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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Perennializing marginal croplands: going back to the future to mitigate climate change with resilient biobased feedstocks

Managing annual row crops on marginally productive croplands can be environmentally unsustainable and result in variable economic returns. Incorporating perennial bioenergy feedstocks into marginally productive cropland can engender ecosystem services and enhance climate resiliency while also diversifying farm incomes. We use one of the oldest bioenergy-specific field experiments in North America to evaluate economically and environmentally sustainable management practices for growing perennial grasses on marginal cropland. This long-term field trial called 9804 was established in 1998 in eastern Nebraska and compared the productivity and sustainability of corn (Zea mays L.)—both corn grain and corn stover—and switchgrass (Panicum virgatum L.) bioenergy systems under different harvest strategies and nitrogen (N) fertilizer rates. This experiment demonstrated that switchgrass, compared to corn, is a reliable and sustainable bioenergy feedstock. This experiment has been a catalyst for other bioenergy projects which have also expanded our understanding of growing and managing bioenergy feedstocks on marginal cropland. We (1) synthesize research from this long-term experiment and (2) provide perspective concerning both the knowledge gained from this experiment and knowledge gaps and how to fill them as well as the role switchgrass will play in the future of bioenergy.

09 BIOMASS FUELS↗
DOE OSTI2024

Building a FAIR data ecosystem for incorporating single-cell transcriptomics data into agricultural genome to phenome research

Introduction The agriculture genomics community has numerous data submission standards available, but the standards for describing and storing single-cell (SC, e.g., scRNA- seq) data are comparatively underdeveloped. Methods To bridge this gap, we leveraged recent advancements in human genomics infrastructure, such as the integration of the Human Cell Atlas Data Portal with Terra, a secure, scalable, open-source platform for biomedical researchers to access data, run analysis tools, and collaborate. In parallel, the Single Cell Expression Atlas at EMBL-EBI offers a comprehensive data ingestion portal for high-throughput sequencing datasets, including plants, protists, and animals (including humans). Developing data tools connecting these resources would offer significant advantages to the agricultural genomics community. The FAANG data portal at EMBL-EBI emphasizes delivering rich metadata and highly accurate and reliable annotation of farmed animals but is not computationally linked to either of these resources. Results Herein, we describe a pilot-scale project that determines whether the current FAANG metadata standards for livestock can be used to ingest scRNA-seq datasets into Terra in a manner consistent with HCA Data Portal standards. Importantly, rich scRNA-seq metadata can now be brokered through the FAANG data portal using a semi-automated process, thereby avoiding the need for substantial expert curation. We have further extended the functionality of this tool so that validated and ingested SC files within the HCA Data Portal are transferred to Terra for further analysis. In addition, we verified data ingestion into Terra, hosted on Azure, and demonstrated the use of a workflow to analyze the first ingested porcine scRNA-seq dataset. Additionally, we have also developed prototype tools to visualize the output of scRNA-seq analyses on genome browsers to compare gene expression patterns across tissues and cell populations. This JBrowse tool now features distinct tracks, showcasing PBMC scRNA-seq alongside two bulk RNA-seq experiments. Discussion We intend to further build upon these existing tools to construct a scientist-friendly data resource and analytical ecosystem based on Findable, Accessible, Interoperable, and Reusable (FAIR) SC principles to facilitate SC-level genomic analysis through data ingestion, storage, retrieval, re-use, visualization, and comparative annotation across agricultural species.

Genetics & Heredity↗
DOE OSTI2023

Tidal energy extraction modifies tidal asymmetry and transport in a shallow, well-mixed estuary

Tidal energy extraction is increasingly being studied as a potential renewable energy resource in estuaries worldwide. Although it is understood that energy extraction via tidal stream turbines can modify currents and transport within estuaries, it is not clear how the underlying nonlinear physical mechanisms dictating tidal hydrodynamics are modulated. This research investigates the influence of a hypothetical tidal stream turbine array on barotropic tidal processes in a shallow, well-mixed system: the Piscataqua River – Great Bay (PRGB) estuary, using a numerical model. The modeled turbine farm includes 180 turbines which would extract an estimated 44.7 GWh of energy, annually. The tidal hydrodynamic model for the existing condition is validated with in-situ observations of currents and water level before analyzing tidal asymmetry and transport with and without tidal turbines. Results indicate that the tidal turbine array will decrease tidal elevation and current magnitudes system-wide, but generally reduce ebb currents and transport more than flood over most of the estuary footprint, thereby diminishing tidal asymmetry. The smaller asymmetric distortion compared to the no-turbine case is attributed to reductions in the storage volume of water over the estuary’s extensive tidal flat regions between low and high waters which decreases the associated nonlinear intertidal storage mechanism up to 25%. This leads to weakened ebb dominance over estuary sections from the mouth to mid-reaches, where depths are deep enough to keep the combined nonlinear shallow water and frictional effects from asserting control over the storage mechanism. Even in upstream shallow regions where depth-dependent friction controls asymmetry in both cases, the frictional mechanism is reduced only by 10% with turbines. Some environmental considerations of this work are discussed, with focus on sediment transport, water quality, and ecology.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Natural Horizontal Gene Transfer of Antimicrobial Resistance Genes in Campylobacter spp. From Turkeys and Swine

Antibiotic-resistant Campylobacter constitutes a serious threat to public health. The clonal expansion of resistant strains and/or the horizontal spread of resistance genes to other strains and species can hinder the clinical effectiveness of antibiotics to treat severe campylobacteriosis. Still, gaps exist in our understanding of the risks of acquisition and spread of antibiotic resistance in Campylobacter. While the in vitro transfer of antimicrobial resistance genes between Campylobacter species via natural transformation has been extensively demonstrated, experimental studies have favored the use of naked DNA to obtain transformants. In this study, we used experimental designs closer to real-world conditions to evaluate the possible transfer of antimicrobial resistance genes between Campylobacter strains of the same or different species (Campylobacter coli or Campylobacter jejuni) and originating from different animal hosts (swine or turkeys). This was evaluated in vitro through co-culture experiments and in vivo with dual-strain inoculation of turkeys, followed by whole genome sequencing of parental and newly emerged strains. In vitro, we observed four independent horizontal gene transfer events leading to the acquisition of resistance to beta-lactams (blaOXA), aminoglycosides [aph(2")-If and rpsL] and tetracycline [tet(O)]. Observed events involved the displacement of resistance-associated genes by a mutated version, or the acquisition of genomic islands harboring a resistance determinant by homologous recombination; we did not detect the transfer of resistance-carrying plasmids even though they were present in some strains. In vivo, we recovered a newly emerged strain with dual-resistance pattern and identified the replacement of an existing non-functional tet(O) by a functional tet(O) in the recipient strain. Whole genome comparisons allowed characterization of the events involved in the horizontal spread of resistance genes between Campylobacter following in vitro co-culture and in vivo dual inoculation. Our study also highlights the potential for antimicrobial resistance transfer across Campylobacter species originating from turkeys and swine, which may have implications for farms hosting both species in close proximity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Antimicrobial resistance and genomic characterization of Escherichia coli from pigs and chickens in Zhejiang, China

Escherichia coli is considered an opportunistic pathogen and an indicator for antimicrobial resistance (AMR) monitoring. Despite many reports on its AMR monitoring, studies based on genome-based analysis of AMR genes are still insufficient. Here, 181 E. coli strains were isolated from anal swab samples collected from pigs and chickens of animal farms located in Eastern China and sequenced through the Illumina platform. The results showed that 87.85% (159/181) of the E. coli isolates were multidrug-resistant (MDR). Ampicillin (AMP)- spectinomycin (SPT)- tetracycline (TET)- florfenicol (FFC)- sulfisoxazole (SF)- trimethoprim/sulfamethoxazole (SXT) was the predominant AMR pattern. By whole-genome sequencing, we found that ST10 (10.49%, 19/181) and ST48 (7.18%, 13/181) were major sequence types. IncFIB and IncX1 were the most prevalent plasmid replicons. The AMR genes bla NDM-5 (1.10%, 2/181), mcr -1 (1.10%, 2/181), tet (X4) (1.10%, 2/181), and cfr (6.08%, 11/181) were also found in these isolates. In addition, among the 169 virulence genes detected, we identified ast A (37.02%, 67/181), hly A (1.66%, 3/181), hly B (1.66%, 3/181) and hly D (1.66%, 3/181), which were closely related to heat-stable enterotoxin 1 and α-hemolysin. In addition, there were 33 virulence genes associated with the iron uptake system, and 46 were adhesion-related genes. Our study highlighted the need for routine surveillance of AMR with advanced genomic approaches, providing up-to-date data on the prevalence of AMR for the development and execution of antimicrobial stewardship policy.

Zhou, Wei↗
DOE OSTI2022

A triton X-100 assisted PMAxx-qPCR assay for rapid assessment of infectious African swine fever virus

Introduction African Swine Fever (ASF) is a highly infectious disease of pigs, caused by African swine fever virus (ASFV). The lack of vaccines and drugs makes strict disinfection practices to be one of the main measurements to curb the transmission of ASF. Therefore, it is important to assess if all viruses are inactivated after disinfection or after long time exposure in their natural conditions. Currently, the infectivity of ASFV is determined by virus isolation and culture in a biosafety level 3 (BSL-3) laboratory. However, BSL-3 laboratories are not readily available, need skilled expertise and may be time consuming. Methods In this study, a Triton X-100 assisted PMAxx-qPCR method was developed for rapid assessment of infectious ASFV in samples. PMAxx, an improved version of propidium monoazide (PMA), can covalently cross-link with naked ASFV-DNA or DNA inside inactivated ASFV virions under assistance of 0.1% (v/v) TritonX-100, but not with ASFV-DNA inside live virions. Formation of PMAxx-DNA conjugates prevents PCR amplification, leaving only infectious virions to be detected. Under optimum conditions, the limit of detection of the PMAxx-qPCR assay was 2.32log 10 HAD 50 /mL of infectious ASFV. Testing different samples showed that the PMAxx-qPCR assay was effective to evaluate intact ASFV virions after treatment by heat or chemical disinfectants and in simulated samples such as swine tissue homogenate, swine saliva swabs, and environmental swabs. However, whole-blood and saliva need to be diluted before testing because they may inhibit the PCR reaction or the cross-linking of PMAxx with DNA. Conclusion The Triton X-100 assisted PMAxx-qPCR assay took less than 3 h from sample to result, offering an easier and faster way for assessing infectious ASFV in samples from places like pig farms and pork markets.

Liu, Huan↗
DOE OSTI2025

The mutation atlas of giant kelp (Macrocystis pyrifera): a mutation database resource for natural knockouts

Giant kelp (Macrocystis pyrifera) is a paramount species of immense ecological and economic importance. It forms dense underwater forests, providing crucial habitat and serving as a foundation species for diverse marine ecosystems. Understanding the genetics of giant kelp is essential for conservation and sustainable farming, safeguarding these valuable ecosystems and their benefits. By analyzing mutations based on their impact, we can gain insights into the potential functional consequences and implications for the organism, helping to identify critical genes or regions that may play a significant role in adaptation, development, and environmental response. To achieve this, we annotated the effects and impact of spontaneous mutations in 559 giant kelp individuals from four different populations. We found over 15.9 million mutations in genes of giant kelp, and classified them into modifier, low, moderate, and high impact depending on their predicted effects. The creation of this mutation effect database, attached to the seedbank of these individuals, offers several applications, including enhancing breeding programs, aiding genetic engineering with naturally occurring mutations, and developing strategies to mitigate the impact of environmental changes.

Plant Sciences↗
DOE OSTI2023

Assessing complexity and dynamics in epidemics: geographical barriers and facilitators of foot-and-mouth disease dissemination

Introduction: Physical and non-physical processes that occur in nature may influence biological processes, such as dissemination of infectious diseases. However, such processes may be hard to detect when they are complex systems. Because complexity is a dynamic and non-linear interaction among numerous elements and structural levels in which specific effects are not necessarily linked to any one specific element, cause-effect connections are rarely or poorly observed. Methods: To test this hypothesis, the complex and dynamic properties of geo-biological data were explored with high-resolution epidemiological data collected in the 2001 Uruguayan foot-and-mouth disease (FMD) epizootic that mainly affected cattle. County-level data on cases, farm density, road density, river density, and the ratio of road (or river) length/county perimeter were analyzed with an open-ended procedure that identified geographical clustering in the first 11 epidemic weeks. Two questions were asked: (i) do geo-referenced epidemiologic data display complex properties? and (ii) can such properties facilitate or prevent disease dissemination? Results: Emergent patterns were detected when complex data structures were analyzed, which were not observed when variables were assessed individually. Complex properties–including data circularity–were demonstrated. The emergent patterns helped identify 11 counties as ‘disseminators’ or ‘facilitators’ (F) and 264 counties as ‘barriers’ (B) of epidemic spread. In the early epidemic phase, F and B counties differed in terms of road density and FMD case density. Focusing on non-biological, geographical data, a second analysis indicated that complex relationships may identify B-like counties even before epidemics occur. Discussion: Geographical barriers and/or promoters of disease dispersal may precede the introduction of emerging pathogens. If corroborated, the analysis of geo-referenced complexity may support anticipatory epidemiological policies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Rye as an Energy Cover Crop: Management, Forage Quality, and Revenue Opportunities for Feed and Bioenergy

Harvesting a winter rye energy cover crop (Secale cereale L.) could help sustain growing food and energy demand, provide new revenue streams, and enhance ecosystem services without inducing land-use change. A two-year field experiment with three planting methods and three N fertilization rates (0, 60, and 120 kg N ha -1 ) that produced >5.0 Mg ha -1 yr -1 of biomass was evaluated for (1) fresh and anaerobically digested rye forage quality; (2) revenue potential from renewable bioenergy, carbon markets, and digestate feed protein; and (3) potential greenhouse gas (GHG) offsets. We showed that rye can be harvested as forage for animals or anaerobically digested to produce renewable natural gas (RNG), with the residue after digestion (digestate) still available as a feed protein concentrate. Anaerobically digesting rye improved forage quality indicators. Digestion significantly decreased acid- and neutral-detergent fiber (ADF and NDF) by 5.2% and 17.8%, respectively, while significantly increasing crude protein (CP) (33.6%), total digestible nutrients (TDN) (2.0%), relative feed value (RFV) (23.6%), net energy for lactation (8.3%), maintenance (7.5%), and gain (20.0%). Using market prices for RNG, high protein feed, and GHG mitigation, potential on-farm revenue ranged from USD 307 Mg -1 and USD 502 Mg -1 dry matter with an average of USD 402 Mg -1 . However, there are substantial costs associated with RNG and the revenue potential does not represent the profitability of this system. Evaluation of the integrated system showed GHG emissions associated with rye fertilization were more than offset by the benefits of increasing yield in the 60 kg N ha -1 treatment. The overall carbon footprint of the integrated system was strongly carbon negative, confirming the potential of this strategy to sustainably intensify land use in the Midwestern United States.

09 BIOMASS FUELS↗
DOE OSTI2021

Mitigation of Gaseous Emissions from Stored Swine Manure with Biochar: Effect of Dose and Reapplication on a Pilot-Scale

Rural communities are affected by gaseous emissions from intensive livestock production. Practical mitigation technologies are needed to minimize emissions from stored manure and improve air quality inside barns. In our previous research, the one-time surficial application of biochar to swine manure significantly reduced emissions of NH3 and phenol. We observed that the mitigation effect decreased with time during the 30-day trials. In this research, we hypothesized that bi-weekly reapplication of biochar could improve the mitigation effect on a wider range of odorous compounds using a larger scale and longer trials. The objective was to evaluate the effectiveness of biochar dose and reapplication on mitigation of targeted gases (NH3, odorous, volatile organic compounds VOCs, odor, greenhouse gases (GHG)) from stored swine manure on a pilot-scale setup over 8-weeks. The bi-weekly reapplication of the lower biochar dose (2 kg/m2) showed much higher significant percentage reductions in emissions for NH3 (33% without and 53% with reapplication) and skatole (42% without and 80% with reapplication), respectively. In addition, the reapplication resulted in the emergence of a statistical significance to the mitigation effect for all other targeted VOCs. Specifically, for indole, the percentage reduction improved from 38% (p = 0.47, without reapplication) to 78% (p = 0.018, with reapplication). For phenol, the percentage reduction improved from 28% (p = 0.71, without reapplication) to 89% (p = 0.005, with reapplication). For p-cresol, the percentage reduction improved from 31% (p = 0.86, without reapplication) to 74% (p = 0.028, with reapplication). For 4-ethyl phenol, the percentage emissions reduction improved from 66% (p = 0.44, without reapplication) to 87% (p = 0.007, with reapplication). The one-time 2 kg/m2 and 4 kg/m2 treatments showed similar effectiveness in mitigating all targeted gases, and no statistical difference was found between the dosages. The one-time treatments showed significant percentage reductions of 33% and 42% and 25% and 48% for NH3 and skatole, respectively. The practical significance is that the higher (one-time) biochar dose may not necessarily result in improved performance over the 8-week manure storage, but the bi-weekly reapplication showed significant improvement in mitigating NH3 and odorous VOCs. The lower dosages and the frequency of reapplication on the larger-scale should be explored to optimize biochar treatment and bring it closer to on-farm trials.

Chen, Baitong (ORCID:0000000266071253)↗
DOE OSTI2024

Assessment of Envelope- and Machine Learning-Based Electrical Fault Type Detection Algorithms for Electrical Distribution Grids

This study introduces envelope- and machine learning (ML)-based electrical fault type detection algorithms for electrical distribution grids, advancing beyond traditional logic-based methods. The proposed detection model involves three stages: anomaly area detection, ML-based fault presence detection, and ML-based fault type detection. Initially, an envelope-based detector identifying the anomaly region was improved to handle noisier power grid signals from meters. The second stage acts as a switch, detecting the presence of a fault among four classes: normal, motor, switching, and fault. Finally, if a fault is detected, the third stage identifies specific fault types. This study explored various feature extraction methods and evaluated different ML algorithms to maximize prediction accuracy. The performance of the proposed algorithms is tested in an emulated software–hardware electrical grid testbed using different sample rate meters/relays, such as SEL735, SEL421, SEL734, SEL700GT, and SEL351S near and far from an inverter-based photovoltaic array farm. The performance outcomes demonstrate the proposed model’s robustness and accuracy under realistic conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Analysis of Random Forest Modeling Strategies for Multi-Step Wind Speed Forecasting

Although the random forest (RF) model is a powerful machine learning tool that has been utilized in many wind speed/power forecasting studies, there has been no consensus on optimal RF modeling strategies. This study investigates three basic questions which aim to assist in the discernment and quantification of the effects of individual model properties, namely: (1) using a standalone RF model versus using RF as a correction mechanism for the persistence approach, (2) utilizing a recursive versus direct multi-step forecasting strategy, and (3) training data availability on model forecasting accuracy from one to six hours ahead. These questions are investigated utilizing data from the FINO1 offshore platform and Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) C1 site, and testing results are compared to the persistence method. At FINO1, due to the presence of multiple wind farms and high inter-annual variability, RF is more effective as an error-correction mechanism for the persistence approach. The direct forecasting strategy is seen to slightly outperform the recursive strategy, specifically for forecasts three or more steps ahead. Finally, increased data availability (up to ~8 equivalent years of hourly training data) appears to continually improve forecasting accuracy, although changing environmental flow patterns have the potential to negate such improvement. We hope that the findings of this study will assist future researchers and industry professionals to construct accurate, reliable RF models for wind speed forecasting.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Reburning of Animal Waste Based Biomass with Coal for NO x Reduction, Part I: Feedlot Biomass (FB) and Coal:FB Blends

Cattle biomass (CB or manure from cattle) is proposed as reburn fuel under slightly fuel-rich conditions. The CB includes wastes from cattle feedlots (cattle grown in feedlots to slaughter weights of 450–640 kg) termed as Feedlot Biomass (FB) and cattle wastes from dairy farms termed as Dairy Biomass (DB). NOx emissions from coal-fired power plants can be reduced by using pure CB and Coal:CB mixtures as reburn fuels (10~30% by heat) injected after the primary combustion region. Experiments with Coal:CB mixtures as reburn fuels were performed using the 30 kW burner facility. Part I deals with results from experiments using pure FB and Coal:FB blends as reburn fuels while Part II presents results on extent of NOx reduction using pure DB and Coal:DB blends as reburn fuels (RF). In the current work, results on NOx emission are presented with FB and Coal:FB blends as RF. The parametric studies include: equivalence ratio in reburn zone (ERRBZ), vitiated air, angle of reburn nozzles, presence and absence of heat exchangers (HEXs), and baseline NOx concentration. The optimum operating conditions for FB reburning were found to be conditions with vitiation at ERRBZ = 1.1 with 45° upward counter-current injection in the presence of HEXs. NOx emissions were reduced by as much as 96%.

09 BIOMASS FUELS↗
DOE OSTI2022

Solar Irradiance Ramp Forecasting Based on All-Sky Imagers

Solar forecasting constitutes a critical tool for operating, producing and storing generated power from solar farms. In the framework of the International Energy Agency’s Photovoltaic Power Systems Program Task 16, the solar irradiance nowcast algorithms, based on five all-sky imagers (ASIs), are used to investigate the feasibility of ASIs to foresee ramp events. ASIs 1–2 and ASIs 3–5 can capture the true ramp events by 26.0–51.0% and 49.0–92.0% of the cases, respectively. ASIs 1–2 provided the lowest (<10.0%) falsely documented ramp events while ASIs 3–5 recorded false ramp events up to 85.0%. On the other hand, ASIs 3–5 revealed the lowest falsely documented no ramp events (8.0–51.0%). ASIs 1–2 are developed to provide spatial solar irradiance forecasts and have been delimited only to a small area for the purposes of this benchmark, which penalizes these approaches. These findings show that ASI-based nowcasts could be considered as a valuable tool for predicting solar irradiance ramp events for a variety of solar energy technologies. The combination of physical and deep learning-based methods is identified as a potential approach to further improve the ramp event forecasts.

14 SOLAR ENERGY↗
DOE OSTI2022

Atmospheric Drivers of Wind Turbine Blade Leading Edge Erosion: Review and Recommendations for Future Research

Leading edge erosion (LEE) of wind turbine blades causes decreased aerodynamic performance leading to lower power production and revenue and increased operations and maintenance costs. LEE is caused primarily by materials stresses when hydrometeors (rain and hail) impact on rotating blades. The kinetic energy transferred by these impacts is a function of the precipitation intensity, droplet size distributions (DSD), hydrometeor phase and the wind turbine rotational speed which in turn depends on the wind speed at hub-height. Hence, there is a need to better understand the hydrometeor properties and the joint probability distributions of precipitation and wind speeds at prospective and operating wind farms in order to quantify the potential for LEE and the financial efficacy of LEE mitigation measures. However, there are relatively few observational datasets of hydrometeor DSD available for such locations. Here, we analyze six observational datasets from spatially dispersed locations and compare them with existing literature and assumed DSD used in laboratory experiments of material fatigue. We show that the so-called Best DSD being recommended for use in whirling arm experiments does not represent the observational data. Neither does the Marshall Palmer approximation. We also use these data to derive and compare joint probability distributions of drivers of LEE; precipitation intensity (and phase) and wind speed. We further review and summarize observational metrologies for hydrometeor DSD, provide information regarding measurement uncertainty in the parameters of critical importance to kinetic energy transfer and closure of data sets from different instruments. A series of recommendations are made about research needed to evolve towards the required fidelity for a priori estimates of LEE potential.

17 WIND ENERGY↗
DOE OSTI2023

Functional Meta-Analysis of the Proteomic Responses of Arabidopsis Seedlings to the Spaceflight Environment Reveals Multi-Dimensional Sources of Variability across Spaceflight Experiments

The human quest for sustainable habitation of extraterrestrial environments necessitates a robust understanding of life’s adaptability to the unique conditions of spaceflight. This study provides a comprehensive proteomic dissection of the Arabidopsis plant’s responses to the spaceflight environment through a meta-analysis of proteomics data from four separate spaceflight experiments conducted on the International Space Station (ISS) in different hardware configurations. Raw proteomics LC/MS spectra were analyzed for differential expression in MaxQuant and Perseus software. The analysis of dissimilarities among the datasets reveals the multidimensional nature of plant proteomic responses to spaceflight, impacted by variables such as spaceflight hardware, seedling age, lighting conditions, and proteomic quantification techniques. By contrasting datasets that varied in light exposure, we elucidated proteins involved in photomorphogenesis and skotomorphogenesis in plant spaceflight responses. Additionally, with data from an onboard 1 g control experiment, we isolated proteins that specifically respond to the microgravity environment and those that respond to other spaceflight conditions. This study identified proteins and associated metabolic pathways that are consistently impacted across the datasets. Notably, these shared proteins were associated with critical metabolic functions, including carbon metabolism, glycolysis, gluconeogenesis, and amino acid biosynthesis, underscoring their potential significance in Arabidopsis’ spaceflight adaptation mechanisms and informing strategies for successful space farming.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

What’s in My Toolkit? A Review of Technologies for Assessing Changes in Habitats Caused by Marine Energy Development

Marine energy devices are installed in highly dynamic environments and have the potential to affect the benthic and pelagic habitats around them. Regulatory bodies often require baseline characterization and/or post-installation monitoring to determine whether changes in these habitats are being observed. However, a great diversity of technologies is available for surveying and sampling marine habitats, and selecting the most suitable instrument to identify and measure changes in habitats at marine energy sites can become a daunting task. We conducted a thorough review of journal articles, survey reports, and grey literature to extract information about the technologies used, the data collection and processing methods, and the performance and effectiveness of these instruments. We examined documents related to marine energy development, offshore wind farms, oil and gas offshore sites, and other marine industries around the world over the last 20 years. A total of 120 different technologies were identified across six main habitat categories: seafloor, sediment, infauna, epifauna, pelagic, and biofouling. The technologies were organized into 12 broad technology classes: acoustic, corer, dredge, grab, hook and line, net and trawl, plate, remote sensing, scrape samples, trap, visual, and others. Visual was the most common and the most diverse technology class, with applications across all six habitat categories. Technologies and sampling methods that are designed for working efficiently in energetic environments have greater success at marine energy sites. In addition, sampling designs and statistical analyses should be carefully thought through to identify differences in faunal assemblages and spatiotemporal changes in habitats.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

A Tidal Hydrodynamic Model for Cook Inlet, Alaska, to Support Tidal Energy Resource Characterization

Cook Inlet in Alaska has been identified as a prime site in the U.S. for potential tidal energy development, because of its enormous tidal power potential that accounts for nearly one-third of the national total. As one important step to facilitate tidal energy development, a tidal hydrodynamic model based on the unstructured-grid, finite-volume community ocean model (FVCOM) was developed for Cook Inlet to characterize the tidal stream energy resource. The model has a grid resolution that varies from about 1000 m at the open boundary to 100–300 m inside the Inlet. Extensive model validation was achieved by comparing model predictions with field observations for tidal elevation and velocity at various locations in Cook Inlet. The error statistics confirmed the model performs reasonably well in capturing the tidal dynamics in the system, e.g., R2 > 0.98 for tidal elevation and generally > 0.9 for velocity. Model results suggest that tides in Cook Inlet evolve from progressive waves at the entrance to standing waves at the upper Inlet, and that semi-diurnal tidal constituents are amplified more rapidly than diurnal constituents. The model output was used to identify hotspots that have high energy potential and warrant additional velocity and turbulence measurements such as East Foreland, where averaged power density exceeds 5 kw/m2. Lastly, a tidal energy extraction simulation was conducted for a hypothetical turbine farm configuration at the Forelands cross section to evaluate tidal energy extraction and resulting changes in far-field hydrodynamics.

16 TIDAL AND WAVE POWER↗