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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 181 records · Page 10

Design and Testing of a Liquid Nitrous Oxide and Ethanol Fueled Rocket Engine

A small-scale, bi-propellant, liquid fueled rocket engine and supporting test infrastructure were designed and constructed at the Energetic Materials Research and Testing Center (EMRTC). This facility was used to evaluate liquid nitrous oxide and ethanol as potential rocket propellants. Thrust and pressure measurements along with high-speed digital imaging of the rocket exhaust plume were made. This experimental data was used for validation of a computational model developed of the rocket engine tested. The developed computational model was utilized to analyze rocket engine performance across a range of operating pressures, fuel-oxidizer mixture ratios, and outlet nozzle configurations. A comparative study of the modeling of a liquid rocket engine was performed using NASA CEA and Cantera, an opensource equilibrium code capable of being interfaced with MATLAB. One goal of this modeling was to demonstrate the ability of Cantera to accurately model the basic chemical equilibrium, thermodynamics, and transport properties for varied fuel and oxidizer operating conditions. Once validated for basic equilibrium, an expanded MATLAB code, referencing Cantera, was advanced beyond CEAs capabilities to predict rocket engine performance as a function of supplied propellant flow rate and rocket engine nozzle dimensions. Cantera was found to comparable favorably to CEA for making equilibrium calculations, supporting its use as an alternative to CEA. The developed rocket engine performs as predicted, demonstrating the developedMATLAB rocket engine model was successful in predicting real world rocket engine performance. Finally, nitrous oxide and ethanol were shown to perform well as rocket propellants, with specific impulses experimentally recorded in the range of 250 to 260 seconds.

33 ADVANCED PROPULSION SYSTEMS↗

SolCalc: A Suite for the Calculation and the Display of Magnetic Fields Generated by Solenoid Systems

SolCalc is a software suite that computes and displays magnetic fields generated by a three dimensional (3D) solenoid system. Examples of such systems are the Mu2e magnet system and Helical Solenoids for muon cooling systems. SolCalc was originally coded in Matlab, and later upgraded to a compiled version (called MEX) to improve solving speed. Matlab was chosen because its graphical capabilities represent an attractive feature over other computer languages. Solenoid geometries can be created using any text editor or spread sheets and can be displayed dynamically in 3D. Fields are computed from any given list of coordinates. The field distribution on the surfaces of the coils can be displayed as well. SolCalc was benchmarked against a well-known commercial software for speed and accuracy and the results compared favorably.

43 PARTICLE ACCELERATORS↗

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.↗

A new hybrid genetic algorithm for optimizing the single and multivariate objective functions

In this work a new hybrid genetic algorithm was developed which combines a rudimentary adaptive steepest ascent hill climbing algorithm with a sophisticated evolutionary algorithm in order to optimize complex multivariate design problems. By combining a highly stochastic algorithm (evolutionary) with a simple deterministic optimization algorithm (adaptive steepest ascent) computational resources are conserved and the solution converges rapidly when compared to either algorithm alone. In genetic algorithms natural selection is mimicked by random events such as breeding and mutation. In the adaptive steepest ascent algorithm each variable is perturbed by a small amount and the variable that caused the most improvement is incremented by a small step. If the direction of most benefit is exactly opposite of the previous direction with the most benefit then the step size is reduced by a factor of 2, thus the step size adapts to the terrain. A graphical user interface was created in MATLAB to provide an interface between the hybrid genetic algorithm and the user. Additional features such as bounding the solution space and weighting the objective functions individually are also built into the interface. The algorithm developed was tested to optimize the functions developed for a wood pelleting process. Using process variables (such as feedstock moisture content, die speed, and preheating temperature) pellet properties were appropriately optimized. Specifically, variables were found which maximized unit density, bulk density, tapped density, and durability while minimizing pellet moisture content and specific energy consumption. The time and computational resources required for the optimization were dramatically decreased using the hybrid genetic algorithm when compared to MATLAB's native evolutionary optimization tool.

feedstock↗

An optimization of the FPGA trigger based on the artificial neural network for a detection of neutrino-origin showers

Observations of ultra-high energy neutrinos became a priority in experimental astro-particle physics. Up to now, the Pierre Auger Observatory did not find any candidate on a neutrino event. This imposes competitive limits to the diffuse flux of ultra-high energy neutrinos in the EeV range and above. A very low rate of events potentially generated by neutrinos is a significant challenge for a detection technique and requires both sophisticated algorithms and high-resolution hardware. A trigger based on a artificial neural network was implemented into the Cyclone{sup R} V E FPGA 5CEFA9F31I7. The prototype Front-End boards for Auger-Beyond-2015 with Cyclone{sup R} V E can test the neural network algorithm in real pampas conditions in 2015. Showers for muon and tau neutrino initiating particles on various altitudes, angles and energies were simulated in CORSICA and Offline platforms giving pattern of ADC traces in Auger water Cherenkov detectors. The 3-layer 12-10-1 neural network was taught in MATLAB by simulated ADC traces according the Levenberg-Marquardt algorithm. Results show that a probability of a ADC traces generation is very low due to a small neutrino cross-section. Nevertheless, ADC traces, if occur, for 1-10 EeV showers are relatively short and can be analyzed by 16-point input algorithm. For 100 EeV range traces are much longer, but with significantly higher amplitudes, which can be detected by standard threshold algorithms. We optimized the coefficients from MATLAB to get a maximal range of potentially registered events and for fixed-point FPGA processing to minimize calculation errors. Currently used Front-End boards based on no-more produced ACEXR PLDs and obsolete Cyclone{sup R} FPGAs allow an implementation of relatively simple threshold algorithms for triggers. New sophisticated trigger implemented in Cyclone{sup R} V E FPGAs with large amount of DSP blocks, embedded memory running with 120 - 160 MHz sampling may support to discover neutrino events in the Pierre Auger Observatory. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

D and D decision model and mobile application for selection of fixative, strippable coating, and decontamination gel products - 15696

Deactivation and decommissioning (D and D) is the process of taking an active/excess/abandoned facility to a final disposition end state. D and D presents unique hazards that must be addressed from a safety, programmatic, environmental, and technological standpoint. This definition is especially applicable to Savannah River Site's 235-F facility. The facility was constructed in the 1950's as part of the weapons complex materials production and fabrication. The most significant quantities of residual contamination remaining in 235-F building is in the form of Plutonium-238. A Decision Model was created using MatLab to work hand-in-hand with a product list containing commercially available D and D products. This model was created to further enhance and accelerate the decontamination process. It is envisioned that D and D engineers will be able to use this Decision Model in the field via a mobile device. It allows the user to select four inputs to match their situation. The model searches the database and returns the products that fit the criteria selected by the user. This Decision Model will be made available in a web-based application and as a mobile application to ensure end users can access it when needed. The MatLab code recognizes what position in the text box is selected and then this input is converted to the corresponding string. The string is then compared with the information in the product list in the specified column in order to reduce processing time. Then the products that contain the string inputted are displayed on the table and are separated by category. The web-based version of the model will receive three specified criteria and sub-criteria from the user and update the table with products that fit each criteria. A web-based version of this Decision Model is under way and will be set up on the D and D KM-IT platform. There will be two versions of this mobile application: for devices with internet connection and for those that do not have internet connection. This will ensure end users have access to the Decision application at any time or place during the D and D process. A mobile version of the model will also be developed in the near future.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

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↗

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↗

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↗

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↗

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↗

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↗

Analysis of irradiated U-7wt%Mo dispersion fuel microstructures using automated image processing

The High Performance Research Reactor Fuel Development (HPPRFD) program is responsible for developing low enriched uranium (LEU) fuel substitutes for high performance reactors fueled with highly enriched uranium (HEU) that have not yet been converted to LEU. The uranium-molybdenum (U-Mo) fuel system was selected for this effort. In this study, fission gas pore segmentation was performed on U-7wt%Mo dispersion fuel samples at three separate fission densities using an automated image processing interface developed in MATLAB. Pore size distributions were attained that showed both expected and unexpected fission gas behavior. In general, it proved challenging to identify any dominant trends when comparing fission bubble data across samples from different fuel plates due to varying compositions and fabrication techniques. Here, the results exhibited fair agreement with the fission density vs. porosity correlation developed by the Russian reactor conversion program.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Characterization of fission gas bubbles in irradiated U-10Mo fuel

Irradiated U-10Mo fuel samples were prepared with traditional mechanical potting and polishing methods with in a hot cell. They were then removed and imaged with an SEM located outside of a hot cell. The images were then processed with basic imaging techniques from 3 separate software packages. The results were compared and a baseline method for characterization of fission gas bubbles in the samples is proposed. It is hoped that through adoption of or comparison to this baseline method that sample characterization can be somewhat standardized across the field of post irradiated examination of metal fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Sensitivity study of parameters important to Molten Salt Reactor Safety

This paper presents a molten salt reactor (MSR) design parameter sensitivity study using a nodal dynamic modelling methodology with explicitly modified point kinetics equation and Mann’s model for heat transfer. Six parameters that can impact MSR safety are evaluated. A MATLAB-Simulink model inspired by Thorcon’s 550MW th MSR is used for parameter evaluations. A safety envelope was formed to encapsulate power, maximum and minimum temperature, and temperature-induced reactivity feedback. The parameters are perturbed by ±30%. The parameters were then ranked by their subsequent impact on the considered safety envelope, which ranks acceptable parameter uncertainty. The model is openly available on GitHub.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

TIA: A forward model and analyzer for Talbot interferometry experiments of dense plasmas

Interferometry is one of the most sensitive and successful diagnostic methods for plasmas. However, owing to the design of most common interferometric systems, the wavelengths of operation and, therefore, the range of densities and temperatures that can be probed are severely limited. Talbot–Lau interferometry offers the possibility of extending interferometry measurements to x-ray wavelengths by means of the Talbot effect. While there have been several proof-of-concept experiments showing the efficacy of this method, it is only recently that experiments to probe High Energy Density (HED) plasmas using Talbot–Lau interferometry are starting to take place. To improve these experimental designs, we present here the Talbot-Interferometry Analyzer (TIA) tool, a forward model for generating and postprocessing synthetic x-ray interferometry images from a Talbot–Lau interferometer. Although TIA can work with any two-dimensional hydrodynamic code to study plasma conditions as close to reality as possible, this software has been designed to work by default with output files from the hydrodynamic code FLASH, making the tool user-friendly and accessible to the general plasma physics community. Here, the model has been built into a standalone app, which can be installed by anyone with access to the MATLAB runtime installer and is available upon request to the authors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Precision Local Burnup Assessment Through Dynamic Peak Fitting in Atom Probe Tomography for Depleted, Enriched, and Irradiated Metallic and Ceramic Fuels

Abstract Burnup estimation in nuclear fuels is vital for evaluating fuel performance, transportation, and safe fuel storage. Accurate assessments of burnup from service period and spent fuels involve tracking the consumption of fissile isotopes of uranium (U) offering a direct insight into energy changes within the fuels especially for thermal spectrum reactors. In current approach, mass spectroscopic technique in atom probe tomography (APT) is utilized for accurate quantification of U isotopes. Quantification of U peaks in mass spectrum is performed on asymmetric shapes due to delayed signals, known as thermal tails, particularly for poorly conducting samples analyzed in laser mode. In this study, we introduce a novel quantification tool for isotopic analysis from APT datasets by developing a fitting algorithm based on shapes of the peaks. A MATLAB-based dynamic peak fitting toolbox is developed and designed to adapt to various peak shapes, ensuring accurate quantification of U isotopes. The effectiveness of this approach is demonstrated in standard Ni-Cr sample, depleted and enriched U samples, and U-based fuels with different burnup levels. The viability of this approach for isotopic quantification is demonstrated on both metallic and ceramic fuels.

Burnup↗

Full-Wave and Circuit-Based Simulations of Cable Insulation Aging/Damage Using Time-Frequency Domain Reflectometry

This paper presents a combined full-wave and circuit-based simulation study to investigate the important topic of cable insulation aging and physical damage. The analysis employs the time-frequency domain reflectometry (TFDR) technique that combines the advantages of both time domain reflectometry (TDR) and frequency domain reflectometry (FDR) for improved location identification and feature resolution. Coaxial cable sections with a location containing insulation aging or physical damage are simulated using Ansys High Frequency Structure Simulator (HFSS). Simulated scattering (S) parameters are then imported into the Advanced Design System (ADS) solver for time domain simulation where a Gaussian windowed chirp signal or ‘chirplet’ is launched. Finally, continuous wavelet transform (CWT) is applied in MATLAB to perform time-frequency analysis of the reflected waveforms. The results reveal that a small change in the relative permittivity of the insulation or the presence of a small point of physical damage on the insulation is reflected as a considerable change in the CWT magnitude demonstrating the efficacy of the method.

cable aging, Non Destructive Examination, time-fre↗