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Lunar-and Martian-based plant growth facilities pose novel challenges to design and management of porous medium-based root-zone environments. For example, to achieve similar equilibrium water content distribution using potting soil, a 10 cm tall root zone on earth needs to be 60 cm tall on the moon. We used analytical models to parameterize porous plant growth media for reduced gravity conditions. This approach is straight-forward because the equilibrium capillary potential scales linearly with gravity force. However, the highly non-linear water retention character is tied to particle size through the resulting pore-size distribution. Therefore interpreting the corresponding particle size and generating and evaluating the porous medium hydraulic properties remains a challenge. Soil physical principles can be applied to address the ultimate concern of controlling fluids (O2, H2O) within the plant root-zone in reduced gravity.

‘Blue’ photons are energetically expensive to produce, so the most energy-efficient lamps contain the least amount of blue light. ‘Blue’ photons are not used as efficiently in photosynthesis as ‘red’ photons, but blue light has dramatic effects on plant growth. We studied the growth and development of soybean, wheat, and lettuce plants under high pressure sodium and metal halide lamps with yellow filters creating 5 fractions of blue light (< 0.1%, 2%, 6%, 12%, and 26%) at 200 and 500 μmol m-2 s-1 PPF. The response of dry mass, stem length, leaf area, SLA, and tillering/branching to blue light was species dependent. Blue light fraction determined the stem elongation response in soybean, whereas the absolute amount of blue light determined the stem elongation response in lettuce. Lettuce was highly sensitive to blue light fraction between 0% and 6% blue, but results were complicated by sensitivity to lamp type. For the parameters we studied, wheat did not respond to blue light.

NREL completed a temporal and geospatial analysis of telematics data to estimate the fraction of platoonable miles traveled by class 8 tractor trailers currently in operation. This paper discusses the value and limitations of very large but low time-resolution data sets, and the fuel consumption reduction opportunities from large scale adoption of platooning technology for class 8 highway vehicles in the US based on telematics data. The telematics data set consist of about 57,000 unique vehicles traveling over 210 million miles combined during a two-week period. 75% of the total fuel consumption result from vehicles operating in top gear, suggesting heavy highway utilization. The data is at a one-hour resolution, resulting in a significant fraction of data be uncategorizable, yet significant value can still be extracted from the remaining data. Multiple analysis methods to estimate platoonable miles are discussed.