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

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Sensitivity and Importance Measure Analyses for Various Design Architectures for High Safety-Significant Safety-Related Digital Instrumentation and Control Systems of Nuclear Power Plants

A transition from analog instrumentation and control (I&C) technologies to digital I&C technologies is taking place for license renewals of existing nuclear power plants and for operating licenses of new advanced reactors. This transition necessitates research on risk and economic assessments of digital I&C technologies to ensure the long-term safety and reliability of vital systems, reduce uncertainty in licensing costs in addition to timeline, support integration of digital I&C systems in the plant, and find the most efficient technology upgrades. Adding redundancy within systems or components is a common means of improving design safety; however, it can also make designs more prone to common-cause failures (CCFs). Introducing diversity into redundant systems or components is a way to mitigate and possibly eliminate CCFs, but it also increases plant complexity and may be costly. The balance between redundancy and diversity remains a challenge for digital I&C systems. This study performs sensitivity and importance analyses for four design architectures of two digital I&C systems—the reactor-trip system and the engineered safety features actuation system. For each system, two architectures are examined, including a redundant, non-diverse configuration and a redundant, diverse configuration. The sensitivity analysis will provide insights on the impact of introducing diversity to system reliability. The importance results will help identify risk-significant and risk-sensitive components and failure modes, which may be good candidates for future design improvement.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Cropbox: a declarative crop modelling framework

Abstract We introduce Cropbox, a novel modelling framework that supports various aspects of crop modelling in a unique yet concise style. Building a crop model can be easily riddled with technical details looking trivial at first but later becoming major obstacles that hamper the whole development or application process. This is particularly the case when implementing models from scratch without relying on an established framework. Cropbox adopts a declarative approach providing a domain-specific language to reduce technical debt and assist modellers to focus on high-level abstraction formed by relations between variables and enclosing systems, rather than tinkering with low-level implementation details. The syntax of Cropbox framework is based on the Julia programming language and is deliberately constrained to avoid unintended side effects caused by common mistakes while its architecture remains open to extension. We highlight key capabilities of the framework through case studies featuring a leaf gas-exchange model and a whole-plant simulation model. We also illustrate potential extensions for supporting functional-structural plant modelling by demonstrating a 3D root architectural model as an example.

Yun, Kyungdahm (ORCID:0000000322894386)↗
DOE OSTI2020

Dynamic Construction, Perception, and Remodeling of Plant Cell Walls

Plant cell walls are dynamic structures that are synthesized by plants to provide durable coverings for the delicate cells they encase. They are made of polysaccharides, proteins, and other biomolecules and have evolved to withstand large amounts of physical force and to resist external attack by herbivores and pathogens but can in many cases expand, contract, and undergo controlled degradation and reconstruction to facilitate developmental transitions and regulate plant physiology and reproduction. Recent advances in genetics, microscopy, biochemistry, structural biology, and physical characterization methods have revealed a diverse set of mechanisms by which plant cells dynamically monitor and regulate the composition and architecture of their cell walls, but much remains to be discovered about how the nanoscale assembly of these remarkable structures underpins the majestic forms and vital ecological functions achieved by plants.

biofuels (including algae and biomass), bio-inspir↗
DOE OSTI2022

DEEPER: An Intergrated Platform for Deeper Roots

Crops with deeper roots would have multiple benefits, including better drought tolerance, reduced requirement for nitrogen fertilizer, and better sequestration of atmospheric CO 2 . DEEPER is an integrated platform of phenomic, genomic, and in silico technologies to generate maize lines with deeper roots. DEEPER is: LEADER (Leaf Elemental Accumulation from Deep Roots) is a breakthrough technology to nondestructively measure rooting depth by using the plant itself as a sensor. LEADER uses handheld X-ray Fluorescence spectrometry to quantify foliar accumulation of elements that are differentially distributed in the soil profile. LEADER is nondestructive and is orders of magnitude cheaper, faster, and more precise than any competing assay of rooting depth in the field. LEADER is able to distinguish deep-rooted from shallow-rooted maize lines in the field without the need for costly and noisy soil coring. RootRobot/DIRT3D, to automatically phenotype root architecture in any field, combining RootRobot, a mechatronics platform to excavate, clean, section, and image mature root crowns, with DIRT3D, software to quantify architectural traits in 3D. Anatomics, a high-throughput platform to phenotype root anatomy, combining LAT 2.0, a technology for 3D imaging of root anatomy and composition, with RootScan3D, software to automatically extract 3D anatomical and cell wall composition metrics from LAT 2.0 output. Using this platform we discovered two novel root traits, parenchyma cell wall thickness and multiseriate cortical sclerenchyma, that improve rooting depth and drought tolerance in maize and wheat. OpenSimRoot/Deep, software to simulate root interaction with hard subsoils. Using this platform we discovered novel concepts regarding how to increase crop rooting depth by modulating how individual root axes respond to hard soil. DeepGenes, a toolkit of genes, parent lines, and genomic selection strategies to enable breeding hybrids with deeper roots. We discovered 3 novel root genes that increase rooting depth in maize and wheat. DEEPER discovered novel root phenotypes for deeper rooting, and delivered validated ideotypes for deeper-rooted maize; novel technologies to rapidly assess root depth, root architecture and anatomy in field-grown plants; novel software tools for root modeling and 3D image analysis of root architecture and anatomy; and validated genes and genomic selection models to deploy traits for deeper rooting in maize breeding. Each DEEPER technology is transformative in its own right, and exceeds existing technologies. They are mutually synergistic, deployable for field-grown plants, and are ready for application. The phenotyping and modeling technologies are readily applicable to many crops, and genetic leads in maize may have utility in other grasses. Taken as a whole they represent a transformative platform to develop deeper-rooted crops, with greater drought tolerance, reduced fertilizer requirement, and greater carbon sequestration.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Risk Analysis of Various Design Architectures for High Safety-significant Safety-related Digital Instrumentation and Control Systems of Nuclear Power Plants during Accident Scenarios

This report documents the plus-up activities performed by Idaho National Laboratory (INL) during Fiscal Year (FY) 2022 for the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program, Risk Informed Systems Analysis (RISA) Pathway, digital instrumentation and control (DI&C) risk assessment project. In FY 2019, the RISA Pathway initiated a project to develop a risk assessment strategy for delivering a strong technical basis to support effective, licensable, and secure DI&C technologies for digital upgrades/designs. An integrated risk assessment technology for the DI&C systems was proposed for this strategy, which aims to (1) provide a best-estimate, risk-informed capability to quantitatively and accurately estimate the safety margin obtained from plant modernization, especially for the high safety-significant safety-related (HSSSR) DI&C systems, (2) support and supplement existing advanced risk-informed DI&C design guides by providing quantitative risk information and evidence, (3) offer a capability of design architecture evaluation of various DI&C systems to support system design decisions and diversity and redundancy applications, (4) assure the long-term safety and reliability of HSSSR DI&C systems, and (5) reduce uncertainty in costs and support integration of DI&C systems in the plant. To achieve these technical goals and deal with the expensive licensing justifications from regulatory insights, the LWRS-developed framework instructs nuclear vendors and utilities on how to effectively lower the costs associated with digital compliance and speed industry advances by: (1) defining an integrated risk-informed analysis process for DI&C upgrade, including hazard analysis, reliability analysis, and consequence analysis, (2) applying systematic and risk-informed tools to address common cause failures (CCFs) and quantify corresponding failure probabilities for DI&C technologies, particularly software CCFs, (3) evaluating the impact of digital failures at the component level, system level, and plant level, and (4) providing insights and suggestions on designs to manage the risks, thus to support the development, licensing, and deployment of advanced DI&C technologies on nuclear power plant (NPPs). Adding diversity within system or components is the main means to eliminate and mitigate CCFs, but diversity also increases plant complexity and errors and may not address all sources of systematic failures. How to optimize the diversity and redundancy applications for the safety-critical DI&C systems remains a challenge. To deal with the technical issues in addressing potential software CCFs in HSSSR DI&C systems of NPPs and supporting relevant design optimization, the framework provides: ? An integrated best-estimate, risk-informed capability to address new technical digital issues quantitatively, accurately, and efficiently in plan modernization progress, such as software CCFs in HSSSR DI&C systems of NPPs ? A common and a modularized platform for DI&C designers, software developers, cybersecurity analysts, and plant engineers to efficiently predict and prevent risk in the early design stage of DI&C systems ? Technical bases and risk-informed insights to assist U.S. Nuclear Regulatory Commission (NRC) and industry to address and fulfill the risk-informed alternatives for evaluation of CCFs in HSSSR DI&C systems of NPPs ? An integrated risk-informed tool that offers a capability of design architecture evaluation of various DI&C systems to support system design decisions in diversity and redundancy applications. The plus-up research and development efforts of this project in FY 2022 are focused on methodology improvement of software CCF modeling and estimation, prevention analysis, importance analysis and risk analysis of various design architectures of HSSSR DI&C systems. This work greatly enhances the capability of the LWRS-developed framework for the risk assessment and design optimization of safety-critical DI&C systems. It should be noted that all the analyses are performed for the demonstration of the LWRS-developed framework, not for the evaluation of relevant systems. Results are obtained based on very limited design information and testing data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Transformational Solid Oxide Fuel Cell (SOFC) Technology

This project was conducted under the Co-operative Agreement No. DE-FE0027584 with the US Department Energy to developed advanced Solid Oxide Fuel Cell (SOFC) Technologies. The overall objective of this project was to advance SOFC technology at the cell and stack level to enhance cell robustness and durability, increase performance, and reduce balance-of-plant (BOP) requirements. By reducing system complexity combined with the increases in power density and efficiency, the ultimate goal of the project was to increased reliability and to reduce capital and operating costs of installed systems. The project was focused on pathways that will reduce the cost of the SOFC cell and stack, including the following areas: Robust, redox tolerant cell technology Lower cost cell manufacturing through advances in cell design, which will reduce the amount of material, energy and time used in the fabrication of SOFCs High performance, low temperature electrolyte based on improvement of established materials Innovative SOFC stack architecture which truly integrates Balance of Plant functionality into the stack level design Thermal management of the fuel cell stack for increased durability and expanded window of operation Novel stack design amenable for use in sub-MW to multi-MW-scale power plants and having low replacement cost The incorporation of balance-of-plant (BOP) equipment into the stack platform increased the economic viability of smaller scale systems. The project objectives were met by a multi-prong approach, including new cell design complemented with modifications to existing cell technology, as well as a new stack design incorporating components typically included in the BOP, such as heat exchangers, oxidizer, fuel reformers, and recycle systems. The project culminated with demonstration of a stack test validating the viability of the cell and stack improvements. A cost model was also developed to estimate costs for the advanced stack technology at high volume manufacturing levels. The net outcome of the project is SOFC cell and stack technology with costs significantly below current DOE targets without compromising and, in some cases, improving on the performance and degradation rate demonstrated with the current state-of-the-art stack design. The results of this project advanced the reliability, robustness, and endurance of low-cost SOFC technology that ultimately are ready to be deployed in coal power systems with greater than 60 percent efficiency (based on higher heating value of fuel) and the capability for ≥97% CO 2 capture at a cost-of-electricity that is approximately 40 percent below presently available Integrated Gasification Combined Cycle systems.

03 NATURAL GAS↗
DOE OSTI2024

Climate adaptation and sustainability in switchgrass: exploring plant-microbe-soil interactions across continental scale environmental gradients

Less carbon-intensive energy sources are needed to reduce greenhouse gas emissions and their predicted role in climate change. There is growing interest in the potential of biofuels for meeting this need. A critical question is whether large-scale biofuel production can be sustainable over the time scales needed to mitigate our carbon debt from fossil fuel consumption. The carbon balance and ultimately the sustainability of biofuel feedstock production is the result of complex climate-coupled interactions between carbon fixation, sequestration, and release through combustion. Similarly, the long-term productivity of biofuels depends on the environmental factors limiting plant growth. These factors are often related to soil resources which involve complex interactions at the plant-microbe-soil interface impacting their availability and cycling. Our collaborative project addressed sustainable switchgrass (Panicum virgatum) production by exploring Plant Systems, Plant-Microbiome Interactions, and Ecosystem Processes through the integrating lens of Multi-Scale Modeling. Our research was based on detailed characterization of genetically diverse switchgrass genotypes planted in common gardens across a continental latitudinal gradient. The underlying theme of our Plant Systems research was the use of locally adapted plant material to explore plant function, to understand the mechanistic basis of environmental interactions, and to discover the plant genes important for adaptation and sustainability in the face of climate change. Our Plant-Microbiome Interaction project characterized the microbial communities associated with switchgrass using genomic tools. Our Ecosystem Processes research focused on carbon cycle responses at the ecosystem level using stand level plantings. Finally, our Multi-Scale Modeling helped to define conditions of a sustainable biofuel system and identify key tradeoffs between genetic diversity, productivity, and ecosystem services. Genome-wide association analyses were used to identify alleles that contribute to successful establishment and biomass production across North America. Together, our work provided a baseline analyses of the potential of switchgrass as a biofuel feedstock. Our project resulted in a number of successful outcomes. First, we were successful in collecting switchgrass germplasm across the species range, propagating the material, and establishing common garden experiments across the species range. In collaboration with DOE JGI, we successfully assembled the first tetraploid switchgrass genome and published this resource with an analyses of the genetic basis local adaptation from our gardens (Lowry et al. 2019, Lovell et al. 2021). The gardens were used to characterize the genetic architecture for a number of important plant phenotypes. Our project also conducted extensive sampling and sequencing to characterize the bacterial and fungal associates of switchgrass roots and leaves. We showed that host genotype, location, and harvesting practices can play a role in microbiome assembly (Singer et al. 2019 & 2022, Van Wallendael et al. 2020 & 2022, Edwards et al. 2023). Our ecosystem processes work created baseline dataset of carbon and nutrient cycling in realistic stand plantings of switchgrass. Data from this experiment provided new insight into the role of plant traits, phenology, and local environments in ecosystem processes like soil respiration, net-ecosystem exchange, and dynamics of soil and plant nutrients (Ricketts et al. 2023). Finally, our crop modelling experiments help to characterize the sensitivity of common modeling frameworks to parameters, identify key limiters of productivity across large geographic scales, and leverage patterns of local adaptation in prediction. Ultimately, these studies help to identify critical plant-microbe-soil traits that may be manipulated, through breeding or agronomic management, to improve the sustainability of biofuel feedstocks.

09 BIOMASS FUELS↗
DOE OSTI2023

Patterns in interactions of variably acetylated xylans with hydrophobic cellulose surfaces

The recalcitrance of plant cell wall lignocellulosic biomass to deconstruction is a major hurdle to sustainable biofuel/bioproduct economy. A multitude of interactions stabilize lignocellulosic biomass structure. Among these, tight packing of hemicellulose-cellulose is partly responsible for biomass recalcitrance. Here, unrestrained molecular dynamics simulations are employed to understand the influence of the nature and pattern of naturally-occuring acetyl decorations of the xylan backbone on interactions with the (100) hydrophobic cellulose surface. Periodically O2-acetylated xylan (2AcX) assume twofold helical screw conformations that are stabilized by a combination of multiple hydrophobic contacts and hydrogen bonds with the hydrophobic cellulose surface. In contrast, acetylation at the O3 position in xylan obstructs interactions, thereby adopting threefold helical screw conformations that potentially preferably interact with lignin rather than cellulose. Fully acetylated xylan desorbs from the surface implying a minimum number of unsubstituted residues on the xylan backbone is required for interaction with the surface. Here, the substituted residues must form ~ 20% fewer contacts than the unsubstituted residues to sustain stable twofold helical screw xylan conformations on the cellulose surface. Thus, specific roles of macromolecular conformations of cellulose and hemicellulose in influencing the supramolecular interactions and function of plant cell walls have been determined.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

The SvFUL2 transcription factor is required for inflorescence determinacy and timely flowering in Setaria viridis

Inflorescence architecture in cereal crops directly impacts yield potential through regulation of seed number and harvesting ability. Extensive architectural diversity found in inflorescences of grass species is due to spatial and temporal activity and determinacy of meristems, which control the number and arrangement of branches and flowers, and underlie plasticity. Timing of the floral transition is also intimately associated with inflorescence development and architecture, yet little is known about the intersecting pathways and how they are rewired during development. Here, we show that a single mutation in a gene encoding an AP1/FUL-like MADS-box transcription factor significantly delays flowering time and disrupts multiple levels of meristem determinacy in panicles of the C 4 model panicoid grass, Setaria viridis. Previous reports of AP1/FUL-like genes in cereals have revealed extensive functional redundancy, and in panicoid grasses, no associated inflorescence phenotypes have been described. In S. viridis, perturbation of SvFul2, both through chemical mutagenesis and gene editing, converted a normally determinate inflorescence habit to an indeterminate one, and also repressed determinacy in axillary branch and floral meristems. Our analysis of gene networks connected to disruption of SvFul2 identified regulatory hubs at the intersection of floral transition and inflorescence determinacy, providing insights into the optimization of cereal crop architecture.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Synthetic Electricity Market Data Generation and HERON Use Case Setup of Advanced Nuclear Reactors Coupled with Thermal Energy Storage Systems

This study evaluates and optimizes advanced nuclear reactors coupled with thermal energy storage (TES) systems in an Integrated Energy System (IES) architecture to enable advanced nuclear power plants (A NPP) to participate in multi-commodity markets, thus enhancing their economic competitiveness. Nuclear-TES coupling scenarios studied herein are designed attenuate the nuclear heat dynamics and defer energy delivery to a later time, enabling the nuclear reactor to continue operating at or near steady-state design conditions as usual while also enabling flexible generation. Three A-NPPs, namely, an advanced light-water reactor (A LWR), a high temperature gas-cooled reactor (HTGR) and a liquid-metal fast reactor (LMFR) were selected as the initial use cases for demonstrating the technoeconomic of thermally balanced energy storage coupling design for thermal power extraction. Each of the reactor technologies were evaluated in two different electricity markets. Stochastic optimization approach was adopted which included the evaluation of price signals from the Pennsylvania-New Jersey-Maryland (PJM) market, and Electric Reliability Council of Texas (ERCOT), using an autoregressive moving average (ARMA) model. Risk Analysis Virtual Environment (RAVEN) tool and its dispatch optimization plugin, the Holistic Energy Resource Optimization Network (HERON), were used to perform dispatch and capacity optimization, using the price data provided by the ARMA models. The results from the Nuclear-TES use cases will be used to design and characterize dynamic integrated system behavior and feedback.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

sCO2 Primary Power Large-Scale Pilot Plant FEED Summary

Echogen Power Systems and its project partners the Electric Power Research Institute, CDM Smith, Riley Power Inc. (a Babcock Power Inc. company), and the University of Missouri completed the Front-End Engineering Design (FEED) study of a nominal 10 MWe supercritical carbon dioxide (sCO2) large-scale pilot plant based on Recompression Brayton Cycle (RCBC) architecture. The FEED study was completed under Phase II of the U.S. Department of Energy Fossil Fuel Large-Scale Pilots program. The FEED study scope included the preliminary design of the combustion and environmental control systems, the primary heater, the sCO2 power cycle and its associated turbomachinery, and the balance of plant equipment to determine accurate cost and schedule requirements for fabrication and installation of the system at the University of Missouri’s Combined Cooling, Heat, and Power Plant, located in Columbia, Missouri. The RCBC sCO2 cycle presents superior thermodynamic efficiency compared to steam-Rankine cycles and is adaptable to a broad range of heat sources. The risk aversion of the power generation industry requires a successful large-scale pilot plant demonstration to enable financing and deployment of commercial-scale plants. Therefore, successful construction and demonstration of a 10 MWe RCBC sCO2 power plant would empower a transformational step forward for the efficiency of the next generation of utility power plants. This paper provides details on the primary heater, environmental control systems, and sCO2 power cycle design and performance.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS1990

Adaptive noncolocated velocity feedback for vibration damping

A method is proposed for adaptive noncolocated velocity feedback control of flexible structure vibrations. The approach, denoted as auto-tuning, is to drive the system into a sequence of controlled oscillations to provide accurate knowledge of the plant characteristics in the vicinity of the phase cross-over frequencies. An allpass phase notch filter cascade is used as the control architecture to phase stabilize each destabilizing mode in the plant transfer function. The allpass phase notch filter cascade is tuned precisely by the information extracted from the controlled oscillations.

Bayard, David S.↗
DOE OSTI2021

Comparative Investigation of System-Level Optimized Power Conversion System Architectures to Reduce LCOE for Large-Scale PV-Plus-Storage Farms

PV-plus-storage (PVS) has become a prevalent configuration for newly commissioned large-scale solar projects. However, the optimal power conversion system (PCS) architecture has not been investigated yet. This paper first validates the limited impact of inverter cost on LCOE and then explores a system-level optimized PCS architecture with extended LCOE reduction to proliferate large-scale dispatchable solar energy. Two state-of-the-art architectures including central inverters (CI), traditional 480/600 V string inverters (SI) are compared with newly proposed medium voltage string inverters (MVSI) and multiport DC transformer (MDCT). With verified layouts and single line diagrams (SLDs) of 20 MW PVS plants, the losses and costs breakdown of different architectures are extracted and the PCS related LCOEs are derived. In this analysis, all electrical bill of materials (EBOS) elements, inverters, battery storage and its associated components, are included, whose losses and costs are obtained from markets, manufacturers, and literature. Besides, the sensitivities of PCS-related LCOEs to Inverter-Loading-Ratio (ILR) are also investigated. Here, the results show that compared with CI and SI with 1.5 kV PV, 4 kV MVSI and 34 kV MDCT present an extended LCOE reduction across all ILR from 1.0 to 3.0, making them economically favorable candidates for PVS farms.

14 SOLAR ENERGY↗
DOE OSTI2022

Uncovering natural variation in root system architecture and growth dynamics using a robotics-assisted phenomics platform

The plant kingdom contains a stunning array of complex morphologies easily observed above-ground, but more challenging to visualize below-ground. Understanding the magnitude of diversity in root distribution within the soil, termed root system architecture (RSA), is fundamental in determining how this trait contributes to species adaptation in local environments. Roots are the interface between the soil environment and the shoot system and therefore play a key role in anchorage, resource uptake, and stress resilience. Previously, we presented the GLO-Roots (Growth and Luminescence Observatory for Roots) system to study the RSA of soil-grown Arabidopsis thaliana plants from germination to maturity (Rellán-Álvarez et al., 2015). In this study, we present the automation of GLO-Roots using robotics and the development of image analysis pipelines in order to examine the temporal dynamic regulation of RSA and the broader natural variation of RSA in Arabidopsis , over time. These datasets describe the developmental dynamics of two independent panels of accessions and reveal highly complex and polygenic RSA traits that show significant correlation with climate variables of the accessions’ respective origins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Antifungal symbiotic peptide NCR044 exhibits unique structure and multifaceted mechanisms of action that confer plant protection

In the indeterminate nodules of a model legume Medicago truncatula, ~700 nodule-specific cysteine-rich (NCR) peptides with conserved cysteine signature are expressed. NCR peptides are highly diverse in sequence, and some of these cationic peptides exhibit antimicrobial activity in vitro and in vivo. However, there is a lack of knowledge regarding their structural architecture, antifungal activity, and modes of action against plant fungal pathogens. Here, the three-dimensional NMR structure of the 36-amino acid NCR044 peptide was solved. This unique structure was largely disordered and highly dynamic with one four-residue α-helix and one three-residue antiparallel β-sheet stabilized by two disulfide bonds. NCR044 peptide also exhibited potent fungicidal activity against multiple plant fungal pathogens, including Botrytis cinerea and three Fusarium spp. It inhibited germination in quiescent spores of B. cinerea. In germlings, it breached the fungal plasma membrane and induced reactive oxygen species. It bound to multiple bioactive phosphoinositides in vitro. Time-lapse confocal and superresolution microscopy revealed strong fungal cell wall binding, penetration of the cell membrane at discrete foci, followed by gradual loss of turgor, subsequent accumulation in the cytoplasm, and elevated levels in nucleoli of germlings. Spray-applied NCR044 significantly reduced gray mold disease symptoms caused by the fungal pathogen B. cinerea in tomato and tobacco plants, and postharvest products. Our work illustrates the antifungal activity of a structurally unique NCR peptide against plant fungal pathogens and paves the way for future development of this class of peptides as a spray-on fungistat/fungicide.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Quantitative genetic-by-soil microbiome interactions in a perennial grass affect functional traits

Plants interact with diverse microbiomes that can impact plant growth and performance. Recent studies highlight the potential beneficial aspects of plant microbiomes, including the possibility that microbes facilitate the process of local adaptation in their host plants. Microbially mediated local adaptation in plants occurs when local host genotypes have higher fitness than foreign genotypes because of their affiliation with locally beneficial microbes. Here, plant adaptation results from genetic interactions of the host with locally beneficial microbes (e.g. host genotype-by-microbiome interactions). We used a recombinant inbred line (RIL) mapping population derived from upland and lowland ecotypes of the diploid C4 perennial bunch grass Panicum hallii to explore quantitative genetic responses to soil microbiomes focusing on functional root and shoot traits involved in ecotypic divergence. We show that the growth and development of ecotypes and their trait divergence depends on soil microbiomes. Moreover, we find that the genetic architecture is modified by soil microbiomes, revealing important plant genotype-by-microbiome interactions for quantitative traits. We detected a number of quantitative trait loci (QTL) that interact with the soil microbiome. Our results highlight the importance of microbial interactions in ecotypic divergence and trait genetic architecture in C4 perennial grasses.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1997

Plant Growth Models Using Artificial Neural Networks

In this paper, we descrive our motivation and approach to devloping models and the neural network architecture. Initial use of the artificial neural network for modeling the single plant process of transpiration is presented.

Neural Networks Research↗
DOE OSTI2026

Maintenance strategy, structural design, and site layout of the ST-E1 fusion power plant

An effective fusion reactor maintenance scheme enables safe operations and short downtimes. This in turn leads to high availability, which is critical to the commercial viability of a power-producing plant. In tokamak-based fusion power plants, the chosen maintenance approach has a significant impact on the spatial design of the tokamak, as well as the surrounding infrastructure, and therefore needs to be considered from the outset. Tokamak Energy has developed a pre-concept design of a fusion power plant, ST-E1. This work describes the major drivers and constraints that have been considered, presents the tokamak architecture and chosen maintenance regime, and discusses how this enables the plant’s two-phased approach to demonstrating commercial operations. It also shows the implications for the design of other systems areas, in particular the machine structural arrangement and bioshield and hot cell layout. The reactor core segmentation and removal scheme replaces entire toroidal segments radially through a large vacuum port, along a single axis only. The result is a change-tolerant machine and plant layout that can accommodate the evolving designs of the tokamak.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗