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The research and development during the project focused on the design and optimization of an integrated heat exchanger/thermal energy storage (HX/TES) system, the charging and discharging performance of the developed HX/TES system, and the experimental investigation of lab-scale prototypes based on the full-scale system.
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This report documents the activities performed by the Idaho National Laboratory (INL) during fiscal year (FY) 2020 for the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program, Risk-Informed System Analysis (RISA) Pathway, Enhanced Resilient Plant (ERP) Systems research. The purpose of the RISA Pathway research and development is to support plant owner-operator decisions with the aim to improve the economics, reliability, and maintain the high levels of safety of current nuclear power plants over periods of extended plant operations. The concept of ERP refers to the combinations of accident-tolerant fuel (ATF), optimal use of diverse and flexible coping strategy (FLEX), enhancements to plant components and systems, and the incorporation of augmented or new passive cooling systems, as well as improved fuel cycle efficiency. The objective of the ERP research effort is to use the RISA methods and toolkit in industry applications, including methods development and early demonstration of technologies, in order to enhance existing reactors’ safety features (both active and passive) and to substantially reduce operating costs through risk-informed approaches to plant design modifications to the plant and their characterization. One main focus of the FY 2020 efforts documented in this report was to extend the analyses conducted in FYs 2018 and 2019 for a pressurized water reactor (PWR) to a boiling water reactor (BWR). The same analysis process, risk analysis approaches, and analysis tools as in the previous work for PWR were used for a generic BWR with near-term ATF cladding (i.e., Iron-Chromium-Aluminum [FeCrAl] cladding and Chromium [Cr]-coated cladding) designs under the postulated station blackout (SBO) and medium loss-of-coolant (MLOCA) accident scenarios. In addition, a FLEX model was developed and incorporated into a generic BWR probabilistic risk assessment (PRA) model using the INL-developed software tool, Systems Analysis Programs for Hands-on Integrated Reliability Evaluations (SAPHIRE), to assess the risk impact from FLEX. The other main focus of the FY 2020 efforts was to advance analysis methods, including developing dynamic approach for FLEX human reliability analysis (HRA) using the INL-developed software tool, Event Modeling Risk Assessment using Linked Diagrams (EMRALD), as well as developing a multicriterion benefit evaluation (MCBE) method for evaluating costs and benefits of safety enhancements in nuclear power plants (NPPs). As a case study, the MCBE method was applied to evaluate the costs and benefits brought by FLEX implementation.
Cellulose is a β-1,4 linked glucose polymer that is synthesized by higher plants, algae and even by some bacteria and animals, making it the most abundant polymer on earth. As the major load bearing structure of the plant cell wall, it is hugely important in terms of plant growth and development, and in recent years it has gained interest for its biotechnological applications. Naturally, there has been a large concerted research effort to uncover the regulatory mechanisms underpinning cellulose synthesis. During the last century, several major breakthroughs in our understanding of cellulose synthesis in algae, bacteria, and plants have been pivotal in advancing the field of cellulose research, improving the likelihood that cellulose synthesis could be feasibly adapted for sustainable purposes. In this work, we will summarize the major hypotheses and advancements made during the last century on the regulation of cellulose biosynthesis, focusing on Arabidopsis thaliana.
Fly ash stored in landfills and ponds across the United States is an attractive, abundant domestic resource for the cost-effective recovery of rare earth elements (REE) and other critical minerals (CM). Physical Sciences Inc. (PSI) and its team members, Winner Water Services (WWS) and University of Kentucky/Center for Applied Energy Research (UK/CAER) successfully executed a multiphase program that developed technologies and their implementation in a pilot plant. We demonstrated plant operations for cost-effective and environmentally-friendly production of rare earth element oxide (REO) concentrates, and the critical minerals scandium and aluminum (in the forms of salts or oxide products), from coal ash. We also constructed and demonstrated a research-scale (0.5 kg/day) micropilot facility to validate the key physical and chemical processing operations, predict yields, and troubleshoot process bottlenecks. The project team then designed, constructed and operated two decoupled pilot plants: (1) an operational pilot plant for physical separation processes with capacity of 0.4 metric tons per day (tpd), where we optimized processes to produce selected ash fractions as the feedstock for chemical processing and as valuable byproducts such as cenospheres, magnetic ash, and secondary fuel carbon, and (2) an operational pilot plant for chemical ash processing with a capacity of 0.5 tpd that developed optimized processes for the production of: (a) REO concentrates, (b) critical minerals (Sc, Al), and (c) beneficiated ash as a valuable byproduct suitable for cement applications. In Phase I, the project team (with Equinox Chemicals in place of WWS) developed and demonstrated the feasibility of the physical and chemical separation processes, developed the design of a pilot plant, and began the development of a preliminary techno-economic model. In the baseline (initial) Phase II program, the project team developed and demonstrated the above pilot scale plant, producing salable REE concentrates, including Y and Sc (REYSc), plus commercially viable byproducts, using environmentally safe and high-yield physical and chemical enrichment processes. The team successfully demonstrated chemical pilot design, construction, shakedown, and operations of the plant. We produced the Phase II deliverable REYSc concentrate ((50 g of >60 wt.% purity REYSc salts on elemental basis), generated the feed for the Phase II follow-on program, identified processing challenges for future optimizations, and refined the techno-economic model. In the Phase II follow-on program, the project team: (1) developed and demonstrated processes to increase the REE amount by 3X (content basis) and convert the Phase II REE salt mixture to an oxide mixture, (2) produced/delivered >38 g of REO mixture with >85 wt.% purity (elemental basis); (3) developed processes to recover critical minerals scandium and aluminum from intermediate streams; (4) produced/delivered > 1 g of scandium salt mixture with >85 wt. % purity (elemental basis); (5) produced/delivered > 100 g of aluminum oxide type material with >70% wt. purity (elemental basis); and (6) updated the techno-economic model from the baseline Phase II program to assess CAPEX and OPEX of a commercial operation. This program has developed extensive databases on process chemistry, unit operations, plant engineering, and techno-economics that will enable further scale-up toward commercial plant design. Specific future developments will be focused on achieving dramatic savings in energy, reagent usage, and operating costs. The combined results will contribute significantly for maturing the technologies of REE recovery from coal byproducts and promote the establishment of domestic REE and CM supply chains.
Abstract The aviation industry’s growing interest in renewable jet fuel has encouraged the exploration of alternative oilseed crops. Replacing traditional fossil fuels with a sustainable, domestically sourced crop can substantially reduce carbon emissions, thus mitigating global climate instability. Pennycress (Thlaspi arvense L.) is an emerging oilseed intermediate crop that can be grown during the offseason between maize (Zea mays) and soybean (Glycine max) to produce renewable biofuel. Pennycress is being domesticated through breeding and mutagenesis, providing opportunities for trait enhancement. Here, we employed metabolic engineering strategies to improve seed oil composition and bolster the plant's economic competitiveness. FATTY ACID ELONGATION1 (FAE1) was targeted using CRISPR-Cas 9 gene editing to eliminate very long chain fatty acids (VLCFAs) from pennycress seed oil, thereby enhancing its cold flow properties. Through an integrated multiomics approach, we investigated the impact of eliminating VLCFAs in developing and mature plant embryos. Our findings revealed improved cold-germination efficiency in fae1, with seedling emergence occurring up to 3 d earlier at 10 °C. However, these alterations led to a tradeoff between storage oil content and composition. Additionally, these shifts in lipid biosynthesis were accompanied by broad metabolic changes, such as the accumulation of glucose and ADP-glucose quantities consistent with increased starch production. Furthermore, shifts to shorter FA chains triggered the upregulation of heat shock proteins, underscoring the importance of VLCFAs in stress signaling pathways. Overall, this research provides crucial insights for optimizing pennycress seed oil while preserving essential traits for biofuel applications.
Biomass contains up to 14 essential elements that serve as nutrients for plant growth and development, including photosynthesis and enzyme functionalities. These elements in different chemical forms (e.g., minerals) constitute the inorganic fraction of biomass and can cause operational issues in thermal and biochemical biomass conversion technologies. In biomass gasification and pyrolysis processes, for instance, inorganics can cause fouling, tar formation, and corrosion. In catalytic and biochemical processes, inorganics can poison catalysts, alter biochemical pathways, and modify product yields and selectivity. This review provides an overview of the inorganic content in biomass feedstocks, the critical role inorganics play in plant biochemistry, the effect that inorganics have in various thermochemical and biochemical biomass conversion technologies, and different approaches to remove them from biomass. We provide recommendations for future research, focusing on developing technologies to effectively remove inorganics from biomass, using the inorganics to improve soil quality and for alternative applications, and designing biorefineries to convert demineralized biomass obtained from diverse sources.
The power grid is undergoing a significant transformation with the rapid increase in inverter-based resources (IBRs), including large-scale photovoltaic (PV) plants. Ensuring reliable and resilient grid operation in this new paradigm necessitates high-granularity electromagnetic transient (EMT) modeling that accurately captures the behavior of individual inverters and their interactions within IBR plants. Central to this approach is the detailed representation of both the IBR plant’s collector system and the dynamics of individual inverters. To achieve this, a high-granularity EMT model of a large-scale PV plant has been developed using advanced simulation algorithms, including matrix splitting and the Schur complement. These proposed techniques significantly enhance simulation speed, numerical stability, and accuracy while improving the modularity and efficiency of the collector system’s representation. The effectiveness of the proposed methods is validated through simulations of a representative large-scale PV plant consisting of 125 individual PV inverters, 25 IBR unit transformers, and a 52-bus collector system.
Abstract Green fluorescent protein (GFP) has been widely used for monitoring gene expression and protein localization in diverse organisms. However, highly sensitive imaging equipment, like fluorescence microscope, is usually required for the visualization of GFP, limitings its application to fixed locations in samples. A reporter that can be visualized in real-time regardless the shape, size and location of the target samples will increase the flexibility and efficiency of research work. Here, we report the application of a GFP-like protein, called eYGFPuv, in both transient expression and stable transformation, in two herbaceous plant species ( Arabidopsis and tobacco) and two woody plant species (poplar and citrus). We observed bright fluorescence under UV light in all of the four plant species without any effects on plant growth or development. eYGFPuv was shown to be effective for imaging transient expression in leaf and root tissues. With a focus on in vitro transformation, we demonstrated that the transgenic events expressing 1x eYGFPuv could be easily identified visually during the callus stage and the shoot stage, enabling early and efficient selection of transformants. Furthermore, whole-plant level visualization of eYGFPuv revealed its ubiquitous stability in transgenic plants. In addition, our transformation experiments showed that eYGFPuv can also be used to select transgenic plants without antibiotics. This work demonstrates the feasibility of utilizing 1x eYGFPuv in studies of gene expression and plant transformation in diverse plants.
The United States is committed to achieving a 50 to 52 percent reduction from 2005 levels in economy-wide net greenhouse gas pollution by 2030, creating a carbon pollution-free power sector by 2035, and achieving net zero emissions economy-wide by no later than 2050. Nuclear energy is essential to meeting those goals. That includes the existing fleet and advanced reactors that are moving forward for deployment and under development. Nuclear power plants produce 20 percent of the total electricity supply in the United States today and are the largest source of carbon-free energy. However, we have an opportunity to expand significantly nuclear energy’s percentage of electricity generated in the United States. The U.S. Department of Energy (DOE) Office of Nuclear Energy (NE) report - developed in response to President Biden’s Executive Order “America’s Supply Chains” signed in 2021 - describes the nuclear supply chain and investigates challenges for continued operation of today’s 93 reactors and construction of advanced reactors. The supply chain is critical for successfully enabling the continued operation of the existing domestic fleet of light-water reactors as well as supporting deployment of advanced nuclear technologies.
Nuclear power plants collect and store large volumes of heterogeneous data from various components and systems. With recent advances in machine learning (ML) techniques, these data can be leveraged to develop diagnostic and short-term forecasting models to better predict future equipment condition. Maintenance operations can then be planned in advance whenever degraded performance is predicted, thus resulting in fewer unplanned outages and the optimization of maintenance activities. This enables lower maintenance costs and improves the overall economics of nuclear power. This paper focuses on developing a short-term forecasting process that leverages a feature selection process to distill large volumes of heterogeneous data and predict specific equipment parameters. A variety of feature selection methods, including Shapley Additive Explanations (SHAP) and variance inflation factor (VIF), were used to select the optimal features as inputs for three ML methods: long short-term memory (LSTM) networks, support vector regression (SVR), and random forest (RF). Each combination of model and input features was used to predict a pump bearing temperature both 1 and 24 hours in advance, based on actual plant system data. The optimal inputs for the LSTM and SVR were selected using the SHAP values, while the optimal input for the RF consisted solely of the response variable itself. Each model produced similar 1-hour-ahead predictions, with root mean square errors (RMSEs) of roughly 0.006. For the 24-hour-ahead predictions, differences could be seen between LSTM, SVR, and RF, as reflected by model performances of 0.036 +- 0.014, 0.0026 +- 0, and 0.063 +- 0.004 RMSE, respectively. As big data and continuous online monitoring become more widely available, the proposed feature selection process can be used for many applications beyond the prediction of process parameters within nuclear infrastructure.
This study explores the potential benefit to the used nuclear fuel actinide recovery flowsheet of a process simplification and establish the experimental work needed to develop the simplified flowsheet. The simplification is based on replacing acid dissolution of used nuclear fuel with dissolution in the tri-butyl phosphate solvent used in the industrially mature Plutonium Uranium Reduction Extraction flowsheet. Though characterized by considerable uncertainty, simplified flowsheets appear feasible and potentially offer significant reductions in process complexity, nitrate inventory, secondary liquid effluent generation and plant footprint. Initial development of the technology should focus on key fission product and actinide dissolution as a function of process conditions and understanding the fundamental chemistry of tri-butyl phosphate solvent chemistry. Development of ancillary technologies for minor actinide separations and fuel pretreatment for tritium management is also recommended.
Uncovering genes encoding enzymes responsible for the biosynthesis of diverse plant metabolites is essential for metabolic engineering and production of plant metabolite-derived medicine. With the availability of multi-omics data for an ever-increasing number of plant species and the development of computational approaches, the metabolic pathways of many important plant compounds can be predicted, complementing a more traditional genetic and/or biochemical approach. In this work, we summarize recent progress in predicting plant metabolic pathways using genome, transcriptome, proteome, interactome, and/or metabolome data, and the utility of integrating these data with machine learning to further improve metabolic pathway predictions.
Utilities and grid operators worldwide are under significant pressure to incorporate intermittent renewable sources while strategizing on how to maintain the necessary stability and reliability of the grid. The development of a power plant which will be capable of flexible operation to meet the needs of the grid as more intermittent sources like wind and solar energy are incorporated is key to maintain the reliability of the grid. Through the use of innovative and cutting-edge technologies that improve efficiency and reduce carbon emissions, and being small compared to today's conventional utility-scale power plants, the modular Staged, Pressurized Oxy-Combustion (SPOC) process envisioned by and under development at Washington University in St. Louis (WUSTL) has the potential to achieve these goals. Specifically, the process offers: 1) a modular plant design that allows for better operational flexibility; 2) the utilization of fuel-staging and pressurized oxy-combustion, resulting in smaller plant size, improved plant efficiency, and reduced costs for pollutant and CO2 removal compared to traditional power plants with post-combustion capture technology; and 3) the use of small modular boilers and pollutant removal units that can be constructed off-site leading to reduced capital costs for the plant. WUSTL is advancing the development of the critical components for the SPOC power plant, including the integrated combustor-boiler system and the direct contact cooler. To demonstrate the boiler convective section and to obtain critical data for commercial-scale pressurized boiler design, a simulated convective heat transfer boiler test section was designed and integrated with the combustor (radiant section). A direct contact cooler (DCC) was integrated with the combustor-boiler to demonstrate the dynamic operation of the integrated system and the performance of the DCC, including the efficiency for simultaneous removal of NOx and SOx. This talk will present an update on the evaluation of the critical components for system integration, including heat transfer data from the simulated boiler, scrubbing efficiency for the DCC under different operating conditions, and CFD modeling and validation for burner and boiler development.
This final report summarized the research efforts and major findings of the Phase I Project “Development of Corrosion- and Erosion-Resistant Coatings for Advanced Ultra-Supercritical Materials”, for the period of October 1, 2019 – Sept. 30, 2021. This project is a collaborative endeavor between Tennessee Tech University, Purdue University, Oak Ridge National Laboratory, Siemens Corporation, and Eastern Plating, LLC, aiming at improving the durability and lifetime of high-pressure (HP) steam turbine blades in advanced ultra-supercritical (A-USC) coal-fired power plants through the development of corrosion/erosion-resistant coatings manufactured via a low-cost electrolytic codeposition process. While Tribaloy alloy T-400C was identified by the U.S. A-USC Materials Consortium as a promising coating composition, further composition optimization is needed to enhance its corrosion and erosion resistance for protecting the A-USC Ni-base turbine components. An integrated computational and experimental approach was employed to optimize coating composition/microstructure and processing parameters. In order to identify candidate coating compositions that could offer balanced properties, thermodynamic calculations were performed to explore the γ+Laves composition space in the Co-Ni-Cr-Mo-Si system with different alloying additions at 600-800 °C. Guided by the calculation results, experimental assessment of selected alloys led to the development of a new generation of Tribaloy compositions with the optimal levels of Cr, Mo and Si, reactive element (e.g., 0.4-0.6 wt.% Y) and other alloying additions. The low-cost and non-line-of-sight electro-codeposition process was employed to deposit a Ni(Co)-CrMoSiY composite coating on commercial Haynes 282 (H282) Ni-base alloy. A diffusion treatment was subsequently applied to convert the composite to the Tribaloy-type coating. Both the codeposition parameters and heat treatment conditions were varied to achieve the desired coating composition, microstructure and phase constituents. In addition, since additive manufacturing (AM) may be an alternative cost-saving option for potential A-USC turbine repair, laser direct deposition was explored to fabricate the H282 alloy with minimal defects. The electro-codeposited Tribaloy coating was also applied to the AM H282 substrate to demonstrate the viability of the coating process in improving the surface finish of AM alloys. Both high-temperature oxidation performance and solid particle erosion (SPE) resistance of model alloys and electro-codeposited coatings were evaluated. About 25 model alloys with various Cr/Mo ratios and reactive element levels, as well as partial substitution of Mo with Nb were evaluated with regard to their oxidation resistance in both air and pure steam at 760-800°C. Compositions based on Ni(Co)-20Cr-18Mo-2.6Si-0.6Y (wt.%) showed significantly improved oxidation resistance over the baseline T400-C. Based on the alloy development results, three generations of new Tribaloy coatings (Gen-1, Gen-2, and Gen-3) with various Mo/Cr contents and Y levels were prepared via electro-codeposition and their microstructure/performance were evaluated. Outstanding air and steam oxidation resistance was achieved for the Gen-2 and Gen-3 coatings. Furthermore, while the SPE resistance of the coatings depended on many factors such as temperature, environment, erodent, velocity and impact angle, the coated samples exhibited similar or better SPE resistance compared to the H282 substrate when magnetite was used as erodent (which is a realistic erodent in A-USC steam turbines). The new Tribaloy coatings also had good long-term compatibility with the H282 alloy substrate. The two large-sized rotating barrels were designed, constructed, and employed to coat dummy HP blades. Uniform coating thickness and microstructure were achieved at various blade locations. Also, a preliminary techno-economic analysis of the proposed coating process was conducted to quantify the cost-effectiveness and to assess the commercial viability of the corrosion- and erosion-resistant coatings. It is estimated that a cost reduction of ~30% could be achieved with the electro-codeposition coating process over the state-of-the-art high velocity oxygen fuel (HVOF) thermal spray. Compared to the leading Tribaloy coating technologies such as HVOF and plasma transfer alloying, electro-codeposition based process has advantages such as low-cost process equipment, uniform deposition even for complex shapes, low levels of contaminants/porosities, reduction of powder waste, and potentially better surface finish and longer turbine service life. The Phase 1 study has demonstrated that it is feasible to develop an electro-codeposited Tribaloy coating with balanced corrosion and erosion properties, even though additional research efforts such as further coating process scale-up and longer-term performance evaluation under realistic A-USC conditions are clearly needed.
Despite their advantages, distributed energy resources (DERs) bring inherent uncertainty and variability into the landscape of modern power systems. As DER penetration grows, conventional generators like hydropower plants have to respond more often to arrest the imbalance in the net load. Hydropower turbines provide their best operational performance with minimal wear and tear when operating at regions of maximum efficiency. However, the current needs for hydropower plants require them to operate under varying load conditions and thus sub-optimal operating points leading to additional stress. To relieve the hydropower plants, this paper proposes a hybridization strategy where a hydropower unit is paired with an energy storage system (ESS) to increase operational flexibility and mitigate damage to the hydro plant. Models are developed to represent the operation of the hybrid system, quantify degradation, and assess economic benefits. Moreover, an innovative controller disaggregates the market dispatch signal into separate control setpoints for the ESS and hydropower unit. In case studies performed on a real-world hydropower facility, it was found that the ESS-based hybridization can extend the life of the hydropower plant by 5% on average. Notably, the economic benefits from reduced maintenance and deferred investment are estimated to be around $3.6 million.
The rhizosphere is the narrow region of soil surrounding the roots of plants that is influenced by root exudates, root secretions, and associated microbial communities. This region is crucial to plant growth and development and plays a critical role in nutrient uptake, disease resistance, and soil transformation. Understanding the function of exogenous compounds in the rhizosphere starts with determining the spatiotemporal distribution of these molecular components. Using liquid microjunction surface-sampling probe mass spectrometry (LMJ-SSP-MS) and microfluidic devices with attached microporous membranes enables in situ, nondisruptive, and nondestructive spatiotemporal measurement of exogenous compounds from plant roots. However, long imaging times (>2 h) can negatively affect plant heath and limit temporal studies. Here, we present a novel strategy to optimize the number and location of sampling sites on these microporous membrane-covered microfluidic devices. In conclusion, this novel, “structure-driven” sampling workflow takes into consideration the channel structure of the microfluidic device to maximize sampling from the channels and minimize acquisition time (~4× less time in some cases while providing similar chemical image accuracy), thus reducing stress on plants during in situ LMJ-SSP-MS analysis.
Abstract The stems of bioenergy sorghum hybrids at harvest are > 4 m long, contain > 40 internodes and account for ~ 80% of harvested biomass. In this study, bioenergy sorghum hybrids were grown at four planting densities (~ 20,000 to 132,000 plants/ha) under field conditions for 60 days to investigate the impact shading has on stem growth and biomass accumulation. Increased planting density induced a > 2-fold increase in sorghum internode length and a ~ 22% decrease in stem diameter, a typical shade avoidance response. Shade-induced internode elongation was due to an increase in cell length and number of cells spanning the length of internodes. SbGA3ox2 (Sobic.003G045900), a gene encoding the last step in GA biosynthesis, was expressed ~ 20-fold higher in leaf collar tissue of developing phytomers in plants grown at high vs. low density. Application of GA3 to bioenergy sorghum increased plant height, stem internode length, cell length and the number of cells spanning internodes. Prior research showed that sorghum plants lacking phytochrome B, a key photoreceptor involved in shade signaling, accumulated more GA1 and displayed shade avoidance phenotypes. These results are consistent with the hypothesis that increasing planting density induces expression of GA3-oxidase in leaf collar tissue, increasing synthesis of GA that stimulates internode elongation.