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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Impacts of Riparian and Non-riparian Woody Encroachment on Tallgrass Prairie Ecohydrology

Woody encroachment has impacted grassland ecohydrology worldwide, prompting management strategies aimed at woody vegetation removal to prevent or mitigate loss of water yield. For this work, we measured stream discharge following sustained cutting of riparian trees (2010–2020) in a native tallgrass prairie (northeastern Kansas, USA). Discharge has declined at this site since the 1980’s despite a concurrent increase in precipitation. This decline has been previously attributed to increased transpiration of stream water by riparian vegetation. We used water stable isotopes (δ 18 O and δ 2 H) to determine whether riparian grasses, shrubs, and trees primarily used stream/groundwater or soil water. Additionally, we quantified the increase in riparian and non-riparian woody cover (1978–2020) and combined it with sap-flux data to estimate changes in transpirative water loss. Sustained cutting of riparian trees did not result in increased discharge. Rather than stream/groundwater, the largest proportion of water used by riparian trees (Quercus spp.) was deep soil water. Cornus drummondii (clonal woody shrub) used a higher proportion of stream water and had greater overall variability in water-use. Riparian shrub cover increased about 57% from 1978 to 2020. Over the same time period, shrub cover increased about 20% in areas outside the riparian zone, resulting in an estimated 25% increase in daily transpirative water loss. Although stream water use was less than 50% for all riparian zone species, the total increase in shrub cover on this watershed, coupled with higher transpiration rates of shrubs, suggests that these woody species—within and outside the riparian zone—are key contributors to observed declines in stream flow in this system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Plentiful electricity turns wholesale prices negative

In 2020, average wholesale electricity prices in the United States fell to $21/MWh, their lowest level since the beginning of the 21st century. Low natural gas prices and the proliferation of low marginal cost resources like wind and solar had already established a trend toward lower wholesale prices, and this trend was exacerbated by declining electricity demand due to the Covid-19 pandemic in 2020. Negative real-time hourly wholesale prices occurred in about 4% of all hours and wholesale market nodes across the United States, but these were not distributed evenly. Regional clusters emerged, for example, in the Permian Basin in western Texas, and in Kansas and western Oklahoma in the Southwest Power Pool (SPP), negative prices accounted for more than 25% of all hours. Negative electricity prices result either from local congestion of the transmission system leading supply to exceed demand locally or due to system-wide oversupply. Looking at the latter condition in SPP, we find that all major generator types contribute to this excess supply, because of limited ramping flexibility or self-scheduled out-of-market unit commitments. Additional monetary production incentives such as renewable energy credits or tax credits also enable negative bids; indeed, negative prices predominantly occur when demand levels are low and wind production levels are high. Frequent negative prices can inform the value of additional renewable energy investments at specific locations, the need for transmission and storage development, and opportunities load growth or adaptation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
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 OSTI2024

Nth-plant scenario for blended pellets of Miscanthus, Switchgrass, and Corn Stover using multi-modal transportation: Biorefineries and depots in the contiguous U.S.

The sustainability of the biofuel industry depends on the development of a mature conversion technology on a national level that can take advantage of the economies of scale: the nth-plant. Here, this study addresses the logistic challenge of mobilizing national cellulosic feedstock supplies for a sustainable bioenergy industry. A Mixed Integer Linear Programming (MILP) model was developed and updated to deliver on-spec biomass that considers both a desired quantity and quality at the biorefinery. Our supply chain analysis includes multi-modal transport (truck and rail), varying depot and biorefinery sizes, and feedstock blends of corn stover (harvested by either a two- or three-pass method), switchgrass, and miscanthus. The following US states: Illinois, Kansas, Missouri, North Carolina, Oklahoma, Georgia, and Texas were identified as key locations for producing accessible miscanthus. Based on our most optimistic scenario, using trucks as the only transportation mode in 2040 with a cost target of $\$$79/dt, corn stover, switchgrass, and miscanthus could help meet 48% of the EPA target, 173 million dry tons that translate into 7.8 billion GGE. The addition of rail transportation for biomass delivery to biorefineries could help meet 79% of the EPA target, 283 million dry tons that translate into 12.7 billion GGE.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

A multi-criteria land suitability assessment of field allocation decisions for switchgrass

With the goal of evaluating biomass resource availability in certain regions in the United States, the Department of Energy, Department of Agriculture, Environmental Protection Agency, national laboratories, and Forest Service research laboratories, together with academic and industry collaborators, performed a resource analysis study, 2016 Billion-Ton Report: Advancing Domestic Resources for a Thriving Bioeconomy, Volume 1: Economic Availability of Feedstocks, using POLYSYS model to estimate biomass potential. The study provided county- and state-level biomass potential projections, with biomass feedstock production estimates and suitability assessment of lands acreage likely to transition to energy crops. For this analysis, we estimate biomass supply by year 2028, more specifically, lands acreage transition to switchgrass in the Midwest of the United States, across 50 counties in 3 states (Nebraska, Kansas, and Colorado). We propose a multi-criteria site suitability framework, to determine the potential acreage and production for switchgrass, at the field level. Site selection criteria span agronomic and ecosystem services such as previous land cover, crop rotation, soil water holding capacity, crop productivity, field efficiency, topography, soil organic matter, soil leaching propensity, distance to surface water bodies, and soil erosivity. Efficient agricultural field selection for dedicated energy crops field allocation is critical to evaluate biomass resource availability, and it is our position that estimation at the field level would provide a more accurate and useful estimation to support an emerging bioeconomy. Using field suitability scores and county-level assessments, we model land allocation decision for energy crop in the future, estimating the spatial distribution of dynamics of energy crop adoption with priority to fields scoring the highest. Additionally, compared with POLYSYS results from the report mentioned above, our method shows good performance overall, with about 2% and 1.2% of difference in switchgrass acreage allocation and crop production, respectively.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Energy performance of an operational government building retrofitted with ceiling phase change material tiles in a mixed-humid climate

The aging U.S. building stock requires various retrofit measures to enhance their energy efficiency. Here, this study explores the integration of thermal energy storage and advanced building controls as viable retrofit solutions for load flexibility and peak demand response while maintaining the occupants' comfort. A detailed assessment is conducted on the energy use of an administrative building in Sumner County, Kansas, focusing on the implementation of phase change materials (PCMs) in the ceiling of occupied zones. First, a time-resolved, whole-building energy model is developed in EnergyPlus, incorporating complex thermal behaviors such as air exchange between the plenum space and occupied zones, envelope leakage, and operational schedules. The model is then validated using experimental field test data, and subsequently a parametric assessment of key PCM properties and application strategies is performed to evaluate cooling electricity demand benefits. The parametric study shows that the optimal retrofit strategy, comprising a PCM with 23°C peak melting temperature, 0.125 in. (3.17 mm) thickness, and 150 kJ/kg latent heat, combined with active controls that include 8 h of precooling, forced convection under the ceiling, and a 2°C thermostat setback during peak hours, can result in a maximum load shift during the peak period of 99.6 % and the total electricity savings during the peak period of 98.9 % for the optimum case and thus provide significant cost savings under time-of-use pricing scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Farmer characteristics and decision-making: A model for bioenergy crop adoption

We report the commercial development of biofuels and bioproducts depends on whether renewable biomass feedstock is available while not directly competing with the production of food. Farmers are one of the most important stakeholders in the biofuel supply chain and confront a range of uncertainties while entering the bioenergy market. Their decision-making process is extremely complex and rarely purely rational. Modeling farmer behavior requires considering a wide range of individual-level factors, socio-temporal dynamics, institutional settings, and their interactions. These characteristics make agent-based modeling a suitable framework for evaluating such systems. We developed a model to simulate farmer bioenergy crop adoption behavior across a 50-county study region in Nebraska, Kansas, and Colorado. The analysis considers adoption decisions for two bioenergy feedstocks, crop residues and energy crops. We examine the influence of individual and farm characteristics, market structure, social networks, and media influence on farmer adoption decisions. Our results indicate that different factors can have varied impacts on the speed of adoption for the crop residues and energy crops. Identifying levers that have the most impact on grower adoption can inform the design of interventions both from policy and private sector standpoints with important implications for the future the bioenergy industry.

09 BIOMASS FUELS↗
DOE OSTI2021

Is a Prescribed Fire Sufficient to Slow the Spread of Woody Plants in an Infrequently Burned Grassland? A Case Study in Tallgrass Prairie

In many mesic grasslands, such as the central Great Plains in North America, frequent fire is a key regulator of ecological processes. Long periods of infrequent fire facilitate the conversion of herbaceous-dominated grassland to woody-dominated shrubland or woodland. At the Konza Prairie Biological Station in northeast Kansas, one infrequently burned portion of the landscape has undergone transformation from grassland to woodland after nearly 30 yr without fire. In Spring 2017, a prescribed burn was implemented to assess fire effectiveness on woody plant mortality. A postfire census of 3 000+ individual woody plants identified the distribution of species by size (height), topographic position, and slope on the landscape. Mortality and canopy fire damage were calculated for each individual. In lowland locations with near-continuous shrub cover (30.7% of the landscape), woody plants were unaffected by fire. However, in upland and slope locations, where shrubs and trees were sparser, survival probability varied by topographic position and species. In these locations 68% of all woody individuals experienced 90% or greater fire damage to the canopy, with 56% of these individuals exhibiting new canopy regrowth within 2 mo after the fire. Here, the two most abundant woody shrubs, Cornus drummondii and Rhus aromatica, showed high survival at all height classes and landscape positions. The two abundant tree species, Gleditsia triacanthos and Juniperus virginiana, showed increased survival probability with tree height that varied by landscape position. Survival of J. virginiana also varied according to proximity and size of neighboring clonal shrubs, providing a mechanism for persistence of this fire-sensitive tree species even at small height classes. The probability survival curves developed here are useful for managers assessing when to prescribe fire to maximize mortality for J. virginiana and provide insight relevant for broader ecological understanding of woody encroachment within grasslands throughout the world.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Learning-based demand-supply-coupled charging station location problem for electric vehicle demand management

We present a learning-based, demand-supply-coupled optimization model for the charging station location problem (CSLP), aiming to integrate the concept of electric vehicle (EV) charging demand management into the planning of charging infrastructures. In stage one, a gradient boosting-based learning model is developed to predict the charging demand of a charging station based on 15 defined features. Next, in stage two, a demand–supply-coupled CSLP model is developed to optimize the total charging usage rates of both existing and newly selected charging stations. We design a gradient-based stochastic spatial search algorithm to solve the proposed model. A case study with 6-year charging event data from Kansas City Missouri is performed. Results show that the proposed method can generate satisfactory charging demand predictions, and can increase charging usage rates by 14%, outperforming two benchmark approaches. Furthermore, the results of this research are poised to guide agencies in identifying optimal locations for new charging stations.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Technology Impact and Resource Assessment of Existing and Planned U.S. Biofuel Production: Life Cycle Water Consumption, Water Stress, Land Use, and Criteria Air Pollutants

Biofuels have the potential to strengthen the U.S. energy supply, enhance energy security, and promote economic development. As the United States continues to expand biofuel production, quantifying resource requirements and location-specific constraints is crucial for planning, siting, and technology development to support long-term viability. Accordingly, this work assesses the life cycle resource consumption (water consumption, and land use), water stress and criteria air pollutants associated with expanded U.S. biofuel production over the 2020–2035 period, based on producers’ plans. We perform a bottom-up technology impact assessment and resource assessment by integrating facility-level production statistics with Argonne’s Research and Development (R&D) GREET model and county-level water-stress characterization factors from Available Water Remaining for the United States (AWARE-US) model. Results suggest that by 2035, biofuels could meaningfully contribute to U.S. energy demand, driven primarily by first-generation and waste-based feedstocks with plans for substantial capacity expansion, although cellulosic and e-fuel technologies remain limited. However, growth must be managed to minimize impacts on water resources and land use. These impacts vary by fuel type and facility location, specifically, projected expansion increases water consumption and can elevate water-stress impacts in certain regions like Nebraska, Kansas, Colorado, Idaho, California and North Texas. Direct land use also increases overall, particularly for first-generation feedstocks such as corn and soybeans. These findings underscore the need for continued technological improvements and innovative strategies to manage resource demands as the industry scales and to support complementary deployment within the evolving U.S. energy system.

09 BIOMASS FUELS↗
DOE OSTI2020

Simulation of Continental Shallow Cumulus Populations Using an Observation-Constrained Cloud-System Resolving Model

Continental shallow cumulus (ShCu) clouds observed on 30 August 2016 during the Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) field campaign are simulated by using an observation-constrained cloud-system resolving model. On this day, ShCu forms over Oklahoma and southern Kansas and some of these clouds transition to deeper, precipitating convection during the afternoon. We apply a four-dimensional ensemble-variational (4DEnVar) hybrid technique in the Community Gridpoint Statistical Interpolation (GSI) system to assimilate operational data sets and unique boundary layer measurements including a Raman lidar, radar wind profilers, radiosondes, and surface stations collected by the U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) atmospheric observatory into the Weather Research and Forecasting (WRF) model to ascertain how improved environmental conditions can influence forecasts of ShCu populations and the transition to deeper convection. Independent observations from aircraft, satellite, as well as ARM's remote sensors are used to evaluate model performance in different aspects. Several model experiments are conducted to identify the impact of data assimilation (DA) on the prediction of clouds evolution. The analyses indicate that ShCu populations are more accurately reproduced after DA in terms of cloud initiation time and cloud base height, which can be attributed to an improved representation of the ambient meteorological conditions and the convective boundary layer. Extending the assimilation to 18 UTC (local noon) also improved the simulation of shallow-to-deep transitions of convective clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Learning the structure of wind: A data-driven nonlocal turbulence model for the atmospheric boundary layer

In this work, we develop a novel data-driven approach to modeling the atmospheric boundary layer. This approach leads to a nonlocal, anisotropic synthetic turbulence model which we refer to as the deep rapid distortion (DRD) model. Our approach relies on an operator regression problem that characterizes the best fitting candidate in a general family of nonlocal covariance kernels parameterized in part by a neural network. This family of covariance kernels is expressed in Fourier space and is obtained from approximate solutions to the Navier–Stokes equations at very high Reynolds numbers. Each member of the family incorporates important physical properties such as mass conservation and a realistic energy cascade. The DRD model can be calibrated with noisy data from field experiments. After calibration, the model can be used to generate synthetic turbulent velocity fields. To this end, we provide a new numerical method based on domain decomposition which delivers scalable, memory-efficient turbulence generation with the DRD model as well as others. We demonstrate the robustness of our approach with both filtered and noisy data coming from the 1968 Air Force Cambridge Research Laboratory Kansas experiments. Using these data, we witness exceptional accuracy with the DRD model, especially when compared to the International Electrotechnical Commission standard.

17 WIND ENERGY↗
DOE OSTI2021

Learning electric vehicle driver range anxiety with an initial state of charge-oriented gradient boosting approach

This manuscript focuses on the modeling of electric vehicle (EV) driver’s range anxiety, a fear that a vehicle does not have sufficient range, or state of charge (SOC) of the battery pack, to reach its destination and would strand its occupants. Despite numerous research studies on the modeling of charging behaviors, modeling efforts to understand at what battery percentages do EV drivers charge their vehicles, and what are the associated contributing factors, are rather limited. To this end, an ensemble learning model based on gradient boosting is developed. The model sequentially fits new predictors to new residuals of the previous prediction and, then, minimizes the loss when adding the latest prediction. A total of 18 features are defined and extracted from the multisource data, which cover information on driver, vehicles, stations, traffic conditions, as well as spatial-temporal context information of the charging events. The analyzed dataset includes 4.5-year’s charging event log data from 3,096 users and 468 public charging stations in Kansas City Missouri, and the macroscopic travel demand model maintained by the metropolitan planning organization. Here, the result shows the proposed model achieved a satisfactory result with a R square value of 0.54 and root mean square error of 0.14, both better than multiple linear regression model and random forest model. To reduce range anxiety, it is suggested that the priorities of deploying new charging facilities should be given to the areas with higher daily traffic prediction, with more conservative EV users or that are further from residential areas.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Further adoption of conservation tillage can increase maize yields in the western US Corn Belt

Conservation tillage can reduce soil erosion, increase soil health, and decrease labor and fuel input costs. Despite these benefits, potential yield impacts remain an important concern for farmers considering adoption. Previous research suggests that conservation tillage is likely to have the largest yield benefits in more arid conditions, but a lack of field-level analyses across climatic, management and soil conditions limits confidence in such predictions. Satellite imagery provides the opportunity to monitor agricultural lands at sub-field resolution across large spatial scales and wide environmental gradients. Here we investigate the maize yield impacts of conservation tillage in the semi-arid western US Corn Belt, using sub-field resolution datasets on tillage practices and crop yields derived from satellite data spanning four states (Nebraska, Kansas, South Dakota, and North Dakota) between 2008 and 2020. On these datasets, we estimate heterogenous yield outcomes for several thousand maize fields across gradients in climate, soil quality and irrigation status by using a causal forests analysis, an adaptation of the random forests machine-learning algorithm for causal inference on observational data. We find that long-term adoption of conservation tillage increased rainfed maize yields by an average of 9.9% in the region. Impacts on irrigated yields were small and not statistically significant. These results, along with an analysis of variables related to greater than average yield benefits, indicate that improved water infiltration and retention are the primary reasons for conservation tillage benefits. Despite yield benefits, many fields estimated to see increased yields under long term low till have not adopted the practice. Therefore, we identify specific counties likely to benefit most from increased levels of adoption. Our results strengthen the understanding of the impacts of conservation agriculture on crop yields and help define environments and counties most likely to benefit from conservation tillage.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Spatio-temporal differences in leaf physiology are associated with fire, not drought, in a clonally integrated shrub

Abstract In highly disturbed environments, clonality facilitates plant survival via resprouting after disturbance, resource sharing among interconnected stems and vegetative reproduction. These traits likely contribute to the encroachment of deep-rooted clonal shrubs in tallgrass prairie. Clonal shrubs have access to deep soil water and are typically thought of as relatively insensitive to environmental variability. However, how leaf physiological traits differ among stems within individual clonal shrubs (hereafter ‘intra-clonal’) in response to extreme environmental variation (i.e. drought or fire) is unclear. Accounting for intra-clonal differences among stems in response to disturbance is needed to more accurately parameterize models that predict the effects of shrub encroachment on ecosystem processes. We assessed intra-clonal leaf-level physiology of the most dominant encroaching shrub in Kansas tallgrass prairie, Cornus drummondii, in response to precipitation and fire. We compared leaf gas exchange rates from the periphery to centre within shrub clones during a wet (2015) and extremely dry (2018) year. We also compared leaf physiology between recently burned shrubs (resprouts) with unburned shrubs in 2018. Resprouts had higher gas exchange rates and leaf nitrogen content than unburned shrubs, suggesting increased rates of carbon gain can contribute to recovery after fire. In areas recently burned, resprouts had higher gas exchange rates in the centre of the shrub than the periphery. In unburned areas, leaf physiology remained constant across the growing season within clonal shrubs (2015 and 2018). Results suggest single measurements within a shrub are likely sufficient to parameterize models to understand the effects of shrub encroachment on ecosystem carbon and water cycles, but model parameterization may require additional complexity in the context of fire.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Intra-canopy leaf trait variation facilitates high leaf area index and compensatory growth in a clonal woody encroaching shrub

Leaf trait variation enables plants to utilize large gradients of light availability that exist across canopies of high leaf area index (LAI), allowing for greater net carbon gain while reducing light availability for understory competitors. While these canopy dynamics are well understood in forest ecosystems, studies of canopy structure of woody shrubs in grasslands are lacking. To evaluate the investment strategy used by these shrubs, we investigated the vertical distribution of leaf traits and physiology across canopies of Cornus drummondii, the predominant woody encroaching shrub in the Kansas tallgrass prairie. We also examined the impact of disturbance by browsing and grazing on these factors. Our results reveal that leaf mass per area (LMA) and leaf nitrogen per area (Na) varied approximately threefold across canopies of C. drummondii, resulting in major differences in the physiological functioning of leaves. High LMA leaves had high photosynthetic capacity, while low LMA leaves had a novel strategy for maintaining light compensation points below ambient light levels. The vertical allocation of leaf traits in C. drummondii canopies was also modified in response to browsing, which increased light availability at deeper canopy depths. As a result, LMA and Na increased at lower canopy depths, leading to a greater photosynthetic capacity deeper in browsed canopies compared to control canopies. This response, along with increased light availability, facilitated greater photosynthesis and resource-use efficiency deeper in browsed canopies compared to control canopies. Furthermore, our results illustrate how C. drummondii facilitates high LAI canopies and a compensatory growth response to browsing—both of which are key factors contributing to the success of C. drummondii and other species responsible for grassland woody encroachment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Harvest and nitrogen effects on bioenergy feedstock quality of grass-legume mixtures on Conservation Reserve Program grasslands

Perennial grass mixtures established on Conservation Reserve Program (CRP) lands can be an important source of feedstock for bioenergy production. This study aimed to evaluate management practices for optimizing the quality of bioenergy feedstock and stand persistence of grass-legume mixtures under diverse environments. A 5-year field study (2008–2012) was conducted to assess the effects of two harvest timings (at anthesis vs after complete senescence) and three nitrogen (N) rates (0, 56, 112 kg N ha -1 ) on biomass chemical compositions (i.e., cell wall components, ash, volatiles, total carbon, and N contents) and the feedstock energy potential, examined by the theoretical ethanol yield (TEY) and the total TEY (i.e., the product of biomass yield and TEY, L ha -1 ), of cool-season mixtures in Georgia and Missouri and a warm-season mixture in Kansas. The canonical correlation analysis (CCA) was used to investigate the effect of vegetative species transitions on feedstock quality. Although environmental variations (mainly precipitation) greatly influenced the management effect on chemical compositions, the delayed harvest after senescence generally improved feedstock quality. In particular, the overall cell wall concentrations and TEY of the warm-season mixtures increased by approximately 7%. Additional N supplies improved the total TEY of both mixtures by ~1.6–4.2 L ha -1 per 1.0 kg N ha -1 input but likely lowered the feedstock quality, particularly for the cool-season mixture. The cell wall concentrations of cool-season mixture reduced by approximately 3%–6%. The CCA results indicated that the increased legume compositions (under low N input) likely enhanced lignin but reduced ash concentrations. This field research demonstrated that with proper management, grass-legume mixtures on CRP lands can provide high-quality feedstock for bioenergy productions.

09 BIOMASS FUELS↗
DOE OSTI2022

Separating Oil-Water Mixtures Using Bump Arrays

Particle separation is an important process step across many fields. One technique being applied for separating solids such as blood components or sand particles from carrier fluids is the use of arrays of aligned posts called deterministic lateral arrays to bump particles to one side in the flow stream to enhance separation. This technique may be useful for separation of deformable particles. The ability to efficiently separate two-phase industrial (oil/water) mixtures is key for future use of valuable resources. Over 1 trillion gallons of petroleum production water could be reclaimed annually for reuse in the drought-ridden western US states. The ability to reclaim this petroleum production water may be critical for the Central High Plains (Colorado, Kansas, Oklahoma, Texas, and New Mexico). Trends in just the High Plains area already lost 20 to 25% of the irrigated farming area due to insufficient ground water storage to irrigate, and farmland losses are expected to grow to 40%. Proving this technology is key to reuse of petroleum production water for crop irrigation or to replace water from currently failing aquifers in rich agricultural lands of the Central High Plains. We conducted experiments applying mesofluidic separation for flowing two-phase (oil/water) mixtures. Experiments were conducted using oils of differing viscosities with water as the carrier fluid; separation was achieved over a range of oil-water concentrations. We describe the results of these experiments in this paper.

oil-water separation, micelle, droplet separation,↗