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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A Cybersecurity Event Simulation Tool and Platform

Digital Instrumentation and Control Systems (ICSs) have replaced analog control systems in nuclear power plants raising cybersecurity concerns. To study and understand the cybersecurity risks of nuclear power plants both high fidelity models of the plant physics and controllers must be created, and a framework to test and evaluate cyber security events must be established. A testing and evaluation framework of cybersecurity events consists of a method of interfering with control systems, a simulation of the plant network, and a network packet capture and recording tool. Sandia National Labs (SNL) in collaboration with the University of New Mexico’s Institute for Space and Nuclear Power Studies (UNM-ISNPS) is developing such a cybersecurity testing framework.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

New direction of nuclear code development: artificial intelligence

It has been a long-lasting aspiration of the nuclear power community to apply artificial intelligence (AI) technologies to nuclear power plants (NPPs), as AI is expected to substantially improve the efficiency, reliability, and continuity of NPPs. Along with the recent rise of AI featured with machining learning, there is an ever-increasing interest in utilizing the data-orientated technologies for nuclear power. In this chapter, we provide a brief summary of the history of AI and the previous efforts on introducing AI to nuclear reactor systems in 1980s. These histories suggest that although with a promising future, AI in NPPs also faces unique challenges, which are still not fully addressed and need special attention. We also introduced some recent studies that apply machine learning techniques to nuclear code development.Keywords: Nuclear power plants, code for nuclear power, artificial intelligence, expert system, machine learning

Lin, Lianshan↗
DOE OSTI2023

A2E2G (Atmosphere to Electrons to the Grid platform) [SWR-23-22]

A2E2G is a platform that integrates 1) forecasting tools to account for weather uncertainty, with 2) aerodynamic wind plant models to account for wake dynamics and wind plant operation, and 3) economic models to advise on operation for a wind power plant that offers grid services in addition to energy. The A2E2G platform can be used as a high-level controller for a wind plant for market participation and real-time wind plant control. The A2E2g platform is a holistic Python tool with modules that can be run to 1) advise on market participation and 2) control and operate a wind power plant in real time. The A2E2g framework assumes two stages: the first stage is in day-ahead and the second stage is in real-time. Managing uncertainty is key in the first stage and managing variability is key in the second stage. The different components have models written and developed in the Python programming language. The code is assembled into a Python package and can be easily downloaded and installed from the A2E2g repository (https://github.com/NREL/a2e2g).

Sinner, Michael↗
DOE OSTI2020

Data analytics for leak detection in a subcritical boiler

For decades, boiler leaks have been the leading cause of forced outages in the coal-fired unit. The leak occurrences are currently escalating since the existing plants must satisfy faster-ramping rates to support grid operation. Data analytics including Principal Component Analysis, Canonical Variate, and Fisher Discriminant Analysis were combined for detecting and characterizing the leak in a commercial 650 MW subcritical coal-fired power plant. The combined approach was shown to be highly effective in the fault investigation that would not have been easily achieved by an individual technique. The variability in both training and validation datasets was first evaluated using PCA. Then, the CV-FDA was employed to discriminate among faults, and to categorize the processed data into two main groups: no-leak (0) and leak (1), providing the timeframe and location of the leak occurrence. Furthermore, about 8,014 observations from 81 process variables were initially included in the calculation, while the variable count was reduced to 4 with less than 1% misclassification rate in total observations. Finally, the leak was isolated in the waterwall section. Thus, the outcome of this research may provide early detection and isolation of faulty operations in the coal-fired power plant that involves a considerable number of process variables.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

An optimization approach for cryogenic distillation-based protium removal systems in magnetic fusion energy fuel cycles

Tritium inventory reduction for fusion power plants is central to the successful adoption of fusion energy. The advent of direct internal recycling in deuterium-tritium fusion fuel cycle design has led to significant reduction in startup tritium inventory estimates for fusion power plants but requires an isotope rebalancing and protium removal (IRPR) system to ensure acceptable isotopic fuel composition. Cryogenic distillation is a potential solution for near-term deployment in an IRPR system due to its demonstrated performance in similar operating regimes. Using protium removal in the fuel cycle as the primary performance metric, this paper presents an optimization methodology for a single-column continuous cryogenic distillation-based IRPR system for a 500 MW fus magnetic fusion device. Distillation column optimization was performed using the CryOgenic Distillation For Isotopic Separation of Hydrogen (CODFISH) code developed at Savannah River National Laboratory. The distillation column design presented maximizes direct recycling of hydrogen isotopes from the fusion chamber exhaust to the fueling system while minimizing IRPR system steady-state tritium inventory. The optimized IRPR distillation column presented achieves direct recycling of 60 % of the hydrogen isotopes in the fusion chamber exhaust with an estimated steady-state system tritium inventory <30 g. In conclusion, the optimized IRPR distillation column operation was then used to estimate the design requirements for a detritation column to treat the IRPR system effluent stream.

CryOgenic distillation↗
DOE OSTI2025

A Practical Comparison of Data-Driven Prognostics Methods for Energy Systems

This study explores data-driven prognostics for nuclear power plant (NPP) condensers, focusing on tube fouling. We utilized the Asherah nuclear power plant simulator (ANS) to compare four methods: Random Forest (RF), Support Vector Regressor (SVR), Fully Connected Neural Network (FCNN), and Long Short-Term Memory Neural Network (LSTM). By simulating various fouling scenarios in the ANS, we generated data with different degradation rates under transient operations. The models were trained and tested on these data, with performance evaluated visually and numerically including uncertainty assessment. The LSTM model excelled, exhibiting minimal prediction noise and the most accurate remaining useful life estimates across all degradation levels. Its ability to capture long-term dependencies and produce cleaner outputs makes it a strong candidate, although accurate training data across the entire component lifespan are crucial. The RF model emerged as a robust alternative, providing reliable predictions with high confidence. The FCNN and SVR models, while less effective overall, showed potential under specific conditions. FCNN offers a less complex alternative to LSTM and might benefit from larger datasets. SVR excels in precision when the quality of the training data is high. Furthermore, this study highlights the operational benefits of advanced prognostics in the energy sector and emphasizes the need for further research in NPP condenser health management through real-life experiments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Nondestructive Evaluation (NDE) of Cable Anomalies using Frequency Domain Reflectometry (FDR) and Spread Spectrum Time Domain Reflectometry (SSTDR)

This report presents a comparative assessment of the performance of frequency domain reflectometry (FDR) and spread spectrum time domain reflectometry (SSTDR) in detecting a wide range of electrical cable anomalies. All tests and results reported herein were performed at the PNNL Accelerated and Real-Time Environmental Nodal Assessment (ARENA) cable and motor test bed. The primary objective of this work was to evaluate the effectiveness of SSTDR, a fledgling cable monitoring technique that shows promise for application in online monitoring of energized cable systems, against FDR, an offline technique widely employed in the nuclear power plant (NPP) industry. FDR tests are becoming more widely used in nuclear power plant cable aging management and test programs – particularly for low voltage cables. FDR capabilities for these kinds of tests have been reported by PNNL and others. The FDR test is performed on de-energized cables by connecting the FDR instrument to two of the cable conductors, or one conductor and the shield. A broad band low voltage (< 5 V) chirp is introduced in the cable, and any reflected response is captured in the frequency domain. The captured reflection is then processed by performing an inverse Fourier transform to a time domain response which can then be converted to a distance response based on the cable velocity of propagation (VoP). SSTDR measurements are functionally similar to FDR measurements in that a broad-band voltage signal composed of a square or sine wave modulated pseudo-random sequence of chips (< 5 volts), is injected onto one of the cable conductors. The injected signal will experience partial energy reflection and transmission at each impedance discontinuity along the transmission line. Any reflected response is detected by computing a cross-correlation between the reflected signals and a delayed copy of the incident SSTDR signal. the time delay for the reflected signal to experience the best matched correlation with the incident signal, indicates the travel time for the signal to reach a change in impedance. By knowing this time delay and velocity of propagation (VoP) of the signal, one can compute the physical distance. A big advantage that SSTDR measurements have over other methods is the ability to be connected to energized or live wires (currently up to 1kV) thereby enabling online monitoring of cables. SSTDR has been used successfully in several applications, e.g., aircraft, rail, and photovoltaic systems. In this work FDR and SSTDR cable assessment techniques were used to characterize a variety of cable anomalies and faults including: (1) Presence or absence of a motor; (2) Ground faults and short circuit faults; (3) Moist environments and water ingress faults; (4) Accelerated thermal aging. Both shielded and non-shielded cables were evaluated in this report. Offline measurements were made using FDR and online measurements were made by SSTDR for a range of test scenarios. Based on the results across all cable anomalies evaluated in this study, FDR displayed high sensitivity towards cable condition assessment, while SSTDR showed promise for future application in monitoring NPP cable systems. However, further developments are suggested to improve the resolution and sensitivity of SSTDR towards faults and anomalies in low voltage cables.rt presents a comparative

42 ENGINEERING↗
DOE OSTI2025

Digital Real-Time Simulation and Power Quality Analysis of a Hydrogen-Generating Nuclear-Renewable Integrated Energy System

This paper investigates the challenges and solutions associated with integrating a hydrogen-generating nuclear-renewable integrated energy system (NR-IES) under a transactive energy framework. The proposed system directs excess nuclear power to hydrogen production during periods of low grid demand while utilizing renewables to maintain grid stability. Using digital real-time simulation (DRTS) in the Typhoon HIL 404 model, the dynamic interactions between nuclear power plants, electrolyzers, and power grids are analyzed to mitigate issues such as harmonic distortion, power quality degradation, and low power factor caused by large non-linear loads. A three-phase power conversion system is modeled using the Typhoon HIL 404 model and includes a generator, a variable load, an electrolyzer, and power filters. Active harmonic filters (AHFs) and hybrid active power filters (HAPFs) are implemented to address harmonic mitigation and reactive power compensation. The results reveal that the HAPF topology effectively balances cost efficiency and performance and significantly reduces active filter current requirements compared to AHF-only systems. During maximum electrolyzer operation at 4 MW, the grid frequency dropped below 59.3 Hz without filtering; however, the implementation of power filters successfully restored the frequency to 59.9 Hz, demonstrating its effectiveness in maintaining grid stability. Future work will focus on integrating a deep reinforcement learning (DRL) framework with real-time simulation and optimizing real-time power dispatch, thus enabling a scalable, efficient NR-IES for sustainable energy markets.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Flexible FlueCO2

Carbon dioxide (CO2) emission reductions remain a significant challenge on the path to clean energy. There are increasing legislative, social, and environmental factors motivating CO2 emissions reduction from power plants with carbon capture and storage (CCS). CCS in natural gas combined cycle (NGCC) power plants is critical to achieve a net-zero carbon electricity grid. Enhanced 45Q tax credits provide new incentives, but currently available technologies are unable to profitably operate in grids with deep variable renewable penetration which require flexible NGCC operation. Luna Labs has developed the FlueCO2 membrane to enable a profitable NGCC-CCS process. The FlueCO2 membrane couples steam transport across the membrane to CO2 transport in the opposite direction, enabling high capture efficiencies and low energy costs even at low CO2 concentrations. The dual-phase membrane can operate in the range of typical flue gas temperatures and pressures and does not require temperature or pressure cycling. Luna Labs’ FlueCO2 technology enables flexible and profitable operation of NGCC plants with lower capital investment and impact on electricity prices. In this Phase 1 project, Luna Labs utilized experimental testing, modeling, process simulation, and standardized costing methodologies to evaluate the techno-economic value of a 650 MW greenfield NGCC plant with FlueCO2 (NGCC-FlueCO2). Key design requirements for operation were established and plant performance under load-leveling conditions was validated through computational fluid dynamics and process modeling. Luna Labs developed a dynamic modeling tool which modeled plant operational modes across a variety of tax structures and electricity pricing scenarios to project the overall Net Present Value (NPV) of the NGCC-FlueCO2. FlueCO2 minimizes the impact of CCS integration on plant operation by integrating directly into the NGCC heat recovery steam generator (HRSG). By tapping into the plant’s low-pressure (LP) steam, operators can divert LP steam to the greenfield NGCC and/or CCS process in response to dynamic markets. Since FlueCO2 will not significantly affect HRSG (or NGCC) operation, CCS only turns off during peak power demand (>$250/MWh). Under baseload conditions, FlueCO2 lowers the capital (37%), energy (36%) and carbon capture (<$40/tonne) costs and can increase the overall plant lifetime NPV by approximately ~$1B in comparison with NGCC solvent-based capture reference cases (NETL Case 31B). Luna Labs has shared its costing tools with several interested partners and customers, which follows a generalizable approach to costing analysis.

Kelly, Jesse↗
DOE OSTI2020

Initial Engineering Design of a Post-Combustion CO 2 Capture (PCC) System for Duke Energy’s East Bend Station Using Membrane-Based Technology

The Electric Power Research Institute (EPRI) led a U.S. Department of Energy (DOE) funded study for a membrane-based post-combustion CO 2 capture (PCC) system retrofit to an existing U.S. coal power plant. EPRI teamed with technology suppliers, Membrane Technology and Research (MTR), engineering consultants Nexant, Trimeric Corporation and Bechtel Power Corporation, to develop a first-of-a-kind initial design and cost estimate for a PCC system at Duke Energy’s East Bend Station (EBS) in Kentucky. This project provides a comprehensive overview of the plant design proposed and develops estimated costs to within +/- 30% accuracy for retrofitting the existing EBS coal-fired power plant with the latest MTR’s second-generation Polaris™ membrane technology for CO 2 flue gas removal. The projects primary objective was to develop a design for Duke Energy that will require “minimally invasive surgery” on their existing 600-MWe coal-fired power plant, located on the Ohio River in Boone County, Kentucky. Unlike the current commercially available solvent-based capture systems that require a reliable source of steam to operate, the MTR membrane-based capture system is driven primarily by electric power. This direct, bolt-on approach to retrofitting carbon capture could potentially reduce the impact on the existing power plant, by minimal disruption of the existing facility’s infrastructure and operating procedures. This may also reduce the amount of retrofit downtime before the power plant can resume normal operations. A second objective was to reduce the cost of each ton of captured CO 2 while maintaining the existing 600 MW net output of the East Bend Station. With this aim in mind, various options to provide the necessary auxiliary power for the capture system were evaluated for the site. The full report describes in detail the overall design, layout and components of the entire EBS membrane capture system. The equipment and sizes, the capital cost estimate encompassing both engineering design and construction for the carbon capture process and balance of plant systems is presented. A detailed techno-economic analysis is also undertaken to examine the business case for capture.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Gasification of Coal and Biomass: The Route to Net-Negative-Carbon Power and Hydrogen

One promising process that is a candidate for meeting the goals of the US Department of Energy’s 21st Century Power Plant initiative is to gasify a mixture of coal and biomass to yield a syngas, which can have CO2 removed and then be used to produce hydrogen as well as an off-gas that can be used to flexibly produce power. This concept would overall be carbon net-negative and readily meet the 21st Century Power Plant initiative targets of smaller scale MW generation, high ramp rates and turndown, feedstock flexibility, and high efficiency—at a reasonable cost. Moreover, adding the large-scale production of “ultra-green” hydrogen yields a system tailored for the coming hydrogen economy, providing long-term energy storage and an attractive co-product for sale. The objective of the work being led by the Electric Power Research Institute, Inc. (EPRI), with support by Bechtel Corporation (Bechtel), Gas Technology Institute (GTI), Hamilton Mauer International, Inc. (HMI), Nebraska Public Power District (NPPD), NexantECA, Inc. (Nexant), and Wärtsilä, is to perform a front-end design and engineering (FEED) study on an oxygen-blown gasification system coupled with water-gas shift, pre-combustion CO2 capture, and pressure-swing adsorption working off a coal/biomass mix to yield high-purity hydrogen and a fuel off-gas that can generate power. Several designs are being considered that will be capable of producing 50 MW net from a flexible generator, over 8500 kg/hr of hydrogen, and net-negative CO2 emissions, at an efficiency of 50% net HHV. The plant would be hosted at an NPPD site, where opportunities for enhanced oil recovery and sequestration have been investigated and the need for low-carbon power and hydrogen is imminent. The principal biomass to be used is corn stover—prevalent in Nebraska where the plant will be located—mixed with Powder River Basin (PRB) coal, necessitating a gasifier that can use this feedstock and be flexible to allow other types. Waste plastics will also be reviewed for use. Two oxygen-blown gasifiers have been identified as candidates that have done testing with biomass including corn stover: the GTI gasifier—a high-pressure, fluidized-bed type—and HMI’s, a lower pressure moving-bed type. Both have relative advantages that are being investigated in the Phase I design study, with a resultant down select of one system for which the FEED will be performed in Phase II. The technical tasks for the proposed project are: • Design Development: Completion of design activities necessary to provide inputs for the FEED study. Multiple design cases will be assessed with the selection of the optimal one for the FEED. • Investment Case Preparation: Development of the draft investment case for the proposed process with business cases performed for the proposed host site and two other locations. • Host Site Selection: Evaluation of the two potential host sites within NPPD’s portfolio to select the preferred candidate based on technical, economic, and environmental considerations. • Environmental Information Volume (EIV) Development: Completion of the EIV for the host site. • FEED Study: Completion of a FEED study based on the design selected in Phase I. A Greenhouse Gas Life Cycle Analysis will also be performed for the process. • Update Investment Case: Finalization of the investment case based on findings from the FEED. The advantages of the proposed project are significant. Having an engaged U.S. power utility willing to provide a host site that will produce energy from coal plus a deep and experienced team is critical; the process meets all the goals of DOE’s 21st Century Power Plant initiative at an estimated total plant cost of ~$880M and a production cost of hydrogen of ~$2/kg-H2 while producing net-negative carbon power. If developed, this process has real commercial potential in the United States—supported by EPRI’s initial review of the considerable interest from selected U.S. utilities—and elsewhere around the globe. The process has fewer environmental hurdles compared to other concepts, lowering regulatory and protest risks—providing a pathway to preserving the viability of a critical indigenous energy source by transforming its use to match a changing world. This presentation will outline the motivation for the effort, summarize project plans, work completed to date, results of the Design Development task, and detailed work scope for the remainder of the project.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Analysis of historic fires to determine most frequent challenging events

The fire probabilistic risk assessment framework for nuclear power plants relies on experimental data to determine expected fire behavior or to validate models to predict fire conditions in the plant. To support reducing the uncertainty in this experimental data, a research effort was conducted to identify the most frequent and challenging fire scenarios using historic fire data from nuclear power plants in the United States. To support this effort, an electronic version of the publicly available Updated Fire Event Database developed by Electric Power Research Institute was produced resulting in data on 2111 fire events, 540 events were labelled as being challenging fires with 74.2% of these challenging fire events being due to eleven selected fire types. In conclusion, of these fire types, electrical and electronic equipment, transient combustibles, and liquid fires were the most frequent of the challenging fires. The fire scenario specifics were characterized for each of the eleven selected types and then related to existing fire experiments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Unified Universal Control and Coordination of Inverter-Based Resources, and Validation for a PV + Battery Hybrid Plant

As renewable energy deployment grows, hybrid power plants (HPPs) combining photovoltaic (PV) and battery systems must evolve to offer both energy and grid stability services. These systems typically include a mix of grid-following (GFL) and grid-forming (GFM) inverters, presenting unique coordination and control challenges. This Department of Energy–funded project developed and validated a Unified Universal Control and Coordination (UUCC) framework for such PV + battery hybrid plants, enabling seamless and stable operation, including ultrafast black start, autonomous synchronization, and robust frequency and voltage regulation, under different grid conditions. The project significantly advanced the understanding of inverter-based resource (IBR) control by developing and validating three complementary system-level approaches for hybrid GFL/GFM operation: 1. A combined Virtual Resistance (VR)-based GFL and Virtual Oscillator Control (VOC)-based GFM method, where each inverter type is governed by a specialized control strategy. Together, these achieve stable, fast-response coordination, eliminating inrush current and enabling smooth black start and grid synchronization across a wide range of grid strengths. 2. A Deadbeat-based UUCC strategy, which uses discrete-time, switching-cycle-level control for both GFL and GFM inverters. This approach replaces traditional PI/PLL control with a control parameter-free, high-bandwidth framework that supports stable LVRT and instantaneous synchronization under all conditions. 3. A benchmark comparison with Siemens’ commercial GFM microgrid controller, which provided a fast baseline platform. The commercial approach decoupled v & f control was implemented on a commercial microgrid controller.The baseline commercial benchmark helped highlight superior transient response and black start performance offered by the deadbeat and VOC approaches. These technical contributions offer substantial improvements over conventional inverter control schemes, which often rely on slow phase-locked loop (PLL)-based synchronization, require careful control parameters tuning, and prone to unstable in weak grids with GFL inverters and in stiff grid with GFM inverters therefore challenging for hybrid GFL+GFM under all grid conditions. The deadbeat-based UUCC framework enables simpler, faster, and more robust operation of hybrid IBR systems using wide-bandgap (WBG) devices such as SiC power semiconductors. The rapid expansion of hybrid distributed energy resources (DERs), including residential and commercial PV-BESS installations such as Tesla Powerwall, PV with vehicle-to-grid (V2G) capability, and other integrated configurations, presents complex operational challenges for medium-voltage radial distribution feeders. These networks are subject to frequent disturbances such as faults, switching operations, rapid reclosing sequences, and feeder reconfigurations, all of which introduce dynamic stress on IBRs. In addition, planned feeder segmentation and deliberate islanding for resilience will require DERs that can autonomously perform blackstart, establish voltage and frequency references, and resynchronize with the main grid. The advanced deadbeat-based UUCC control and blackstart functionalities developed in this project directly address these requirements, enabling decentralized and autonomous operation of inverter-dominated DERs in distribution systems under a wide range of fault and reconfiguration scenarios. From a public benefit perspective, these innovations enable more reliable and cost-effective integration of renewable energy into distribution networks. The ability to autonomously black start and stabilize grids under varying grid conditions support accelerates recovery from outages and support decentralized resilient energy systems. By reducing system complexity and improving performance, this project lays critical groundwork for future inverter-dominated power grids that are clean, reliable, and accessible to all.

14 SOLAR ENERGY↗
DOE OSTI2022

Integration of Wireless Sensor Networks and Battery-free RFID for Advanced Reactors

To address an important need for Nuclear Power Plants (NPPs) to significantly reduce the amount of the required cables for sensor data communications, this Phase I SBIR effort successfully developed and demonstrated a novel low-cost proof-of-concept prototype of a secure wireless sensor network backbone communications system. This system combines commercially available low power, low cost XBEE wireless communications network and passive (battery-free) Radio Frequency Identification (RFID) systems to report individual sensor data and their location through the containment wall for rapid response to anomalies in nuclear facilities. This WIreless Sensing and Locating (WISLO) system network architecture allows non-intrusive wireless collection of sensor data with the sensor’s accurate location information from inside of the instrumentation or containment area with minimal need for power sources. The multi-node sensor data in the containment area is wirelessly transmitted to outside through the metal reinforced concrete walls without the need for any batteries. The WISLO system could be readily used in current reactor fleet and future advanced reactors, as well as in small modular reactors (SMR). The WISLO system is the first dual frequency battery-free trough the wall communications backbone system developed specifically for use in nuclear power plants. It not only can modernize the sensor monitoring practices in the existing reactor fleet, but also offers a secure, low-cost solution to advanced reactors and SMRs by removing cables and issues related to them such as cable integrity, reporting delays, and installation and maintenance costs. The intent is to improve process safety, reliability, efficiency, and cost effectiveness to the monitoring and maintenance process in current and future plants. As we address the next productization and manufacturing capabilities in the next phase, this system will serve the needs of many commercial and government applications in remote monitoring of sensor data that demand battery-free transmission of sensor data such as Internet-of-Things (IOT).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Nano-Engineered Catalyst Supported on Ceramic Hollow Fibers for the Utilization of CO 2 in Dry Reforming to Produce Syngas

The objective of this project was to develop a novel catalytic reactor containing nano-engineered catalysts for the utilization of CO 2 (captured from coal-fired power plants and other CO 2 emitting sources) in dry methane reforming (DMR) (CO 2 + CH 4 → 2 H 2 + 2 CO) to produce synthesis gas (syngas). The technology aims to reduce CO2 emissions by developing beneficial uses for CO 2 from coal-fired power plants. It also offers an alternative to mitigate CO 2 emissions in areas where geologic storage may not be an optimal solution and/or utilization could significantly offset the costs of carbon capture and sequestration. The nano-engineered Ni-based catalyst was prepared by atomic layer deposition (ALD). The Ni particles were as small as ~2-4 nm. The nano-engineered catalyst showed CH 4 conversion >95%, H 2 /CO ratio in the range of 0.7-1.0, and CH 4 reforming rate as high as 2,500 L/h/gNi at 850 ºC and pressure of 15-25 psia. The Ni-based ALD catalyst also showed good stability in DMR reaction during a 200-h continuous operation at 850 °C. This is due to strong bonding between the nanoparticles and substrates since the Ni nanoparticles were chemically bonded to the substrate during the ALD process. The high thermal stability maintains the high dispersion of Ni nanoparticles, which can inhibit coke formation because their step edges are small enough to limit carbon nucleation and growth. Technoeconomic analysis (TEA) indicates the levelized cost of syngas (LCOS) is $172/ton with our technology, which is lower than the equivalent (molar) cost of hydrogen produced by steam methane reforming (SMR) or autothermal reforming (ATR). The major operating cost is natural gas feed and fuel, and the levelized cost is highly sensitive to the price of natural gas and relatively insensitive to the CAPEX. Revenues from syngas could have a significant impact on the net cost of electricity (COE), depending on the cost of natural gas and the selling price of syngas, estimated at $36 per MWh if the syngas were sold at $195 per ton. Following DOE NETL’s guidance, a lifecycle analysis (LCA) was conducted to compare with SMR. The functional unit for the basis of comparison was defined as 1kg carbon monoxide in the product stream. The global warming potential (GWP) of our process was found to be 40% lower than the state-of-the-art SMR process. The sensitivity analysis confirms the emissions are most sensitive to the natural gas fuel requirements to deliver heat to the process.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

Low energy neutrino detection with a compact water-based liquid scintillator detector

In this study, the conceptual design and physics simulations of a near-field Water-based Liquid Scintillator (WbLS) detector placed 100 m from the Akkuyu Nuclear Power Plant (ANPP), currently under construction and aiming at being Turkey’s first nuclear power plant, is presented. The ANPP is an excellent opportunity for neutrino studies and the development of an R &D program for neutrino detectors in Turkey. The Reactor Neutrino Experiments of Turkey (RNET) program includes a compact detector with a 2.5-ton volume of WbLS and a ~ 30% photo-coverage, and the program is planned to be expanded with a medium-size 30-ton detector that will be an international testbed for WbLS and new detector technologies through low energy neutrino studies. In the following, the focus will be on the smaller ~2.5 ton detector, instrumented with 8-in. high quantum efficiency PMTs and two layers of cosmic veto paddles, covering all sides of the detector, to track and veto cosmic particles. Inverse Beta Decay (IBD) events from electron anti-neutrinos generated in the reactor core are simulated using the RAT-PAC simulation package and several liquids with different percentages of Liquid Scintillator (LS) and Gadolinium (Gd) are investigated.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Mass transfer intensification through increased surface wetting and liquid turbulence using 3D printing structured packing for CO2 capture

The absorber column is one of the most expensive pieces of equipment to construct in the solvent-based post-combustion carbon capture unit. In order to decrease the absorber size and reduce capital costs, novel polymer packings were proposed by enhancing surface wettability and local turbulence within liquid solvent. The novel packings intensify the mass transfer in CO2 absorption and show better separation efficiency than traditional structured packings. In this work, the economic influence of applying the more efficient packing with a shorter absorber column is studied in a techno-economic analysis for a carbon capture unit at a coal-fired power plant. The baseline case includes CO2 capture unit in a supercritical pulverized coal power plant to generate 650 MWe (net) of electricity, where the additional CO2 capture unit leads to 63.4% increase of LCOE. While implementing UK PCC with traditional and novel packings, there will be 47.2% and 46.4% LCOE increase separately, both of which are lower than the baseline value. Applying more efficient packing and smaller absorber could further lessen the LCOE increase. The UK PCC with traditional packings reduces CO2 capture cost by 23.4% and the application of the advanced packings allows to the reduction increases to 24.4%.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

The role of nuclear in China’s energy future: insights from integrated assessment

China, the world’s largest electricity consumer, has strong motivations to deploy nuclear power due to increasing electricity demand and environmental concerns. However, there are social, institutional, and technical barriers to future nuclear expansion. This paper provides an updated assessment of nuclear energy potential in China with analyses at both national and provincial levels and compares results with studies previously conducted. Using an integrated assessment model, this paper considers the interactions among different socioeconomic development pathways, technology options, climate policies, and social/political concerns on inland siting. Among all factors explored, climate policies have the most significant impact on accelerating the deployment of nuclear technologies. Inland siting of nuclear power plants increases total capacity, but the impact is limited without climate policy. The amount of annual nuclear generation across scenarios and studies is unlikely to rise above 11% by 2030 and 30% by 2050 of total Chinese electricity generation. A dramatic increase in total Chinese nuclear energy generating capacity – around 3900 TWh of nuclear generation by 2050 – is only possible in scenarios where China sees electricity demand increase substantially, sticks to and tightens its current Paris Accord commitments, achieves low costs of nuclear technologies, and allows inland siting of nuclear power plants.

China, integrated assesment, Nuclear Power Plants↗