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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Automotive Silicon Carbide Power Module Cooling With A Novel Modular Manifold And Embedded Heat Sink

The next generation of integrated power electronics packages will implement wide-bandgap devices with ultrahigh device heat fluxes. Although jet impingement has received attention for power electronics thermal management, it is not used in commercial electric vehicles (EVs) because of the associated pressure drop and reliability concerns. Here, in this paper, we present a modular thermal management system designed for automotive power electronics. The system achieves superior thermal performance to benchmarked EVs, while adhering to reliability standards and with low pumping power. The system utilizes a low-cost and lightweight plastic manifold to generate jets over an optimized heat sink, which is embedded in the direct-bonded-copper (DBC) substrate. The embedded heat sink concept leverages additive manufacturing to add elliptical pin fins to the DBC substrate. The heat sink geometry is optimized for submerged jet impingement using a unit-cell model and an exhaustive search algorithm. The model predictions are validated using unit-cell experiments. A full-scale power module model is then used to compare the DBC-embedded heat sink against direct DBC cooling and baseplate-integrated heat sinks for single-sided (SS) and double-sided (DS) cooling concepts. Using the SS and DS DBC-embedded cooling concepts, the models predict a thermal resistance that represents a reduction of 75% and 85% compared to the 2015 BMW i3, respectively, for the same water-ethylene glycol inverter flow rate. We have shown that an inverter with a 100-kilo-Watt-per-liter power density is achievable with the proposed design.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Long short-term memory embedded nudging schemes for nonlinear data assimilation of geophysical flows

Reduced rank nonlinear filters are increasingly utilized in data assimilation of geophysical flows, but often require a set of ensemble forward simulations to estimate forecast covariance. On the other hand, predictor-corrector type nudging approaches are still attractive due to their simplicity of implementation when more complex methods need to be avoided. However, optimal estimate of nudging gain matrix might be cumbersome. In this paper, we put forth a fully nonintrusive recurrent neural network approach based on a long short-term memory (LSTM) embedding architecture to estimate the nudging term, which plays a role not only to force the state trajectories to the observations but also acts as a stabilizer. Furthermore, our approach relies on the power of archival data and the trained model can be retrained effectively due to power of transfer learning in any neural network applications. In order to verify the feasibility of the proposed approach, we perform twin experiments using Lorenz 96 system. Our results demonstrate that the proposed LSTM nudging approach yields more accurate estimates than both extended Kalman filter (EKF) and ensemble Kalman filter (EnKF) when only sparse observations are available. With the availability of emerging AI-friendly and modular hardware technologies and heterogeneous computing platforms, we articulate that our simplistic nudging framework turns out to be computationally more efficient than either the EKF or EnKF approaches.

42 ENGINEERING↗
DOE OSTI2024

Fully quantum algorithm for mesoscale fluid simulations with application to partial differential equations

Fluid flow simulations marshal our most powerful computational resources. In many cases, even this is not enough. Quantum computers provide an opportunity to speed up traditional algorithms for flow simulations. We show that lattice-based mesoscale numerical methods can be executed as efficient quantum algorithms due to their statistical features. This approach revises a quantum algorithm for lattice gas automata to reduce classical computations and state preparation at every time step. For this, the algorithm approximates the qubit relative phases and subtracts them at the end of each time step. Phases are evaluated using the iterative phase estimation algorithm and subtracted using single-qubit rotation phase gates. Further, this method optimizes the quantum resource required and makes it more appropriate for near-term quantum hardware. We also demonstrate how the checkerboard deficiency that the D1Q2 scheme presents can be resolved using the D1Q3 scheme. The algorithm is validated by simulating two canonical partial differential equations: the diffusion and Burgers' equations on different quantum simulators. We find good agreement between quantum simulations and classical solutions for the presented algorithm.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Flow-based likelihoods for non-Gaussian inference

We investigate the use of data-driven likelihoods to bypass a key assumption made in many scientific analyses, which is that the true likelihood of the data is Gaussian. In particular, we suggest using the optimization targets of flow-based generative models, a class of models that can capture complex distributions by transforming a simple base distribution through layers of nonlinearities. We call these flow-based likelihoods (FBL). We analyze the accuracy and precision of the reconstructed likelihoods on mock Gaussian data, and show that simply gauging the quality of samples drawn from the trained model is not a sufficient indicator that the true likelihood has been learned. We nevertheless demonstrate that the likelihood can be reconstructed to a precision equal to that of sampling error due to a finite sample size. We then apply FBLs to mock weak lensing convergence power spectra, a cosmological observable that is significantly non-Gaussian (NG). We find that the FBL captures the NG signatures in the data extremely well, while other commonly used data-driven likelihoods, such as Gaussian mixture models and independent component analysis, fail to do so. This suggests that works that have found small posterior shifts in NG data with data-driven likelihoods such as these could be underestimating the impact of non-Gaussianity in parameter constraints. By introducing a suite of tests that can capture different levels of NG in the data, we show that the success or failure of traditional data-driven likelihoods can be tied back to the structure of the NG in the data. Here, unlike other methods, the flexibility of the FBL makes it successful at tackling different types of NG simultaneously. Because of this, and consequently their likely applicability across datasets and domains, we encourage their use for inference when sufficient mock data are available for training.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Probabilistic Voltage Sensitivity based Preemptive Voltage Monitoring in Unbalanced Distribution Networks

With increasing penetration of renewable energy and active consumers, control and management of power distribution networks has become challenging. Renewable energy sources can cause random voltage fluctuations as their output power depends on weather conditions. Conventional voltage control schemes such as tap changers and capacitor banks lack the foresight required to quickly alleviate voltage violations. Thus, there is an urgent need for effective approaches for predicting and mitigating voltage violations as a result of random fluctuations in power injections. This work proposes a novel voltage monitoring approach based on low-complexity, data-driven probabilistic voltage sensitivity analysis. The usefulness of this work is not only in predicting voltage violations in unbalanced distribution grids, but also in opening up the door for optimal voltage control. Using system data and forecasts, the proposed approach predicts the distribution of system node voltages which is then used to to identify nodes that may violate the nominal operational limits with high probability. The method is tested on the IEEE 37 node distribution system considering integrated distributed solar energy sources. The method is validated against the classic load flow based method and offers over 95% accuracy in predicting voltage violations.

Abujubbeh, Mohammad↗
DOE OSTI2023

A Power Takeoff Device for a Small Marine Hydrokinetic Turbine Deployed from an Unmanned Floating Platform

The design, development, and field-testing of a power takeoff (PTO) device equipped with a ball-type continuously-variable transmission (B-CVT) for a small marine hydrokinetic (MHK) turbine deployed from a floating unmanned autonomous mobile catamaran platform is described. The turbine is a partially-submerged multi-blade undershot waterwheel (USWW). The objective is to develop a PTO for the optimal conversion of the MHK energy harnessed by the turbine to electric power, which is stored in battery banks onboard the MHK platform. Modeling, simulation, and bench testing of the USWW and PTO show the feasibility of utilizing the B-CVT's variable gear ratio to decouple the USWW and generator speeds, maintaining the waterwheel within its optimal tip speed ratio (TSR) while varying the generator speed, thereby increasing the efficiency of the PTO. Results of bench and field testing in support of characterizing the power conversion capabilities of the PTO are described. The system being developed is in support of potential self-powered autonomous mobile recharge stations for unmanned aerial vehicles (U A V s) operating in coastal zones. Field tests of the complete MHK platform with 9 blades on the waterwheel and wheel sub mergences of 10 and 12 inches (full blade submergence) were performed. The overall proof-of-concept was successfully demonstrated, with the system satisfactorily capturing and converting water flow energy into electricity. The feasibility of utilizing the B-CVT as a means of increasing the PTO power capture capabilities and efficiency is analyzed.

Pimentel, Hugo↗
DOE OSTI2025

Molecular Design Considerations for Azobenzene Anolytes

Realization of high-density batteries requires the development of anolytes that display highly negative reduction potentials, solubility, and persistence in the charged state. Azobenzenes have garnered interest as potential anolytes for redox flow batteries. Here, we report the synthesis of a family of substituted azobenzene derivatives and evaluation of their solution-phase electrochemical properties. Systematic synthetic derivatization of this scaffold allows (1) access to anolytes of varying solubility, including intrinsically liquid derivatives that represent potential high-density charge carriers; (2) systematic variation of the reduction potential, and in some cases redox inventory, that provides azobenzenes with highly negative reduction potentials; and (3) control of the lifetime of the azobenzene radical anions that result from one-electron reduction. Electrokinetic experiments demonstrated that fast electron transfer occurs for all derivatives examined. Spectroscopic characterization of monoreduced azobenzene derivatives establishes that decomposition of the azobenzene radical anion proceeds via bimolecular disproportionation. Together, these results provide an experimental basis for the optimization of azobenzene anolytes for electrochemical storage applications, including redox flow batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Identifying Hydropower Operational Flexibilities in Presence of Streamflow and Net-load Uncertainty (Final Technical report)

In the existing operations, hydropower contributions to future system flexibility are generally modeled while maintaining traditional operating rules and constraints in supporting grid operation, such as the balancing of variable renewable energy production. Moreover, operation of large scale hydropower systems on major rivers has been investigated for decades, utilizing various systems engineering approaches, with the evolving electric grid, as the result of renewable resources integration, compounded by the changing climate (variability of river flows, intensification of hydrologic cycle resulting in more frequent extreme events) affecting water availability, the need for more advanced stochastic modeling and effective uncertainty analysis approaches have become necessary. The research results supported by this funding and presented in this report provide a new look at hydropower operational flexibility enforced by the changes identified above. Understanding how hydropower operates in response to the underlying uncertainties with respect to the system constraints is crucial in identifying its operational flexibility potentials. In this project, the flexibility of the operating hydropower facility is described by capturing uncertainties in both water and power system and formulating the operations as a multistage stochastic optimization problem. The proposed approach supports short- to seasonal-term operations and planning decision horizons.

13 HYDRO ENERGY↗
DOE OSTI2020

Distributed fiber sensing systems for 3D combustion temperature field monitoring in coal-fired boilers using optically generated acoustic waves (Final Report)

In this project, we have developed and tested three kinds of fiber optic sensing systems for real time monitoring of temperature variations within an industrial scale boiler furnace. The fiber optic sensing systems target spatial and temporal distributions of high temperature profiles in a boiler furnace in fossil power plants. The reconstructed temperature profile will provide critical input for the control mechanisms to optimize the combustion process. This temperature profile will address the essential problem for fossil power plants in achieving higher efficiency and fewer pollutant emissions. Acoustic pyrometer systems have been used to reconstruct temperature field of power plant boilers based on measuring TOF (times-of-flight) of sound waves along some straight paths in a 2D cross-section of the boiler. In this project, optically generated acoustic signals from a fiber optic sensing system have replaced the acoustic signals generated from an electrical transducer. A 3D reconstruction algorithm replaced the previous 2D model. In this project, three kinds of fiber optic sensing systems have been developed and tested. They are fiber optic sensing system I, fiber optic sensing system II (Distributed Sensing System I) and fiber optic sensing system III (Distributed Sensing System II). For fiber optic sensing system I, the fiber optic ultrasound generator acts as a signal generator. A microphone, hydrophone or other electronic devices serve as a signal receiver. In this system, there are one generator and one receiver. Distance test, water temperature test, air temperature test, air temperature reconstruction, and GE ISBF pilot test were performed by Fiber optic sensing system I. The fiber optic sensing system I successfully detected temperature in all these tests. We got 2D temperature reconstruction results by using the fiber optic sensing system I and it matched the reference data. The fiber optic sensing system I successfully survived in GE ISBF boiler environment (480 °F). For fiber optic sensing system II (Distributed Sensing System I), it is an all optical ultrasound system. The fiber optic ultrasound generator acts as a signal generator. Fiber Bragg Grating (FBG) and Fabry-Perot (FP) sensor act as a signal receiver. In this system, there is one generator and one receiver. Aluminum plate temperature test, furnace high temperature test, and GE ISBF pilot test were performed by the fiber optic sensing system II. Fiber optic sensing system II successfully detected the temperature in all these tests. The fiber optic sensing system II successfully survived at up to 700 °C furnace environment and 320 °C GE ISBF boiler environment. For fiber optic sensing system III (Distributed Sensing System II), it is also an all optical ultrasound system. The fiber optic ultrasound generator acts as a signal generator. Multiple FP fiber sensors act as signal receivers. In this system, there is one generator and three receivers. Three GE ISBF pilot tests were performed by fiber optic sensing system III. The fiber optic sensing system III survived in the cold flow tests in GE’s ISBF pilot test facility. However, we didn’t get high temperature data by using this system since the nanosecond laser issues. During the period of the project, test trials, data simulation and algorithm optimization was performed successfully. For real time temperature field construction, the sampling rate must be fast enough to capture the field variations. The technology of Code-division multiple access (CDMA) is well studied which could allow parallel multiplexing, even if signals overlap in time or frequencies. Moreover, it has been known that extending the length of signal significantly improves SNR. For acoustic signals, these multiplexing techniques have also been widely used, mainly for sonar and acoustic communications. The CDMA modulation technique has been proposed and studied to guarantee high network throughput, low channel access delay and low energy consumption. We have studied the temperature field reconstruction using Gaussian Radial Basis Functions (GRBF)-based approximation approach. Reconstruction of 3D temperature field using Neural Networks with measured TOF and known propagation paths is feasible. 2D and 3D temperature field reconstruction simulation results are achieved. The milestone status is shown in Table 1. We finished milestone 1-8 and milestone 10. For milestone 9, we did three pilot tests by using the fiber optic sensing system III (Distributed Sensing System II) at GE Power. However, due to the failure of the ns laser, we did not get the temperature results. We conducted some additional tasks that were not originally proposed: 1) We fabricated a fiber optic sensing system I and did a pilot test based on this system. 2) In the proposal, we proposed two pilot tests at GE Power. In reality, we finished at least seven pilot tests at GE Power. GE Power has made a lot of efforts for supporting the pilot tests. 3) We got a simulation results based on CDMA. In summary, most of the tasks have been accomplished. The outcome of this project removed a few barriers that hinder the achievement of the final product of the distributed sensing systems. With the successful accomplishment of this project, a prototype of the fiber optic sensing system can be fabricated to attract more interests from companies and other funding agencies.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Microfluidic Liquid-Liquid Extraction Chip with Integrated Raman Sensors (Phase I and Phase II Final Report)

As demand for electricity continues to increase worldwide, the world’s nuclear power generating capacity will continue to grow. Nuclear power is the most environmentally benign way of producing electricity on a large scale. The long-term successful use of nuclear power, however, is critically dependent upon adequate and safe processing and disposal of spent nuclear fuels. A very important feature of nuclear energy is that spent fuels can be reprocessed to recover fissile and fertile materials that can then be used as fresh fuel for nuclear power plants. The DOE-NE Fuel Cycle Research and Development (FCR&D) is currently developing nuclear material reprocessing technologies. In a typical nuclear fuel reprocessing system, centrifugal contactors are used as liquid-liquid extraction devices where two immiscible liquids are mixed at high speeds using a rotor, which creates a fine dispersion of droplets of organic phase in an aqueous phase that contains the analyte. Understanding the extraction efficiency at these contactors through modeling and simulation is important in the development of reprocessing technologies and the optimization of current technologies such as the PUREX process. The outcome of this program will be a liquid-liquid microfluidic flow cell chip with embedded spectroscopic sensors for the analysis of extracted analytes. This device will be useful in the optimization of new fuel reprocessing schemes as well as existing reprocessing processes by providing a microfluidic modeling platform to optimize extraction parameters. The Phase I and Phase II work developed a microfluidic chip design that allows integration of Raman and absorption fiber optic probes and successfully demonstrated the feasibility of using Raman and absorption probes to detect key analytes that partition into the aqueous and organic phases.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

TOGETs Overview

The Transmission Optimization with Grid Enhancing Technologies (TOGETs) project will guide future research to fill in gaps on publicly available knowledge of Grid Enhancing Technologies (GETs) and conduct a full scale, multi-faceted field exercise. Ultimately the project aims to test, verify and validate deployed GETs in a transmission system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Pathways to High-Power-Density Redox Flow Batteries

Redox flow batteries (RFBs) promise to fill a crucial missing link in the energy transition: inexpensive and widely deployable grid and industrial-scale energy storage for intermittent renewable electricity. While numerous lab-scale and demonstration-scale RFBs have been delivered, widespread commercial deployment is still limited by high electrolyte, stack, and balance of plant capital costs. Increasing the power density of RFBs is correlated with lower stack costs, primarily because the area needed for expensive electrode and membrane components to reach a target power density is reduced. Here, in the present contribution, we summarize the areal power densities reported for lab-scale RFBs, critically evaluate major pathways employed for power optimization, and identify opportunities for developing yet-higher power density systems.

25 ENERGY STORAGE↗
DOE OSTI2021

Revisiting Theoretical Limits for One Degree-of-Freedom Wave Energy Converters

This work revisits the theoretical limits of one degree-of-freedom wave energy converters (WECs). This work considers the floating sphere used in the OES Task 10 WEC modeling and verification effort for analysis. Analytical equations are derived to determine bounds on displacement amplitude, time-averaged power (TAP), and power-take-off (PTO) force. A unique result found shows that the TAP absorbed by a WEC can be defined solely by the inertial properties and radiation hydrodynamic coefficients. In addition, a unique expression for the PTO force was derived that provides lower and upper bounds when resistive control is used to maximize power generation. For complex conjugate control, this same expression only provides a lower bound, as there is theoretically no upper bound. These bounds assist in comparing the performance of the floating sphere if it were to extract energy using surge or heave motion. The analysis shows because of differences in hydrodynamic coefficients for each oscillating mode, there are different frequency ranges that provide better power capture efficiency. The influence of a motion constraint on TAP while utilizing a nonideal power take-off is examined and found to reduce the losses associated with bidirectional energy flow. The expression to calculate TAP with a nonideal PTO is modified by the electrical conversion efficiency and the ratio of the PTO spring and damping coefficients. Furthermore, the PTO spring and damping coefficients were separated in the expression, allowing for limits to be set on the PTO coefficients to ensure net power generation.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Tri-Level Linear Programming Model for Automatic Load Shedding Using Spectral Clustering

Traditional load shedding schemes can be inadequate in grids with high renewable penetration, leading to unstable events and unnecessary grid islanding. Although for both manual and automatic operating modes load shedding areas have been predefined by grid operators, they have remained fixed, and may be sub-optimal due to dynamic operating conditions. In this work, a distributed tri-level linear programming model for automatic load shedding to avoid system islanding is presented. Preventing islanding is preferred because it reduces the need for additional load shedding besides the disconnection of transmission lines between islands. This is crucial as maintaining the local generation-demand balance is necessary to preserve frequency stability. Furthermore, uneven distribution of generation resources among islands can lead to increased load shedding, causing economic and reliability challenges. This issue is further compounded in modern power systems heavily dependent on non-dispatchable resources like wind and solar. The upper-level model uses complex power flow measurements to determine the system areas to shed load depending on actual operating conditions using a spectral clustering approach. The mid-level model estimates the area system state, while the lower-level model determines the locations and load values to be shed. The solution is practical and promising for real-world applications.

Baquedano-Aguilar, Mario D.↗
DOE OSTI2025

Hybridization Assessment of Trybrid Pumped Storage Hydropower System—Part 1: A Case Study of Corral Summit

This report is a part of the deliverables for technical assistance provided to Cat Creek Energy for the Coral Summit Trybrid (Triple Hybrid-Pumped Storage Hydropower, Battery Energy Storage System, and photovoltaic solar energy) energy project. This report explores the operational benefits and challenges of hybridizing an open loop PSH (200MW) located at Mackay, Custer County, Idaho with solar PV (Ground mount 300MW and floating 40MW) and battery (720MWhr). This document reports two activities performed as a part of the hybridization assessment task 1) optimal resource allocation and energy management strategy, and 2) power quality and reliability assessment. From optimal resource allocation and energy management strategy (activity 1), the following key findings can be observed: • Conventional PSH (CPSH) with two reversible pump turbines and separate penstocks can provide required flexibility equivalent to that from two ternary PSH with separate penstock. With single unit CPSH, upper reservoir head cannot be maintained accurately, the variation of water level is rapid and pump mode flexibility is not available. These disadvantages can be overcome by single unit TPSH. However, using two CPSH units with separate penstocks also overcome these disadvantages with the formation of the hydraulic short circuit between two conventional units. • Flooding of the lower reservoir is a severe concern when considering continuous operation for black start. This limits the duration of continuous operation from PSH alone to around 50 hours. Due to the complementary PV and battery action, the duration of continuous operation and smooth power output can be extended. • An optimization problem is framed that maximizes the power output on an hourly basis while minimizing constraint violations and respecting seasonal variations of solar PV and load profiles . Two value streams, arbitrage and baseload generation are served by this profile. It was uncovered that for smooth power output during regular operation, PV curtailment will be required, or the battery capacity needs to be increased above 90MW to accommodate additional PV. From power quality and reliability assessment (activity 2) the following takeaway points can be observed: • The Trybrid, when integrated at the Lost River bus, and limited to 250MW in generation mode and -150MW in the pump mode, causes no violation of voltage or flow.

13 - HYDRO ENERGY↗
DOE OSTI2020

Multiresolution GPC-Structured Control of a Single-Loop Cold-Flow Chemical Looping Testbed

Chemical looping is a near-zero emission process for generating power from coal. It is based on a multi-phase gas-solid flow and has extremely challenging nonlinear, multi-scale dynamics with jumps, producing large dynamic model uncertainty, which renders traditional robust control techniques, such as linear parameter varying H ∞ design, largely inapplicable. This process complexity is addressed in the present work through the temporal and the spatiotemporal multiresolution modeling along with the corresponding model-based control laws. Namely, the nonlinear autoregressive with exogenous input model structure, nonlinear in the wavelet basis, but linear in parameters, is used to identify the dominant temporal chemical looping process dynamics. The control inputs and the wavelet model parameters are calculated by optimizing a quadratic cost function using a gradient descent method. The respective identification and tracking error convergence of the proposed self-tuning identification and control schemes, the latter using the unconstrained generalized predictive control structure, is separately ascertained through the Lyapunov stability theorem. The rate constraint on the control signal in the temporal control law is then imposed and the control topology is augmented by an additional control loop with self-tuning deadbeat controller which uses the spatiotemporal wavelet riser dynamics representation. The novelty of this work is three-fold: (1) developing the self-tuning controller design methodology that consists in embedding the real-time tunable temporal highly nonlinear, but linearly parametrizable, multiresolution system representations into the classical rate-constrained generalized predictive quadratic optimal control structure, (2) augmenting the temporal multiresolution loop by a more complex spatiotemporal multiresolution self-tuning deadbeat control loop, and (3) demonstrating the effectiveness of the proposed methodology in producing fast recursive real-time algorithms for controlling highly uncertain nonlinear multiscale processes. The latter is shown through the data from the implemented temporal and augmented spatiotemporal solutions of a difficult chemical looping cold flow tracking control problem.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Catalytic Removal of Oxygen and Pollutants in Exhaust Gases from Pressurized Oxy-Combustors

The primary goal of this project was to develop and validate advanced catalytic materials and systems for purifying the flue gas generated from pressurized oxy-combustors in an effort to achieve the purity specifications of carbon dioxide (CO 2 ) streams required by the U.S. Department of Energy (USDOE) for application in enhanced oil recovery. The technology has shown great potential for improving energy efficiency, simplifying process complexity, and lowering costs compared with current state-of-the-art oxy-combustion flue gas purification technologies. Laboratory studies were conducted for the development, characterization, and screening of metal catalysts for residual oxygen (O 2 ) reduction with methane (CH 4 ) and multifunctional carbon catalysts for combined nitrogen oxides (NO x ), sulfur oxides (SO x ), and mercury (Hg) removal. A bench-scale reverse-flow fixed-bed (RFFB) reactor and a trickle-bed direct-contact cooler (DCC) reactor capable of treating 15 standard liters per min of pressurized oxy-combustion flue gas were fabricated and tested with both a simulated flue gas in the laboratory and a slipstream of actual flue gas at a 100 kW th Staged, Pressurized Oxy-Combustion (SPOC) pilot facility. Process simulation and techno-economic studies were performed to evaluate the energy efficiency and cost of the developed catalytic flue gas purification process integrated into a conceptual 550-MWe SPOC power plant. The goal and objectives of the project have been successfully accomplished. A cobalt-manganese (CoMn) oxide catalyst was developed and demonstrated in the bench-scale RFFB reactor in either a reverse-flow or one-direction flow mode of operation that met the success criterion of performance for residual O 2 reduction. A carbon catalyst was developed and demonstrated in the bench-scale DCC reactor that met the success criterion of performance for combined NO x /SO x /Hg removal. Slipstream testing of the integrated DCC-RFFB system at the SPOC pilot facility demonstrated stable operation and verified the superior performance obtained in the laboratory. The techno-economic analysis showed that a 550-MWe SPOC plant integrated with the catalytic flue gas purification process would result in costs of electricity of $\$$96.94/MWh and $\$$80.27/MWh in two assessed cases compared with $\$$91.07/MWh reported for the USDOE’s Current Technology Case, which generated only a partially pure CO 2 stream. On the basis of the results and findings from this project, scale-up studies of materials production and system demonstration and optimization studies of reactors and processes are recommended at the next stage of technology development.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Hall–Petch strengthening limit through partially active segregation in nanocrystalline Ag-Cu alloys

The breakdown from grain-size strengthening to softening mechanisms is generally well understood for high-purity nanocrystalline materials when the mean grain size decreases to the nanometer range. In nanocrystalline alloys, however, the stabilization of nanosized grains by grain-boundary solute segregation complicates the above mechanisms. Moreover, current segregation models have little predictive power for determining the optimal solute content that maximizes Hall-Petch strengthening effects. In this article, using large-scale hybrid Monte-Carlo/molecular dynamic simulations, we present a systematic study of the Hall–Petch breakdown in Cu-segregated Ag alloys with grain sizes ranging from 8 nm to 59 nm, where three concentration-dependent regimes of plasticity are described: (1) Classical segregation strengthening behavior at low solute contents, (2) shear band-induced softening at high solute contents, and (3) a previously unknown, but extended plateau of maximum strengths for intermediate solute contents from 4 to 15 at.%, which we term as nanocrystalline Sterling silver. We find that flow strengths in nanocrystalline Sterling alloys naturally exhibit a zero-slope limit at the smallest grain sizes that is well below the ideal Hall–Petch strengthening trend. This phenomenon results from partially active grain-boundary segregation that acts to influence interfacial plasticity in some, but not all, grain boundary regions. Our findings amplify the atomic nature of solute segregation and interaction at grain boundaries and its complex roles on grain boundary-mediated plasticity mechanisms in nanocrystalline alloys.

36 MATERIALS SCIENCE↗