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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Characterization and Deconstruction of Oligosaccharides in Black Liquor From Deacetylation Process of Corn Stover

The National Renewable Energy Laboratory (NREL) developed low severity Deacetylation and Mechanical Refining (DMR) process under atmospheric pressure, generates highly fermentable, low toxicity sugar syrups and highly reactive lignin streams. The dilute alkali deacetylation step saponifies acetyl groups from the hemicellulosic fraction of biomass into a black liquor waste stream that also contains solubilized acetic, ferulic, p-coumaric acids, lignin-carbohydrate complexes (LCCs), oligosaccharides, and solubilized lignin. Valorization of the soluble components in the deacetylation black liquor waste stream requires characterization of the black liquor. Our analyses show that glucan, xylan, and lignin were three main components in black liquor and the oligosaccharides in the black liquor were mainly dimers and trimers with arabinofuranose branch groups mainly on the xylooligomers. GPC chromatograms showed that the black liquor also contained oligomeric lignin moieties with molecular weights ranging between 1,800 and ~10,000 Da. Enzymatic saccharification of the black liquor was conducted based on the compositional and structural information. Incorporation of commercial cellulase and hemicellulase enzyme preparations with various accessary enzymes showed up to 57% hydrolysis of the xylooligosaccharides in the black liquor to monomeric sugars, which could be used to improve biorefinery carbon utilization in biological fermentations to improve end product fuel or bioproduct volumes per metric ton of biomass processed. This is so far the first study about characterizing DMR black liquor and exploring breaking down the oligosaccharides in black liquor for potential use.

09 BIOMASS FUELS↗
DOE OSTI2017

Development of the IBSAL-SimMOpt Method for the Optimization of Quality in a Corn Stover Supply Chain

Variability on the physical characteristics of feedstock has a relevant effect on the reactor’s reliability and operating cost. Most of the models developed to optimize biomass supply chains have failed to quantify the effect of biomass quality and preprocessing operations required to meet biomass specifications on overall cost and performance. The Integrated Biomass Supply Analysis and Logistics (IBSAL) model estimates the harvesting, collection, transportation, and storage cost while considering the stochastic behavior of the field-to-biorefinery supply chain. This paper proposes an IBSAL-SimMOpt (Simulation-based Multi-Objective Optimization) method for optimizing the biomass quality and costs associated with the efforts needed to meet conversion technology specifications. The method is developed in two phases. For the first phase, a SimMOpt tool that interacts with the extended IBSAL is developed. For the second phase, the baseline IBSAL model is extended so that the cost for meeting and/or penalization for failing in meeting specifications are considered. The IBSAL-SimMOpt method is designed to optimize quality characteristics of biomass, cost related to activities intended to improve the quality of feedstock, and the penalization cost. A case study based on 1916 farms in Ontario, Canada is considered for testing the proposed method. Analysis of the results demonstrates that this method is able to find a high-quality set of non-dominated solutions.

09 BIOMASS FUELS↗
DOE OSTI2022

Estimation of Corn Latent Heat Flux from High Resolution Thermal Imagery

Crop evapotranspiration (ET), which is directly related to latent heat flux, is also a key indicator in determining the water status of crops. In order to estimate the latent heat flux, two-source energy balance (TSEB) models have been developed for thermal imagery from satellite platforms. However, because of the coarse resolution of thermal sensors on the satellite, distinguishing soil and vegetation is difficult which complicates the calculation process and introduces errors in latent heat estimates. In this research, high-resolution thermal datasets (0.05 m) and corresponding RGB datasets (0.03 m) were used for calculating crop latent heat flux using an adapted TSEB model. The RGB datasets were used for supervised classification of soil and vegetation, and the classification results were then used to filter the thermal mosaics to separate vegetation and soil temperatures. The vegetation temperature is used for calculating latent heat flux and the results are validated against the ground reference measurements of latent heat using a handheld porometer. The objective of this research is to introduce a workflow including an adapted TSEB model which is customized for high resolution thermal images from unmanned aircraft systems (UAS) to estimate the latent heat flux of row crops in agricultural fields. Nine dates of data collection in 2018 and 2020 have been evaluated and the root mean square error (RMSE) varies between 16 to 106 W/m2 depending on the days after planting (DAP) and the time of measurement for each day. The results indicate that the workflow introduced here is able to provide estimates of instantaneous latent heat flux (evapotranspiration) measurements for row crops in agricultural fields which will enable people to make reliable decisions related to irrigation scheduling.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1975

NASA crop calendars: Wheat, barley, oats, rye, sorghum, soybeans, corn

Crop calenders used to determine when Earth Resources Technology Satellite ERTS data would provide the most accurate wheat acreage information and to minimize the amount of ground verified information needed are presented. Since barley, oats, and rye are considered 'confusion crops, i.e., hard to differentiate from wheat in ERTS imagery, specific dates are estimated for these crops in the following stages of development: (1) seed-bed operation, (2) planting or seeding, (3) intermediate growth, (4) dormancy, (5) development of crop to full ground cover, (6) heading or tasseling, and flowering, (7) harvesting, and (8) posting-harvest operations. Dormancy dates are included for fall-snow crops. A synopsis is given of each states' growing conditions, special cropping practices, and other characteristics which are helpful in identifying crops from ERTS imagery.

Stuckey, M. R.↗
NASA NTRS1978

Solar silicon via the Dow Corning process

Carbon, as a reductant for quartz, must be made available so as to have suitable reactivity in conjunction with high purity, especially with respect to boron and phosphorus. A detailed experimental plan was developed to do this. Different sources of carbon were selected to be subjected to various purification methods and reactivity-enhancement processes. A developmental scale arc furnace was installed to perform quartz-carbon reactivity testing.

Hunt, L. P.↗
NASA NTRS1980

A project to evaluate moisture stress in corn and soybean areas of western and southwestern Minnesota

Remote sensing techniques, particularly LANDSAT data, were used to assess soil moisture stress through crop signature in southwestern Minnesota. Related objectives were: localization of droughty, well drained, and poorly drained soils; detection of stress from hail, wind, and disease damage; and the use of remote sensing data for agricultural management. Since the amount and distribution of precipitation were adequate during the 1977 and 1978 growing seasons, no significant stress occurred. Crop conditions were very favorable. As a result, crop signatures were too uniform to reflect soilscape variations and crop condition changes. In 1979 precipitation was again adequate to excess, particularly in June and August. In some cases, poorly drained sites especially, stress conditions developed as a result of excess of water and could be identified on color infrared photographs.

Rust, R. H.↗