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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Detecting impacts of surface development near weather stations since 1895 in the San Joaquin Valley of California

Abstract Temperature readings observed at surface weather stations have been used for detecting changes in climate due to their long period of observations. The most common temperature metrics recorded are the daily maximum (TMax) and minimum (TMin) extremes. Unfortunately, influences besides background climate variations impact these measurements such as changes in (1) instruments, (2) location, (3) time of observation, and (4) the surrounding artifacts of human civilization (buildings, farms, streets, etc.) Quantifying (4) is difficult because the surrounding infrastructure, unique to each site, often changes slowly and variably and is thus resistant to general algorithms for adjustment. We explore a direct method of detecting this impact by comparing a single station that experienced significant development from 1895 to 2019, and especially since 1970, relative to several other stations with lesser degrees of such development (after adjustments for the (1) to (3) are applied). The target station is Fresno, California (metro population ~ 15,000 in 1900 and ~ 1 million in 2019) situated on the eastern side of the broad, flat San Joaquin Valley in which several other stations reside. A unique component of this study is the use of pentad (5-day averages) as the test metric. Results indicate that Fresno experienced + 0.4 °C decade −1 more nighttime warming (TMin) since 1970 than its neighbors—a time when population grew almost 300%. There was little difference seen in TMax trends between Fresno and non-Fresno stations since 1895 with TMax trends being near zero. A case is made for the use of TMax as the preferred climate metric relative to TMin for a variety of physical reasons. Additionally, temperatures measured at systematic times of the day (i.e., hourly) show promise as climate indicators as compared with TMax and especially TMin (and thus TAvg) due to several complicating factors involved with daily high and low measurements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Main bearing response in a waked 15-MW floating wind turbine in below-rated conditions

Increased wind turbine size raises unknowns related to structural flexibility. Moreover, moving to deeper waters, component reliability becomes more critical. This work investigates main bearing response dependence on drivetrain flexibility and wake impingement in a two-turbine wind farm. A 15-MW floating direct-drive turbine is considered. Large eddy simulations (LES) are employed to model neutral, stable and unstable atmospheric conditions at below-rated mean wind speed, while the engineering codes OpenFAST and FAST.Farm simulate turbine and wake behavior. Results indicate significant sensitivities in fatigue estimates to lateral distance between the upstream and downstream turbine. The trends are most substantial in stable conditions, where the waked downwind main bearing sees twice the fatigue damage estimates of the upstream turbine for one position and 50% for another. Main bearing fatigue sensitivity to drivetrain flexibility is minor, while properly including generator rotor inertia loads is important for the axial forces of the locating (axially fixed) bearing, especially in stable conditions.

17 WIND ENERGY↗
DOE OSTI2026

Unlocking plant-microbial interactions in deep Mollisols in the Midwestern US: Linking depth gradients in roots, microbial activity, and soil carbon in agroecosystems

Deep-rooted plants may build soil carbon (C) stocks, but most research has focused on shallow soils, leaving gaps in our understanding of how shifts in the balance between decomposition and C inputs drive soil C accumulation with depth. Thus, our objectives were to: (1) link depth gradients in root biomass with microbial activity and soil C stocks down to 1 m, and (2) examine the potential of simple C inputs to prime soil C across depths. To this end, we dug 5 quantitative soil pits in Argiudolls under mature perennial miscanthus plots in the SoyFACE Farm (Champaign-Urbana, IL). We added 13 C labeled glucose to our soils to determine the fate of simple C inputs with depth. We found that fine root biomass, total soil C, mineral-associated organic C (MAOC), particulate organic C (POC), and microbial activity (as measured by potential enzyme activity) declined with depth. POC declined more rapidly than MAOC, resulting in an increase in the ratio of MAOC-to-POC. Root biomass, enzyme activity (either acid phosphatase or n-acetyl-glucosaminadase) activity, and microbial respiration explained 74% and 38% of the variability in soil total C and MAOC, respectively, while POC was dependent on root biomass and microbial respiration (47%). Although the incorporation of simple 13 C inputs into MAOC was similar across depths, these inputs led to greater net MAOC losses in shallow soils than in deeper soils between 50 and 100 cm. The divergent impact of simple C inputs across depths may suggest that MAOC in shallow soils is more susceptible to priming losses, while C inputs into deep soils may instead be more persistent. Collectively, our results suggest that depth gradients in soil C stocks represents a balance between inputs, decomposition, and microbial necromass production and that increases in root C inputs by deep-rooted plants may have the potential to build stable MAOC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Development of a Time-Height Profile Assimilation Technique for Large-Eddy Simulation

Mesoscale-to-microscale coupling (MMC) aims to address the limited scope of traditional large-eddy simulations by driving the microscale flow with information concerning large-scale weather patterns provided by mesoscale models. We present a new offline MMC technique for horizontally homogeneous microscale flow conditions, in which internal forcing terms are computed based on mesoscale time–height profiles of mean-flow quantities. The advantage of such an approach is that it can be used to drive a microscale simulation with either mesoscale or observational data, and that it does not rely on specific terms in the mesoscale budget equations, which are typically not part of the default output of a mesoscale solver. The performance of the proposed profile assimilation technique is assessed based on the simulation of a typical diurnal cycle over the Scaled Wind Farm Technology site in west Texas. Results indicate that simple data assimilation techniques lead to unphysically high levels of shear and turbulence caused by the algorithm’s inability to cope with inaccuracies in the mesoscale time–height profiles. Modifying the algorithm to account for vertical coherence in the mesoscale source terms gives the microscale solver a greater ability to correct the provided mesoscale time–height profiles, leading to improved predictions of shear and turbulence statistics. The resulting turbulence statistics are in good agreement with meteorological tower observations and simulation results obtained with state-of-the-art coupling techniques using mesoscale budget components.

data assimilation↗
DOE OSTI2023

A simple way to integrate distributed storage into a wholesale electricity market

Abstract Current plans to decarbonize the electric supply system imply that the generation from wind and solar sources will grow substantially. This growth will increase the uncertainty of system operations due to the inherent variability of these renewable sources, and as a result, more reserve capacity will be required to provide the ramping (flexibility) needed for reliable operations. This paper assumes that all of the increased uncertainty comes from wind farms on the grid, and it shows how distributed storage managed locally by aggregators can provide the ramping needed without introducing a separate market for flexibility. This can be accomplished when the aggregators minimize the expected daily cost of the energy purchased from the grid for their customers by submitting optimal bids into the wholesale market with high and low price thresholds for discharging and charging the storage. This model is illustrated using a stochastic multi-period security constrained optimal power flow together with realistic data for a reduction of the network in the Northeast Power Coordinating Council region of the United States. The results show that the bidding strategy for distributed storage provides ramping to the grid just as effectively as storage managed by a system operator.

Lamadrid, Alberto J.↗
DOE OSTI2021

The MBARI-WEC: a power source for ocean sensing

Abstract Interest in wave energy converters to provide autonomous power to various ocean-bound systems, such as autonomous underwater vehicles, sensor systems, and even aquaculture farms, has grown in recent years. The Monterey Bay Aquarium Research Institute has developed and deployed a small two-body point absorber wave energy device suitable to such needs. This paper provides a description of the system to support future open-source access to the device and further the general development of similar wave energy systems. Additionally, to support future control design and system modification efforts, a set of hydrodynamic models are presented and cross-compared. To test the viability of using a linear frequency-domain admittance model for controller tuning, the linear model is compared against four WEC-Sim models of increasing complexity. The linear frequency-domain model is found to be generally adequate for capturing system dynamics, as the model agreement is good and the degree of nonlinearity introduced in the WEC-Sim models is generally less than 2.5%.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Chapter 21: Sustainable Technologies for Seaweed Conversion to Biofuels and Bioproducts

Seaweeds are attractive candidates to supply the future sustainable, photosynthetic, bioenergy feedstocks thanks to their cultivation promise in offshore marine farms, with year-round production, and no external nutrient requirements. Despite this potential, there are significant challenges associated with realizing both the cultivation and harvesting logistics, as well as in developing an efficient conversion platform to fuels and products. Effective and scalable and economically viable conversion processes tailored to a seaweed are discussed in detail and gaps on identified needs for yield and efficiency improvements. Among the conversion processes discussed here, anaerobic fermentation of seaweeds to bioenergy products, including organic acids and biomass, is promising to disrupt the current bioenergy landscape.

anaerobic digestion↗
DOE OSTI2024

A Conceptual Design and Economic Assessment of a Chitin Biorefinery Based on Shrimp Processing Wastes

Due to the extensive production of shrimp in captivity, waste generation has increased significantly and has become an environmental problem. The recovery of biomolecules can be an important way to mitigate the environmental problems associated with processing in this sector. In this sense, the present work aimed to evaluate a biorefinery approach for valuing shrimp farming waste to obtain astaxanthin, chitin and chitosan. Stoichiometric segmentation was used as a tool to identify the process steps, whose information on process variables (fresh water consumption, flow rate and reaction conditions) was adapted from the literature. A biorefinery coupled to a shrimp processing plant was proposed for the immediate use of highly perishable biomass, to guarantee the quality of the extracted products and reduce storage and transportation costs. In practice, the biomass treatment sequence adopted (demineralization followed by deproteinization) eliminates the depigmentation step, as the chitin obtained has a lighter tone. The proposed route was evaluated for four scenarios based on two indicators: gross economic potential (EGP) and metrics for inspection of sales and reagents (MISR). The results indicate that economic viability is achieved only for the production of chitosan, resulting in a gross revenue of US$832.50/cycle and a MISR value > 1. The sale of astaxanthin promotes an increase of US$3.73/cycle in the EGP, considered too low for the inclusion of another stage in the process.

astaxanthin↗
DOE OSTI2026

Noise-aware optimization in nominally identical manufacturing and measuring systems for high-throughput parallel workflows

Device-to-device variability in experimental noise critically impacts reproducibility, especially in automated, high-throughput systems like additive manufacturing farms. While manageable in small labs, such variability can escalate into serious risks at larger scales, such as architectural 3D printing, where noise may cause structural or economic failures. This contribution presents a noise-aware decision-making algorithm that quantifies and models device-specific noise profiles to manage variability adaptively. It uses distributional analysis and pairwise divergence metrics with clustering to choose between single-device and robust multi-device Bayesian optimization strategies. Unlike conventional methods that assume homogeneous devices or enforce generic robustness, the proposed framework explicitly determines whether shared optimization across devices is appropriate based on the degree of inter-device noise heterogeneity. This enables improved performance, reproducibility, and efficiency. An experimental case study involving three nominally identical 3D printers (same brand, model, and close serial numbers) demonstrates reduced redundancy, lower resource usage, and improved reliability, along with improved convergence stability and solution quality through the selection of the appropriate optimization strategy based on the degree of inter-device noise heterogeneity. Overall, this framework establishes a general approach for precision- and resource-aware optimization in scalable, automated experimental platforms, demonstrated here on a representative multi-device 3D printing case study.

Schenk, Christina↗
DOE OSTI2023

Landscape-scale management for biodiversity and ecosystem services

Compelling evidence has accumulated that biodiversity in agricultural landscapes is declining. Reversing this trend requires us to transform how we envision and manage agricultural systems. Here, while most current efforts focus on modifying practices at the field scale, organisms are also affected by ecological patterns and processes that transcend individual fields and farms. Consequently, effective conservation of biodiversity and related ecosystem services will require addressing practices at the landscape scale as well.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Fine resolution remote sensing spectra improves estimates of gross primary production of croplands

Gross primary production (GPP) is a fundamental measure of the terrestrial carbon cycle critical to our understanding of ecosystem function under the changing climate and land use. Remote sensing enables access to continuous spatial coverage, but remains challenged in heterogeneous croplands. Coarse resolution products, like MOD17A (500 m), may aggregate fragmented land cover types commonly found in heavily managed landscapes and misrepresent their respective contribution to carbon production. Consequently, this study demonstrates the capability of fine-resolution imagery (20-30 m) and available red-edge vegetation indices to characterize GPP across seven Midwest cropping systems. Four sites were established on a 22-year-old USDA Conservation Reserve Program (CRP); and the other three on land conventionally farmed with corn-soybean-wheat rotation (AGR). We compare in situ GPP estimates from eddy-covariance towers with ten satellite models: eight variants of the vegetation photosynthesis models (VPM), of which five include a red-edge vegetation index, as well as conventional products Landsat CONUS GPP (30 m) and MOD17A2H V6 (500 m). Daily and cumulative fine-resolution imagery integrated within VPM generally agreed with tower-based GPP in heterogeneous landscapes more than those from MODIS 500 m VPM or conventional GPP products from MOD17AH V6 or Landsat 8 CONUS. Here, replacing EVI2 with red-edge indices NDRE2, NDRE1, and MTCI in Sentinel 2 VPMs notably improved explanation of variance and estimation of cumulative GPP. While existing methods using MODIS- and Landsat-derived GPP are important baselines for regional and global studies, future research may benefit from the higher spatial, temporal, and radiometric resolution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Opportunities for bioenergy crops to support transitions from irrigated agriculture and conserve the U.S. High Plains Aquifer

This study investigates potential economic and groundwater driven transitions from irrigated maize production—the dominant irrigated cropping system in the High Plains Aquifer (HPA) region—to alternative crops such as sorghum and switchgrass, two common bioenergy feedstocks. Unsustainable groundwater extraction in the U.S. High Plains presents critical challenges including reduced irrigation capacities, diminished crop yields, lower land values, and escalating energy costs. Using a spatially explicit optimization framework combined with comprehensive economic and hydrogeological data, we evaluate optimal land-use strategies and irrigation system investments over a 30-year planning period. Results indicate significant regional variability in the future economic viability of irrigated agriculture, driven by differences in aquifer recharge rates, groundwater availability, and market conditions. Nebraska and parts of northern Texas can sustain irrigated maize profitability due to relatively favorable groundwater conditions and lower land rents, respectively. In contrast, many portions of Kansas and southern Texas are more likely to transition to dryland agriculture within two decades. Colorado and New Mexico show potential for significant adoption of switchgrass production as an alternative biomass-based energy crop. Overall, over the 30-year horizon, our model implies that approximately 23% of currently irrigated maize area across the HPA region may transition to dryland farming under business-as-usual conditions. This transition is complemented by a threefold increase in non-irrigated sorghum production, from 0.20 to 0.77 Mt yr−1, indicating that groundwater-driven shifts in agricultural production may support a larger regional base for bioenergy feedstocks. The study also reveals opportunities for producers to optimize economic returns and biomass production potential.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Outdoor annual algae productivity improvements at the pre-pilot scale through crop rotation and pond operational management strategies

The Development of Integrated Screening, Cultivar Optimization, and Verification Research (DISCOVR) collaborative consortium operated pre-pilot scale outdoor ponds to deliver much-needed multi-year, long-term and consistent, algae cultivation data relevant to understanding the current state of technology in terms of expected seasonal algae biomass productivity. Over the course of four years from 2018 to 2021, twelve identical 4.2 m 2 mini-ponds were run in triplicate sets to test strains and operational strategies demonstrated in small-, indoor photobioreactors, in pursuit of increasing overall algae areal productivity and projected farm yield. Fourteen different cultivars derived from a strain screening pipeline were tested. Through deliberate seasonal crop rotation and improvements in operational strategies, annual biomass productivity increased from 11.6 to 17.6 g m -2 day -1 , a > 50% increase over the 2018 baseline. Both brackish and marine strains were included and four out of the fourteen strains consistently yielded high productivity across multiple years; brackish strains Monoraphidium minutum (26BAM) and Scenedesmus obliquus (UTEX393), and marine strains Tetraselmis striata (LANL1001) and Picochlorum celeri (TG2). These freely available datasets, which represent nearly complete annual daily coverage of cultivation metrics including weather, pond temperature and pH, nutrients, and productivity, are unique in the public domain and seek to fill agronomic and operational knowledge gaps to help in the eventual commercialization of algal biofuels and bioproducts.

09 BIOMASS FUELS↗
DOE OSTI2023

Development of a field-deployable qPCR assay for real-time pest monitoring in algal cultivation systems

Outdoor cultivation is commonly used to produce algal biomass for a variety of bioproducts including food, feed, fuel, pharmaceuticals, and nutraceuticals. Outdoor cultivation ponds are highly susceptible to pest pressures that may lead to periods of low productivity or even entire loss of the algal crop. Consequently, there is a need for rapid, real-time tracking of pests for early intervention to mitigate crop loss. In this work, we describe the development of a field deployable, low-cost qPCR assay for detecting both known and novel pests of a farmed eukaryotic alga species, Nannochloropsis sp. We performed a proximity guided metagenome deconvolution approach (ProxiMeta™) to discover novel pests that temporally correspond to periods of reduced pond productivity. This approach provided high-quality metagenome assemblies that were used to design qPCR probes to detect specific pests of interest. The portable qPCR assay, designed to be deployed at remote field locations, enables low-cost surveillance with a rapid (2 h) turn-around time. Frequent sampling allows for early detection and prompts intervention strategies to remedy infected ponds to minimize crop loss. The qPCR assay was used to successfully detect a known predatory bacterium within the order Bdellovibrionales both in the lab and at a remote field location. Furthermore, we assembled the genome of two novel, site-specific pests in the Saprospiraceae family and successfully designed qPCR probes that differentially detected their presence in two different pond locations. Ultimately, this assay has the potential to monitor multiple pests simultaneously and tailor targets to match likely pest infections that differ across geographical locations, helping to mitigate crop loss on a large scale.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Life-cycle analysis of soybean meal, distiller-dried grains with solubles, and synthetic amino acid-based animal feeds for swine and poultry production

Swine and poultry meat production are two important sectors in the U.S. economy. They play an important role in environmental sustainability because they contribute to the greenhouse gas (GHG) emissions as the result of agricultural and production activities. To improve the sustain ability of swine and poultry meat production, it is important to understand the environmental effects and identify the key drivers of the production activities. In this work, we presented an environmental assessment of the production of swine (i.e., pork) and poultry (i.e., broiler chicken). We conducted a life-cycle analysis of formulating animal feeds using soybean meal, corn, distiller-dried grains with solubles (DDGS), and synthetic amino acids as candidate ingredients to produce swine and poultry. We evaluated GHG emissions, fossil fuel consumption, and water consumption from formulating and utilizing a variety of animal feeds based on these ingredients for swine and poultry production, using an expanded version of the Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET (R)) model. With pork and broiler chicken as the finished products, the functional unit was defined as one kg of live-weight animal at the farm gate. Feed production was the major contributor to the life-cycle GHG emissions (88 % and 91 % of the total GHG emissions for swine and poultry production, respectively) and fossil fuel consumption (79 % and 84 % of the total fossil fuel consumption for swine and poultry process, respectively). Among the four ingredient types, amino acids had the biggest GHG emission footprint; however, DDGS had the largest effect on increasing GHG emissions of swine and poultry production.

animal feed production↗
DOE OSTI2021

Life cycle energy and environmental impacts of hydroprocessed renewable jet fuel production from pennycress

There is a growing interest in making the overall aviation industry more environmentally-friendly by developing advanced biofuels. In this context, the main driver is establishing feedstocks with lower environmental loads and higher energy use efficiency. The objective of this study was to evaluate the energy requirement and environmental impacts of hydroprocessed renewable jet fuel (HRJ) production from pennycress. The system boundary included pennycress production, logistics, oil extraction and conversion to HRJ, wastewater treatment, and electricity and steam generation. Energy allocation method was used for the analysis. The functional unit was considered to be one GJ of HRJ, and the biorefinery size was considered to be 18.9 million l/yr (5 million gal/yr) HRJ. Energy use efficiency of pennycress-based HRJ production was estimated to be 3.9–5.5 (90% central range), which was higher than that of HRJ from other oilseeds, such as canola. Global warming potential of pennycress-based HRJ (35–49 kgCO 2 eq/GJ of HRJ (90% central range)) was also lower than those of HRJ from similar oilseeds and the commercial jet fuel baseline. Pennycress production was the main contributor to the total energy use and environmental impacts of HRJ production, mainly due to the use of nitrogen fertilizer for production, and fuel combustion for farm operations. Pennycress yield was identified as the most sensitive parameter affecting the energy use efficiency and environmental impacts of HRJ production. Furthermore, the outcomes of this study are useful for identifying the performance targets towards improving energy use efficiency and environmental performance of pennycress-based HRJ production at the commercial scale.

09 BIOMASS FUELS↗
DOE OSTI2025

Sustainable aviation fuel from ethanol: Techno-economic analysis and life cycle analysis

Sustainable aviation fuel (SAF) is crucial for improving energy security, enhancing domestic production, and reducing carbon emissions in the aviation sector. Among various SAF production technologies, the ethanol-to-jet (ETJ) pathway is a promising option due to its economic viability and technological maturity. This study integrates a techno-economic analysis (TEA) and a life cycle analysis (LCA) to evaluate emissions reduction strategies for SAF production via the ETJ pathway, considering use of ethanol derived from both corn grain and corn stover. Conventional corn grain-derived ETJ fuel reduces greenhouse gas (GHG) emissions by 22 % compared to fossil jet fuel, with potential reductions of 26 %–96 % when incorporating renewable energy sources, with a 6 %–32 % increase in the minimum fuel selling price (MFSP). Corn stover-derived ETJ achieves a 77 % GHG reduction but with higher MFSPs compared to corn grain ETJ. Carbon capture and storage (CCS without considering the cost for piping and sequestration, only compression) reduces the emissions of corn grain-derived ETJ by up to 32 gCO 2 e/MJ and enables negative emissions for corn stover-derived ETJ, with MFSP increases ranging from 1 % to 22 %. While carbon capture and utilization (CCU) increase ethanol yield by 47 %, it raises MFSPs by 54 % due to high electricity demand. Sustainable farming practices provide only limited carbon intensity (CI) reductions individually but do offer cumulative benefits when combined. These findings highlight the trade-offs between cost and environmental impact, providing insights to optimize SAF production strategies and support aviation sector goals for emissions reduction.

09 BIOMASS FUELS↗