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NASA NTRS1981

Parametric analysis of closed cycle magnetohydrodynamic (MHD) power plants

A parametric analysis of closed cycle MHD power plants was performed which studied the technical feasibility, associated capital cost, and cost of electricity for the direct combustion of coal or coal derived fuel. Three reference plants, differing primarily in the method of coal conversion utilized, were defined. Reference Plant 1 used direct coal fired combustion while Reference Plants 2 and 3 employed on site integrated gasifiers. Reference Plant 2 used a pressurized gasifier while Reference Plant 3 used a ""state of the art' atmospheric gasifier. Thirty plant configurations were considered by using parametric variations from the Reference Plants. Parametric variations include the type of coal (Montana Rosebud or Illinois No. 6), clean up systems (hot or cold gas clean up), on or two stage atmospheric or pressurized direct fired coal combustors, and six different gasifier systems. Plant sizes ranged from 100 to 1000 MWe. Overall plant performance was calculated using two methodologies. In one task, the channel performance was assumed and the MHD topping cycle efficiencies were based on the assumed values. A second task involved rigorous calculations of channel performance (enthalpy extraction, isentropic efficiency and generator output) that verified the original (task one) assumptions. Closed cycle MHD capital costs were estimated for the task one plants; task two cost estimates were made for the channel and magnet only.

Owens, W.↗

NASA NTRS1994

Phytochrome, plant growth and flowering

Attempts to use artificially lit cabinets to grow plants identical to those growing in sunlight have provided compelling evidence of the importance of light quality for plant growth. Changing the balance of red (R) to far-red (FR) radiation, but with a fixed photosynthetic input can shift the phytochrome photoequilibrium in a plant and generate large differences in plant growth. With FR enrichment the plants elongate, and may produce more leaf area and dry matter. Similar morphogenic responses are also obtained when light quality is altered only briefly (15-30 min) at the end-of-the-day. Conversely, for plants grown in natural conditions the response of plant form to selective spectral filtering has again shown that red and far-red wavebands are important as found by Kasperbauer and coworkers. Also, where photosynthetic photon flux densities (PPFD) of sunlight have been held constant, the removal of far-red alone alters plant growth. With FR depletion plants grown in sunlight are small, more branched and darker green. Here we examine the implications for plant growth and flowering when the far-red composition of incident radiation in plant growth chambers is manipulated.

King, R. W.↗

NASA NTRS2003

Plant Response to Microwaves at 2.45 GHz

One method of beaming to Earth energy captured by Space Solar Power (SSP) satellites is by using microwaves. Since microwaves are non-ioniz ing and of low energy they probably will have little or no direct eff ect (either long- or short-term) on terrestrial biota. This contentio n must to be proved however, before the public will accept a continuo us beam of microwaves being sent to the ground near populated areas or onto agricultural lands. To begin to address this question, an exper iment has been done that exposed an important agronomic plant speaes (alfalfa, Medicago sativa L.) to a continuous microwave beam at 2.45 GHz and from between 0.5 to 1.2 milli-watts per square centimeter. Th e hypothesis was that plants exposed to microwaves will be no differe nt from those control plants that were not exposed to microwaves. The microwaves were broadcast over a tray of mature, growing plants in the laboratory. The control plants were subjected to the same environme ntal conditions (light, temperature, soil and nutrients) minus the mi crowave exposure. Both populations of plants were watered as needed. As may be seen, the experiment was designed so that the only variable to which the test plants were subjected was microwave exposure. Prec ise, non-destructive measurements were taken of leaf chlorophyll concentration over the period of the experiment. Also measured were gross plant variables such as stem length, internodal distance, and, at the end of the experiment, above-ground biomass, both fresh and dry weig hts. Soil temperatures on bare soil and under the plant canopy were a lso measured. After seven weeks of exposure to microwaves there was n o sigruficant difference between control and test plant populations. A number of other plant/ microwave exposure studies will be discussed in this presentation. However, this experiment is one of the few publ ished examples of organisms being exposed to continuos microwave illu mination at one of the proposed SSP microwave frequencies and intensi ties.

Skiles, J. W.↗

DOE OSTI2019

Fault-tolerant power-distribution modules for a power plant

Embodiments are directed to fault-tolerant power-distribution modules (PDM). A PDM is included in a power plant to provide a portion of the power generated by the plant as a direct current (DC) signal for the operation of the plant. A power-distribution system distributes a portion of the power generated by the plant to one or more PDMs, as an alternating current (AC) signal. The PDMs provide electrical power to various plant loads. The plant loads may be related to the safety of the operation of the power plant. At least one of the plant loads is a non-safety related load. A PDM may be a DC power supply. The power plant may include one or more power-generating module (PGM) assemblies. At least one of the PGM assemblies may include a nuclear reactor. Accordingly, the power plant may be a modular nuclear power plant.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2019

Multi-modular power plant with off-grid power source

A multi-modular power plant may include a plurality of on-site nuclear power modules configured to generate a power plant output, wherein one or more of the nuclear power modules may be designated as service module units which are configured to generate a first portion of the power plant output. A remainder of the nuclear power modules may be configured to generate a second portion of the power plant output. A number of power plant systems may be configured to operate using electricity associated with a house load of the power plant, wherein the first portion of the power plant output is equal to or greater than the house load. Additionally, a switchyard may be configured to electrically connect the power plant to a distributed electrical grid. The distributed electrical grid may be configured to service a plurality of geographically distributed consumers, and the switchyard may be configured to apply the second portion of the power plant output to the distributed electrical grid. The switchyard may further be configured to apply at least part of the first portion of the power plant output to the power plant systems during a loss of power from the distributed electrical grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Multi-modular power plant with dedicated electrical grid

A multi-modular power plant includes a plurality of on-site nuclear power modules that generate a power plant output, and a number of power plant systems which operate using electricity associated with a house load of the power plant. A switchyard associated with the power plant may electrically connect the power plant to a distributed electrical grid. The distributed electrical grid may be configured to service a plurality of geographically distributed consumers. Additionally, the switchyard may electrically connect the power plant to a dedicated electrical grid. The dedicated electrical grid may provide electricity generated from the power plant output to a dedicated service load, and the power plant output may be equal to or greater than a combined load of the dedicated service load and the house load. At least a portion of the power plant output may be distributed to both the power plant systems and the dedicated electrical grid.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2012

BIO-MONITORING FOR URANIUM USING STREAM-SIDE TERRESTRIAL PLANTS AND MACROPHYTES

This study evaluated the abilities of various plant species to act as bio-monitors for environmental uranium (U) contamination. Vegetation and soil samples were collected from a U processing facility. The water-way fed from facility storm and processing effluents was the focal sample site as it represented a primary U transport mechanism. Soils and sediments from areas exposed to contamination possessed U concentrations that averaged 630 mg U kg{sup -1}. Aquatic mosses proved to be exceptional accumulators of U with dry weight (dw) concentrations measuring as high as 12500 mg U kg{sup -1} (approximately 1% of the dw mass was attributable to U). The macrophytes (Phragmites communis, Scripus fontinalis and Sagittaria latifolia) were also effective accumulators of U. In general, plant roots possessed higher concentrations of U than associated upper portions of plants. For terrestrial plants, the roots of Impatiens capensis had the highest observed levels of U accumulation (1030 mg kg{sup -1}), followed by the roots of Cyperus esculentus and Solidago speciosa. The concentration ratio (CR) characterized dry weight (dw) vegetative U levels relative to that in associated dw soil. The plant species that accumulated U at levels in excess of that found in the soil were: P. communis root (CR, 17.4), I. capensis root (CR, 3.1) and S. fontinalis whole plant (CR, 1.4). Seven of the highest ten CR values were found in the roots. Correlations with concentrations of other metals with U were performed, which revealed that U concentrations in the plant were strongly correlated with nickel (Ni) concentrations (correlation: 0.992; r-squared: 0.984). Uranium in plant tissue was also strongly correlated with strontium (Sr) (correlation: 0.948; r-squared: 0.899). Strontium is chemically and physically similar to calcium (Ca) and magnesium (Mg), which were also positively-correlated with U. The correlation with U and these plant nutrient minerals, including iron (Fe), suggests that active uptake mechanisms may influence plant U accumulation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

An integrated framework of plant form and function: the belowground perspective

Summary Plant trait variation drives plant function, community composition and ecosystem processes. However, our current understanding of trait variation disproportionately relies on aboveground observations. Here we integrate root traits into the global framework of plant form and function. We developed and tested an overarching conceptual framework that integrates two recently identified root trait gradients with a well‐established aboveground plant trait framework. We confronted our novel framework with published relationships between above‐ and belowground trait analogues and with multivariate analyses of above‐ and belowground traits of 2510 species. Our traits represent the leaf and root conservation gradients (specific leaf area, leaf and root nitrogen concentration, and root tissue density), the root collaboration gradient (root diameter and specific root length) and the plant size gradient (plant height and rooting depth). We found that an integrated, whole‐plant trait space required as much as four axes. The two main axes represented the fast–slow ‘conservation’ gradient on which leaf and fine‐root traits were well aligned, and the ‘collaboration’ gradient in roots. The two additional axes were separate, orthogonal plant size axes for height and rooting depth. This perspective on the multidimensional nature of plant trait variation better encompasses plant function and influence on the surrounding environment.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

A Business Case for Nuclear Plant Control Room Modernization

This paper presents a generic business case for implementation of technology that supports Control Room Modernization (CRM). The analysis presented in two forms; 1) a standalone technology upgrade, and 2) a technology upgrade that is built upon and incremental to a prior business case created for Mobile Work Packages (MWP). The business case contends that advanced communication and networking and analytical technologies will allow NPP to conduct control room operations with improved focus by reducing human factors and redundant manpower, and therefore operate with fewer errors. While some labor savings can be harvested in terms of overtime, the majority of savings are demonstrated as reduced time to take the plant off line and bring back on line in support of outages. The benefits are quantified to a rough order of magnitude that provides directional guidance to NPPs that are interested in developing a similar business case. This business case focuses on modernization of the operator control room and does not consider a complete overhaul and modernization of a plants instrument and control systems. While operators may be considering such an investment at their plants, the sizable capital investment required is not likely supported by a cost/benefit analysis alone. More likely, it is driven by obsolescence and reliability issues, and requires consideration of mechanical condition of plant systems, capital depreciation, financing, relicensing and overall viability of the plant asset over a 20-year horizon in a competitive market. Prior studies [REF] have indicated that such a modernization of plant I&C systems, alone or as part of a larger modernization effort, can yield very significant reductions in O&M costs. However, the depth of research and analysis required to develop a meaningful business case for a plant modernization effort is well beyond the scope of this study. While CRM as considered in this study can be easily integrated as part of grander plant modernization effort, it can also be considered as a stand-alone project, implemented as a supervisorial layer over and above existing systems. CRM is enabled by a suite of technologies, which are described in further detail in the body of this report. They include: • Modernized control room with interactive displays • High-bandwidth wireless networks • Mobile devices • Component identification technology • Mobile wireless video cameras • Smart or task based operator displays • Computer-Based Procedures (CBP)/Automated Mobile Work Packages (MWP) • Intelligent plant configuration • Advanced data analytics An analysis was conducted to determine how these technologies might impact outage operations at an NPP. The analysis concluded that outage management capabilities would be improved with application of these technologies, and result in annual benefits for the plant. These improved capabilities were identified and described in further detail in this report. • Reduction in need redundant manpower (verification, etc) • Improved critical path shutdown and restart duration during outages • Reduction in human factors and errors • Remote watches • Paperless outage coordination • Bulk work optimization

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS2005

Light-emitting diodes as an illumination source for plants: a review of research at Kennedy Space Center

The provision of sufficient light is a fundamental requirement to support long-term plant growth in space. Several types of electric lamps have been tested to provide radiant energy for plants in this regard, including fluorescent, high-pressure sodium, and metal halide lamps. These lamps vary in terms of spectral quality, which can result in differences in plant growth and morphology. Current lighting research for space-based plant culture is focused on innovative lighting technologies that demonstrate high electrical efficiency and reduced mass and volume. Among the lighting technologies considered for space are light-emitting diodes (LEDs). The combination of red and blue LEDs has proven to be an effective lighting source for several crops, yet the appearance of plants under red and blue lighting is purplish gray, making visual assessment of plant health difficult. Additional green light would make the plant leaves appear green and normal, similar to a natural setting under white light, and may also offer psychological benefits for the crew. The addition of 24% green light (500-600 nm) to red and blue LEDs enhanced the growth of lettuce plants compared with plants grown under cool white fluorescent lamps. Coincidentally, these plants grown under additional green light would have the additional aesthetic appeal of a green appearance.

NASA Discipline Life Support Systems↗

DOE OSTI2026

scPlantAnnotate: an accurate and robust transformer-based model for plant cell type annotation

Accurate cell type annotation remains a major bottleneck in plant single-cell RNA sequencing (scRNA-seq), where existing tools are often adapted from animal studies and perform sub-optimally on plant data. The lack of plant-specific computational frameworks limits the construction of plant cell atlases and downstream biological discovery. We develop and evaluate scPlantAnnotate, a Transformer-based reference annotation framework tailored for plant scRNA-seq data, and benchmark it against state-of-the-art deep learning and conventional methods across multiple plant species. Species-specific scPlantAnnotate models were trained using curated datasets from Arabidopsis thaliana, Zea mays, Oryza sativa, and Glycine max. We compared scPlantAnnotate with leading baselines under both standard random-split evaluation and a more stringent leave-one-dataset-out setting, which tests robustness to completely unseen datasets and tissue types. scPlantAnnotate consistently outperforms existing approaches across all four species under random-split evaluation. In the leave-one-dataset-out setting for A. thaliana, where performance drops markedly for all methods due to strong batch effects and dataset heterogeneity, scPlantAnnotate nonetheless achieves the highest Accuracy, Macro-F1, Balanced Accuracy, and Macro-AUROC on average and ranks first on most held-out datasets. These results demonstrate improved robustness to dataset shifts, a critical yet underexplored challenge in plant scRNA-seq analysis. A freely accessible web server enables users to annotate their own datasets using pretrained models. scPlantAnnotate provides a plant-specific, Transformer-based framework for single-cell annotation that delivers state-of-the-art performance and enhanced robustness to unseen datasets. By addressing limitations of existing tools and enabling scalable reference-based annotation, scPlantAnnotate supports the development of comprehensive plant cell atlases and facilitates broader use of single-cell genomics in plant biology.

Bioinformatics↗

DOE OSTI2021

Coupling plant litter quantity to a novel metric for litter quality explains C storage changes in a thawing permafrost peatland

Abstract Permafrost thaw is a major potential feedback source to climate change as it can drive the increased release of greenhouse gases carbon dioxide (CO 2 ) and methane (CH 4 ). This carbon release from the decomposition of thawing soil organic material can be mitigated by increased net primary productivity (NPP) caused by warming, increasing atmospheric CO 2 , and plant community transition. However, the net effect on C storage also depends on how these plant community changes alter plant litter quantity, quality, and decomposition rates. Predicting decomposition rates based on litter quality remains challenging, but a promising new way forward is to incorporate measures of the energetic favorability to soil microbes of plant biomass decomposition. We asked how the variation in one such measure, the nominal oxidation state of carbon (NOSC), interacts with changing quantities of plant material inputs to influence the net C balance of a thawing permafrost peatland. We found: (1) Plant productivity (NPP) increased post‐thaw, but instead of contributing to increased standing biomass, it increased plant biomass turnover via increased litter inputs to soil; (2) Plant litter thermodynamic favorability (NOSC) and decomposition rate both increased post‐thaw, despite limited changes in bulk C:N ratios; (3) these increases caused the higher NPP to cycle more rapidly through both plants and soil, contributing to higher CO 2 and CH 4 fluxes from decomposition. Thus, the increased C‐storage expected from higher productivity was limited and the high global warming potential of CH 4 contributed a net positive warming effect. Although post‐thaw peatlands are currently C sinks due to high NPP offsetting high CO 2 release, this status is very sensitive to the plant community's litter input rate and quality. Integration of novel bioavailability metrics based on litter chemistry, including NOSC, into studies of ecosystem dynamics, is needed to improve the understanding of controls on arctic C stocks under continued ecosystem transition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Soil Origin and Plant Genotype Modulate Switchgrass Aboveground Productivity and Root Microbiome Assembly

Switchgrass (Panicum virgatum) is a model perennial grass for bioenergy production that can be productive in agricultural lands that are not suitable for food production. There is growing interest in whether its associated microbiome may be adaptive in low- or no-input cultivation systems. However, the relative impact of plant genotype and soil factors on plant microbiome and biomass are a challenge to decouple. To address this, a common garden greenhouse experiment was carried out using six common switchgrass genotypes, which were each grown in four different marginal soils collected from long-term bioenergy research sites in Michigan and Wisconsin. We characterized the fungal and bacterial root communities with high-throughput amplicon sequencing of the ITS and 16S rDNA markers, and collected phenological plant traits during plant growth, as well as soil chemical traits. At harvest, we measured the total plant aerial dry biomass. Significant differences in richness and Shannon diversity across soils but not between plant genotypes were found. Generalized linear models showed an interaction between soil and genotype for fungal richness but not for bacterial richness. Community structure was also strongly shaped by soil origin and soil origin × plant genotype interactions. Overall, plant genotype effects were significant but low. Random Forest models indicate that important factors impacting switchgrass biomass included NO 3 – , Ca 2+ , PO 4 3– , and microbial biodiversity. We identified 54 fungal and 52 bacterial predictors of plant aerial biomass, which included several operational taxonomic units belonging to Glomeraceae and Rhizobiaceae, fungal and bacterial lineages that are involved in provisioning nutrients to plants.

plant biomass↗

DOE OSTI2018

Cyclic di-AMP Acts as an Extracellular Signal That Impacts Bacillus subtilis Biofilm Formation and Plant Attachment

ABSTRACT There is a growing appreciation for the impact that bacteria have on higher organisms. Plant roots often harbor beneficial microbes, such as the Gram-positive rhizobacterium Bacillus subtilis , that influence their growth and susceptibility to disease. The ability to form surface-attached microbial communities called biofilms is crucial for the ability of B. subtilis to adhere to and protect plant roots. In this study, strains harboring deletions of the B. subtilis genes known to synthesize and degrade the second messenger cyclic di-adenylate monophosphate (c-di-AMP) were examined for their involvement in biofilm formation and plant attachment. We found that intracellular production of c-di-AMP impacts colony biofilm architecture, biofilm gene expression, and plant attachment in B. subtilis . We also show that B. subtilis secretes c-di-AMP and that putative c-di-AMP transporters impact biofilm formation and plant root colonization. Taken together, our data describe a new role for c-di-AMP as a chemical signal that affects important cellular processes in the environmentally and agriculturally important soil bacterium B. subtilis . These results suggest that the “intracellular” signaling molecule c-di-AMP may also play a previously unappreciated role in interbacterial cell-cell communication within plant microbiomes. IMPORTANCE Plants harbor bacterial communities on their roots that can significantly impact their growth and pathogen resistance. In most cases, however, the signals that mediate host-microbe and microbe-microbe interactions within these communities are unknown. A detailed understanding of these interaction mechanisms could facilitate the manipulation of these communities for agricultural or environmental purposes. Bacillus subtilis is a plant-growth-promoting bacterium that adheres to roots by forming biofilms. We therefore began by exploring signals that might impact its biofilm formation. We found that B. subtilis secretes c-di-AMP and that the ability to produce, degrade, or transport cyclic di-adenylate monophosphate (c-di-AMP; a common bacterial second messenger) affects B. subtilis biofilm gene expression and plant attachment. To our knowledge, this is the first demonstration of c-di-AMP impacting a mutualist host-microbe association and suggests that c-di-AMP may function as a previously unappreciated extracellular signal able to mediate interactions within plant microbiomes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

Power Plant Retirements: Trends and Possible Drivers

This paper synthesizes available data on historical and planned power plant retirements. Specifically, we present data on historical generation capacity additions and retirements over time, and the types of plants recently retired and planned for retirement. We then present data on the age of plants that have recently retired or that have plans to retire. We also review the characteristics of plants that recently retired or plan to retire vs. those that continue to operate, focusing on plant size, age, heat rate, and SO 2 emissions. Finally, we show the level of recent thermal plant retirements on a regional basis and correlate those data with a subset of possible factors that may be contributing to retirement decisions. This basic data synthesis cannot be used to precisely estimate the relative magnitude of retirement drivers. Nor do we explore every possible driver for retirement decisions. Moreover, future retirement decisions may be influenced by different factors than those that have affected past decisions. Nonetheless, it is clear that recently retired plants are relatively old, and that plants with stated planned retirement dates are—on average—no younger. We observe that retired plants are smaller, older, less efficient, and more polluting than operating plants. Based on simple correlation graphics, the strongest predictors of regional retirement differences appear to include SO 2 emissions rates (for coal), planning reserve margins (for all thermal units), variations in load growth or contraction (for all thermal units), and the age of older thermal plans (for all thermal units). Additional apparent predictors of regional retirements include the ratio of coal to gas prices and delivered natural gas prices. Other factors appear to have played lesser roles, including the penetration variable renewable energy (VRE), recent non-VRE capacity additions, and whether the region hosts an ISO/RTO.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

Wind Plant Performance Prediction Benchmark Phase 1 (Technical Report)

Financial risk resulting from the uncertainty associated with developing, owning, and operating wind power plants remains a barrier to reducing the levelized cost of energy (LCOE). On average, modern wind power plants in the U.S. underperform their expected annual energy output by 3.5-4.5% , with many underperforming by over 10%. To compensate for this uncertainty, investors require a larger return on investment (ROI) and apply "knock-down" factors that mask much of the underlying sources of uncertainty. Wind energy projects thus have reduced access to low-cost capital. Furthermore, operating wind plants often take a simple approach to estimating operations & maintenance (O&M) costs (e.g. straight-line estimates based on similar plants), which can eat into profits. To overcome these issues, the wind industry must improve the models they use for estimating wind plant performance and operations. An industry consortium (IC) requested that the National Renewable Energy Laboratory (NREL) lead a Department of Energy (DOE) working group to benchmark the accuracy of wind power plant energy predictions against real operational data. The IC was also motivated by DOE and NREL's potential to characterize systematic energy underperformance, identify sources of uncertainty, and explore root causes. The Wind Plant Performance Prediction (WP3) project was created out of this request, and this report represents the successful completion of Phase 1 of the WP3 project. During the project, wind plant owners provided both pre-construction and operational data to NREL. The pre-construction data was provided to wind resource assessment (WRA) consultants so they could conduct energy yield assessments (EYA). NREL took all of the completed EYAs, along with the operational data, and conducted an operational assessment to benchmark the EYA results against actual operational data. Given the large amounts of sensitive data required for this effort, as well as historical opposition to sharing data within industry, successful completion of Phase 1 represents an unprecedented milestone for industry data sharing. To improve the accuracy and confidence of pre-construction EYAs, wind plant owners and investors need better, more certain, energy yield predictions. The WP3 Benchmark Project is an industry-driven response to this reality. For the first time, industry has taken the important step of working together at scale, sharing valuable operational data with DOE and NREL in order to investigate the sources of bias and uncertainty in these energy estimates. This IC provides wind plant preconstruction and operational data to NREL in an organized and documented fashion and provides guidance and feedback as needed. The IC also provides introspection of the design of experiment, key metrics of success, data challenges, analysis best practices, and quality of results.

17 WIND ENERGY↗

DOE OSTI2021

Hybrid Analytics Solution to Improve Coal Power Plant Operations

This project focused on developing advanced methods for thermal performance monitoring of a coal-fueled power plant. The specific goal was to develop and demonstrate a new thermal performance monitoring approach using a hybrid model that integrates a physics-based heat balance model with a machine learning-based pattern recognition model. The hybrid model enables increased accuracy and scope of the thermal analysis and an improved ability to monitor and detect changes in plant operation. This new approach takes full advantage of the individual model capabilities and creates an important new set of capabilities not previously possible using the two types of models separately. Using the heat balance model, a rich set of derived parameters (virtual sensors) are calculated from the measured plant operating data at each time point. The combined measured and derived data values are used by machine learning algorithms to create pattern recognition models over the range of normal unit operation. To create the monitoring models, historical data from normal operation of the plant is first processed by the heat balance model to compute the derived parameter data. The result is a greatly expanded set of normal operating data that can be used as input to create the pattern recognition model. Once the models are calibrated for normal operation, the hybrid model is suitable for use in continuous online monitoring. During online monitoring, new plant operating data is processed first by the heat balance model and then by the pattern recognition model. Results from the pattern recognition model quantify the deviation of each measured or derived parameter from its expected value in normal operation. The hybrid models can detect abnormal changes in plant operating data with very high accuracy and sensitivity. When abnormal behavior is detected, alerts are generated automatically for evaluation by the plant monitoring staff. The new hybrid solution product was developed and verified in the performance of the project. The hybrid solution was tested first in a simulation environment that mimicked the plant data systems and infrastructure used by U.S. power generating plants and utilities. The hybrid solution was then deployed for real-time, online monitoring of an operating coal-fueled power plant at a field test site. Field testing demonstrated that all hybrid solution development objectives were accomplished. The project work was based on combining the capabilities of two existing software products to create the new hybrid solution product. One of these was the existing MapEx® heat balance product and the other was the existing SureSense® advanced pattern recognition product. Each of these separate products was assessed to be at a Technology Readiness Level (TRL) of 9 at the start of the effort. The hybrid solution product was assessed to be at a TRL of 2 at the start of the project based on early feasibility work by the project team. At completion of the field testing performed in the project, the hybrid solution product was assessed to be at a TRL of 7. The project team expects that the hybrid solution product will be deployed commercially and will achieve a TRL of 9 within one year after completion of the project.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2023

Understanding Plant Signaling Via Innovations in Probe Delivery and Imaging

The goal of this project was to develop tools for studying plant processes in living tissues. We wanted a method for introducing probes for studying plant processes such that plants could remain intact and imaged iteratively. Towards this end, we successfully optimized carbon nanofibers that we showed could deliver non-permeable signaling probes/biomolecules to plant cells. These were created on a rigid backing and also successfully transferred to a flexible backing to use with curved plant structures. We also built fiber optic microscopes that permit iterative non-destructive fluorescence or light micrographs and created protocols and devices to stabilize plant organs during imaging. These tools were developed in conjunction with research aimed understanding receptor-mediated peptide trafficking and responses relevant to plant cell growth and defense tradeoff. During this project, we designed and built two fiberoptic fluorescence microscopes; (b) designed, fabricated and validated different nanospike designs for delivering probes to plants, including the feasibility of delivering DNA constructs for expression studies; (c) developed fluorescent peptide probes (active and inactive versions of a secreted receptor ligand called phytosulfokine or PSK) and performed mobility tests after application to plants using microscopy; (d) used appropriate genetic plant backgrounds to facilitate PSK trafficking and response mechanisms; (e) determined the transcriptional changes due to PSK-induced signaling related to growth/defense tradeoff; (f) performed experiments showing the growth/defense tradeoff involves repression of specific defense components in response to PSK. This project also involved the training of two PhD students and five Masters students.

47 OTHER INSTRUMENTATION↗