides Colombian students with an opportunity to enhance their research skills in Astronomy, Astrophysics, and Cosmology. During this three-month program, our main objective was to study the Photon Transfer Curves (PTC) of the Vera C. Rubin Observatory, specifically the gain, and to compare it with the gain obtained through pairs of flats. Overall, the study of PTCs is crucial in understanding the performance of detectors and instruments used in Astronomy. The Vera C. Rubin Observatory is an important facility that will enable researchers to carry out a wide range of studies in this field, making it essential to investigate its gain performance. We used run 13144 to construct the PTCs and 13186 to analyze the crosstalk. We employed the LSST Science Pipelines (also known as the DM stack), a software under development for this observatory, which performs all the necessary reductions for the construction of the PTCs. We also used simulations to replicate the observed effects. Initially, we found a 5% difference between the gain calculated by PTC and pairs of flats for a flow range between 5000 and 10000 ADU. Simulations showed that this difference was due to the handling of statistics and the assumption that the distribution following the Lupton equation is Gaussian. We found an error interval for this flow region based on the vendor, with (1.8 ± 0.7, 4.1 ± 0.9) % for E2V and (0.85 ± 0.7, 2.2 ± 0.9) % for ITL. From the PTC, we also obtained the average Full Well Capacity of LSSTCam as 130000 ± 10000$ electrons. We identified a list of segments where we found differences with the results obtained by SLAC National Acceleration Laboratory in PTC parameters, low saturation level, or other defects. We detected and corrected the effect of statistics in the gain calculation using pairs of flats and proposed a code change, which was implemented in the pipeline software. We do not recommend correcting for crosstalk as it does not significantly affect the parameters and does not change the shape of the PTC. However, the opposite is true for the nonlinearity correction.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2018

Embedded Sensors and Controls to Improve Component Performance and Reliability - Final Report

Oak Ridge National Laboratory has researched embedded instrumentation and controls (I&C) for extreme environments under the Department of Energy, Office of Nuclear Energy's Nuclear Energy Enabling Technology program. Advanced sensors and controls have the potential to dramatically increase the performance and efficiency of nuclear reactor components, however, the extreme environments of exiting and advanced reactor designs limit the options for sensors, actuators, and control designs. To address two of the extreme environment challenges to embedded I&C, the focus of this research is to fill technology gaps needed for electromagnetic systems that can operate at temperatures greater than 700 C in corrosive environments. A magnetically suspended, canned-rotor pump was chosen for the embedded I&C development platform because it is a system with a practical need in industry and because the sensors, actuators, and embedded I&C technologies needed to successfully build this platform will be widely applicable to any high-temperature components that utilize electromagnetic interactions. This design also eliminates the need for pump seals and mechanical bearings which are the main sources of pump failures and maintenance costs. During the project a conceptual design for the high-temperature magnetically suspended pump was developed and analyzed for manufacturability and reliability. Specifications for the materials, control system, sensors, mechanical performance, high-temperature wiring, and electromagnetic properties were developed for the conceptual design. The canned rotor design of the high-temperature pump presents unique fluid force characteristics arising from the thin fluid channel between the rotor and stator. A model of the fluid forces was developed and the impact of these forces on the stability and performance of magnetic bearing controllers was studied. Then a room temperature bench-scale magnetic testbed was designed and fabricated for testing the performance of sensors and electromagnetic actuators, modern control design techniques, closed-loop system identification, state estimation, and model uncertainty. Finally, a loop-scale testbed with submerged magnetic bearings was designed and fabricated. This testbed will be used to analyze the stability and performance of control system designs in response to the nonlinear and cross-coupling fluid effects between the shaft axes of motion, rotordynamics, gyroscopic effects, and impeller disturbances.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗