Predicting Process Area Workforce for Human Resource Development in a Nuclear Power Plant
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Egieya, Jafaru Musa↗
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Predicting Process Area Workforce for Human Resource Development in a Nuclear Power Plant
Explore the source record for details and available documents.
Dahunsi, Stephen↗
Attrition Cycling of Thermally Aged Generation 3 Particle CSP Media
An experimental methodology to simulate and characterize the attrition of solid particles used as heat transfer and storage media in third generation concentrating solar power plants was developed and implemented.
14 SOLAR ENERGY↗
Risk-informed Predictive Analytics To Achieve Cost-effective Condition-based Monitoring And Maintenance Strategy
The research involves developing risk-informed predictive analytic capabilities to achieve condition-based monitoring and maintenance strategies to reduce overall maintenance costs. The research utilizes data (real-time data, periodic data, and institutional knowledge) related to a particular plant asset from a specific nuclear plant site to develop risk-informed predictive analytic algorithms. The developed algorithms and codes are used to optimize the maintenance strategy and estimate/forecast generation costs based on the state of health of the plant asset. Developed codes specifically include 1. Parameter estimation code based on Bayesian inference 2. Statistical data analysis code 3. Feature engineering code 4. Health classifier code 5. Diagnosis code 6. Prognosis code 7. Hazard code 8. Generation risk code 9. Economic code
Agarwal, Vivek↗
Nanoparticle cellular internalization is not required for RNA delivery to mature plant leaves
Rapidly growing interest in the nanoparticle-mediated delivery of DNA and RNA to plants requires a better understanding of how nanoparticles and their cargoes translocate in plant tissues and into plant cells. However, little is known about how the size and shape of nanoparticles influence transport in plants and the delivery efficiency of their cargoes, limiting the development of nanotechnology in plant systems. In this study we employed non-biolistically delivered DNA-modified gold nanoparticles (AuNPs) of various sizes (5-20 nm) and shapes (spheres and rods) to systematically investigate their transport following infiltration into Nicotiana benthamiana leaves. Generally, smaller AuNPs demonstrated more rapid, higher and longer-lasting levels of association with plant cell walls compared with larger AuNPs. We observed internalization of rod-shaped but not spherical AuNPs into plant cells, yet, surprisingly, 10 nm spherical AuNPs functionalized with small-interfering RNA (siRNA) were the most efficient at siRNA delivery and inducing gene silencing in mature plant leaves. These results indicate the importance of nanoparticle size in efficient biomolecule delivery and, counterintuitively, demonstrate that efficient cargo delivery is possible and potentially optimal in the absence of nanoparticle cellular internalization. Additionally, our results highlight nanoparticle features of importance for transport within plant tissues, providing a mechanistic overview of how nanoparticles can be designed to achieve efficacious biocargo delivery for future developments in plant nanobiotechnology.
59 BASIC BIOLOGICAL SCIENCES↗
Combined Nitrogen and Phosphorous Recovery via Electrochemical Technology Integration into Municipal Wastewater Treatment Plants
This project developed electroN-P, an electrochemical technology for recovering nitrogen and phosphorus as a fertilizer product from anaerobic digester centrate, targeting an advancement from TRL 4 to 6. The reactor was scaled 220× from a 250 mL batch cell to a continuous 4-channel system treating 55 L of wastewater, recovering >80% of phosphorus. Energy consumption under constant-voltage operation was lower than the embedded energy of conventional fertilizers, while constant-current operation produced a cost-competitive product with a smaller reactor footprint. TEA and LCA outcomes were highly sensitive to the magnesium source; alternative magnesium salt configurations projected reduced costs and embedded energy compared to sacrificial rods, but at the expense of significantly longer operation times. The recovered fertilizer performed comparably to diammonium phosphate and triple superphosphate in soil and plant trials. Integrating the technology into a whole-plant model reduced aeration energy by nearly 50%, lowering the levelized cost of water treatment from $0.668/m 3 to $0.648/m 3 . Results support targeting commercialization at smaller (≤1 MGD) facilities with high-strength digester streams. Further investigation into the transport and corrosion kinetics governing sacrificial anode wear is recommended to support continuous, longer-term operation.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Models implemented in the methodological approach to design the initial STEP first wall contour
The official Spherical Tokamak for Energy Production mission aims to demonstrate the ability to generate net electricity from fusion with the STEP Prototype Power plant. One of the key technological and engineering challenges in fusion power plants is managing the loads on the first wall within acceptable limits. Therefore, the conceptual design development of the STEP Prototype Power plant needs to be based on load estimates derived using legitimate plasma physics assumptions through dynamic and flexible tools. The current design foresees the STEP main chamber first wall to withstand steady-state heat loads of up to ~1 MW/m 2 , excluding critical regions expected to receive higher heat loads such as the baffle regions approaching the divertors. These critical areas will require ad hoc assessments and will be designed with the presence of limiters. This article focuses on the models and methodology adopted for designing the 2-D poloidal contour of the STEP first wall, based on the anticipated charged particle and radiation heat loads during normal operation. Firstly, the models adopted for calculating the charged particle and radiation heat loads are introduced. The first model is validated through benchmarking against the particle tracing code SMARDDA, while the second model is verified by comparing it with data from the MAST-U experiment. Secondly, the model used to design the 2-D first wall contour according to the heat loads is explained. We acknowledge that this preliminary design stage assumes certain simplifications, notably an axisymmetric geometry, for computational efficiency and clarity in presentation. It is understood that subsequent design phases will address the complexities of real-world engineering, including non-axisymmetric effects, transient plasma scenarios, and the impact of disruptions on the first wall design. Finally, an automatic procedure based on these models is presented for defining the 2-D poloidal contour of the STEP first wall to minimize heat loads, taking into account the need to radiate most of the alpha-particle and auxiliary heating power. Here, by providing an overview of the models, methodology, and an automatic procedure, this paper contributes to the design process of the STEP first wall, addressing the engineering challenges associated with fusion power plant development.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Scalable Predictive And Risk Technologies
The research involves developing scalable technologies for risk-informed predictive analytics to achieve condition-based monitoring and maintenance strategies to reduce overall maintenance costs. The research utilizes data (real-time data, periodic data, and institutional knowledge) related to a particular plant asset from a specific nuclear plant site to develop technologies to scale risk-informed predictive analytic algorithms across different plant assets at the plant site and across the nuclear fleet. The developed algorithms and codes are used to optimize the maintenance strategy and estimate/forecast generation costs based on the state of health of the plant asset. Developed codes specifically include 1. Parameter estimation using plant operation data 2. Federated and Transfer learning model 3. Feature group based Multi-kernel SVM 4. Three state markov model
Manjunatha, KoushikAraseethota↗
The PHASE Project: New Research and Tools to Inform Pollinator Habitat on Utility-Scale Solar
The solar industry is responding to demand for building a clean energy future. At the same time, pollinator declines and habitat losses are resulting in listing consideration for once-common species like monarch butterflies, plus petitions to list bees and other species. How can projects responsibly co-locate pollinator plantings at solar facilities? What ecological and performance benefits can be realized from pollinator plantings? How do developers and owners weigh the costs and challenges of maintaining pollinator plantings and determine the effects it has on power generation, community acceptance, and operations? The Pollinator Habitat Aligned with Solar Energy (PHASE) project is a four-year research project that aims to answer these questions and better support the solar industry in successfully implementing pollinator plantings. This project is funded by the U.S. Department of Energy's Solar Energy Technologies Office. In collaboration with an advisory group composed of industry and technical professionals, the PHASE team developed methodologies to evaluate the impacts of plantings on both biodiversity and the facility operations, including the diversity of plant and insect communities, pollinator services being provided by the site, and the effects of pollinator vegetation on panel temperature and efficiency. The PHASE team also used data to develop tools designed to better support solar industry decision-making on pollinator vegetation including a Pollinator Planting Implementation Manual, a Cost Comparison Tool, a Seed Selection Tool, and Habitat Assessment Module Guidance. Final versions of the four tools will be released this year.
agrivoltaic↗
Redundant roles of four ZIP family members in zinc homeostasis and seed development in Arabidopsis thaliana
Zinc (Zn) is essential for normal plant growth and development. The Zn-regulated transporter, iron-regulated transporter (IRT)-like protein (ZIP) family members are involved in Zn transport and cellular Zn homeostasis throughout the domains of life. In this study, we have characterized four ZIP transporters from Arabidopsis thaliana (IRT3, ZIP4, ZIP6, and ZIP9) to better understand their functional roles. The four ZIP proteins can restore the growth defect of a yeast Zn uptake mutant and are upregulated under Zn deficiency. Single and double mutants show no phenotypes under Zn-sufficient or Zn-limited growth conditions. In contrast, triple and quadruple mutants show impaired growth irrespective of external Zn supply due to reduced Zn translocation from root to shoot. All four ZIP genes are highly expressed during seed development, and siliques from all single and higher-order mutants exhibited an increased number of abnormal seeds and decreased Zn levels in mature seeds relative to wild type. The seed phenotypes could be reversed by supplementing the soil with Zn. Finally, our data demonstrate that IRT3, ZIP4, ZIP6, and ZIP9 function redundantly in maintaining Zn homeostasis and seed development in A. thaliana.
59 BASIC BIOLOGICAL SCIENCES↗
Coal Power Plant Reinvestment Visualization Tool
This tool, available at https://energycommunities.gov/coal-power-plant-reinvestment-visualization-tool/, serves as a public database and map for the purposes of enabling state and local economic development officials, project developers, and power plant owners to identify and pursue opportunities for plant and community reinvestment. The Coal Power Plant Reinvestment Visualization Tool focuses on coal power plants that have been closed or set-to-retire, alongside key infrastructure characteristics that are relevant for potential redevelopment reinvestment opportunities, including the opportunity to query these data based off pre-defined or user-set queries to identify opportunities for coal power facility reinvestment to support solar, wind, manufacturing, and nuclear. These Data for visualization and query include, but are not limited to: • Electric Transmission Lines • EPA Brownfield Sites (assessed with Federal funding) • Petroleum Terminals • Ports • Railroads • Others The tool will be updated periodically to provide relevant information to enable state and local economic development officials, project developers, and power plant owners to identify and pursue opportunities for economic revitalization and community reinvestment. Within this application data are focused on U.S. power plants with coal generation, where at least one on-site generator utilizes or utilized coal as a fuel source, including planned retirements through 2058 (EIA, 2024). Additional information on energy communities and revitalization opportunities can be accessed on the Interagency Working Group on Coal & Power Plant Communities & Economic Revitalization Energy Communities website (https://energycommunities.gov).
Closures↗
GmMPK6 Positively Regulates Salt Tolerance through Induction of GmRbohI1 in Soybean
Salt stress is a critical environmental stress that impairs plant growth and development, especially in crop productivity; therefore, understanding the salt response in plants is the basis for their development of salt tolerance. Under salinity, soybean mitogen-activated protein kinase 6 (GmMPK6) is activated and positively regulates reactive oxygen species (ROS) generation. However, it is not yet elucidated how GmMPK6 regulates ROS generation and its role in salt tolerance. Here, we show that GmMPK6, solely activated in NaCl treatment, and gene expression of GmRbohI1 was not only reduced by MPK inhibitor SB202190 in NaCl treatment, but also increased in a GMKK1-expressing protoplast. Furthermore, SB202190 and the NADPH-oxidase inhibitor, diphenyleneiodonium chloride, increased susceptibility to salt stress. The expression of GmRD19A was induced by NaCl treatment, but this expression was compromised by SB202190. Consequently, we revealed that GmMPK6 induces ROS generation through the transcriptional regulation of GmRbohI1 and increases salt tolerance in soybean.
59 BASIC BIOLOGICAL SCIENCES↗
Developing an AI-Powered Zero-Trust Cybersecurity Framework for Malware Prevention in Nuclear Power Plants
This study presents the development of an AI-powered Zero-Trust cybersecurity framework for malware prevention in nuclear power plants. The framework aims to enhance the security of critical systems within nuclear power plants by adopting the principles of Zero-Trust and leveraging artificial intelligence (AI) technologies. By assuming no implicit trust in any user or device and continuously authenticating and authorizing access, the framework ensures a robust defense against malware attacks. The integration of AI allows for the detection and prevention of malware through behavioral analytics, endpoint protection, network segmentation, and continuous monitoring. The paper discusses the key considerations, steps, and technologies involved in developing this framework, emphasizing the importance of regular updates, training, compliance, and auditing. The proposed framework serves as a comprehensive approach to safeguarding nuclear power plants from sophisticated malware threats and protecting the integrity and safety of critical infrastructure.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Maintaining the structural and functional homeostasis of the plant endoplasmic reticulum
The endoplasmic reticulum (ER) is a ubiquitous organelle that is vital to the life of eukaryotic cells. It synthesizes essential lipids and proteins, and initiates the glycosylation of intracellular and surface proteins. As such, the ER is necessary for cell growth and communication with the external environment. The ER is also a highly dynamic organelle, whose structure is continuously remodeled through an interaction with the cytoskeleton and the action of specialized ER shapers. Recent and significant advances in ER studies have brought to light conserved and unique features underlying the structure and function of this organelle in plant cells. Exciting developments in the understanding of the mechanisms for plant ER structural and functional homeostasis, particularly those that underpin ER network architecture and ER degradation, are presented and discussed in this work.
59 BASIC BIOLOGICAL SCIENCES↗
Comparison of Fuel Cycles for Lead-Lithium and Pure Lithium Liquid Metal Walls in a Magnetized Target Fusion Power Plant
General Fusion (GF) is developing an adaptable, commercial fusion power plant based on magnetized target fusion (MTF). The GF approach involves forming a spherical torus of deuterium-tritium plasma in a large (~4 m diameter) cavity formed in liquid metal, and then collapsing that cavity with an array of pneumatic piston drivers. The liquid metal is constantly flowing through the fusion chamber and out to processing systems where tritium and heat will be extracted using tritium extraction technologies and heat exchangers, respectively. Here, this study focuses on two candidate designs for the liquid metal blanket and first wall material for the General Fusion Magnetized Target Fusion (GF MTF) power plant and assesses their impact on the tritium fuel cycle. The first candidate is the lead lithium eutectic (LLE) and the second candidate is pure lithium (Li). It was found that the main differences between LLE and Li designs are the extraction technologies required to remove tritium from the blanket and the amount of tritium and its distribution within the facility. More than 80% of the in-process tritium inventory for the LLE design is contained in the isotope separation system, while for the Li design, over 60% of the in-process tritium inventory is contained within the blanket material. This is due to significant tritium retention by Li. For the Li blanket, the burden of tritium processing rests on the blanket extraction technology rather than the traditional exhaust processing route. Thus, the blanket extraction technology is a main driver of tritium inventory in the Li system and determines the subsequent interface with the tritium processing plant.
General Fusion↗
Data for Expression of a Bacterial Trehalose 6-Phosphate Synthase Gene otsA in Camelina sativa Seeds Promotes the Channelling of Carbon Towards Oil Accumulation
Improving seed oil yield is essential for developing Camelina sativa as a sustainable biofuel crop. Fatty acid synthesis depends on the production of acetyl-CoA from photosynthetically derived sugars. Trehalose 6-phosphate (T6P), a proxy for sucrose availability, can link sugar status to plant growth and development. Synthesised by trehalose 6-phosphate synthase (TPS) from UDP-glucose and glucose-6-phosphate, T6P plays a regulatory role in metabolism. Our previous studies on Arabidopsis transgenic lines constitutively expressing the E. coli otsA (encoding TPS) showed increased T6P levels and seed triacylglycerol, along with stunted growth. In the present study we express otsA in camelina under the control of a seed-specific Phaseolin promoter. Seeds of the resulting transgenic lines accumulated high levels of T6P, and a 15%–20% increase in total fatty acids and triacylglycerol compared to wild-type. Molecular analysis showed the transgenic seeds had reduced SnRK1 activity, elevated WRI1 protein levels, and increased the levels of WRI1 and its target genes, along with enhanced rates of fatty acid synthesis that increased seed weights relative to wild type. Notably, the increase in oil did not affect seed protein levels but did reduce the soluble metabolite fraction. Crucially, seed-specific expression of otsA mitigated the growth defects associated with constitutive otsA expression, and the transgenic lines showed normal seed development and germination. These findings demonstrate that targeted T6P modulation via seed-specific otsA expression is an effective metabolic engineering strategy to boost oil production in camelina and potentially in other oilseed crops and bioenergy crops such as energycane, sorghum and miscanthus.
Lipids↗
Plant science decadal vision 2020–2030: Reimagining the potential of plants for a healthy and sustainable future
Abstract Plants, and the biological systems around them, are key to the future health of the planet and its inhabitants. The Plant Science Decadal Vision 2020–2030 frames our ability to perform vital and far‐reaching research in plant systems sciences, essential to how we value participants and apply emerging technologies. We outline a comprehensive vision for addressing some of our most pressing global problems through discovery, practical applications, and education. The Decadal Vision was developed by the participants at the Plant Summit 2019, a community event organized by the Plant Science Research Network. The Decadal Vision describes a holistic vision for the next decade of plant science that blends recommendations for research, people, and technology. Going beyond discoveries and applications, we, the plant science community, must implement bold, innovative changes to research cultures and training paradigms in this era of automation, virtualization, and the looming shadow of climate change. Our vision and hopes for the next decade are encapsulated in the phrase reimagining the potential of plants for a healthy and sustainable future. The Decadal Vision recognizes the vital intersection of human and scientific elements and demands an integrated implementation of strategies for research (Goals 1–4), people (Goals 5 and 6), and technology (Goals 7 and 8). This report is intended to help inspire and guide the research community, scientific societies, federal funding agencies, private philanthropies, corporations, educators, entrepreneurs, and early career researchers over the next 10 years. The research encompass experimental and computational approaches to understanding and predicting ecosystem behavior; novel production systems for food, feed, and fiber with greater crop diversity, efficiency, productivity, and resilience that improve ecosystem health; approaches to realize the potential for advances in nutrition, discovery and engineering of plant‐based medicines, and "green infrastructure." Launching the Transparent Plant will use experimental and computational approaches to break down the phytobiome into a "parts store" that supports tinkering and supports query, prediction, and rapid‐response problem solving. Equity, diversity, and inclusion are indispensable cornerstones of realizing our vision. We make recommendations around funding and systems that support customized professional development. Plant systems are frequently taken for granted therefore we make recommendations to improve plant awareness and community science programs to increase understanding of scientific research. We prioritize emerging technologies, focusing on non‐invasive imaging, sensors, and plug‐and‐play portable lab technologies, coupled with enabling computational advances. Plant systems science will benefit from data management and future advances in automation, machine learning, natural language processing, and artificial intelligence‐assisted data integration, pattern identification, and decision making. Implementation of this vision will transform plant systems science and ripple outwards through society and across the globe. Beyond deepening our biological understanding, we envision entirely new applications. We further anticipate a wave of diversification of plant systems practitioners while stimulating community engagement, underpinning increasing entrepreneurship. This surge of engagement and knowledge will help satisfy and stoke people's natural curiosity about the future, and their desire to prepare for it, as they seek fuller information about food, health, climate and ecological systems.
59 BASIC BIOLOGICAL SCIENCES↗
US Department of Energy Better Plants Program’s Approach to Manufacturing Workforce Development
Multiple studies suggest that by 2030, millions of jobs may go unfilled because of a significant skills gap between the current manufacturing workforce and the workforce needed to support the shift toward advanced and sustainable manufacturing. According to US manufacturers, finding the right talent is more difficult now than in previous years. Developing a well-trained workforce will play a critical role in transforming the manufacturing sector into a net-zero contributor of greenhouse gas emissions by 2050. To help reduce energy, water, waste, and greenhouse gas emissions as well as build a strong, sustainable manufacturing workforce, the US Department of Energy created the voluntary Better Plants program in 2011. This study discusses the program’s various workforce development activities, including in-plant trainings, virtual in-plant trainings, and in-person bootcamps. The target audiences, training objectives, and topics designed to upskill workers for a low-carbon manufacturing future are described. Feedback that was collected (e.g., new training topics, certifications, hands-on activities) while working with more than 270 US manufacturers for the past 12 years on workforce development are discussed. Finally, some strategies are proposed to address the feedback.
Guo, Wei↗