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DOE OSTI2017

Processing Methodology for Double Sensor Probe in a Bubbly Flow

Bubbly flow phenomenon is the most common flow pattern in nuclear plant system. In this paper, according to Hibiki and Bartel, the experiment was designed to observe the fluid conditions surrounding nuclear rod. In recent years, double sensor probe is one of the measuring techniques for the bubbly flow. It can measure local void fraction and bubble velocity. After mathematical statistical calculation, interfacial area concentration is obtained by Kataoka. The double sensor probe method, with the advantage for measuring local interfacial area concentration, has become widely used in many measurement methods. The paper of Liu and Zhao were referred to establish the post-processing for the raw data obtained from measuring instrument. After drawing the signal of the probe, it is important to analyze the raw data for the elimination of unnecessary noise signal and highlight the characteristic signal. Based on the same experimental condition, the different filtering methods, Simple Moving Average (SMA) and Gaussian average, were compared and discussed by the double sensor probe.

42 ENGINEERING↗

DOE OSTI2014

TRIPOLI-4{sup R} version 9 Shielding for the Shielding Community: Overview, Relevant Benchmarking for Shielding and Licensing Policy - Paper 49

This is a review paper of the Shielding only version of TRIPOLI-4. TRIPOLI-4 and TRIPOLI-4 S: TRIPOLI{sup R} represents a family of radiation transport codes using the Monte Carlo method (1,2). It has been continuously developed at CEA since the mid 60's. TRIPOLI-4{sup R}, being the fourth generation, has been developed starting from the mid 90's in C++. It tracks neutrons from 20 MeV down to 10{sup -5} eV, photons, electrons and positrons from 100 MeV to 1 keV, in 3D arbitrary geometries either in TRIPOLI{sup R} proprietary format or ROOT(4) format. It reads its continuous energy nuclear data from any evaluation in ENDF format, including but not limited to JEFF-3.1.1 and ENDF/BVII.0. It has various simulation modes, fixed-source (with or without fission), criticality, or both of them chained. A variety of tallies are available: averaged flux in a volume (track length and collision estimators), surface flux and current, point flux, reaction rates, deposited energy, dpa, pka, gamma spectroscopy, mesh tallies, tallies for criticality (k{sub eff}, beta eff, kinetic parameters). It provides the user with embedded response functions from IRDF and EAF as well. Several variance reduction techniques (3), including automated ones, make it particularly suitable to deep penetration problems (implicit capture, Russian roulette, exponential biasing with automatic estimation of the importance map). It may run in parallel, on single multi-core machines as well as heterogeneous networks of stations or massively parallel machines. It comes with productivity tools designed to speed-up the elaboration and verification of the input deck as well as the output analysis: 2D interactive display of geometry; 2D display of mesh tallies and collision sites; 3D input deck modeler; compatibility with ROOT tools to post-process TRIPOLI{sup R} outputs. Its V and V test base is made of more than 1000 internationally accepted benchmarks from ICSBEP and SINBAD (REPLICA, ASPIS, NESDIP) and covers all its application domains, including several shielding cases which will be detailed in the talk. TRIPOLI-4{sup R} is the reference Monte Carlo code for CEA, EDF, and also for AREVA for a number of applications. A 'Shielding-only' version has been designed to specifically answer the needs of the shielding community. It is distributed through the NEA Databank with a license for R and D, covering the fusion applications, whose terms are detailed in the paper.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2015

Minimum critical masses and their uncertainties for several fissile nuclides and reflectors - 14296

A systematic effort was undertaken to reevaluate the minimum critical mass for several fissile nuclides and reflectors. This was done using MCNP6 in combination with several modern nuclear data libraries, viz. ENDF/B-VII.1, JENDL-4.0 and JEFF-3.1.1. This combination was benchmarked extensively against criticality safety benchmarks. The procedure to extract the minimum critical mass from the MCNP6 calculations was carefully implemented, so that it would have a negligible impact on the accuracy of the end results. All parts of the calculation, i.e. nuclear data processing, MCNP6 models, and post-processing, were applied consistently for all cases, involving varying fissile nuclides and reflectors. Results for the minimum critical mass were generated for {sup 233,235}U, {sup 236,239,241}Pu, {sup 242m}Am, {sup 243,245,247}Cm, and {sup 249,251}Cf, for the case of water moderation and water reflection. For {sup 235}U, the minimum critical mass was also calculated for cases with other reflectors, such as beryllium, heavy water, graphite, lead, and concrete. The results for the water reflection cases are in good agreement with most of the literature values, but for the cases with reflectors such as graphite, lead, or concrete, there are sizable differences. The accuracy of the results was assessed in two ways. First, a comparison was made with criticality safety benchmark results, by selecting benchmarks that resemble the minimum mass systems the most. It was clear that for {sup 233,235}U and {sup 239}Pu with water reflection, the differences in minimum critical masses between the libraries are consistent with the differences obtained for benchmark cases. The difference between the benchmark calculations and the benchmark values is then an indication of the accuracy with which one can simulate comparable systems. Secondly, sensitivity runs were performed with the new MCNP6 sensitivity option, based on ENDF/B-VII.1 nuclear data. For each fissile nuclide, the sensitivity of k{sub eff} to cross sections such as capture, fission, elastic, inelastic was calculated for the minimum critical mass case. The same was done for the {sup 1}H and {sup 16}O cross sections in the moderator and reflector. The uncertainty in k{sub eff} was calculated by combining the sensitivity profiles with the appropriate ENDF/B-VII.1 covariance matrix, using the SUSD code. As a final step, the uncertainty in k{sub eff} can be translated to an uncertainty in the minimum critical mass. (author)

42 ENGINEERING↗

DOE OSTI2024

High Temperature Test Facility At Scale Testing, Validation, and Demonstration

Theses slides will be used to brief the Tribal DOE and Council Chairman for the project listed below. The High Temperature Test Facility (HTTF) is a demonstration-scale high temperature electrolysis (HTE) system that provides the ability to produce, process, store, and dispense electrolytically produced hydrogen. The system will be designed to accommodate electrolysis systems from various industry partners. The HTTF will be supplied up to 10 MW of power for electrolysis at 5 separate test article locations, each up to 2MW. The system will include post-processing and compression, storage, and capabilities to provide hydrogen for consumption by future end users. The HTTF will also provide the ability to test and demonstrate an HTE system in a configuration that would simulate the use of a nuclear generated steam supply for the high temperature heat source. The HTTF will be located at the Central Facilities Area (CFA) adjacent to CFA-686 on the INL site, 45 miles west of Idaho Falls.

08 HYDROGEN↗

DOE OSTI2024

Spatiotemporal Automatic Calibration of Infrastructure Lidar, Radar, and Camera with a Global Navigation Satellite System: Preprint

Robust and accurate perception is important for modern intelligent transportation systems (ITS), which use sensors of various modalities for data fusion to create a digital twin of an intersection. Sensor calibration is an important process that creates a unified coordinate frame for the sensor output data so that it can be used for data fusion. Classical approaches for sensor calibration are time-consuming, require an overlapping field of view for feature matching, and are not feasible for ITS application as they cause disruptions in the flow of traffic. In this paper, we present a spatiotemporal automatic calibration approach to calibrate multiple infrastructure lidar, radar, and cameras installed at a traffic intersection. The approach uses global navigation satellite system (GNSS) positioning information shared by connected vehicles, and when the vehicle is detected by the sensor, we match the sensor detections with the GNSS coordinates. The proposed algorithm is evaluated with a real-world dataset utilizing detections from two radars, cameras, and lidars with a test vehicle instrumented with a post-processing kinematic (PPK)-corrected GNSS driving past the sensors installed at a four-way traffic intersection. The experimental results show that the proposed automatic calibration approach can achieve the transformation with a root mean squared error of less than 0.5 for radar and lidar and less than 2 for camera detections. The ability to rapidly calibrate sensors not only benefits initial installations, but can also be used for system health monitoring, while utilizing available connected vehicle data to test the real-time sensor fidelity and operational status.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

Characterization of build parameters and microstructure in low heat input WAAM of Ni-based superalloy Haynes 282

Conference paper for 2024 10th International Conference on Advances in Materials, Manufacturing & Repair for Power Plants. Ni-based superalloy Haynes 282 is a prime candidate for advanced power generation systems due to its superior fabricability, weldability, and high-temperature performance. Additive manufacturing offers potential cost and time savings for gas turbine components. Wire-arc direct energy deposition can create large components but often requires post-processing treatments, such as hot isostatic pressing (HIP), to address porosity. This study explores a low heat-input, high deposition rate GMAW process to achieve fully dense Haynes 282 without HIP. Twenty-one blocks were deposited, varying travel and wire feed speeds. Initial analysis (visual inspection, microstructural examination, and CT) revealed the impact of build parameters on internal porosity and defects. Scanning electron microscopy provided insights into structural heterogeneity and microstructural properties. Related journal article can be found at https://doi.org/10.31399/asm.cp.am-epri-2024p0001.

Adam, Benjamin↗

DOE OSTI2023

Distributed Coaxial Cable Sensors for In-Situ Condition Based Monitoring of Coal-Fired Boiler Tubes

The increasing contributions of renewable energy sources present new challenges to the operation and maintenance of the existing coal-fired power plants. One of the major operational risks is the unexpected failure of superheater boiler tubes, leading to the most unplanned power plant outrages. The boiler tube failure is difficult to predict due to the harsh operating environments. Therefore, condition-based monitoring (CBM) with a reliable high temperature sensor becomes necessary to produce a meaningful assessment of the health condition of boiler tubes and their remaining lifetime. In this work, the stainless-steel and quartz coaxial cable sensor (SSQ-CCS) is proposed for in-situ distributed monitoring of the boiler tube temperatures in existing coal-fired power plants. Comprehensive tests have been conducted with an in-house testing facility at Clemson University to study and evaluate the sensors’ performance in the temperature range of 100℃ to 600℃. The results indicated that the measurement resolution of the SSQ-CCS sensor is better than 1℃, and the drift is less than 2% over long-period testing. Meanwhile, multi-physics finite element analysis has been conducted to optimize the design and evaluate the safety of the SSQ-CCS temperature sensor under various operational conditions. Based on the performance obtained in the laboratory-scale testing, a field test has been implemented at a power plant. Four SSQ-CCS temperature sensors were installed for in-situ monitoring of the temperatures of a power plant’s superheat tube assembles. The data acquisition system has been successfully set up and collected sensing signals for more than three months. The sensing signals have been post-processed, and the monitored temperature history through the SSQ-CCS temperature sensor has been validated and compared with the conventional high temperature thermal couple data.

Jiao, Xinyu↗

DOE OSTI2025

Electrical and Thermal Load Impacts of Three District Heating and Cooling Designs for an Existing Community in Washington, DC

District energy systems that provide building heating and cooling are a promising option to provide low-cost, energy efficient heating and cooling solutions for communities. As some buildings move to electrified heating designs, there may be significant increases in electric grid demand, particularly in the winter. District energy systems may be able to help reduce these high electrical demands on the electric grid, while also providing decreased overall energy consumption with an increased flexibility in electrical energy usage. To evaluate and compare district options for district-based heating and cooling, an existing neighborhood of Washington, DC consisting of 35 existing buildings was selected as a case study. This study models and compares a fourth generation (4G) district heating and cooling systems that provide hot and chilled water from a central plant directly to each prosumer and a fifth generation (5G) district heating and cooling systems that provide near-ambient water via geothermal boreholes to interface with an energy transfer station with a heat pump at each prosumer. These district systems are compared against a baseline of the non-connected buildings with their self-contained and current HVAC systems. The neighborhood was selected as a good candidate for a district system for its diversity of loads (mix of different commercial and property types) and the availability of building characteristics. URBANopt District Energy Systems (DES) was used to model the buildings and create initial Modelica models for the district systems. Finally, the DES models were tuned and simulated in Dymola, and the outputs were post-processed for verification and to calculate the electrical and thermal grid impact metrics. This is the first documentation of this workflow and its complete analysis. The three designed systems are compared via their grid metrics including: total energy consumption, electrical demand peak loads, daily peak-to-valley ratios, and system ramping. A detailed discussion is provided about how each system impacts and interacts with the electric grid.

15 GEOTHERMAL ENERGY↗

DOE OSTI2025

Angular Correlation Date Measurements with the GeRMAC system

Advanced modeling and simulation efforts have improved at Idaho National Laboratory in recent years with a solid foundation of experimental results. Current computational methods represent significant modeling capabilities but are limited by the accuracy and availability of nuclear data. The creation of pre- and post-processing software tools to address these limitations is fundamental to the improvement of nuclear science modeling capacities. One aspect of predictive modeling tools deals with gamma-rays emitted from radionuclides, including fissile or fissionable material, fission products, or activation products, produced in reactor experiments or other neutron environments. The resulting radionuclides decay in unique ways, providing complications upon measurement as a result of random and cascade, or true, coincidence summing. These effects are not easily quantified during modeling efforts of gamma-ray source terms., The germanium rotational measurements for angular correlation (GeRMAC) system was built to quantify the relative angles for gamma rays emitted by radionuclides of interest to investigate true coincidence, or cascade, summing as well as the nuclear energy levels of decay schemes of interest. Proof of concept studies utilize a series of laboratory check sources to provide validity, and it will soon be used to perform the same measurements for fission products of interest. The resulting data can be used to implement into a Monte Carlo code, such as Geant4, to provide more precise gamma-ray source terms following irradiations of materials.

73 - NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

Classic and Quantum Task-Based Intelligent Runtime for QIRs Running on Multiple QPUs

High-performance computing systems are rapidly evolving into heterogeneous platforms that fuse quantum accelerators with traditional classical processing units (CPUs) and graphical processing units (GPUs). This convergence calls for runtimes capable of managing both classical and quantum workloads in a unified manner. We introduce an intelligent, task-based runtime that marries the Intelligent RuntIme System (IRIS) asynchronous scheduler with a quantum programming stack through the Quantum Intermediate Representation Execution Engine (QIR-EE). Our design allows programs written in the quantum intermediate representation (QIR) to be dispatched concurrently to a variety of back-ends, including multiple quantum simulators and nascent quantum processors, enabling genuine hybrid execution on a single node. To illustrate its practicality, we partition a 4-qubit and 20-qubit circuit into three sub-circuits using quantum circuit cutting via the QCut library. Each sub-circuit is simulated independently by the QIR-EE driver within IRIS, after which a classical post-processing step merges the simulation results to recover the outcome of the original full-circuit computation. This case study demonstrates how finer task granularity can enable the parallel execution and lower the simulation burden per quantum task while preserving overall accuracy, highlighting the feasibility of our hybrid approach.

Miniskar, Narasinga Rao [ORNL] (ORCID:000000018259↗

DOE OSTI2026

Heat Transfer Experiments of a 1st Stage Blade Cascade for Supercritical CO2 Oxy-Combustion Turbine Application

The results of internally cooled 1st stage blade (S1B) cascade testing in a supercritical CO2 environment is presented. The turbine blade design has been previously established for the end application of an oxy-combustion turbine operating in the Allam-Fetvedt cycle with turbine inlet conditions of 305 bar and 1150°C. The internally cooled blade features leading edge (LE) region impingement cooling, mid-section ribbed serpentine passages, and a pin-finned trailing edge (TE) region before cooling ejection holes. The geometry for the tested blade cascade has a cooled central blade with un-cooled blades on either side to match flowpath areas of the actual turbine. The flowpath reuses internal components previously employed for mid-section region ribbed serpentine passage experiments that established Nusselt number enhancement ratios over a range of Reynolds numbers from 100,000-400,000. New components include flow conditioning plates upstream and downstream of the blade cascade to adequately represent the flow field and blade external heat transfer coefficient profiles for the actual turbine. The cooled central blade utilizes uniform crystal temperature sensors (UCTS) with six sensors each on the blade pressure and suction surfaces distributed radially and from LE to TE. The post-processed UCTS quantified the maximum wall temperature seen at each installed sensor location. The test procedure consisted of establishing supercritical CO2 cooling flow temperature and flow rate and maintaining it throughout the test. The flow rate aims to match that for the actual in-service turbine blade design and is maintained through an orifice restriction to keep the pressure differential between internal cooling flow and external hot flow nearly constant. For the sCO2 flow path external to the blade, temperatures were ramped throughout the test via control of the test loop’s natural gas burner heater. The maximum temperature seen was 468°C and held constant for a duration of 10 minutes at which the blade metal temperature was predicted to be at its maximum before ramping down. For the turbine blade design for service inlet conditions, external flow path computational fluid dynamics (CFD) results and an internal cooling 1-D thermal and hydraulic flow network model using experimentally validated correlations served as thermal finite element (FE) boundary conditions to predict blade metal temperatures. These predicted temperatures were subsequently utilized in a structural FE model to predict blade life ratings dictated by Haynes 282 creep strength data, having a strong dependence on temperature. The boundary conditions experienced during testing are used in the same workflow and compared to the experimental results, with the goal of validating the analysis methodology and providing insight on the uncertainty in local metal temperature predictions.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2026

Affine Transformations to Enable Machine Learning for Semi-Quantitative EDS Analysis

Energy Dispersive X-ray Spectroscopy (EDS) is an essential technique for determining elemental concentrations and distributions within microstructures, critical for materials discovery, optimization, and qualification. However, most published EDS data is qualitative because current quantitative EDS analysis methods require extensive calibration and post-processing, limiting their practicality and widespread adoption. This work seeks to establish a framework for accelerated EDS characterization and spectrum analysis that can leverage ML to analyze correlations between various elemental compositions and resulting EDS spectra. The complex physics and data result in a high-dimensional problem that grows exponentially with the number of elements in the system and the complexity of the spectrum analysis. ML provides a way to compute and optimize the results of this highly dimensional problem in a flexible way to tailor it to the user’s specific needs and material system. However, the framework emphasizes transparency through a strictly mathematical affine transformation, so the analysis remains understandable and reviewable to facilitate adoption by the scientific community. While currently implemented methods are simplistic and unvalidated, further development and demonstration of this framework could enable high-throughput, accurate, and accessible EDS characterization.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

Affine Transformations to Correlate Experimental and Simulated EDS Spectra for Multi-Element Systems

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

BFSVBF (BatFinder Smart Video BioFilter) [SWR-22-87] and Multi-class BatFinder Smart Video BioFilter Keras

Bats are notoriously difficult to study, therefore, identifying specific behavioral trends and the precise environmental conditions at the time of collision requires a monitoring solution that can reliably collect relevant data. To date, thermal infrared video surveillance has been extensively applied to study bats and has proven to be a powerful yet cumbersome tool. Current analytical approaches are time consuming because data processing data has not been fully automated. In the past, steps have been taken to record avian and bat activity in conjunction with complicated image processing techniques that separate species from other moving objects within the field of view (i.e. clouds and portions of the wind turbine). Once the videos are collected, the post-processing does not allow real time monitoring and identification, leading to a delay in both studying the behavior of these species and determining the effectiveness of any impact reduction strategy being studied. Moreover, object identification capability is lacking, thus limiting the usefulness of video data. To resolve these issues, we are using open source computer vision and machine learning techniques allowing for automatic detection of objects in real-time with the ability to correlate these objects with environmental variables and recording the flight paths of each object. The code has gone through five rounds of development with images used to train the models. This advancement allows for automated real-time data collection, identification, and tracking, thereby eliminating the need for long and tedious post-analysis processing of the videos. We will discuss the two open source and publicly available machine learning models developed within this scope of this work: 1) a binary model with a 97.5% accuracy in identifying the difference between an object and an empty scene, including wind turbine and clouds; and 2) a multiple classification model with the capability of identifying the type of object detected: bats (90% accuracy), birds (83% accuracy), insects (69% accuracy) and non-biological (99% accuracy).

Yarbrough, John↗

DOE OSTI2016

Feasibility of in situ controlled heat treatment (ISHT) of Inconel 718 during electron beam melting additive manufacturing

A novel technique was developed to control the microstructure evolution in Alloy 718 processed using Electron Beam Melting (EBM). In situ solution treatment and aging of Alloy 718 was performed by heating the top surface of the build after build completion scanning an electron beam to act as a planar heat source during the cool down process. Results demonstrate that the measured hardness (478 ± 7 HV) of the material processed using in situ heat treatment similar to that of peak-aged Inconel 718. Large solidification grains and cracks formed, which are identified as the likely mechanism leading to failure of tensile tests of the in situ heat treatment material under loading. Despite poor tensile performance, the technique proposed was shown to successively age Alloy 718 (increase precipitate size and hardness) without removing the sample from the process chamber, which can reduce the number of process steps in producing a part. Lastly, tighter controls on processing temperature during layer melting to lower process temperature and selective heating during in situ heat treatment to reduce over-sintering are proposed as methods for improving the process.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Removing Fluoride from Double Four-Membered Rings Yielding Defect-Free Zeolites under Mild Conditions Using Ozone

We have investigated ozone treatment of as-made LTA zeolites under mild temperature conditions (175 °C) using experiments and periodic DFT as a method of energy savings and engineering defects such as silanol nests in comparison with conventional calcination at 550 °C. We have studied ozone treatment on LTA samples synthesized with 1,2-dimethyl-3-(4-methylbenzyl) imidazolium (denoted as “BULKY”) as the primary organic structure-directing agent (OSDA) and with various amounts of tetramethylammonium (TMA) as a secondary OSDA. Ozone treatment of LTA-BULKY at 175 °C was found to give defect-free, pristine LTA materials as determined by 29 Si NMR, 13 C NMR, Raman spectra, and DFT to assign the spectra. This represents a significant and unexpected finding: that fluoride ions can be completely removed from double four-membered rings (D4Rs) under such mild conditions. Furthermore, ozone treatment of LTA-BULKY-TMA samples removed BULKY but left behind TMA/F, giving a new and more diverse structural landscape of Si environments in LTA. Ab initio MetaDynamics calculations provide pathways with relatively low barriers, explaining how fluoride ions can be removed from D4Rs, leaving behind defect-free LTA materials under mild conditions.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Sulfidation kinetics of titanium and Ti-6Al-4V with elemental sulfur

The sulfidation kinetics of titanium and Ti-6Al-4V (Ti64) using elemental sulfur were studied by measuring the amount of metal consumed instead of the change in mass or scale thickness. Here this metal consumption approach combines the parabolic oxidation law, Arrhenius equation, and Pilling-Bedworth ratio to determine the apparent activation energy and the pre-exponential factor of consumption of Ti64 during sulfidation. The estimations of apparent activation energy and pre-exponential factor were 110.4 kJ·mol -1 and 1.3×10 -9 m 2 s -1 for the titanium-sulfur, and 116.2 kJ·mol -1 and 1.2×10 -9 m2s -1 for the Ti64-sulfur system. Finally, a material removal predictor was developed to predict the amount of Ti64 consumed for a given sulfidation temperature and time.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Additive manufacturing of high‐density silicon carbide ceramics through post‐processing spark plasma sintering

This research advances the field of additive manufacturing (AM) of silicon carbide (SiC) ceramics by integrating spark plasma sintering (SPS) to enhance material density, mechanical strength, and thermal properties. Traditional AM techniques struggle to achieve the high‐density SiC required for demanding applications, such as aerospace engineering, where high thermal conductivity and mechanical strength are paramount. Here, our study addresses these challenges by incorporating SPS as a post‐processing step, achieving near‐theoretical maximum densities and significantly reducing porosity, thereby resulting in outstanding thermal conductivity in SiC ceramics. We developed a specialized SiC ink optimized for 3D printing, ensuring structural integrity after deposition through tailored rheological properties. The application of SPS facilitates rapid, uniform sintering, essential for attaining superior density, mechanical properties, and thermal performance. Our experimental results, confirmed through scanning electron microscopy analysis, demonstrate significant microstructural properties, mechanical strength, and thermal conductivity, showcasing the effectiveness of integrating SPS in AM processes. This innovative approach not only expands the capabilities of AM in producing complex, high‐density ceramic structures but also broadens the potential applications of SiC in demanding environments.

36 MATERIALS SCIENCE↗