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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.

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.

Viability of bioregeneration for life support – providing food, water and air – on long-duration missions depends critically on cost of the plant habitat and on plant productivity in this habitat. Previous estimates, e.g. Drysdale and Wheeler, 2002 of both cost and productivity have been made using existing chamber designs, in particular the BIO-Plex (Bioregenerative Planetary Life Support Systems Test Complex) Plant Growth System intermediate design review (IDR) design. However, this design was developed for a terrestrial testbed, and is not optimized for use in space, much less for a particular space environment. Nor has productivity been determined experimentally for this configuration. We have examined this design and updated it for use on the Moon, with 709-hr days (light / dark cycles), using both natural and artificial light. Each system within the plant habitat was evaluated and modified to some extent for the desired use.

Urea is 85% of the recycled nitrogen in a life support system. Urea is quickly converted to NH4+ but nitrification to NO3− is difficult. Supplying NH4+ directly to plants eliminates the need for a nitrifying bioreactor. Most plant physiology textbooks indicate that NH4+ is toxic to plants, but we now know that this may not be true if pH is rigorously controlled. However, the long-term effects of high NH4+/ NO3− uptake ratios are poorly understood. In four studies, two cultivars of wheat were grown to maturity with NH4+/ NO3− ratios from 0 to 0.85 in recirculating hydroponic solution. In the third and fourth studies, NH4+ was supplied as (NH4)2SO4, NH4CI, or both. Contrary to conventional wisdom, there was no beneficial effect of supplying 25% of the N as NH4+ compared to a nitrate control. The high NH4+ treatment (85% NH4+) reduced seed yield by 20% in the first two studies, but yield was not reduced in the third and fourth studies.

Over the past 10 years we have published several papers describing what we call the Energy Cascade approach to crop modeling. We have now incorporated this approach into an interactive PC model that is available for use by other research groups. The model utilizes the primary environmental inputs (temperature, PPF, photoperiod, ’ CO2) along with crop developmental parameters (temperature and photoperiod effects on days to flowering; temperature effect on duration of grain fill) to predict daily canopy carbon gain, yield efficiency (kg per day; kg per mol of photons), and harvest index. The model outputs a series of graphs including a daily carbon gain graph that can be verified by daily gas-exchange data. The model allows for phasic environmental control in which the environmental inputs are changed during the life cycle to improve yield efficiency. Here we describe the principles underlying the model. The effects of sub-optimal environmental conditions will also be examined.

‘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.

Crop physiologists have often been suprised at the lack of correlation between single leaf photosynthesis and yield. Conversely, canopy photosynthesis is highly correlated with yield. This difference should not be suprising because canopy photosynthesis is an integrated measure of 3 of the 4 physiological components of yield. These 4 components are: 1. absorption of PPF by photosynthetic tissue, 2. carbon fixation (photosynthesis), 3. carbon use (respiration), and 4. carbon partitioning (harvest index). We have used this model to analyze the short and long-term consequences of environmental changes on plant productivity. The individual components of the model can be measured separately. This paper reviews the model and focuses on the third component: carbon use efficiency.