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DOE OSTI2016

Neutron Detector Signal Processing to Calculate the Effective Neutron Multiplication Factor of Subcritical Assemblies

This report describes different methodologies to calculate the effective neutron multiplication factor of subcritical assemblies by processing the neutron detector signals using MATLAB scripts. The subcritical assembly can be driven either by a spontaneous fission neutron source (e.g. californium) or by a neutron source generated from the interactions of accelerated particles with target materials. In the latter case, when the particle accelerator operates in a pulsed mode, the signals are typically stored into two files. One file contains the time when neutron reactions occur and the other contains the times when the neutron pulses start. In both files, the time is given by an integer representing the number of time bins since the start of the counting. These signal files are used to construct the neutron count distribution from a single neutron pulse. The built-in functions of MATLAB are used to calculate the effective neutron multiplication factor through the application of the prompt decay fitting or the area method to the neutron count distribution. If the subcritical assembly is driven by a spontaneous fission neutron source, then the effective multiplication factor can be evaluated either using the prompt neutron decay constant obtained from Rossi or Feynman distributions or the Modified Source Multiplication (MSM) method.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2016

NSR&D Program Fiscal Year 2015 Funded Research Stochastic Modeling of Radioactive Material Releases Final Report

Nonreactor nuclear facilities operating under the approval authority of the U.S. Department of Energy use unmitigated hazard evaluations to determine if potential radiological doses associated with design basis events challenge or exceed dose evaluation guidelines. Unmitigated design basis events that sufficiently challenge dose evaluation guidelines or exceed the guidelines for members of the public or workers, merit selection of safety structures, systems, or components or other controls to prevent or mitigate the hazard. Idaho State University, in collaboration with Idaho National Laboratory, has developed a portable and simple to use software application called SODA (Stochastic Objective Decision-Aide) that stochastically calculates the radiation dose distribution associated with hypothetical radiological material release scenarios. Rather than producing a point estimate of the dose, SODA produces a dose distribution result to allow a deeper understanding of the dose potential. SODA allows users to select the distribution type and parameter values for all of the input variables used to perform the dose calculation. Users can also specify custom distributions through a user defined distribution option. SODA then randomly samples each distribution input variable and calculates the overall resulting dose distribution. In cases where an input variable distribution is unknown, a traditional single point value can be used. SODA, developed using the MATLAB coding framework, has a graphical user interface and can be installed on both Windows and Mac computers. SODA is a standalone software application and does not require MATLAB to function. SODA provides improved risk understanding leading to better informed decision making associated with establishing nuclear facility material-at-risk limits and safety structure, system, or component selection. It is important to note that SODA does not replace or compete with codes such as MACCS or RSAC; rather it is viewed as an easy to use supplemental tool to help improve risk understanding and support better informed decisions. The SODA development project was funded through a grant from the DOE Nuclear Safety Research and Development Program.

42 ENGINEERING↗

DOE OSTI2018

Extracting the Data From the LCM vk4 Formatted Output File

These are slides about extracting the data from the LCM vk4 formatted output file. The following is covered: vk4 file produced by Keyence VK Software, custom analysis, no off the shelf way to read the file, reading the binary data in a vk4 file, various offsets in decimal lines, finding the height image data, directly in MATLAB, binary output beginning of height image data, color image information, color image binary data, color image decimal and binary data, MATLAB code to read vk4 file (choose a file, read the file, compute offsets, read optical image, laser optical image, read and compute laser intensity image, read height image, timing, display height image, display laser intensity image, display RGB laser optical images, display RGB optical images, display beginning data and save images to workspace, gamma correction subroutine), reading intensity form the vk4 file, linear in the low range, linear in the high range, gamma correction for vk4 files, computing the gamma intensity correction, observations.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2018

SE 296 Capstone Project Proposal for Katelyn Yeamans UCSD Fall 2018

This project shall be a comprehensive evaluation in the changes in the physical attributes of PETN pellets when stored for prolonged periods under typical storage conditions. The scope of this project is intended to meet the Capstone Project requirements of the UCSD Structural Engineering Master’s Degree and provide useful insight for pellet production and processing. The intended result is a summary report and an accompanying MATLAB program file. The duration of this investigation is not to exceed twelve weeks. If the project cannot be completed within the given time frame,report documentation shall consist of progress-to-date and recommended future work summary and a to a progress-to-date version of the MATLAB file.

36 MATERIALS SCIENCE↗

DOE OSTI2021

All Optical Neural Networks for Low Power Edge Computing

We developed a simplistic physics-based model of an all-optical neural network that mimics the encoder part of an autoencoder neural network for image compression. Our approach relies on the generation of a MATLAB-based model for both data compression and decompression and utilizes MATLAB's built-in autoencoder networks in combination with simple propagation of optical fields between layers constituting phase elements via Fourier transform. We optimize the phase elements using the particle swarm optimization technique and using our model, we demonstrate a compression ratio of 25% for 2828-pixel input images containing numeric digits from 0 to 9.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Simulink Modeling and Dynamic Study of Fixed-Speed, Variable-Speed, and Ternary Pumped Storage Hydropower

Pumped Storage Hydropower (PSH) is one of the most popular energy storage technologies in the world. It uses an upper reservoir to store water which can be later used during high-demand. In the United States, most of the energy storage capability actually corresponds to PSH. Moreover, PSH also brings multiple benefits to grid operation. This report presents the Simulink models of three common PSH technologies: Fixed-Speed (FS), Variable-Speed (VS), and Ternary (T)-PSH. These models are available to the general public on this GitHub repository, which contains the MATLAB model initialization files, the Simulink model files, and supplementary MATLAB code used to obtain the figures in this work. For each PSH model, an introductory description of the model components and other relevant functionalities are provided. For further information regarding the models and the initialization parameters, the reader is referred to the shared files in the repository. This report also presents the dynamic behavior of each model. The response of such models to a load event is analyzed and matched with each model's features. A custom IEEE 39 bus case is employed for the FS and T-PSH simulations, while the VS-PSH is simulated on a simplified three-bus test system due to the computational complexity of the model. For the T-PSH, the steady-state and the switching between several operating modes are also studied in this work.

13 HYDRO ENERGY↗

DOE OSTI2022

Progress Report on Model Development for the Transport of Aerosol through Microchannels

This report summarizes the current progress in the development of a phenomenological model of aerosol transport, deposition, and plugging through microchannels. The purpose is to introduce a generic, reliable numerical model for the prediction of aerosol transport, deposition, and plugging in leak paths while accounting for potential plugging formation, to a user community involving researchers, regulators, and industry. In that regard, a Graphical User Interface (GUI) was generated by integrating the individual MATLAB scripts that make up the model and adding additional features to aid the general understanding of the problem to a user. This report focuses on the model development and features included. Further, predictions from the GUI are compared with experimental data for validation. The strength of the GUI is the ability of a user to plug in basic parameters such as the initial pressure conditions and canister model specifications in order to obtain a first principal approximation of vital information such as the blowdown pressure differential, aerosol penetration, and deposition as a function of time. The user can obtain this without the know-how of the underlying MATLAB scripts and thus enables the model to be readily applied by regulators, industry, and shareholders to reduce the uncertainty in the off-site radiological consequences. The report also lists future tasks under this work scope. This includes ongoing efforts to include additional crack geometries (divergent and divergent-convergent slots) to the model; GUI development and improvement based on feedback from users, and integration of aerosol source term data from Sibling Pin tests into the model as we approach realistic canister stress corrosion cracking–induced aerosol release scenarios.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Internship Work Report

I worked on two projects during my summer internship at Sandia. My official title was “Intern - Mission Tech Electrical Eng./Computer Eng.- R&D Undergraduate Summer.” I worked at the central location, which is Albuquerque, New Mexico. The department you are placed in at Sandia doesn’t always correspond to the people you will be working with. For example, I only directly worked with one person from my department this summer. On one of my projects, I worked with a diverse team of engineers from many different departments. On my other project, I mainly worked with two departments, as the project had two distinct parts. As mentioned earlier, I worked on two projects during my summer at Sandia. The first project focused on a lightweight embedded controller in an advanced FPGA System-on-Chip for radar signal processing applications. The term “controller” refers to a hardware device that directs the flow of data between two entities. An FPGA is a reprogrammable integrated circuit (as opposed to an integrated circuit with one purpose). An FPGA was used on this project so in order to protype various ideas for our System-on-Chip. My role on the project was to implement designs on the fabric of the FPGA and design a state machine (written in C) for the processor. My second project was also heavily involved with embedded systems but had a different application. It focused on using a Newton-Raphson control algorithm to stabilize an inverted pendulum using a novel microcontroller. The pendulum dynamics were derived, and it was successfully simulated in MATLAB. I worked on integrating the microcontroller with the inverted pendulum machinery, and converting the Newton-Raphson control algorithm from MATLAB into C. The inverted pendulum was successfully stabilized using a simple PID controller and industry-standard microcontroller. The project is still ongoing, and the team is gearing up for more tests using the novel Newton-Raphson control algorithm and novel microcontroller

42 ENGINEERING↗

DOE OSTI2024

Integrate Latimer Controls' Solution into RTAC (CRADA Final Report, CRD-23-24672)

Latimer Controls, Inc. was awarded two vouchers under the Department of Energy's American-Made Solar Prize Round 6 to conduct collaborative research at a national laboratory. The National Renewable Energy Laboratory (NREL) was selected as a partner to assist Latimer Controls in the performance evaluation of its photovoltaic (PV) control software. This collaboration focuses on developing a hardware-in-the-loop (HIL) testbed at NREL, which will be used to test and validate the Latimer PV control technology in a realistic yet de-risked environment. Both Latimer and NREL teams will work together to analyze the collected test data, derive insights, and disseminate the scientific findings. Recent studies underscore the potential of solar energy as a zero-marginal-cost and zero-emission flexibility resource within the bulk power system, particularly when integrated with advanced control systems. To enhance the performance of such systems, Latimer Controls has developed leading-edge technologies, including machine learning (ML) algorithms and hierarchical inverter set-point allocation methods. These innovations are designed to estimate the operational headroom of large PV plants for grid integration and control. However, comprehensive validation under real-world conditions remains necessary. To address this gap, the concurrent CRADA project proposes the real-world application and validation of the Latimer Control solution within a HIL environment. Initially, the Latimer algorithm was developed and tested within MATLAB Simulink, a platform suitable for research-level simulations and iterative development. However, transitioning this technology to a real solar site as an industry-ready solution necessitates implementation in a format compatible with widely used solar power plant controllers. In this additional CRADA work, the MATLAB Simulink-based logic will be translated into Structured Text, a programming language compliant with IEC 61131 standards, which is commonly used for custom logic implementations in industry-leading programmable logic controllers (PLCs), such as the Schweitzer SEL real-time automation controller (RTAC). This transition will facilitate the deployment of the Latimer Control solution in real-world solar power plants, thereby advancing the technology towards commercialization.

14 SOLAR ENERGY↗

DOE OSTI2022

Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series: Supporting Data

This dataset consists of soil temperature time series that were used to estimate soil thermal diffusivity and its uncertainty trough the probabilistic modelling approach developed and presented in the article named "Probabilistic estimation of depth-resolved profiles of soil thermal diffusivity from temperature time series" and published in Earth Surface Dynamics. There are two compressed (.zip) files that contains synthetic (Synthetic_soiltemp_Teller.zip) and field (Field_soiltemp_Teller.zip) data. There is one MATLAB file that requires MATLAB to execute but any text editor can open it. The Synthetic_soiltemp_Teller.zip file includes 5 comma-delimited data files (.csv) each of which contains soil temperature time series generated through forward modeling (i.e., heat-conduction process in a heterogeneous medium using an explicit finite difference method) to mimic various types of temperature gradients, trend and fluctuations. These synthetic soil temperatures were used to investigate the impact of different environmental conditions on the uncertainty of thermal diffusivity estimates. The Field_soiltemp_Teller.zip file contains 28 comma-delimited data files (.csv) out of which (a) 27 files includes soil temperature time series recorded from 27 temperature probes located in a site along Teller Road about 40 km northwest of Nome, Alaska (64.72°N, 165.94°W), (b) one includes the name and coordinates of the 27 probes. These field soil temperatures were used to infer soil thermal diffusivity at numerous locations and depths in a discontinuous permafrost environment, and to evaluate the links between the estimated soil thermal diffusivity values and soil physical properties. The comma-delimited data files (.csv) of the synthetic and field soil temperature time series includes date and time (UTC) in the first column and soil temperature from 5 cm below the ground surface to 1.05 m depth (with 5 or 10 cm spacing between sensors) in the other columns. The measurements were acquired every 15 minutes. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Maps of ice wedge thermokarst pool expansion from twenty-seven circumpolar survey areas

This repository includes data and code to accompany the manuscript 'Topography controls variability in circumpolar permafrost thaw pond expansion' by Abolt et al. The data include satellite imagery and derived maps of thermokarst pools from twenty-seven survey areas in North America and Siberia. The code, written in MATLAB (R2021a), contains demonstrations of the workflow for generating the maps. The demonstrations include training a generalized UNet for mapping thermokarst pools using data from three survey areas, 'fine tuning' the UNet for use at a specific survey area using transfer learning, applying a trained UNet to infer thermokarst pool extent within satellite imagery, and performing histogram matching as a pre-processing step to improve satellite imagery contrast. Contains MATLAB script files and M files, TIF files, shape files, XML, Excel, TXT, and CSV files.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Spherical nanoindentation stress-strain analysis, Version 1

Nanoindentation is a tool that allows the mechanical response of a variety of materials at the nano to micron length scale to be measured. Recent advances in spherical nanoindentation techniques have allowed for a more reliable and meaningful characterization of the mechanical response from nanoindentation experiments in the form on an indentation stress-strain curve. This code base, Spin, is written in MATLAB (The Mathworks, Inc.) and based on the analysis protocols developed by S.R. Kalidindi and S. Pathak [1, 2]. The inputs include the displacement, load, harmonic contact stiffness, harmonic displacement, and harmonic load from spherical nanoindentation tests in the form of an Excel (Microsoft) spreadsheet. The outputs include indentation stress-strain curves and indentation properties as well their variance due to the uncertainty of the zero-point correction in the form of MATLAB data (.mat) and figures (.png). [1] S. Pathak, S.R. Kalidindi. Spherical nanoindentation stress–strain curves, Mater. Sci. Eng R-Rep 91 (2015). [2] S.R. Kalidindi, S. Pathak. Determination of the effective zero-point and the extraction of spherical nanoindentation stress-strain curves, Acta Materialia 56 (2008) 3523-3532.

Weaver, Jordan S.↗

DOE OSTI2016

Kinetic Monte Carlo Simulation of Hydrogen Diffusion in Tungsten

Nuclear fusion is considered as the most promising sustainable energy source. If achieved, it could provide electricity to the mankind for millions of years. During the reaction, the fusion ash is continuously removed from the magnetic gap, the divertor region, and the divertor facing component is subjected to intense plasma bombardment. It is proposed to use tungsten as the divertor facing material, because it has low physical sputtering yield and superior thermomechanical properties. However, the high mobility of hydrogen in tungsten and the high bombardment flux bring the hydrogen isotopes deep into the tungsten tile. The presence of hydrogen in tungsten tends to weaken the gram boundaries and produce surface blistering. The ejection of tungsten particulates into the plasma core will cool the reaction and cease the fusion reactions. Therefore, it is important to have a detailed understanding of the hydrogen diffusion in tungsten bulk. The KMC method is a stochastic computer simulation to predict the time evolution of a certain system. Typically, at a given time, the system will evolve through a few possible paths with known probabilities. In each step, the KMC method analyzes the entire system and randomly determines the system evolving events based on all transition rates of all possible events and advance the physical time. This process is repeated till the simulation of the entire physical time is completed. In previous work, the authors developed a kinetic Monte Carlo (KMC) algorithm and program to simulate hydrogen diffusion process on tungsten reconstructed surface. In this article, this KMC method is extended to model the hydrogen diffusion in tungsten bulk. The diffusion coefficients are calculated and fitted to the Arrhenius equation. The result matches the experiment measurement very well. KMC diffusion simulation needs the locations of the hydrogen trapping sites, diffusion paths and the corresponding diffusion energy barriers. The hydrogen interstitial sites in tungsten crystal have been thoroughly studied by density function theory (DFT) and molecular dynamics (MD). Johnson and Carter used DFT to determine the preferred location of the hydrogen interstitial sites m tungsten crystal, which are the tetrahedral sites (T-sites) in body-centered-cubic (bcc) lattice surfaces. All T-sites are located on the surfaces of a lattice cell. There are four T-sites per surface and twelve T-sites per lattice cell. The hydrogen atoms diffuse by traveling from one T-site to one of its nearest four T-site neighbors. Thus, each T-site is surrounded by two neighbors on the same surface, and one neighbor on each of the two adjacent surfaces perpendicular to the surface holding the center T-site. The diffusion barrier between two neighboring T-sites was calculated to be 0.38 eV. Knowing the diffusion path, energy barrier, and the crystal structure, the KMC simulation is readily to be performed. Based on other researchers' DFT calculations, the hydrogen stable interstitial site in tungsten bulk is determined as the tetrahedral site on the surface of the bee lattice. Each T-site has 4 neighbors and the energy barrier between two adjacent T-sites are estimated to be 0.38 eV. Based on those facts and the KMC theory, a MATLAB program is developed to model the hydrogen diffusion in tungsten bulk. In the MATLAB program, substrate temperature, hydrogen concentration, physical time to be simulated, and the number of cycles are all customizable. To compare the KMC determined diffusion coefficients with experiment results in the literature, the simulations are performed for temperature 300 K - 2500 K and low hydrogen concentration (0.1%), mimicking the experiment condition. The calculated diffusion coefficients match the reference values measured by the experiment under low hydrogen concentration condition. The results are also fitted to the Arrhenius equation. The pre-exponential factor and the average activation energy in Arrhenius equation are obtained. The good agreement between simulation and experiment proves that the developed KMC algorithm truly reflect the well-established theory of interstitial hydrogens in tungsten. The developed program could easily be used to model the diffusion process and predict the diffusion coefficients under other concentrations and temperatures. This work is part of the ongoing development of hydrogen diffusion in tungsten integrating surface diffusion (previous work), bulk diffusion (this work), and adsorption/desorption on surface (future work)

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2016

Nitride Fuel Potential for Power Uprates

This work presents the methodology and current results for design analysis of grid supported pressurized water reactor cores using uranium nitride (UN) fuel in square arrays. Uranium nitride has a higher theoretical density and higher thermal conductivity than uranium oxide, allowing for lower fuel temperatures, longer cycle length and higher power densities with similar enrichment. In order to avoid the UN and high temperature water reaction, silicon carbide cladding has been proposed in place of Zircaloy cladding. The analysis aims at finding the maximum thermal power over a range of bundle geometries (rod diameter and pitch). The same methodology is applied to the design of UO{sub 2} oxide fueled cores to provide a fair comparison of the achievable power rating between the two fuel types. Steady-state limits are considered, including fuel bundle pressure drop, minimum departure from nucleate boiling ratio (MDNBR), fuel temperature, fuel rod vibrations and pin fretting and sliding wear. Transients such as loss of flow and overpower accident will be considered. A steady state analysis was undertaken to determine the maximum achievable power that can be sustained by square array fuel assemblies loaded with nitride and oxide fuels with same or better safety performances as the reference design. Steady-state design limits were applied including MDNBR, fuel bundle pressure drop, fuel temperature, cumulative sliding and fretting wear. The major conclusions of this study are as follows: 1) It is possible to achieve significant power increase for UN and UO{sub 2} compared to the reference core power output of 3400 MWth with smaller but more numerous rods and higher pitch over diameter ratios. A power uprate of 25% can be reached according to the VIPRE-MATLAB interface for full core analysis with the same number of spacer grids, and 32% according to the new MATLAB script for single hot channel analysis, with five more spacer grids. For this latter core, a higher enrichment would be required. 2) The nitride fuel temperature constraint from dissociation doesn't influence steady state performances as other design constraints such as MDNBR and pressure loss are more restrictive. The oxide fuel temperature constraint from fission gas release is reached in part of the study domain, but not in the region that allows for possible uprates. 3) As a result, the thermal hydraulic performance of UN and UO{sub 2} are similar. Differences in possible power uprates will arise from fretting and sliding wear. Wear depends of the time spent by the fuel in the core, which depends on burnup and heavy metal inventory. UN being denser, it can allow for power uprates or increased cycle length. There is a trade off between power uprates and cycle length with regards to fuel pin wear. Reducing fuel pin wear by reducing cycle length can allow for higher thermal power. This affects the plants' economics as well. This work will be completed by a transient analysis using CASMO4E, SIMULATE3 and SIMULATE3k to model the neutronics of a nitride fueled core. The transient performances will be used to determine the maximum power uprates while performing as well or better during transients as the reference design. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2016

Recent Progress on the Stochastic Objective Decision Aide (SODA) Application

Idaho State University, in collaboration with Idaho National Laboratory, is engaged in development of a simple to use software application that utilizes stochastic techniques for the calculation of radiation doses associated with hypothetical radioactive material releases. This work is being performed through a grant from the U.S. Department of Energy (DOE) Nuclear Safety Research and Development (NSR and D) Program. Initial progress on the application was reported previously. Recent additions to the application are reported here. The Stochastic Objective Decision Aide (SODA) provides an easy to use software application to help decision makers support their judgment about the need or lack of need for safety structures, systems, and components. SODA is not intended to replace traditional design basis accident dose calculation methodology, nor is it intended to replace existing software used to perform formal dose consequence calculations. Rather, SODA is intended to supplement information obtained from existing codes to give a decision maker more information about an accident scenario. SODA also provides a simple method to perform parametric or sensitivity studies on individual input parameters. Non-reactor nuclear facilities operated under the approval authority of the US DOE use unmitigated hazard evaluations to determine if potential radiological doses associated with design basis events challenge dose evaluation guidelines. Unmitigated events that sufficiently challenge dose evaluation guidelines merit the selection of safety structures, systems, or components (SSCs) to prevent or mitigate the hazard. Dose consequence calculations traditionally involve use of the 'five-factor' formula: ST = MAR.DR.ARF.RF.LPF where ST is the source term (Bq), MAR is the total available material-at-risk (Bq), DR is the damage ratio (no units), ARF is the airborne release fraction (no units), RF is the respirable fraction (no units), and LPF is the leak path factor (no units). Potential radiation doses are then calculated using: CED = χ/Q.BR.ST.DCF (2) where CED is the committed effective dose (Sv), χ/Q is the plume dispersion (s/m{sup 3}), BR is the breathing rate (m{sup 3}/s), ST is the source term (Bq), and DCF is the dose conversion factor (Sv/Bq). Conservative single value input parameters are typically used to represent ARF, RF, LPF and BR. The traditional methodology, while conservative, can lead to skewed conclusions in the balance between cost and risk reduction resulting in over engineered systems with greater design, construction and operating costs. Rather than using a bounding single point value for each parameter in the dose consequence calculation, SODA uses distributions for some or all of the parameters. Each input parameter distribution is stochastically sampled and the resulting dose consequence calculation is repeated many times to develop a dose consequence distribution. The resulting distribution provides more information for the decision maker to rely upon when determining the need for safety SSCs. The SODA application was developed using MATLAB and it incorporates the use of Monte Carlo techniques as well as a graphical user interface (GUI). The application includes user selection of the governing distribution for parameters such as the MAR, DR, ARF, RF, LPF,χ/Q, BR, and DCF. While MATLAB was used for the development work, the application is distributed as a self-contained executable program. Features of the application include pull down menus with available distributions for the various parameters. The user has the option to plot the input parameter distribution that results from the random sampling process. The resulting dose consequence distribution is automatically analyzed to determine its similarity to well know distributions. This was done using the Bayesian Information Criterion method. If the resulting distribution is sufficiently similar to a well-known distribution, the application provides information about the distributions such as the mean value and other parameters. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

A COUPLED DETERMINISTIC TRANSPORT CALCULATION IN COMSOL USING PROPER ORTHOGONAL DECOMPOSITION

A coupled physics problem consisting of radiation transport and heat transfer was modeled using COMSOL Multiphysics to simulate a criticality accident. Reduced order models (ROM) were created to accelerate the radiation transport calculation through Proper Orthogonal Decomposition (POD). Additionally, on-the-fly neutron cross sections were generated from a non-linear function through a feed forward neural network. The Livelink for MATLAB module allowed for data transfer between an otherwise independent solver and in-house modules. A data driven approach to POD was developed to act as a surrogate model to couple with heat transfer, with the POD module written in MATLAB coupled to an isolated heat transfer solve in COMSOL. A coupled transient solution resulted in a good approximation of the flux and temperature, with the maximum error being 3E-2 and 2.5E-3 respectively.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2015

RivGen Controller Performance Raw Data, Igiugig, AK

Contains raw data for operations of Ocean Renewable Power Company (ORPC) RivGen Power System in Igiugig 2015 in Matlab data file format. Two data files capture the data and timestamps for data, including power in, voltage, rotation rate, and velocity. Location, Description, Format, Column 1, Date and time, MM/DD/YYYY, hh:mm:ss, Column 2, DC voltage (after DC filter), VDC, Column 3, DC current into inverters, IDC, Column 4, DC current into secondary resistive load, IDC, Column 5, Power into inverters, kW, Column 6, Power into secondary load, kW, Column 7, Frequency of single phase AC voltage from generator, Hz, Column 8, rotation rate of generator/turbine (rested at 1.1 when stationary), rad/s, Column 9, Velocity Algorithm 2, m/s, Column 10, Velocity Algorithm 3, m/s, Column 11, Rcodes for secondary load, see document "SL Controller PLC Memory", Column 12, Voltage measured between phase A and B, Vll,

16 TIDAL AND WAVE POWER↗

DOE OSTI2018

Methods to measure contact angles in scCO 2 -brine-sandstone systems

Numerous methods are used to measure contact angles ( θ ) in multiphase systems. The wettability and θ are primary controls on CO 2 residual trapping during Geologic Carbon Storage (GCS) and determining these values within rock pores is paramount to increasing storage efficiency. One traditional experimental approach is the sessile drop method which involves θ measurements on a single image of droplets. More recent developments utilize X-ray micro-computed tomography (CT) scans which provide the resolutions necessary to image in situ θ of fluids at representative conditions; however, experimental micro-CT data is limited and varied. To further examine θ distributions in supercritical-CO 2 -brine-sandstone systems, a combination of manual and automated θ measurement methods were utilized to measure θ using both sessile drop and micro-CT images of two sandstone cores. Here, the purpose of this work was threefold: (1) compare two current and two new θ measuring methods using micro-CT images of scCO 2 -brine-sandstone systems; (2) determine how traditional experimental method (sessile drop) θ results compare to in situ θ results (micro-CT); and (3) determine if the Matlab Contact Angle Algorithm (MCAA) from Klise et al. (2016) can be used to measure θ scCO 2 -brine-sandstone systems.

54 ENVIRONMENTAL SCIENCES↗