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At least 361 records · Page 20

Effective Selective Area Doping for GaN Vertical Power Transistors Enabled by Innovative Materials Engineering

GaN vertical power transistors have emerged as promising candidates for future high efficiency high power electronic applications, with the potential to outperform conventional GaN lateral power devices in terms of power, breakdown, and avalanche characteristics. However, the development of current GaN vertical power transistors is seriously hindered by the poor materials performance of selective area doped p-n junctions. A mechanistic understanding of these fundamental materials issues is essential in order to achieve high performance selective area doped p-n junctions and consequently to advance the GaN vertical power transistor technology. To address this challenge, we carried out a comprehensive research program that advance fundamental knowledge in the selective area doping for GaN materials, and which will lead to the development of high performance GaN vertical power transistors. First, we developed innovative fabrication processes, including novel surface etching, surface passivation, and metalorganic chemical vapor deposition (MOCVD) growth, which provided enhanced opportunities for solving the unique challenges of selective area doping in GaN materials. Second, we performed a fundamental materials study using powerful characterization methods including transmission electron microscopy (TEM), ultraviolet (UV-), x-ray and angle-resolved photoelectron spectroscopy (UPS/XPS/ARPES), electron holography, and cathodoluminescence (CL); Third, we investigated several related issues, including Mg incorporation, polarization effects in carrier transport, and non-ideal material effects, which have rarely been explored so far. At the end of this project, we successfully demonstrated (1) fundamental understanding of selective area etching, regrowth, and doping of GaN, and associated knowledge on defects, interface, and breakdown properties. (2) Effective etch and regrowth processing recipes to achieve etch/regrowth GaN p-n diodes with very low leakage of 3.5 nA at 600 V, which meets the ARPA-E target. (2) High performance vertical GaN p-n didoes and vertical junction termination extension (JTE) devices with breakdown voltage of ~ 2 kV, and breakdown electric field of ~ 3.5 MV/cm, which are close to the performance limit of GaN. The successful outcome has resulted in new fundamental understandings in the selective area doping and regrowth process for GaN, which will lead to groundbreaking GaN vertical transistors for high performance next generation power electronics.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Ultrasonic Measurements of Temperature Profile and Heat Fluxes in Coal-Fired Power Plants (Final Report)

Many industrial processes are inaccessible or inhospitable to characterization by traditional temperature measurement methods, such as thermocouples, especially over prolonged exposure to harsh environments. Ultrasound is an established characterization technology with diverse applications ranging from medical imaging to therapies to flaw detection to nondestructive evaluation. Ultrasound may characterize solid materials and components noninvasively as a nondestructive evaluation modality and obtain internal measurements of material properties. For example, the speed of ultrasound propagation changes with Young’s modulus and Poisson’s ratio, which can be found from its measurements. Traditional ultrasonic characterization assumes all material properties remain constant with the position. When this assumption holds, a property of interest may be measured by relating it to the speed of ultrasound propagation (or a speed of sound, SOS) and measuring the SOS by timing the ultrasound propagation through a known distance. However, when a property of interest is spatially distributed, the propagation time depends on the SOS changing with the position along the ultrasound propagation path. The multiple temperature distributions may lead to an identical time of flight (TOF). Temperature is one property that impacts the speed of ultrasound and often cannot be assumed to remain constant with the position. Previously, in the context of temperature, we addressed the challenge of ultrasonic characterization of spatially distributed properties by developing a method for measuring segmental temperature distributions (MSTD). This method divides the ultrasonic propagation into segments bound by echogenic features. These features provide ultrasonic interfaces where some energy is reflected toward the receiving transducer, and the rest continues through the medium. The time-of-flight between the echoes reflected from echogenic features characterizes the spatial distribution in the properties of interest in the corresponding segment of the ultrasonic propagation path. This project demonstrated the application of the MSTD method in industrial conditions of the coal-fired power plant. We implemented the MSTD using metals and alloys waveguides, which may be the existing structure for which the temperature distribution is characterized or purposefully designed waveguides added to the structure by welding or other means specifically to quantify thermal properties using the MSTD method. Previous iterations of the MSTD method used ceramic and cementitious waveguides, which significantly attenuate ultrasound. On the other hand, low attenuation in metallic waveguides creates interactions between echogenic features which compilates the signal analysis in the segmental TOF measurements. We have established the WG design principles that minimize the interferences between trailing and primary echoes and, in some cases, eliminate them. The waveguides in which echoes do not interfere improve the timing accuracy and the robustness of ultrasonic measurements of the spatial distributions in material properties. Our emphasis remained on the estimation of the temperature distributions. We have developed general recommendations for designing ultrasonically segmented waveguides with the reduced influence of trailing echoes. Two of our waveguide designs were tested in the industry. The first waveguide was designed for insertion into a combustion zone of the utility-scale coal-fired power plant boiler. The second design allows the characterization of temperature distribution in the direction normal to the boiler’s water wall, a large heat exchanger converting the chemical energy released during combustion to the steam driving the electrical power generation turbines. These waveguides were designed to operate within a restrictive space of thermally insulated water wall and incorporate densely located echogenic features while combatting the influence of trailing echoes. The project has successfully demonstrated the feasibility of using the developed method for accurate, continuous, and robust temperature measurements in extreme environments of power generation and other industrial processes. It, therefore, has achieved its overarching goal of advancing the technology readiness level of the novel Ultrasound Measurements of Segmental Temperature Distribution (US-MSTD) method for real-time measurements of the temperature distribution and heat fluxes closer to commercial availability, developing a prototype multipoint measurement system, and validating its performance on coal-fired utility boilers. The success of this project was achieved in collaboration with the power generator, Rocky Mountain Power, and set the stage for the transfer of this technology from the laboratory to the industry.

01 COAL, LIGNITE, AND PEAT↗

Integrated Optimization and Control of a Hybrid Gas Turbine/sCO 2 Power System

During phase-I, the project team led by Echogen Power Systems (EPS) had two primary objectives based on investigating the application of gas turbines with supercritical carbon dioxide (sCO 2 ) power cycles. The first objective was to improve the overall efficiency and performance of a hybrid gas turbine/sCO 2 power system through a joint optimization of the two subsystems (gas turbine and sCO 2 power cycle) using non-linear optimization techniques that simultaneously evaluate thermal performance of the combined cycle. The hybrid power system included several points of interaction, including (but not limited to) gas turbine exhaust, fuel heating, inlet chilling and turbine cooling. The second objective was to establish a baseline transient response model of the hybrid power system and a notional microgrid and begin steps to integrate the control systems of the three major elements (gas turbine, sCO 2 cycle and grid controller). The project team established a baseline performance for a combined cycle power plant using a production gas turbine and scaled sCO 2 power cycle only utilizing exhaust heat recovery. Echogen’s non-linear techno-economic optimization code was extended by adding gas turbine component models derived from a in-house developed gas turbine design code. With the two cycles coupled by the gas turbine exhaust, design parameters of both cycles were allowed to vary simultaneously to determine performance opportunity versus isolated designs. Returning to the baseline gas turbine/sCO 2 power cycle transient models: Echogen had in-house developed sCO 2 cycle transient model in GT-Suite system simulation software, and had partnered with Siemens Finspång for gas turbine transient model, and Siemens PTI group to provide micro-grid load profile as well as hybrid power cycle generated load (power and frequency) analysis. The transient model for the SGT-750 Siemens gas turbine was a “black-box” functional mock-up interface (FMI) model developed by Siemens Industrial Turbomachinery in Finspång, Sweden. The SGT-750 is a twin-shaft gas turbine that produces 40 MW electricity with an efficiency of about 40% at ISO conditions. At 100% gas turbine throttle (load), the SGT-750 has average exhaust conditions of 114.6 kg/s and 469.8°C. The transient model for sCO 2 power cycle was developed by Echogen in GT-SUITE 1D system simulation software platform. The basic CO 2 flow circuit has single-shaft turbomachinery with net 11.5 MW electrical power output at design conditions. The power turbine has a double-ended shaft with one end connected to synchronous generator through a fixed-ratio gearbox. The other end of power turbine is connected to the compressor through a continuously variable transmission. The major components of the sCO 2 power cycle modeled include air cooled condenser/cooler, CO 2 compressor, recuperator, two waste heat exchanger coils, power turbine, continuous variable transmission, gearbox and generator. Integration of SGT-750 transient model and sCO 2 power cycle transient model was done in Matlab Simulink. In the integrated model, the gas turbine and sCO 2 power cycle interacted at two points, first one being the gas turbine exhaust gas flow rate and temperature, which were inputs to sCO 2 power cycle model. The second point was the distribution of micro-grid load demand signal between the SGT-750 generator and sCO 2 cycle generator. For a given combined-cycle load demand, the gas turbine load demand was equal to the total demand minus the sCO 2 cycle power generated. In the present study the integrated model was simulated for two cases of grid load demand: (i) for a step change, both positive-step and negative-step, in grid load demand (ii) for a micro-grid load demand curve provided by Siemens PTI group. Finally, the time series plots representing load demand versus integrated system response were presented including the sCO 2 power cycle control system performance plots. The actual generated power and frequency of both the generators, gas turbine and sCO 2 power cycle, was supplied to Siemens PTI group for dynamic grid assessment, results of which are provided in appendices.

03 NATURAL GAS↗

Graph-based Simulation Framework for Power Resilience Estimation and Enhancement

The increasing frequency of extreme weather events poses significant risks to power distribution systems, leading to widespread outages and severe economic and social consequences. This paper presents a novel simulation framework for assessing and enhancing the resilience of power distribution networks under such conditions. Resilience is estimated through Monte Carlo simulations, which simulate extreme weather scenarios and evaluate the impact on infrastructure fragility. Due to the proprietary nature of power network topology, a distribution network is synthesized using publicly available data. To generate the weather scenarios, an extreme weather generation method is developed. To enhance resilience, renewable resources such as solar panels and energy storage systems (batteries in this study) are incorporated. A customized Genetic Algorithm is proposed to determine the optimal locations and capacities for solar panels and battery installations, maximizing resilience while balancing cost constraints. Experiment results demonstrate that on a large-scale synthetic distribution network with more than 300,000 nodes and 300,000 edges, the proposed framework can efficiently evaluate the resilience, and enhance the resilience through the installations of distributed energy resources (DERs), providing utilities with valuable insights for community-level power system resilience estimation and enhancement.

Wang, Xuesong [Wayne State Univ., Detroit, MI (Uni↗

Tri-level hybrid interval-stochastic optimal scheduling for flexible residential loads under GAN-assisted multiple uncertainties

Various building loads, such as heating, ventilation, and air conditioners (HVACs), electric water heaters (EWHs), and electric vehicles (EVs), can introduce opportunities for improving the flexibility of electricity consumption while satisfying the needs of building owners as well as benefiting the resilience of distribution system. To utilize such flexibility, a tri-level distribution market framework is established, including residential consumers, load aggregators (LAs), and the distribution system operator (DSO). In this work, the uncertainties from all three levels are considered. The random consumption behavior at the consumer level is modeled as a Gaussian noise that is also aggregated and transmitted to the LA level. The weather temperature in the LA level is forecasted as an interval, and the photovoltaic (PV) power in the market-clearing level is modeled by a set of power scenarios generated by Generative Adversarial Networks (GANs). Then, a hybrid interval-stochastic programming is proposed to transform the uncertain problems in the first two levels into deterministic ones. For real-time implementations, a rolling horizon optimization (RHO) scheme is employed to continuously optimize the power consumption based on the latest operating information. Finally, case studies on a modified IEEE 69-bus system validate the effectiveness of the proposed uncertainty modeling strategies and the RHO scheme.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Geographically Distributed Co-Simulation for the Interplay of Integrated Energy Systems and Power Grid

The increased penetration of renewable generation induces unbalanced demand-supply on a power grid, while integrated energy systems (IES) can provide high part-load efficiency and high flexibility to support grid resilience. To study the transients and improve dynamic operability, it’s important to investigate the interplay between IES and power grid concurrently using real-time co-simulation approaches. In this presentation, we showed the previous co-simulation test between NETL and INL and discussed how this co-simulation can be beneficial for both IES and power grid research. In addition, we gave an overview about the SuperLab2.0 project, which was a federated national platform to address future power grid challenges. (Virtual presentation to the MILLENNIUM CLEAN and SUSTAINABLE POWER workshop 2025).

Co-simulation↗

Surrogate Model for Distribution Networks Influenced by Weather

Here, we propose a method for generating reduced representations of time series and for constructing low dimensional surrogate models for time dependent calculations of power and voltage in distribution networks. We employ Fourier polynomials. The surrogate model strategy is aimed at reducing the computational cost of time dependent simulations, albeit, at the expense of fidelity. The reduced representation is achieved by identifying a small and most consequential subset of degrees of freedom. In power and voltage distribution networks dynamics that are heavily influenced by strong cyclic weather events, e.g., the hourly, diurnal and seasonal cycles, the weather/climate time series spectrum exposes these most energetic components. Once the degrees of freedom are identified their amplitudes are optimized using training data. The key challenge in using spectral methods in power network surrogates is addressing the computation of quotients. For this we propose a numerically-stable deconvolution strategy.

Weather events↗

Current Practices in Distribution Utility Resilience Planning for Winter Storms

This report is part of a series of hazard-focused case studies examining common practices in electric utility resilience planning. We use standard terminology defining resilience as the ability to anticipate, withstand, absorb, and recover from hazards that cause long duration outages. We distinguish between reliability and resilience using Institute of Electrical and Electronics Engineers (IEEE) 1366-2022, which defines major events as an event that exceeds reasonable design and/or operational limits of the electric power system. Resilience planning is focused on major event days and reliability planning is focused on nonmajor event days. Utility resilience plans are assessed according to common resilience components identified in existing resilience frameworks. The focus of this report is on winter storms in which the primary hazards are heavy snowfall, freezing rain, ice, extreme cold, severe wind, and flooding. These hazards can also contribute to generation shortages, resulting in bulk power system impacts that have consequences for the distribution system, such as load shedding. Stand-alone reports focusing on wildfires and nonwinter storms have been published in parallel with this report. This report can be used as a starting point for understanding potential investment prioritization processes and investment options. This report is intended to improve utility resilience planning by supporting constructive dialogue among utilities, regulators, and other stakeholders.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Distributions of Particles Accelerated by Strong Alfvénic Turbulence

This work presents a model for generating nonthermal power-law tails of particles’ energy probability density functions in turbulent collisionless plasmas, applicable to both nonrelativistic and relativistic scenarios. We propose that strong Alfvénic turbulence energizes plasma particles through curvature acceleration, particularly for particles with Larmor radii comparable to the scales of turbulence. When the energy density of the energized particles increases, the efficiency of the energy exchange process diminishes. As a result, the acceleration process saturates, leading to power-law distributions of particle momentum and energy. In the nonrelativistic case, the momentum probability density function scales as f(p)dp ∝ p −3 dp, while in the ultrarelativistic case, the energy probability density function scales as f(γ)dγ ∝ γ −3 dγ, where γ is the Lorentz factor. This model provides a unified framework for understanding particle acceleration in both energy regimes, complementing existing analytical approaches. The predicted scalings are consistent with available observations of energetic ion distributions in the heliosphere and with the findings from numerical simulations of ultrarelativistic particle acceleration in magnetically dominated plasma turbulence.

Alfven waves↗

Cost-Effectiveness of Local Distribution Tied Solar within KyMEA

KyMEA is a Kentucky joint action agency which provides electric transmission and energy services to eleven municipal utilities. One of KyMEA's member cities, Frankfort, has set a goal to reach 100% renewable generation for the city load by 2023 and 100% carbon free city operations and 100% renewable generation community-wide by 2030. The aim of this research was to determine if the Frankfort city government could reduce its power costs by implementing distribution tied solar while also avoiding any cross subsidization between other KyMEA member utilities or other Frankfort Plant Board customers. The project simulated the KyMEA generation portfolio and transmission system from KyMEA's cost perspective using the NREL Engage capacity expansion model. Running in operate mode, the authors used Engage to compare KyMEA's costs to operate the baseline system to its costs to operate the system with Frankfort meeting some of its load with distribution-tied PV. The cost perspective of Frankfort Plant Board, meanwhile, was simulated using Python. The simulations indicated that it would be cost-beneficial to KyMEA, i.e., that no additional costs would be borne by other members, and that it would be cost-neutral to Frankfort Plant Board for Frankfort city government to implement distribution tied utility-scale PV. The new load attributes resulting from the distribution-tied PV lowered KyMEA's cost to serve load by improving system load factor, reducing system transmission and energy costs, and increasing revenues from market energy sales.

14 SOLAR ENERGY↗

Computational design of microarchitected porous electrodes for redox flow batteries

Porous electrodes are used as the core reactive component across electrochemical technologies. In flowing systems, controlling the fluid distribution, species transport, and reactive environment is critical to attaining high performance. However, conventional electrode materials like felts and papers provide few opportunities for precise engineering of the electrode and its microstructure. To address these limitations, architected electrodes composed of unit cells with spatially varying geometry determined via computational optimization are proposed. Resolved simulation is employed to develop a homogenized description of the constituent unit cells. These effective properties serve as inputs to a continuum model for the electrode when used in the negative half-cell of a vanadium redox flow battery. Porosity distributions minimizing power loss are then determined via computational design optimization to generate architected porosity electrodes. The architected electrodes are compared to bulk, uniform porosity electrodes and found to lead to increased power efficiency across operating flow rates and currents. The design methodology is further used to generate a scaled-up electrode with comparable power efficiency to the bench-scale systems. Finally, the variable porosity architecture and computational design methodology presented here thus offers a novel pathway for automatically generating spatially engineered electrode structures with improved power performance.

25 ENERGY STORAGE↗

Analysis of Defect Irrelevancy in a Non-Insulated REBCO Pancake Coil Using an Electric Network Model

High-temperature superconducting REBCO coated conductor is one of the main candidates for next-generation high field magnets in fusion reactors and particle accelerators owing to their high current-carrying capability. Although these materials can operate at higher temperatures and generate higher magnetic fields than their counterparts with lower critical temperatures, protecting the REBCO magnet against quench is challenging. A variety of candidate technologies that may be able to enable self-protection, including no-insulation technology and insulative coatings with temperature-dependent resistance, are in development. Here, in order to understand current sharing and thermal processes during a quench, we model a REBCO pancake coil as an electrical circuit, considering power generation and heat transfer along conductor turns, and study the current distribution around a local defect with lower critical current. The magnetic field and coil terminal voltage predicted by the simulation was compared to published experimental results. Our results provide useful insights into how current sharing occurs around defects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Powered by dGen Webinar [Slides]

NLR's Powered By Webinar Series featuring NLR's dGen Modeling Tool. The Distributed Generation Market Demand (dGenTM) model simulates customer adoption of distributed energy resources for residential, commercial, and industrial entities in the United States or other countries through 2050. The model enables analysis at multiple geographic levels (national, state, and utility, or below) and offers sophistication in representation of decision-making regarding economic and behavioral considerations. Analysts have used dGen to answer questions about load forecasting and integrated resource planning, policy analysis, locational value of distributed energy resources, and more. dGen is open source, and various energy organizations - including independent system operators, regional transmission organizations, and the California Energy Commission - use the model internally.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Reconfigurable Real-Time Power Grid Emulator for Systems With High Penetration of Renewables

Novel power system control and new utility devices need to be tested before their actual deployment to the power grid. To assist with such a testing need, real-time digital emulators such as RTDS and Opal-RT can be used to connect to the physical world and form a hardware in the loop (HIL) emulation. However, due to the limitations of today's computational resources, the accuracy and fidelity suffer from different levels of model reductions in purely digital simulations. CURENT has developed a reconfigurable electric grid hardware testbed (HTB) to overcome the limitations of digital emulators. The HTB has been used to develop measurement, control, modeling, and actuation techniques for a national grid with a high penetration of renewables. The power electronic-based system includes emulators for synchronous generators; photovoltaics with grid-interfacing inverter; wind turbines; induction motor loads, ZIP loads, power electronic loads; batteries; ac and dc transmission lines; short circuit faults and grid relay protection; and a multiterminal HVDC overlay including power electronics interfaces. The system contains real elements of power flow, measurement, communication, protection, and control that mimic what would be seen in an actual electric grid. This paper presents an overview of the HTB and several scenarios that have been run to determine control and actions needed for the future power grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Joint Management and Optimization of Residential Natural Gas and Electricity Distribution Networks Coupled via Fuel Cells

The attractive features of natural gas as well as the growing electric power demand worldwide have created increasing interest in natural-gas-based distributed generation applications for electric distribution networks. Here, this paper investigates the interdependency between a residential natural gas network and an electric distribution network that are linked together via fuel cells. The modeling of the natural gas network is introduced first, and then the algorithm for gas flow study is presented. The optimal placement and sizing of fuel cell based distributed generation systems are formulated to minimize the losses in both the natural gas network and the electric distribution grid, subject to the constraints imposed by both networks. In addition, a probabilistic model for both gas and electricity demands is developed based on historical electricity and natural gas demand data. A K-means clustering method is used to determine the hourly load states to solve the joint probabilistic optimization problem. Simulation studies are carried out on an integrated system consisting of the IEEE 69-bus distribution network and a radial 27-node natural gas network to verify the developed optimization model and the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Selective Depolymerization for Sculpting Polymethacrylate Molecular Weight Distributions

Chain-end reactivation of polymethacrylates generated by reversible-deactivation radical polymerization (RDRP) has emerged as a powerful tool for triggering depolymerization at significantly milder temperatures than those traditionally employed. In this study, we demonstrate how the facile depolymerization of poly(butyl methacrylate) (PBMA) can be leveraged to selectively skew the molecular weight distribution (MWD) and predictably alter the viscoelastic properties of blended PBMA mixtures. By mixing polymers with thermally active chain ends with polymers of different molecular weights and inactive chain ends, the MWD of the blends can be skewed to be high or low by selective depolymerization. This approach leads to the counterintuitive principle of the “destructive strengthening” of a material. As a result, we demonstrate, as a proof of concept, the encryption of information within polymer mixtures by linking Morse code with the MWDs before and after selective depolymerization, allowing for the encoding of data within blends of synthetic macromolecules.

36 MATERIALS SCIENCE↗

Small Hydropower Interconnections: Best Practices

Small hydropower projects have been the predominant source of capacity growth of U.S. hydropower for more than a decade, and they present the most cost-effective and environmentally permissible avenues for hydropower growth (DOE 2016; Johnson et al. 2018). However, interconnection to electricity distribution and transmission grids is a persistent barrier due to cost surprises and schedule overruns. As a culmination to research into the status and requirements of small hydropower interconnection across the United States, this paper presents the best practices for setting interconnection standards that can improve the process for small hydropower developers. As part of the analysis, the interconnection costs are compared between small hydropower, solar, and wind. The analysis of the small hydropower interconnection landscape across the United States was carried out by Pacific Northwest National Laboratory (PNNL) and Oak Ridge National Laboratory (ORNL) with support from the U.S. Department of Energy Water Power Technologies Office. The research team was guided by a Technical Advisory Group (TAG) and gleaned data from publicly available sources, such as the HydroSource database (ORNL 2020) and interconnection queues hosted by utilities, balancing authorities, independent system operators (ISOs), and regional transmission organizations (RTOs). The results of this work are shared in a series of papers detailing the state of small hydropower in the United States (“Small Hydropower Interconnections: Small Hydropower in the United States”), the variety of state interconnection processes to connect power generators with the grid (“Small Hydropower Interconnections: State Interconnection Processes”), and an analysis of the interconnection processes (“Small Hydropower Interconnections: Analysis of Interconnection Processes”). In this, the final paper in the series, best practices for interconnection processes (“Small Hydropower Interconnections: Best Practices”) are identified from the solar energy and distributed wind energy industries that are transferrable to small hydropower development. This information will help overcome barriers to future small hydropower development.

13 HYDRO ENERGY↗

Analysis of WIRE-21 SPND and Optical Fiber Sensor Measurements

The Wireless Instrumented RB Experiment 2021 (WIRE-21) was a highly instrumented experiment designed to test prototype wireless temperature and pressure sensors developed by Westinghouse Electric Corporation (WEC) in the High Flux Isotope Reactor (HFIR). In addition to these sensors, a suite of other sensors was also integrated into the experiment capsule, including various types of distributed optical fiber sensors and self-powered neutron detectors (SPNDs). This report presents an analysis of the data generated by the SPNDs and optical fiber sensors that were tested under the highest reported neutron flux. The distributed optical fiber sensor results demonstrate that F-doped optical fibers, particularly those inscribed with fs fiber Bragg gratings (FBGs), are capable of surviving fast neutron fluences on the order of 1021 n fast /cm 2 at temperatures relevant to light-water reactors (between 200 and 400°C). However, a significant blue-shift in the optical spectra of these sensors was observed over the course of irradiation which cannot be explained based on the current understanding of radiation-induced compaction in fused silica glass. A mechanistic understanding of this drift has not yet been developed and is proposed as future scope under the Advanced Sensors and Instrumentation program. Of the four SPNDs, only one appeared to operate normally during three cycles of irradiation. A radiation transport model of the experiment in HFIR was used to determine time-dependent neutron flux in this SPND and to calculate the neutron sensitivity of the device. Results showed a cycle averaged sensitivity of 1.5 ×10 -22 and 1.4 ×10 -22 A/nν for the first and third cycles of irradiation, respectively. Additional details pertaining to the optical fibers and SPNDs are included herein.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗