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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Total Power Factor Smart Contract with Cyber Grid Guard Using Distributed Ledger Technology for Electrical Utility Grid with Customer-Owned Wind Farm

In modern electrical grids, the numbers of customer-owned distributed energy resources (DERs) have increased, and consequently, so have the numbers of points of common coupling (PCC) between the electrical grid and customer-owned DERs. The disruptive operation of and out-of-tolerance outputs from DERs, especially owned DERs, present a risk to power system operations. A common protective measure is to use relays located at the PCC to isolate poorly behaving or out-of-tolerance DERs from the grid. Ensuring the integrity of the data from these relays at the PCC is vital, and blockchain technology could enhance the security of modern electrical grids by providing an accurate means to translate operational constraints into actions/commands for relays. This study demonstrates an advanced power system application solution using distributed ledger technology (DLT) with smart contracts to manage the relay operation at the PCC. The smart contract defines the allowable total power factor (TPF) of the DER output, and the terms of the smart contract are implemented using DLT with a Cyber Grid Guard (CGG) system for a customer-owned DER (wind farm). This article presents flowcharts for the TPF smart contract implemented by the CGG using DLT. The test scenarios were implemented using a real-time simulator containing a CGG system and relay in-the-loop. The data collected from the CGG system were used to execute the TPF smart contract. The desired TPF limits on the grid-side were between +0.9 and +1.0, and the operation of the breakers in the electrical grid and DER sides was controlled by the relay consistent with the provisions of the smart contract. The events from the real-time simulator, CGG, and relay showed a successful implementation of the TPF smart contract with CGG using DLT, proving the efficacy of this approach in general for implementing electrical grid applications for utilities with connections to customer-owned DERs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Powertrain Performance and Total Cost of Ownership Analysis for Class 8 Yard Tractors and Refuse Trucks

Advanced powertrain technologies, specifically fuel cell electric powertrains, have gained attention as viable alternatives for medium- and heavy-duty (M/HD) vehicles. However, it is unclear how these alternative powertrain vehicles stack up against their diesel counterparts in terms of performance and total cost of ownership (TCO). Furthermore, there are vehicle segments within the M/HD sector that have remained unstudied for fuel cell electric applications. This analysis aims to provide a comparative scoping-level TCO and performance analysis for two heavy-duty vocation vehicles (Class 8 U.S. port-side yard tractor and Class 8 U.S.-based refuse truck) for both conventional diesel and heavy-duty fuel cell electric (HDFC) powertrains. The refuse truck analysis also considered compressed natural gas powertrains (CNG) for comparison. The analysis includes seven timeframes (2020, 2025, 2030, 2035, 2040, 2045, and 2050) for comparison. This simplified TCO analysis includes only direct costs (fuel price, glider purchase price, and operating & maintenance costs) and excludes any associated indirect cost (e.g., dwell time costs and other opportunity based costs). Representative drive cycles for each vehicle were based on on-board GPS logged data and chosen by the analysis team to represent average, non-extreme driving conditions. At the time the analysis was performed, the Inflation Reduction Act was not in effect and therefore any potential subsidies and future cost reductions enacted under the Inflation Reduction Act were not included. Based on the operational setpoints used in this analysis, HDFC powertrains for both yard tractors and refuse trucks have the potential to achieve TCO advantages over conventional diesel powertrains (and CNG for refuse truck applications) in the near- to mid-term future while meeting the necessary duty cycle performance requirements. Yard tractors and refuse trucks spend a significant amount of time operating at low speeds, with long durations of idling, and experience numerous start/stop occurrences. These operational characteristics favor fuel cell performance as fuel cells operate with higher efficiencies at lower percentages of total power output. Conversely, conventional diesel and CNG engines are most efficient at higher percentages of total power output. This helps HDFC powered yard tractors and refuse trucks realize improved fuel economy when compared to their diesel counterparts, which helps reduce total fuel costs and therefore, total TCO. The analysis demonstrates that fuel prices play a significant role in determining TCO for each vehicle and should remain an R&D focus area. Overall, under the analysis' specified conditions, HDFC yard tractors have the potential to achieve cost parity with diesel yard tractors as early as 2025. For refuse trucks, HDFC refuse trucks have the potential to achieve cost parity with diesel and CNG refuse trucks in 2030 and 2040, respectively.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Energy management systems for forecasted demand error compensation using hybrid energy storage system in nanogrid

This paper proposes an energy management system (EMS) for nanogrids to balance the power supply and forecasted demand in consideration of forecasting errors arising from high instantaneous demand. The proposed EMS employs a power-balancing optimization process for forecasted demand and a reference power modulation strategy for forecasting errors. This power-balancing optimization utilizes nanogrid sources, such as photovoltaics, fuel cells, and batteries, to meet forecasted demand and a supercapacitor charging process to overcome issues with a low energy density. The proposed reference power modulation strategy is utilized to allocate power from a hybrid energy storage system consisting of a battery and supercapacitor in order to compensate for forecasting errors. In addition, this proposed strategy considers battery and supercapacitor constraints such as the power changing rate and total power limitations. Further, the power-balancing optimization process also operates at faster sampling rate than the reference power modulation process in order to improve the computational efficiency. The performance of the proposed EMS is evaluated using real data obtained from the Korea Electric Power Exchange.

25 ENERGY STORAGE↗
DOE OSTI2026

Holistic energy analysis method for thermal management architectures of data centers

Modern high-performance computing (HPC) data centers (DCs), particularly those supporting energy-intensive artificial intelligence (AI) workloads, face escalating thermal management challenges that degrade performance through thermal throttling and drive up cooling power consumption and operational costs. To address this challenge, many have developed a wide variety of thermal management solutions (single-phase, two-phase, direct, indirect, hybrid, and more) which attempt to cool HPC DCs effectively while attempting to minimize overall system power consumption. However, the analysis of these solutions and methods to effectively compare one with another is lacking. Overall power usage effectiveness (PUE) and total-power usage effectiveness (TUE) provide a metric to quantify power consumption but fail to identify components in the system which require further optimization. To address this, we propose a holistic analytical framework – the waterfall diagram (WFD) – which leverages a waterfall chart methodology, offering a comprehensive visualization of both the thermal management system loop and heat flow pathways from individual server components to the outdoor ambient. Use of the WFD enables graphical estimations of power efficiency and cooling performance across each component of a DC cooling system and complements Sankey-style energy flow visualizations by additionally resolving stage-wise temperature changes and incremental TUE contributions. The framework is used in conjunction with simulation-based approaches, to conduct a detailed pressure drop and flow distribution analysis aimed at identifying the optimal coolant distribution architecture for a single-phase direct-to-chip water-cooled DC, which serves as the baseline for subsequent WFD analysis. Among the evaluated architectures, the 3 U modular coolant distribution architecture is found to demonstrate the best performance, considering minimal pressure drop and uniform flow distribution. In addition, TUE is calculated for each cooling loop component based on its associated pressure drop and corresponding pumping power, which are integrated into the WFD. This correlation between TUE and local temperature offers immediate insight into the power efficiency and thermal performance contributions of individual components, facilitating further development and optimization. Examples of WFD applications are presented under varying thermal loads and ambient conditions, demonstrating reasonable cooling strategies. Notably, the 3 U modular architecture maintains a consistent chip case temperature of 85°C, achieving a TUE of 1.016 at ambient temperature of 47°C, and a TUE of 1.026 at ambient temperature of 52°C. The WFD methodology provides an efficient, holistic, and streamlined framework for DC thermal management architecture assessment and enables design optimization which is important for addressing the thermal-fluidic energy challenges of current and next-generation DCs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Fiber-Shaped Fluidic Nanogenerator with High Power Density for Self-Powered Integrated Electronics

Flow-based hydrovoltaic nanogenerators have attracted particular attention as efficient and facile miniature energy-harvesting devices. However, they deliver relatively low output power density and limited power conversion efficiency owing to inefficient charge separation and poor charge accumulation. Here, we report the fabrication of high-performance, fiber-shaped fluidic nanogenerators (FFNGs) that use MoS 2 -encapsulated C fibers. The FFNGs deliver stable output voltages of 540 mV and an ultrahigh power density of 10.8 W m -2 . With experiments and density functional theory calculations, improvements in output performance can be attributed to smaller energy requirements for Na + cation adsorption, increased charge separation, and diffusion layer formations on the near surface. Moreover, self-powered, integrated devices achieve a maximum total power conversion-storage efficiency of ~11% and stable output voltage up to 3.1 V, which is applicable for use in consumer electronics devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A net-zero emissions strategy for China’s power sector using carbon-capture utilization and storage

Decarbonized power systems are critical to mitigate climate change, yet methods to achieve a reliable and resilient near-zero power system are still under exploration. This study develops an hourly power system simulation model considering high-resolution geological constraints for carbon-capture-utilization-and-storage to explore the optimal solution for a reliable and resilient near-zero power system. This is applied to 31 provinces in China by simulating 10,450 scenarios combining different electricity storage durations and interprovincial transmission capacities, with various shares of abated fossil power with carbon-capture-utilization-and-storage. Here, we show that allowing up to 20% abated fossil fuel power generation in the power system could reduce the national total power shortage rate by up to 9.0 percentages in 2050 compared with a zero fossil fuel system. A lowest-cost scenario with 16% abated fossil fuel power generation in the system even causes 2.5% lower investment costs in the network (or $16.8 billion), and also increases system resilience by reducing power shortage during extreme climatic events.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Validation of Hermes-3 turbulence simulations against the TCV-X21 diverted L-mode reference case

Electrostatic flux-driven turbulence simulations with the Hermes-3 code are performed in TCV L-mode conditions in forward and reversed toroidal field configurations, and compared to the TCV-X21 reference dataset (Oliveira et al 2022 Nucl. Fusion 62 096001) qualitatively and with a quantitative methodology. Using only the magnetic equilibrium, total power across the separatrix (120 kW) and total particle flux to the targets (3 x 10 21 s −1 ) as inputs, the simulations produce time-averaged plasma profiles in good agreement with experiment. Shifts in the target peak location when the toroidal field direction is reversed are reproduced in simulation, including the experimentally observed splitting of the outer strike point into two density peaks. The overall normalized discrepancy between simulation and observation is better than any previously reported in the reversed field configuration, and matches the best previously reported in forward field configuration. Differences between simulation and experiment include density profiles inside the separatrix and at the inner target in forward (favorable $\bigtriangledown B$) field configuration. These differences in target temperature in forward field configuration lead to differences in the balance of current to the inner and outer divertor in the private flux region. The cause of these differences is most likely the lack of neutral gas in these simulations, indicating that even in low recycling regimes neutral gas plays an important role in determining edge plasma profiles. These conclusions are consistent with findings in Oliveira et al (2022 https://github.com/SPCData/TCV-X21).

Physics - Plasma physics↗
DOE OSTI2023

Distributed Optimal Power Management for Battery Energy Storage Systems: A Novel Accelerated Tracking ADMM Approach

Optimal power management (OPM) is critical for large-scale battery energy storage systems. Today’s methods often require formidable computational effort due to the design based on centralized numerical optimization. Thus, this paper investigates computationally distributed OPM where the agents based on the cells communicate over a network to cooperatively solve the OPM problem. We propose an accelerated tracking alternating direction method of multipliers (ADMM) algorithm to solve the distributed OPM. The proposed algorithm embeds dynamic average consensus and Nesterov’s acceleration technique in the ADMM algorithm. Not only is the proposed algorithm fully distributed without a need for fusion or aggregating nodes, but it also accelerates convergence. The paper formulates the OPM in a model predictive control framework where it seeks to regulate the charging/discharging power of each battery cell to minimize the total power losses and promote balanced use of the constituent cells while complying with the safety constraints. The paper provides ample simulation results to demonstrate the effectiveness and advantages of the proposed distributed OPM in terms of computation and convergence.

Farakhor, Amir↗
DOE OSTI2023

Extragalactic CO emission lines in the CMB experiments: A forgotten signal and a foreground

High resolution cosmic microwave background (CMB) experiments have allowed us to precisely measure the CMB temperature power spectrum down to very small scales (multipole ℓ ~ 3000). Such measurements at multiple frequencies enable separating the power spectrum of the primary CMB anisotropies with the power spectrum of other signals like CMB lensing, thermal and kinematic Sunyaev-Zel’dovich effects (tSZ and kSZ), and cosmic infrared background (CIB). Here, in this paper, we explore another signal of interest at these frequencies that should be present in the CMB maps: extragalactic CO molecular rotational line emissions, which are the most widely used tracers of molecular gas in the line intensity mapping experiments. Using the SIDES simulations adopted for top hat bandpasses at 150 and 220 GHz, we show that the cross-correlation of the CIB with CO lines has a contribution similar to the CIB-tSZ correlation and the kSZ power, thereby contributing a non-negligible amount to the total power at these scales. This signal, therefore, may significantly impact the recently reported ≥3σ detection of the kSZ power spectrum from the South Pole Telescope collaboration, as the contribution of the CO lines is not considered in such analyses. Our results also provide a new way of measuring the CO power spectrum in cross-correlation with the CIB. Finally, these results show that the CO emissions present in the CMB maps will have to be accounted for in all the CMB auto-power spectrum and cross-correlation studies involving a large-scale structure tracer.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

DBD plasma-assisted ethanol steam reforming for green H 2 production: Process optimization through response surface methodology (RSM)

Herein this work investigates ethanol steam reforming (ESR) to produce hydrogen (H 2 ) in a dielectric barrier discharge (DBD) plasma reactor. A five-level, three-factor experiment design was performed using a response surface methodology (RSM) to evaluate the combined effects of the three process parameters, including discharge power, total flow rate, and ethanol-to-water (EtOH/H 2 O) molar ratio on the plasma-assisted ESR reaction. Quadratic regression models were employed in RSM to fit the experimental results and present the correlation between process parameters and targeted responses (EtOH conversion, H 2 yield, H 2 selectivity, and specific energy requirement (SER) for H 2 production). The results suggested that the EtOH/H 2 O molar ratio is considered to have the most significant effect on the EtOH conversion and H 2 , H 2 selectivity, while the total flow rate is the most significant parameter determining SER for H 2 production. Process optimization demonstrated the optimal process conditions, including a discharge power of 55.9 W, a total flow rate of 26.7 ml/min, and an EtOH/H 2 O molar ratio equal to 0.34. A validation test was performed and confirmed the feasibility of the optimization process.

08 HYDROGEN↗
DOE OSTI2023

Aerodynamic characterization of two tandem wind turbines under yaw misalignment control using actuator line model

Yaw control has proven to be promising in alleviating the wake effects that plague the efficiency of wind farms. In this work, the actuator line modeling (ALM) method is adopted to simulate the flows over two tandem turbines distanced by 3–7 rotor diameters, with the yaw angle of the upstream rotor varying from γ 1 = 0° to 50°. The aim is to provide a comprehensive aerodynamic characterization of this simple wind farm under yaw misalignment control. With increasing yaw angle, the power generated by the downstream rotor increases, compensating the power loss in the upstream rotor, and resulting in significantly higher total power of the two turbines than that without yaw control. The maximum power output is achieved as the upstream wake of the yawed rotor is redirected away from the downstream rotor plane. Behind the downstream rotor, the secondary steering phenomenon is observed, where the wake is also redirected from the centerline. The use of the actuator line model also reveal unsteady aerodynamic characteristics that cannot be captured by lower-fidelity models. For the upstream rotor, the yaw misalignment results in time-varying change in the local angle of attack on the blade, giving rise to unsteady loading. The downstream rotor is partially submerged in the deflected wake incurred by the yawed upstream rotor. As the blade revolves into and out of the wake deficit, the blade experiences cyclic loading, leading to even stronger fluctuations in the aerodynamic loads than the upstream rotor. These analysis provides a comprehensive understanding of the yaw control effects on the two tandem rotors from the perspectives of aerodynamic performance, wake profiles, and unsteady characteristics. In conclusion, the insights gained from the present study can aid the design of collective yaw control strategies of wind farms, and lay the foundation for assessing the fatigue damage associated with yaw misalignment.

17 WIND ENERGY↗
DOE OSTI2020

Binderjet Additive Manufacturing for Complex Heat Exchanger Geometries

Concentrated Solar Power (CSP) systems play a role in the worlds development of renewable energy. Mirrors are used to concentrate sunlight that is converted into electricity or other forms of useful energy. CSP impact depends significantly on its overall economics. The U.S. Department of Energy’s (DOE’s) Solar Energy Technology Office (SETO) cost goals for 2030include $0.05/kWh levelized cost of electricity (LCOE) for a baseload plant [1]. The power cycle cost goal is $900/kWe [1]. The envisioned recompression supercritical carbondioxide (sCO2) power cycle includes four heat exchangers, which together are at least ¾ of the total power cycle cost. Meeting the cost target requires reducing the heat exchanger cost. The 260 bar and 588 °C heat exchanger requirements are challenging. Shell and tube heat exchangers can meet the requirements, but the size and cost are prohibitive. State-of-the-art diffusion bonded printed circuit heat exchanger designs are 3 m3 or larger and expensive to manufacture. Additive manufacturing enables novel heat exchanger geometries that can reduce heat exchanger size and mass [2]. Binderjet technology is an additive manufacturing modality. It selectively deposits binder material onto the powder bed to form a solid part one layer at a time. Once applied, the binder is cured, the remaining powder removed, and the part heat treated in steps to remove the binder, sinter the metal powder, and densify the part. The Binderjet printing process is more than 10x faster than the best-known metal additive modality, direct metal laser melting (DMLM), thus enabling 10x the part through-put rate [3]. The high throughput rate results in a low-cost manufacturing process capable of creating complex heat exchanger geometries. This paper introduces a complex heat exchanger geometry and methods of Binderjet processing to fabricate the geometry.

Barua, Ananda↗
DOE OSTI2022

Characterizing W sources in the all-W wall, all-RF WEST tokamak environment

In this work, experimental data, together with interpretive modeling tools, are examined to study trends in the tungsten (W) source in the all-W environment of the WEST tokamak, both from the divertor and from the main chamber. In particular, a poloidal limiter protecting an ion cyclotron resonance heating (ICRH) antenna is used as proxy for main chamber sourcing. The key study is carried out by stepping up lower hybrid current drive (LHCD) power, as the only auxiliary power source. Limiter and divertor W sources exhibit a qualitatively similar proportionality to the total power crossing the separatrix, P SEP , although the main chamber source remains substantially lower than the divertor source, for the range of P SEP accessible in the experiments. Intepretive modeling of the limiter source is carried out with a particle-in-cell (PIC) sheath model coupled to a surface sputtering model. Oxygen is used as a proxy for all light impurity species allowing for characterization of the critical W erosion regions. To get a good quantitative match to the data, it is necessary to assume that the oxygen arrives at the surface mostly at high ionization stages (4+ and above). A separate simulation with SOLEDGE-EIRENE, constrained to measured upstream scrape-off-layer plasma profiles, gives oxygen fractional abundances that are compatible with the PIC simulation result. This is understood to arise from transport processes that dominate over recombination. Substituting the LHCD by ICRH, in an equivalent experiment, the local W source exhibits a 3× enhancement. This can be matched by the simulation, by assuming local RF electric field rectification, based on ~100 eV peak-to-peak, near-antennna electric field. This work has highlighted the particular importance of understanding the ion charge state balance of light impurities as these are most likely the dominant sputtering species in fusion devices with high-Z walls.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Smart Contracts for Power Grid Applications Using the Advanced DLT Cyber Grid Guard Testbed

In this study is presented two power system applications with distributed ledger technology (DLT) and smart contracts (SC) that were assessed in a Cyber-Grid-Guard System (CGGS) advanced testbed, with protective relays, power meters, communication devices, DLT devices, synchronized time source, clock displays and real time simulator. This CGGS testbed was set in the Advanced Protection Lab, 252 lab space of the Grid Research Integration and Deployment Center (GRID- C), at Oak Ridge National Laboratory. In power grids, customer-owned distributed energy resources (DERs) are more frequent than in the past, and the numbers of points of interconnection (POI) with customer-owned DERs have increased. Disruptive operation from DERs presents a risk to grid operations, and protective relays located at the POI are used to isolate out-of-tolerance or poorly behaving of DERs. Ensuring the integrity of data from the relays at the POI, and DLT could enhance the security of the power grids. The first application is a SC to define and control the allowable total power factor (TPF) of the DER (wind farm) output, and the terms of the SC are implemented using DLT with a CGGS for a customer-owned DER. The TPF SC was implemented by the CGGS using DLT. The experimental model was performed with a real-time simulator using a CGGS and relay in-the-loop. The data collected from the CGGS were used to execute the TPF SC. The TPF limits were between +0.9 and +1.0, and the breakers’ operation in the POI was controlled by the relay using the SC. The events were collected from the real-time simulator, CGGS, and SEL 700GT relay to validate a successful application of the TPF SC using DLT. The second application is a SC to measure and control the allowable voltage service limits (VSL) by the CGGS using DLT. The tests were performed by using a real-time simulator, CGGS and relay in-the-loop. The data was collected from the CGGS that executed the SC. The main constraints were defined based on ANSI C84.1 service voltage limits, and the operation of the breakers in the POI. The events were collected from the CGGS, and SEL 700GT relay to assess a successful operation of the VSL SC using DLT.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Issue Summary of INL Phase IV Transient Results for IAEA CRP on HTGR UAM Benchmark

This report details the Parallel and Highly Innovative Simulation for Idaho National Laboratory (INL) Code System (PHISICS)/Reactor Excursions and Leak Analysis Program (RELAP5)-3D results obtained for the transient core exercises defined for Phase IV of the International Atomic Energy Agency (IAEA) Coordinated Research Project (CRP) on high-temperature gas cooled reactor (HTGR) uncertainty analysis in modeling (UAM). The Phase III models and results are linked to the earlier Standardized Computer Analyses for Licensing Evaluation (SCALE)/Sampler/New ESC-based Weighting Transport (NEWT) data generated for the lattice physics (lattice) stage Phase I of the CRP. The focus of this report is the Uncertainty/Sensitivity Assessment (U/SA) of the prismatic modular high-temperature gas cooled reactor (MHTGR)-350 design, and specifically for Exercises IV-1 and IV-2 of the benchmark: the Control Rod Withdrawal (CRW) and Pressurised Loss of Cooling (PLOFC) events. The statistical U/SA methodology is implemented and demonstrated using the RAVEN code, based on perturbed cross-section libraries obtained from the SCALE/Sampler sequence. Uncertainties in nuclear data (cross-sections and the average number of neutrons produced per fission, 235U[¯v ]) lead to standard deviations (uncertainties of one s) of approximately 0.5% in the core eigenvalues of the MHTGR-350 and core models. For the coupled neutronics/thermal fluid model, local power density uncertainties up to 3.6% were observed in the colder regions of the core, while the local maximum fuel temperature uncertainties reached 1.5% for the models that included thermal fluid uncertainties. The addition of thermal fluid uncertainties dominated the impacts of nuclear data uncertainties in all cases. The main contributors to uncertainties in the power density and fuel temperatures during the transients were uncertainties in the reactor operating conditions (total power, inlet mass flow rate and inlet gas temperature). Variations in the bypass flows did not have significant impact on any of the output variables. For the nuclear data uncertainties it was found that the 235U(¯v ) / 235U(¯v ) covariance produced the largest sensitivities in terms of its impact on the eigenvalue and peak reactor power. It was also observed that the impact of any nuclear data uncertainties on the maximum fuel temperature was much less significant that the impact on eigenvalue and power. Another important finding was that although the use of eight or more energy groups is recommended for best-estimate HTGR simulation, two-group models produced acceptable uncertainty and sensitivity results for most FOMs. Since the statistical U/SA methodology is computationally expensive, and most transient solver requirements will scale directly with the number of energy groups, two energy groups could be used by HTGR developers during the early stages of design when larger uncertainty margins can be tolerated.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Toward local core outlet temperature monitoring in gas-cooled nuclear reactors using distributed fiber-optic temperature sensors

Gas-cooled nuclear reactors operate at temperatures up to 950 °C with significant spatial variations in power generation and coolant flow through hundreds of parallel flow channels, resulting in complex mixing at the core outlet. The high temperatures and complex mixing can damage downstream components, challenge reactor calorimetry for power determination, and result in significant conservatism in calculated peak fuel temperatures, which ultimately limits the total power output. Directly measuring each gas stream individually is unrealistic using single point thermocouples, requiring more robust sensing techniques. Fiber-optic sensors are resilient to high temperatures (up to 1,000 °C) and radiation damage. Moreover, distributed measurements can be made along the length of one fiber, making them potential candidates for monitoring local core outlet temperatures to improve core calorimetry and identify hot channels. Here, to the authors’ knowledge, this manuscript is the first to report spatially distributed fiber optic temperature measurements to quantify mixing at the outlet of a relevant orifice plate under prototypic temperature and flow regimes to assess the feasibility of using fiber-optic sensors for distributed measurements of coolant temperature in gas-cooled reactors. A single optical fiber captured dynamic changes in local temperatures, whereas the mixed outlet temperature exhibited a muted response and could not identify which channels were responsible for the change in the mixed outlet temperature. The discussion focuses on potential challenges for deploying distributed optical fibers in gas-cooled reactors, including the effects of vibrations, radiation-induced signal attenuation and drift, and routing of the fiber while minimizing flow obstructions.

42 ENGINEERING↗