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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A Comprehensive Investigation into the Effect of a Low Surface Energy Treatment on Gas Hydrate, Asphaltene, and Wax Formation, Deposition, and Adhesion

The formation/precipitation and deposition of pipeline solids, such as gas hydrates, asphaltenes, and waxes have long plagued production fields. Given the vast differences in chemistries of these solids, any current prevention or mitigation strategy, particularly for cases in which multiple issues are a concern, is likely to involve an extensive assortment of chemical additives that are both costly and add complexity to the system. Surface treatments (coatings), on the other hand, present a relatively viable option for management strategies. A chemically and physically robust surface treatment with the ability to address deposition issues for multiple pipeline solids could not only decrease the operating expenditures for a field through material cost savings and obviation of downstream separation, but could also simplify produced fluids by eliminating additional chemicals from the mixture. The purpose of this study was to explore the feasibility of a particular surface treatment as part of a solids management strategy. This work used an omniphobic surface treatment to probe its effects on gas hydrate, asphaltene, and wax deposition. Specifically, an interfacial tensiometer (IFT) collected contact angle measurements for wettability studies. High-pressure rocking cells studied gas hydrate nucleation and deposition. A bench-scale flow loop quantified the deposition of oil and asphaltenes after a set time period. Finally, a mechanical shear device measured the adhesion force of wax deposits on untreated/treated surfaces. Static contact angle results showed that the omniphobic surface treatment had reduced surface interaction with water droplets in air, altering from the complete wetting on corroded surfaces to slightly hydrophobic conditions of greater than 100°. In addition, rocking-cell tests indicated that these omniphobic surface treatments may prevent gas hydrate deposition for up to 72 hours. The gas hydrate rocking-cell tests also demonstrated possible increases in induction time and occasional elimination of hydrate nucleation with the surface treatment. Finally, the surface treatment application, which also decreased surface roughness, showed that crude oil and asphaltene particles deposition, as well as the shear required to remove solidified wax deposits, could be reduced by a large factor. Overall, promising results were recorded for all major flow-assurance solids in the presence of the surface treatment.

Engineering↗
DOE OSTI2022

Monitoring of Temperature Measurements for Different Flow Regimes in Water and Galinstan with Long Short-Term Memory Networks and Transfer Learning of Sensors

Temperature sensing is one of the most common measurements of a nuclear reactor monitoring system. The coolant fluid flow in a reactor core depends on the reactor power state. We investigated the monitoring and estimation of the thermocouple time series using machine learning for a range of flow regimes. Measurement data were obtained, in two separate experiments, in a flow loop filled with water and with liquid metal Galinstan. We developed long short-term memory (LSTM) recurrent neural networks (RNNs) for sensor predictions by training on the sensor’s own prior history, and transfer learning LSTM (TL-LSTM) by training on a correlated sensor’s prior history. Sensor cross-correlations were identified by calculating the Pearson correlation coefficient of the time series. The accuracy of LSTM and TL-LSTM predictions of temperature was studied as a function of Reynolds number (Re). The root-mean-square error (RMSE) for the test segment of time series of each sensor was shown to linearly increase with Re for both water and Galinstan fluids. Using linear correlations, we estimated the range of values of Re for which RMSE is smaller than the thermocouple measurement uncertainty. For both water and Galinstan fluids, we showed that both LSTM and TL-LSTM provide reliable estimations of temperature for typical flow regimes in a nuclear reactor. The LSTM runtime was shown to be substantially smaller than the data acquisition rate, which allows for performing estimation and validation of sensor measurements in real time.

Pantopoulou, Stella↗
DOE OSTI2025

Preliminary modeling of triply periodic minimal surface (TPMS) structures using RELAP5-3D

With the United States Department of Energy (DOE)’s goal of quadrupling the nation’s nuclear energy supply by 2050, and with the Advanced Fuels Campaign pushing for new types of advanced reactor fuels and geometries, the need has arisen for new nuclear fuel designs. One such design is to swap out current nuclear fuel geometries in exchange for another type of geometry, called a Triply Periodic Minimal Surface (TPMS). TPMSs are self-supporting, infinitely repeating lattices—attributes that lend themselves well to additive manufacturing. These surfaces also possess enhanced heat transfer properties thanks to their internal area changes and large surface-area-to-volume ratios. Their drawback, however, is an increased pressure drop. Given the small amount of correlations and data (Reynolds numbers in the 2,000–8,000 range), and the minimal amount of experience so far obtained by modeling TPMS structures using 1D systems codes such as the Reactor Excursion and Leak Analysis Program (RELAP5-3D), further research into this topic was needed. Using data from the University of Wisconsin - Madison (UW), curve fits were created for both a Heat Transfer Coefficient (HTC) correlation and a Darcy friction factor empirical coefficient correlation. The curves’ coefficients and multipliers were then output and utilized in RELAP5-3D models of two upcoming experiments—Flow Loop for INFLUX Pressure drop (FLIP) and Microreactor Agile Non-nuclear Experimental Test (MAGNET)—aimed at increasing the available data for Reynolds numbers to the 16,000–36,000 range for TPMS structures. The models were run under the conditions utilized by a Computational Fluid Dynamics (CFD) analysis performed by another group at Idaho National Laboratory. Only CFD pressure drop values were obtained from the FLIP test, and those values showed that the RELAP5-3D models had a lower rate of pressure increase in comparison to the CFD values. In addition, there seemed to be a vertical shift upward in the pressure drop for both models whenever the TPMS porosity decreased, and the RELAP5-3D models showed a higher vertical shift in comparison to the CFD values. The MAGNET results did not correspond to any CFD or experimental results against which they could be compared, so they were instead compared against the proposed CFD input conditions. These values were then compared with each other to make sure the model seemed to be performing as expected, paving the way for future tests that can be run for the purpose of further analyses and comparisons. The pressure drop increased with temperature and mass flow rate independently. The temperature change would decrease with increasing mass flow rate and temperature, which was just as we expected based on the fact that the lower viscosity and decreased density would result in higher friction and churning losses. The last metric that was assessed was the enthalpy flow change, which increased with increasing mass flow rate and decreasing temperature.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

Institute for High Heat Flux Removal (IHHFR). Phases I, II, and III

The IHHFR focused on interdisciplinary applications as it relates to high heat flux engineering issues and problems which arise due to engineering systems being miniaturized, optimized, or requiring increased high heat flux performance. The work in the IHHFR focused on water as a coolant and includes: (1) the development, design, and construction of the high heat flux flow loop and facility; (2) test section development, design, and fabrication; and, (3) single-side heat flux experiments to produce 2-D boiling curves and 3-D conjugate heat transfer measurements for single-side heated test sections. This work provides data for comparisons with previously developed and new single-side heated correlations and approaches that address the single-side heated effect on heat transfer. In addition, this work includes the addition of single-side heated circular TS and a monoblock test section with a helical wire insert. Finally, the present work includes: (1) data base expansion for the monoblock with a helical wire insert (only for the latter geometry), (2) prediction and verification using finite element, (3) monoblock model and methodology development analyses, and (4) an alternate model development for a hypervapotron and related conjugate heat transfer controlling parameters.

2-D Boiling Curves↗
DOE OSTI2012

Gas and liquid measurements in air-water bubbly flows

Local measurements of gas- and liquid-phase flow parameters are conducted in an air-water two-phase flow loop. The test section is a vertical pipe with an inner diameter of 50 mm and a height of 3.2 m. The measurements are performed at z/D = 10. The gas-phase measurements are performed using a four-sensor conductivity probe. The data taken from this probe are processed using a signal processing program to yield radial profiles of the void fraction, bubble velocity, and interfacial area concentration. The velocity measurements of the liquid-phase are performed using a state-of-the-art Particle Image Velocimetry (PIV) system. The raw PIV images are acquired using fluorescent particles and an optical filtration device. Image processing is used to remove noise in the raw PIV images. The statistical cross correlation is introduced to determine the axial velocity field and turbulence intensity of the liquid-phase. Measurements are currently being performed at z/D = 32 to provide a more complete data set. These data can be used for computational fluid dynamic model development and validation. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Conceptual design study for heat exhaust management in the ARC fusion pilot plant

The ARC pilot plant conceptual design study has been extended beyond its initial scope to explore options for managing ∼525 MW of fusion power generated in a compact, high field (B 0 = 9.2 T) tokamak that is approximately the size of JET (R 0 = 3.3 m). Taking advantage of ARC’s novel design – demountable high temperature superconductor toroidal field (TF) magnets, poloidal magnetic field coils located inside the TF, and vacuum vessel (VV) immersed in molten salt FLiBe blanket – this follow-on study has identified innovative and potentially robust power exhaust management solutions. The superconducting poloidal field coil set has been reconfigured to produce double-null plasma equilibria with a long-leg X-point target divertor geometry. Here this design choice is motivated by recent modeling which indicates that such configurations enhance power handling and may attain a passively-stable detachment front that stays in the divertor leg over a wide power exhaust window. A modified VV accommodates the divertor legs while retaining the original core plasma volume and TF magnet size. The molten salt FLiBe blanket adequately shields all superconductors, functions as an efficient tritium breeder, and, with augmented forced flow loops, serves as an effective single-phase, low-pressure coolant for the divertor, VV, and breeding blanket. Advanced neutron transport calculations (MCNP) indicate a tritium breeding ratio of ∼1.08. The neutron damage rate (DPA/year) of the remote divertor targets is ∼3–30 times lower than that of the first wall. The entire VV (including divertor and first wall) can tolerate high damage rates since the demountable TF magnets allow the VV to be replaced every 1–2 years as a single unit, employing a vertical maintenance scheme. A tungsten swirl tube FLiBe coolant channel design, similar in geometry to that used by ITER, is considered for the divertor heat removal and shown capable of exhausting divertor heat flux levels of up to 12 MW/m 2 . Several novel, neutron tolerant diagnostics are explored for sensing power exhaust and for providing feedback control of divertor conditions over long time scales. These include measurement of Cherenkov radiation emitted in FLiBe to infer DT fusion reaction rate, measurement of divertor detachment front locations in the divertor legs with microwave interferometry, and monitoring “hotspots” on the divertor chamber walls via IR imaging through the FLiBe blanket.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Demonstration of RELAP5-3D for transient analysis of a dual coolant lead lithium fusion blanket concept

Our research aims to build a multiphysics framework for transient analysis of the Dual- Coolant Lead-Lithium (DCLL) blanket design of the proposed Fusion Nuclear Science Facility (FNSF) for all Onticipated Operational Occurrences (AOOs) using Reduced Order Models (ROMs). This paper presents an assessment of using RELAP5-3D for transient thermal-hydraulic blanket analysis of the DCLL design. Preliminary validation studies for the RELAP5-3D properties were conducted using a representative vertical flow loop model and a comparison study using experimental data from the thermal convection corrosion loops at ORNL. These studies inspected the thermal hydraulic response of Lead-Lithium Eutectic (PbLi) systems within the RELAP5-3D code; mainly pressure drop and heat transfer, as compared to analytical calculations and experimental data. The Magnetohydrodynamic (MHD) pressure drop effect for liquid metal under the effects of a uniform magnetic field was implemented into our models using an equivalent forms loss coefficient based on the phasic momentum equations. We verified our implementation of MHD pressure drop within RELAP5-3D using a systematic approach consisting of two studies. Models were developed to perform comparison studies based on experimental data from the Argonne Liquid metal EXperiment (ALEX) facility and the Magnetohydrodynamic PbLi Experiment (MaPLE) facility. Using the developed validation basis, we built a simplified DCLL channel model within RELAP5-3D, inspected MHD pressure drop and performed transient temperature analysis. The DCLL channel model used radial heating data from the International Thermonuclear Experimental Reactor (ITER) which was normalized to the FNSF design. Here, a representative startup transient was performed using a relative power curve from the initial ramp up of a long-term power pulse of the Tore Supra reactor. This study demonstrated that RELAP5-3D ROMs are capable of accurate transient analysis of the DCLL blanket. We have since utilized MCNP to develop heating profiles based on the FNSF design and are working toward implementing them into our DCLL model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Developments in Online Monitoring Technologies for Autonomous Microreactor Operations

This report presents the results of an ongoing research and development (R&D) effort to develop an online monitoring (OLM) system to support autonomous microreactor operations. A key component of this work is an evaluation of Artificial Intelligence (AI) and Machine Learning (ML) techniques to identify, diagnose, and predict problems with sensors and processes of the reactor. As described herein, selected methods of AI/ML were used to identify and diagnose anomalous sensor and system behaviors using data from a thermal-hydraulic flow loop and from operating nuclear power plants. This work serves to further the state-of-the-art in OLM technologies for nuclear reactor applications and will ultimately result in a comprehensive system to enable OLM of critical structures, systems, components, and processes in microreactors.

Machine learning↗
DOE OSTI2024

SPIDARman: System-Level Physics-Informed Detection of Anomalies in Reactor Collected Data Considering Human Errors

In nuclear power plants (NPPs), anomalies arising from sensors or human errors (HEs) can undermine the performance and reliability of plant operations. Anomaly detection models can be employed to detect sensor errors and HEs. Additionally, physics-informed machine learning models can utilize the known physics of the system, as described by mathematical equations, to ensure that sensor values are consistent with physical laws. Hence, we propose SPIDARman: System-level Physics-Informed Detection of Anomalies in Reactor Collected Data Considering Human Errors, a holistic physics-informed anomaly detection approach based on generative adversarial networks (GANs) to detect anomalies in both automatically collected sensor data and manually collected surveillance data. Here we test our approach on data collected from a flow loop testbed, showcasing its potential to detect anomalies. Results demonstrate that the proposed model performs better than the baseline GAN-based models in detecting sensor and surveillance anomalies, suggesting the potential of physics-informed anomaly detection GAN models in NPPs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Reinforcement Learning for Anomaly Detection in Nuclear Power Plant Operation and Maintenance

In nuclear power plants (NPPs), timely identification of sensor and human errors is critical to ensure safe and efficient plant operations. Anomaly detection models can be employed for this task. However, traditional anomaly detection approaches may have high dependency on labeled datasets and struggle with adaptability in complex, dynamic environments. Reinforcement learning (RL) has demonstrated significant potential in fault diagnosis and anomaly detection; however, its application to anomaly detection in NPPs remains a relatively underexplored research direction. Hence, to address this gap, in this study, we present a novel physics-informed reinforcement learning model, PIRL-AD: Physics-Informed Reinforcement Learning for Anomaly Detection, that integrates domain knowledge from calorimetric equations into the RL framework for enhanced sensor and human error anomaly detection. We evaluate the performance of PIRL-AD against a non-physics informed RL benchmark and a support vector machine (SVM) on data collected from a forced flow loop testbed. Experimental results suggest that PIRL-AD outperforms other baselines on a range of anomalous datasets that include both sensor and human-induced anomalies across key performance metrics, statistically outperforming the RL and SVM benchmarks with respect to geometric mean (respectively, 92.96% vs. 91.06% vs. 83.01%) and F1-score (respectively, 89.23% vs. 86.98% vs. 77.01%). Furthermore, the findings suggest the potential of physics-integrated reinforcement learning models for enhanced anomaly detection performance in NPPs.

Reinforcement learning↗
DOE OSTI2025

Accelerated Irradiation Testing and Post-Irradiation Characterization: U.S.-Based Capabilities for Advanced Nuclear Systems and Radioisotope Production

Irradiation experiments and post-irradiation examinations, together referred to as irradiation testing (IRT), are prerequisites for nuclear fuel and material qualification for the deployment of new and advanced reactors, as well as radioisotope production, thereby ensuring regulatory compliance. Qualified research and test reactors (RTRs) and testing facilities are essential to enable IRT to verify performance and safety under prototypical reactor conditions. In the past, qualification of new fuels or structural materials required about 20 years. Synergist strategies, advanced tools, and qualified methods are needed to greatly reduce this timeframe of IRT and radioisotope production. This study, termed accelerated-IRT, focuses on identifying gaps and leveraging U.S.-based RTRs and material testing capabilities, leveraging the preliminary evaluation and qualification of selected RTRs to provide a generic as well as specific-case solution paths forward, ensuring adherence to stringent regulatory standards. Furthermore, IRT and radioisotope production utilizing qualified RTRs necessarily includes modeling and simulation to support the design (i.e. neutronics, thermal, and structural aspects) and manufacturing of irradiation test specimens, vehicles, capsules, apparatuses, and flow loops. In addition, IRT can be improved by applying advanced manufacturing techniques and in-pile sensors and instrumentation, as discussed in this study.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Self-assembled reconfigurable pump architectures via magnetic colloidal swarms

Self-assembled swarms of interactive active units, which are adaptive and dynamically reconfigurable to accommodate different functionalities, represent a promising platform for the development of next-generation robotics. Here, we utilize the emergent collective behavior of active magnetic colloids confined in quasi-two-dimensional arrays of overlapping wells to demonstrate the self-organization of a colloidal swarm into a dynamic pump architecture capable of controlled transport of passive cargo particles. This dynamic architecture provides a global unidirectional looping flow pattern along the entire length of the system. We show that the flow direction of the dynamic swarm-based pump can be externally controlled by a phase shift of a driving magnetic field energizing the swarm. The experimental observations are supported by computational modeling based on phenomenological coarse-grained particle dynamics coupled to shallow-water Navier-Stokes hydrodynamics. In conclusion, our findings demonstrate how the emergent collective behavior of a swarm can be orchestrated into a desired functionality by exploiting the interplay between activity and confinement potentials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Preliminary Assessment of Additively Manufactured Cooling Channel Performance for Helium-Cooled Blanket Concepts

Sufficient cooling of the blanket first wall remains a critical challenge for the design and deployment of fusion power plants. Helium has been targeted as a potential blanket coolant due to its inertness and low neutron interactivity, among other advantages. However, the low thermal mass of helium creates a need for heat transfer enhancements in coolant channels to provide adequate cooling to the blanket’s first wall. Toward this end, a series of ribbed flow channels of various rib cross sections and configurations has been produced via additive manufacturing (AM) to study the efficacy of AM for first wall heat transfer enhancement and the optimization of heat transfer geometries. Helium cooling performance is studied in AM test articles at 4 MPa operating pressure, Reynolds numbers up to 197 000, and outer surface heat fluxes up to 42 kW/m 2 in the recently commissioned helium flow loop experiment (HFLE). Preliminary results of this study are presented herein. Heat transfer performance of nominally smooth (i.e., featureless) AM channels is quantified via measured Nusselt numbers and friction factors and compared to off-the-shelf smooth pipe experiments. Results are compared to existing correlations and used to discuss the effects of the AM processes on thermal-hydraulic performance. It is seen that the inherent roughness of the AM channels leads to an increase in both heat transfer coefficient and pressure drop when compared to the conventional pipe. In conclusion, recommendations are made for future studies based on these findings and additional considerations for the deployment of AM blanket cooling components.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Knowledge-Informed Uncertainty-Aware Machine Learning for Time Series Forecasting of Dynamical Engineered Systems

The high complexity and multiscale nature of many engineered systems—such as those in nuclear power plants—make representing and forecasting their dynamic behavior challenging. Physics-based models can be overly complex and computationally intractable, whereas machine learning (ML) tools are often data-hungry and prone to unphysical solutions. This study proposes a knowledge-informed ML-aided hybrid residual modeling approach that offers accurate and efficient time series forecasting for the operation of dynamical engineered systems. Hybrid residual modeling entails a baseline solution from domain knowledge and known physics expressions about the system dynamics integrated with an ML model to capture undiscovered information from the mismatch (i.e., residuals) between true states from measurements and baseline-predicted outputs. This study further quantifies the ML model uncertainty to provide trustworthy solutions. Real-time operational data from thermal-hydraulic flow loops of the cryogenic moderator system in Oak Ridge National Laboratory’s Spallation Neutron Source facility were used to demonstrate the potential of knowledge-informed uncertainty-aware ML in real-world applications. The state variables of the cryogenic helium loop were modeled with (1) first principles–based system identification (sysID), (2) long short-term memory (LSTM) neural network, and (3) hybrid sysID (baseline) + LSTM (residual). The superior predictive capability of the sysID+LSTM model versus stand-alone sysID and LSTM is confirmed by average performance metrics and individual data points across different prediction horizons. By creating a robust representation of the underlying physical system, the widely applicable hybrid residual modeling approach will enable the future development of digital twins for performance prediction, prognostics, and operation control.

Zhao, Xingang↗
DOE OSTI2011

ISOLOK VALVE ACCEPTANCE TESTING FOR DWPF SME SAMPLING PROCESS

Evaluation of the Defense Waste Processing Facility (DWPF) Chemical Process Cell (CPC) cycle time identified several opportunities to improve the CPC processing time. Of the opportunities, a focus area related to optimizing the equipment and efficiency of the sample turnaround time for DWPF Analytical Laboratory was identified. The Mechanical Systems & Custom Equipment Development (MS&CED) Section of the Savannah River National Laboratory (SRNL) evaluated the possibility of using an Isolok{reg_sign} sampling valve as an alternative to the Hydragard{reg_sign} valve for taking process samples. Previous viability testing was conducted with favorable results using the Isolok sampler and reported in SRNL-STI-2010-00749 (1). This task has the potential to improve operability, reduce maintenance time and decrease CPC cycle time. This report summarizes the results from acceptance testing which was requested in Task Technical Request (TTR) HLW-DWPF-TTR-2010-0036 (2) and which was conducted as outlined in Task Technical and Quality Assurance Plan (TTQAP) SRNL-RP-2011-00145 (3). The Isolok to be tested is the same model which was tested, qualified, and installed in the Sludge Receipt Adjustment Tank (SRAT) sample system. RW-0333P QA requirements apply to this task. This task was to qualify the Isolok sampler for use in the DWPF Slurry Mix Evaporator (SME) sampling process. The Hydragard, which is the current baseline sampling method, was used for comparison to the Isolok sampling data. The Isolok sampler is an air powered grab sampler used to 'pull' a sample volume from a process line. The operation of the sampler is shown in Figure 1. The image on the left shows the Isolok's spool extended into the process line and the image on the right shows the sampler retracted and then dispensing the liquid into the sampling container. To determine tank homogeneity, a Coliwasa sampler was used to grab samples at a high and low location within the mixing tank. Data from the two locations were compared to determine if the contents of the tank were well mixed. The Coliwasa sampler is a tube with a stopper at the bottom and is designed to obtain grab samples from specific locations within the drum contents. A position paper (4) was issued to address the prototypic flow loop issues and simulant selections. A statistically designed plan (5) was issued to address the total number of samples each sampler needed to pull, to provide the random order in which samples were pulled and to group samples for elemental analysis. The TTR required that the Isolok sampler perform as well as the Hydragard sampler during these tests to ensure the acceptability of the Isolok sampler for use in the DWPF sampling cells. Procedure No.L9.4-5015 was used to document the sample parameters and process steps. Completed procedures are located in R&D Engineering job folder 23269.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

High Temperature 300°C Directional Drilling System

Many countries around the world, including the USA, have untapped geothermal energy potential. Enhanced Geothermal Systems (EGS) technology is needed to economically utilize this resource. Temperatures in some EGS reservoirs can exceed 300°C. To effectively utilize EGS resources, an array of injector and production wells must be accurately placed in the formation fracture network. This requires a high temperature directional drilling system. Most commercial services for directional drilling systems are rated for 175°C while geothermal wells require operation at much higher temperatures. Two U.S. Department of Energy (DOE) Geothermal Technologies Program (GTP) projects have been initiated to develop a 300°C capable directional drilling system, the first developing a drill bit, directional motor, and drilling fluid, and the second adding navigation and telemetry systems. This report is for the first project, “High Temperature 300°C Directional Drilling System, including drill bit, directional motor and drilling fluid, for enhanced geothermal systems,” award number DE-EE0002782. The drilling system consists of a drill bit, a directional motor, and drilling fluid. The DOE deliverables are three prototype drilling systems. We have developed three drilling motors; we have developed four roller-cone and five Kymera® bits; and finally, we have developed a 300°C stable drilling fluid, along with a lubricant additive for the metal-to-metal motor. Metal-to-metal directional motors require coatings to the rotor and stator for wear and corrosion resistance, and this coating research has been a significant part of the project. The drill bits performed well in the drill bit simulator test, and the complete drilling system has been tested drilling granite at Baker Hughes’ Experimental Test Facility in Oklahoma. The metal-to-metal motor was additionally subjected to a flow loop test in Baker Hughes’ Celle Technology Center in Germany, where it ran for more than 100 hours.

15 GEOTHERMAL ENERGY↗
DOE OSTI2016

Pre-Conceptual Design for Northstar ⁹⁹Mo Process Tritium Removal System

In this report we describe a preliminary concept for a Tritium Removal System (TRS) to remove tritium that is generated in the ⁹⁹Mo production process. Preliminary calculations have been performed to evaluate an approximate size for the system. The concept described utilizes well-established detritiation technology based on catalytic oxidation of tritium and tritiated hydrocarbons to water in a high temperature (400 °C) reactor and capture of water in a molecular sieve bed. The TRS concept involves use of a single system that would cycle through each of the seven online target systems and remove tritium that has been accumulated after one week’s run time. The TRS would perform cleanup operations on each target system for a period of approximately 24 hours. This would occur while the system is still online and just prior to target replacement, so tritium levels would at their minimum values for target replacement. In the concept, during normal operation a small fraction (1%) of the helium recirculating in the system would be diverted through the TRS and returned to the flow loop. With this approach sufficient levels of detritiation can be accomplished in a 24 hour period. In the study it was found that because of the need to maintain low oxygen levels in the system (<100 ppm) this increases the size of the catalytic reactor. As a result of this finding, consideration should be given to other methods for removing tritium from the system. Other methods such as catalytic exchange of tritium with an unsaturated organic compound and subsequent trapping on activated carbon or molecular sieve could offer advantages of reducing reactor size and operation at lower reactor temperature. However the most significant advantage of such an approach would be the ability to operate in very low oxygen environments, which would eliminate any concerns for oxidation of the target.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2016

On Line Enrichment Monitor (OLEM) UF 6 Tests for 1.5" Sch40 SS Pipe, Revision 1

As global uranium enrichment capacity under international safeguards expands, the International Atomic Energy Agency (IAEA) is challenged to develop effective safeguards approaches at gaseous centrifuge enrichment plants while working within budgetary constraints. The “Model Safeguards Approach for Gas Centrifuge Enrichment Plants” (GCEPs) developed by the IAEA Division of Concepts and Planning in June 2006, defines the three primary Safeguards objectives to be the timely detection of: 1) diversion of significant quantities of natural (NU), depleted (DU) or low-enriched uranium (LEU) from declared plant flow, 2) facility misuse to produce undeclared LEU product from undeclared feed, and 3) facility misuse to produce enrichments higher than the declared maximum, in particular, highly enriched uranium (HEU). The ability to continuously and independently (i.e. with a minimum of information from the facility operator) monitor not only the uranium mass balance but also the 235 U mass balance in the facility could help support all three verification objectives described above. Two key capabilities required to achieve an independent and accurate material balance are 1) continuous, unattended monitoring of in-process UF 6 and 2) monitoring of cylinders entering and leaving the facility. The continuous monitoring of in-process UF 6 would rely on a combination of load-cell monitoring of the cylinders at the feed and withdrawal stations, online monitoring of gas enrichment, and a high-accuracy net weight measurement of the cylinder contents. The Online Enrichment Monitor (OLEM) is the instrument that would continuously measure the time-dependent relative uranium enrichment, E(t), in weight percent 235 U, of the gas filling or being withdrawn from the cylinders. The OLEM design concept combines gamma-ray spectrometry using a collimated NaI(Tl) detector with gas pressure and temperature data to calculate the enrichment of the UF 6 gas within the unit header pipe as a function of time. The OLEM components have been tested on ORNL UF 6 flow loop. Data were collected at five different enrichment levels (0.71%, 2.97%, 4.62%, 6.0%, and 93.7%) at several pressure conditions. The test data were collected in the standard OLEM N.4242 file format for each of the conditions with a 10-minute sampling period and then averaged over the span of constant pressures. Analysis of the collected data has provided enrichment constants that can be used for 1.5” stainless steel schedule 40 pipe measurement sites. The enrichment constant is consistent among all the wide range of enrichment levels and pressures used.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗