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At least 145 records · Page 8

129 I, 99 Tc, and U Distribution Coefficients of Subsurface Sediments Collected from the Proposed Site of the Environmental Management Disposal Facility

Performance Assessment calculations were completed in 2020 to evaluate the Environmental Management Disposal Facility (EMDF), a proposed new low-level radioactive waste (LLW) disposal facility on the U.S. Department of Energy’s Oak Ridge Reservation (ORR). Among the large number of input parameters needed for such calculations, are distribution coefficients (K d values; radionuclide concentration solid: liquid ratio) that provide a measure of the tendency of radionuclides to bind to sediments. The objective of this study was to measure K d values of three radionuclides that may pose a disproportionately large amount of risk, U, iodine-129 ( 129 I) and technetium-99 ( 99 Tc). The average 129 I K d value for the 14 geological materials recovered from the proposed EMDF site was 37.8 mL/g and ranged from 0.45 to 140.9 mL/g. These values were consistent, but somewhat larger than previous measurements made with ORR sediments and were about an order of magnitude greater than those used in previous EMDF PA calculations. The median 99 Tc K d value was 365.7 mL/g, much greater than previously reported using ORR geological materials. Five of the 14 tested geological materials sorbed large quantities of 99 Tc, suggesting that the weakly sorbing 99 Tc(VII) species had been reduced to the sparingly soluble 99 Tc(IV) species. The five strongly sorbing sediments had apparent 99 Tc solubility values of approximately <10 -8 mol/L. The median U K d value was 5,726 mL/g. All of the tested geological materials had large K d values, ranging from 625 to >10,208 mL/g. Among the sediment samples that exhibited strong U binding, the apparent solubility value was approximately <10 -9 mol/L. Based on sediment properties and general ORR geological considerations, it was proposed that much of the 129 I and 99 Tc retention could be attributed to the site materials exhibiting low pH (average pH = 4.94), and/or the elevated levels of iron oxides, manganese oxides, and natural organic matter. Similarly, the extremely high U binding measured in these sediments may also be attributed to the low conditions of carbonates, which can complex and therefore solubilize uranyl in these tests due to the low pH, and also the relatively high concentrations of iron and organic coatings on these samples. An implication of this study is that the areas of the EMDF subsurface environment may have natural properties for attenuating 129 I, 99 Tc, and U movement, and potentially other radionuclides, thereby possibly reducing risk posed by burial of LLW at this site.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Versatile compact heater design for in situ nano-tomography by transmission X-ray microscopy

A versatile, compact heater designed at National Synchrotron Light Source-II for in situ X-ray nano-imaging in a full-field transmission X-ray microscope is presented. Heater design for nano-imaging is challenging, combining tight spatial constraints with stringent design requirements for the temperature range and stability. Finite-element modeling and analytical calculations were used to determine the heater design parameters. Performance tests demonstrated reliable and stable performance, including maintaining the exterior casing close to room temperature while the heater is operating at above 1100°C, a homogenous heating zone and small temperature fluctuations. Two scientific experiments are presented to demonstrate the heater capabilities: (i) in situ 3D nano-tomography including a study of metal dealloying in a liquid molten salt extreme environment, and (ii) a study of pore formation in icosahedral quasicrystals. The progression of structural changes in both studies were clearly resolved in 3D, showing that the new heater enables powerful capabilities to directly visualize and quantify 3D morphological evolution of materials under real conditions by X-ray nano-imaging at elevated temperature during synthesis, fabrication and operation processes. This heater design concept can be applied to other applications where a precise, compact heater design is required.

36 MATERIALS SCIENCE↗

Fundamental Investigations into the Properties and Performance of Advanced Materials

Intelligent engineering designs require an accurate understanding of material behavior, since any uncertainties or gaps in knowledge must be counterbalanced with heightened factors of safety, leading to overdesign. Therefore, building better structures and pushing the performance of new components requires an improved understanding of the thermomechanical response of advanced materials under service conditions. This dissertation provides fundamental investigations of several advanced materials: thermoset polymers, a common matrix material for fiber-reinforced composites and nanocomposites; aluminum alloy 7075-T6 (AA7075-T6), a high-performance aerospace material; and ceramic matrix composites (CMCs), an advanced composite for extreme-temperature applications. To understand matrix interactions with various interfaces and nanoinclusions at their fundamental scale, the properties of thermoset polymers are studied at the atomistic scale. An improved proximity-based molecular dynamics (MD) technique for modeling the crosslinking of thermoset polymers is carefully established, enabling realistic curing simulations through its ability to dynamically and probabilistically perform complex topology transformations. The proximity-based MD curing methodology is then used to explore damage initiation and the local anisotropic evolution of mechanical properties in thermoset polymers under uniaxial tension with an emphasis on changes in stiffness through a series of tensile loading, unloading, and reloading experiments. Aluminum alloys in aerospace applications often require a fatigue life of over 109 cycles, which is well over ii the number of cycles that can be practically tested using conventional fatigue testing equipment. In order to study these high-life regimes, a detailed ultrasonic cycle fatigue study is presented for AA7075-T6 under fully reversed tension-compression loading. The geometric sensitivity, frequency effects, size effects, surface roughness effects, and the corresponding failure mechanisms for ultrasonic fatigue across different fatigue regimes are investigated. Finally, because CMCs are utilized in extreme environments, oxidation plays an important role in their degradation. A multiphysics modeling methodology is thus developed to address the complex coupling between oxidation, mechanical stress, and oxygen diffusion in heterogeneous carbon fiber-reinforced CMC microstructures.

Schichtel, Jacob J.↗

Achieving ultrahigh modulus of resilience and enhanced thermal stability in ZnO x /SU-8 interpenetrating network polymer nanocomposite nanopillars

The modulus of resilience, a mechanical property that quantifies the maximum strain energy density a material can store during elastic deformation, is a crucial parameter for materials used in flexible displays, micro/nano-electro-mechanical system (M/NEMS) actuators, and ultra-sensitive pressure sensors. In this study, ZnO x /SU-8 nanocomposite nanopillars with a diameter of 300 nm, fully infiltrated with a uniformly distributed, interpenetrating amorphous ZnO x filler network, were synthesized via vapor-phase infiltration (VPI). In-situ uniaxial nano-compression tests revealed that the modulus of resilience of ZnO x /SU-8 reaches ∼ 12 MJ/m 3 , which is an ultrahigh value among all engineering materials with comparable strength. In addition, the synthesis fidelity, inorganic infiltration depth, and mechanical performance were all significantly improved compared to VPI-synthesized AlO x nanocomposites. Thermal stability, another key requirement for M/NEMS device materials operating under extreme environments, was also notably enhanced. Furthermore, partial crystallization of the amorphous ZnO x fillers during annealing contributed to an additional increase in modulus of resilience, reaching up to ∼ 13.9 MJ/m 3 . This work presents an effective fabrication strategy for producing nanostructured organic–inorganic hybrid nanocomposites with ultrahigh modulus of resilience and superior thermal stability, paving the way for their integration into next-generation flexible displays and high-performance M/NEMS devices working under harsh environments.

36 MATERIALS SCIENCE↗

The Mu2e crystal calorimeter

The Mu2e experiment at Fermilab will search for the charged-lepton flavour violating conversion of negative muons into electrons in the coulomb field of an Al nucleus, planning to reach a single event sensitivity of about $3\cdot10^{−17}$, four orders of magnitude beyond the current best limit.The conversion electron has a clear monoenergetic signature at 104.967 MeV, slightly below the muon rest mass, and will be identified by a complementary measurement carried out by a high-resolution tracker and an electromagnetic calorimeter (EMC). The calorimeter is composed of 1348 pure CsI crystals, each read by two custom UV-extended SiPMs, that are arranged in two annular disks. The EMC should achieve better than 10% energy resolution and 500 ps timing resolution for 100 MeV electrons and maintain extremely high levels of reliability and stability and in a harsh operating environment with high vacuum, 1 T B-field and radiation exposures up to 100 krad and $10^{12} \rm{n}_\rm{1MeVeq}/\rm{cm}^{2}$.The calorimeter technological choice, along with the design of the custom front-end electronics, cooling and mechanical systems were validated through an electron beam test on a large-scale 51-crystals prototype (Module-0) and extensive test campaigns that characterised and verified the performance of crystals, photodetectors, analogue and digital electronics. This included hardware stress tests and irradiation campaigns with neutrons, protons, and photons.The production and QC phases of all calorimeter components is completed apart for the digital electronics that has been revised for improving its resilience to SEU and SEL. A series of vertical slice tests with the final electronics is being carried out on the Module-0 at LNF along with the implementation and validation of the calibration procedures. The first disk has been assembled in 2022 while the second disk is under assembly at the moment of writing. Status of construction will be summarised, along with plans for commissioning and first calibration of the fully assembled disks.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Microgrid energy scheduling under uncertain extreme weather: Adaptation from parallelized reinforcement learning agents

Microgrids are useful solutions for integrating renewable energy resources and providing seamless green electricity to minimize carbon footprint. In recent years, extreme weather events happened often worldwide and caused significant economic and societal losses. Such events bring uncertainties to the microgrid energy scheduling problems and increase the challenges of microgrid operation. Traditional optimization approaches suffer from the inaccuracy of the uncertain microgrid model and the unseen events. Existing reinforcement learning (RL) - based approaches are also hampered by the limited generalization and the increasing computational burden when stochastic formulations are required to accommodate the uncertainties. This paper proposes a new parallelized reinforcement learning (PRL) method based on the probabilistic events to handle the microgrid energy uncertainties. Specifically, several local learning agents are employed to interact with pertinent microgrid environments in a distributed manner and report outcomes to the global agent, which will optimize microgrid energy resources online during extreme events. The stochastic microgrid energy optimization problem is reformulated to include all possible scenarios with probabilities. The advantage estimate functions of learning agents are designed with a backward sweep to transfer the outcomes to the value function updating process. Two simulation studies, stochastic optimization and online testing, are performed to compare with several existing RL approaches. Results substantiate that the proposed PRL method can achieve up to 20% optimization performance improvement with 4 and 28 times less computation cost than Q-learning with experience replay and multi-agent Q-learning approaches, respectively.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Operation of AlGaN Channel HEMTs at 850 °C With ON/OFF Ratio >10 4

Here, we report 850 ° C operation of ultrawide bandgap (UWBG) Al-rich Al 0.68 Ga 0.32 N channel high electron mobility transistors (HEMTs) at atmospheric pressure in nitrogen ambient. Temperature dependent DC electrical characteristics were measured in situ up to 850 ° C, after exposure to 850 ° C for 60 minutes, and at 25 ° C after high temperature testing. At 850 ° C (time, t = 0 min), all HEMTs tested maintained an on/off ratio greater than 10 4 (maximum of 4.6 × 10 4 ). The threshold voltage demonstrated excellent stability with less than ±10% deviation. After returning to 25 ° C, the devices showed negligible degradation. In fact, the off-state gate current decreased and on/off ratio slightly increased. The robustness of these UWBG AlGaN transistors at temperatures up to 850 ° C demonstrates their viability for extreme environment applications.

AlGaN↗

Cooperative Research and Development Agreement among National Energy Technology Laboratory, Advanced Manufacturing LLC, and Connecticut Center for Advanced Technology [Abstract]

The National Energy Technology Laboratory (NETL), Advanced Manufacturing LLC (AMLLC) and Connecticut Center for Advanced Technology (CCAT) will collaborate to develop and manufacture cost-effective, oxide dispersion-strengthened, NiCrFeCo-rich high entropy alloys that are superior to Nickel-based superalloys (e.g. IN740) for repair or replacement service in extreme environments. The new alloys can result in higher efficiency and reduced cost of advanced power systems such as advanced ultra-supercritical (AUSC) boilers and gas turbines. High throughput, multiscale computational modeling will be performed to accelerate alloy discovery by interrogating the intrinsic properties of the alloys including thermodynamic, kinetic, and mechanical properties. Validation and evaluation will be performed, including additive manufacturing, microstructure characterization, and mechanical properties tests.

36 MATERIALS SCIENCE↗

Magnetic Field Sensing via Multi-Material Acoustic Sensing Optical Fibers with Magnetostrictive Cladding Inclusions

In this conducted research, optical fiber sensors are used to measure low strength alternating magnetic fields. Various fiber sensor configurations are tested and investigated to demonstrate sensing capabilities at different field magnitudes and frequencies. Distributed acoustic sensing fibers (DAS) have been largely studied and documented across a variety of applications and sensing systems. This research uses the DAS technology in tandem with magnetostrictive materials to create a distributed multi-material optical fiber magnetic sensor. Magnetic sensing has high demand across different fields and often runs into challenges of extreme environments including high temperature, corrosion, and areas with poor accessibility. The robust and distributed nature of optical fiber sensors which can be cheaply produced for long lengths is an attractive option over other single point magnetic sensors. In down hole applications specifically, having a distributed sensor able to be deployed easily and over long distances for magnetic sensing would be a large improvement to bulkier traditional magnetometers. In the conducted study, different magnetostrictive materials are implemented in distributed optical fiber sensors to analyze and compare the effective sensitivity and potential commercial viability. Nickel, galfenol alloy, and MetGlas alloy inclusions are drawn into fused silica optical fibers with Bragg gratings inscribed later on for DAS capability. Each was investigated for its response to varying AC magnetic fields to determine relative sensitivity and resolution for distributed magnetic field sensing.

Dejneka, Zach↗

Adrastea: An Efficient FPGA Design Environment for Heterogeneous Scientific Computing and Machine Learning

We present Adrastea, an efficient FPGA design environment for developing scientific machine learning applications. FPGA development is challenging, from deployment, proper toolchain setup, programming methods, interfacing FPGA kernels, and more importantly, the need to explore design space choices to get the best performance and area usage from the FPGA kernel design. Adrastea provides an automated and scalable design flow to parameterize, implement, and optimize complex FPGA kernels and associated interfaces. We show how virtualization of the development environment via virtual machines is leveraged to simplify the setup of the FPGA toolchain while deploying the FPGA boards and while scaling up the automated design space exploration to leverage multiple machines concurrently. Adrastea provides an automated build and test environment of FPGA kernels. By exposing design space hyper-parameters, Adrastea can automatically search the design space in parallel to optimize the FPGA design for a given metric, usually performance or area. Adrastea simplifies the task of interfacing with the FPGA kernels with a simplified interface API. To demonstrate the capabilities of Adrastea, we implement a complex random forest machine learning kernel with 10,000 input features while achieving extremely low computing latency without loss of prediction accuracy, which is required by a scientific edge application at SNS. We also demonstrate Adrastea using an FFT kernel and show that for both applications Adrastea is able to systematically and efficiently evaluate different design options, which reduced the time and effort required to develop the kernel from months of manual work to days of automatic builds.

Young, Aaron↗

Demonstration and performance testing of extreme-resolution simulations with static meshes on Summit (CPU & GPU) for a parked-turbine configuration and an actuator-line (mid-fidelity model) wind farm configuration (ECP-Q4 FY2020 Milestone Report)

The goal of the ExaWind project is to enable predictive simulations of wind farms comprised of many megawatt-scale turbines situated in complex terrain. Predictive simulations will require computational fluid dynamics (CFD) simulations for which the mesh resolves the geometry of the turbines and captures the rotation and large deflections of blades. Whereas such simulations for a single turbine are arguably petascale class, multi-turbine wind farm simulations will require exascale-class resources. The primary physics codes in the ExaWind simulation environment are Nalu-Wind, an unstructured-grid solver for the acoustically incompressible Navier-Stokes equations, AMR-Wind, a block-structured-grid solver with adaptive mesh refinement capabilities, and OpenFAST, a wind-turbine structural dynamics solver. The Nalu-Wind model consists of the mass-continuity Poisson-type equation for pressure and Helmholtz-type equations for transport of momentum and other scalars. For such modeling approaches, simulation times are dominated by linear-system setup and solution for the continuity and momentum systems. For the ExaWind challenge problem, the moving meshes greatly affect overall solver costs as reinitialization of matrices and recomputation of preconditioners is required at every time step. The choice of overset-mesh methodology to model the moving and non-moving parts of the computational domain introduces constraint equations in the elliptic pressure-Poisson solver. The presence of constraints greatly affects the performance of algebraic multigrid preconditioners.

17 WIND ENERGY↗

Assessment of Commercial Composite Power Pole Performance

The objective of this report is to assess the performance of composite poles, considering price, durability, resilience to the effects of extreme weather, ongoing maintenance costs, ease of repair, preplacement or upgrading giving special consideration to performance in watersheds and flood prone environments. The report starts with a description of the history and functional requirements of power pole. This is followed by a survey of existing composite pole manufacturing processes with a survey of existing knowledge base answering the above performance requirements. For the information not currently available to the public, an overview of testing procedures is outlined. Finally, an overview of emerging trends in composites and potential opportunities to address technical and economic shortfalls is proposed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

SURFACE FINISHING AND ELECTROLESS NICKEL PLATING OF ADDITIVELY MANUFACTURED (AM) METAL COMPONENTS

This study investigates the application of electroless nickel deposition on additively manufactured stainless steel samples. Current additive manufacturing (AM) technologies produce metal components with a rough surface. Rough surfaces generally exhibit fatigue characteristics, increasing the probability of initiating a crack or fracture to the printed part. For this reason, the direct use of as-produced parts in a finished product cannot be actualized, which presents a challenge. Post-processing of the AM parts is therefore required to smoothen the surface. This study analyzes chempolish (CP) and electropolish (EP) surface finishing techniques for post-processing AM stainless steel components CP has a great advantage in creating uniform, smooth surfaces regardless of size or part geometry EP creates an extremely smooth surface, which reduces the surface roughness to the sub-micrometer level. In this study, we also investigate nickel deposition on EP, CP, and as-built AM components using electroless nickel solutions. Electroless nickel plating is a method of alloy treatment designed to increase manufactured component's hardness and surface resistance to the unrelenting environment. The electroless nickel plating process is more straightforward than its counterpart electroplating.. We use low-phosphorus (2-5% P), medium-phosphorus (6-9% P), and high-phosphorus (10-13% P). These Ni deposition experiments were optimized using the L9 Taguchi design of experiments (TDOE), which compromises the prosperous content in the solution, surface finish, plane of the geometry, and bath temperature. The pre-and post-processed surface of the AM parts was characterized by KEYENCE Digital MicroscopeVHX-7000 and Phenom XL Desktop SEM. The experimental results show that electroless nickel deposition produces uniform Ni coating on the additively manufactured components up to 20 μm per hour. Mechanical properties of as-built and Ni coated AM samples were analyzed by applying a standard 10 N scratch test. Nickel coated AM samples were up to two times scratch resistant compared to the as-built samples. This study suggests electroless nickel plating is a robust viable option for surface hardening and finishing AM components for various applications and operating conditions.

Keywords: additive manufacturing, fatigue, chempol↗

Nuclear reactor radiation and temperature effects on piezoelectric surface acoustic wave devices

Surface acoustic wave (SAW) resonators were characterized in-situ in a nuclear reactor environment at high temperature. Devices based on lithium niobate (LiNbO 3 ), aluminum nitride (sc-AlN), and thin-film aluminum nitride on sapphire substrate (AlN/sapphire) were tested up to 400 °C temperature and 1.9 × 10 12 n/cm 2 s neutron flux. Shifts in device resonant frequency were detected in response to temperature and neutron flux. Devices undergo a frequency change when exposed to neutron flux. At 300 °C, AlN/sapphire produced the strongest neutron flux response about 1.02 ppm at 1.27 × 10 12 n/cm 2 s neutron flux (5.7 × 10 4 rad-Si/hr neutron dose rate), compared to 0.30 ppm for LiNbO 3 and 0.17 ppm for sc-AlN. While the transient kinetics in response to step change in neutron flux support the defect-accumulation mechanism, the concurrent measurement of device temperature using resistive temperature sensor suggests additional heating caused by absorption of gamma rays can also play a role. These results make SAW devices attractive candidates for sensor applications in extreme environments.

Aluminum nitride↗

ROADRUNNER MiniFuel Experiment: Readiness for Insertion

The Research On ADvancing the peRformance of UraNium Nitrides in Extreme enviRonments (ROADRUNNER) campaign is a collaborative irradiation experiment designed to evaluate the performance of uranium nitride (UN) fuel fabricated with controlled variations in density and impurity content. Oak Ridge National Laboratory’s MiniFuel irradiation platform and the High Flux Isotope Reactor (HFIR) are being used to irradiate six targets containing 36 UN miniature disks. These targets have been assembled to systematically investigate burnup and temperature effects under accelerated irradiation conditions. This report documents the finalized test plan, describes the experiment assembly and subcapsule integration process, and confirms the readiness of all ROADRUNNER targets for HFIR insertion. All targets have passed quality control procedures, and five have begun irradiation. The campaign will provide critical performance data to support fuel model validation and future UN qualification efforts.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Active Reduction of Apparent Cable Capacitance

This paper presents a method for reducing apparent cable capacitance seen by sensors. The proposed method is designed for sensing in extreme environments including ultra-high temperatures, but can be applied in benign environments as well. By reducing the cable capacitance, high speed signals can be transmitted over longer distances, allowing the application of advanced control systems that require high bandwidth data for stable operation. A triaxial cable with an associated guard circuit is developed that actively reduces cable capacitance while also rejecting extraneous electric and magnetic interference on the signal. The active capacitance reduction method developed is tested experimentally and shown to reduce apparent cable capacitance to two percent of the static value.

47 OTHER INSTRUMENTATION↗

The impact of tritium phytoremediation on plant health as measured by fluorescence

Phytoremediation, using plants for soil, sediment, or water contaminant clean-up, is an established technology dependent on plant health. Tritium (3H), a radioactive isotope of hydrogen that is generally found in the environment as tritiated water (HTO), is a low-level beta emitter with a half-life of 12.32 years. Chlorophyll fluorescence (CF) for monitoring risk assessment of tritium to plant health was conducted at the Tritium Irrigation Facility (TIF) located on the US Department of Energy's Savannah River Site (SRS) near Aiken, SC. Two fluorometers were evaluated in conjunction with phytoremediation at the 25 –acre TIF where tritiated groundwater is being spray–irrigated on a mixed coniferous/deciduous forested watershed as a means of reducing tritium release to a nearby stream that serves as a tributary to the Savannah River. Tritium activity in irrigated water averaged 104 + 42 pCi mL -1 during the 2003 project. Fluorescence parameters measured by the two fluorometers were well correlated with each other (p < 0.0001). Tritium in water respired from oak leaves ranged up to 1845.13 pCi ml -1 and 2138.22 pCi ml -1 in pine needles. Trees in both the test and control sites were approximately 15 years old. In this report we demonstrated that fluorescence parameters provide an effective way to estimate the impact of HTO on plant health in a noninvasive, extremely rapid, and cost-effective manner. In the current study applying fluorometry, plants within the TIF phytoremediation site exposed to the site tritiated water were not significantly impacted by the tritium phytoremediation based on CF parameters as compared to the control, a nascent non-irrigated site.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Predicting oxidation damage in ultra high-temperature borides: A machine learning approach

Ultra-high temperature (UHT) borides are ceramics materials with melting points above 3000 °C for structural applications in extreme environments. However, at temperatures exceeding 1600 °C and under oxidizing conditions, the material suffers from detrimental degradation. Optimized design and performance of diboride materials under such extreme conditions requires filling the missing composition-microstructure-oxidation gap. This study proposes a computational data-driven framework to connect the processing and microstructure of Ultra-high temperature borides with the oxidation damage. Random Forest Regressor (RFR) model is adopted to forecast the oxide scale thickness developed after oxidation testing based on processing variables and microstructural features. The model trained on a dataset consisting of 107 samples of experimental data extracted from the literature aims to predict oxidation damage. With proper data manipulation and fine model tuning, the predictor could forecast the oxide scale thickness of UHT diborides with a Mean Absolute Error of 37.45 μm and an R-square of 0.83. This model could be used as a high-throughput scheme to design and test new UHT diborides materials computationally. Furthermore, a model with larger composition capabilities could also be developed in the future as more experimental data become available.

36 MATERIALS SCIENCE↗