Vented vectoring-nozzle for STOL and V/STOL aircraft

Vented vectoring-nozzle has superior thrust coefficient and is lighter in weight because it does not require completely enclosed elbow duct ordinarily used to deflect nozzle flow. Improved nozzle has primary nozzle and three-sided elbow deflector

Thrust and mass flow characteristics of four 36 inch diameter tip turbine fan thrust vectoring systems in and out of ground effect

The calibration tests carried out on the propulsion system components of a 70 percent scale, powered model of a NASA 3-fan V/STOL aircraft configuration are described. The three X3/6B/T58 turbotip fan units used in the large scale powered model were tested on an isolated basis over a range of ground heights from H/D of 1.02 to infinity. A higher pressure ratio LF336/J85 fan unit was tested over a range of ground heights from 1.55 to infinity. The results of the test program demonstrated that: (1) the thrust and mass flow performance of the X376B/T58 nose lift unit is essentially constant for H/D variations down to 1.55; at H/D 1.02 back pressurization of the fan exit occurs and is accompanied by an increase in thrust of five percent; (2) a change in nose fan exit hub shape from flat plate to hemispherical produces no significant difference in louvered lift nozzle performance for height variations from H/D = 1.02 to infinity; (3) operation of the nose lift nozzle at the higher fan pressure ratio generated by the LF336/J85 fan system causes no significant change in ground proximity performance down to an H/D of 1.55, the lowest height tested with this unit; and (4) the performance of the left and right X376B/T58 lift/cruise units in the vertical lift mode remains unchanged, within plus or minus two percent for the range of ground heights from H/D = 1.02 to infinity

Investigation of ground effects on large and small scale models of a three fan V/STOL aircraft configuration

Induced lift of a subsonic, three fan, lift/cruise, V/STOL aircraft configuration was investigated using scale modes of a multimission aircraft whose design incorporates a nose mounted lift fan and two lift/cruise units located over the wing. Configuration effects were assessed for lift improvement devices, lift/cruise nozzle rails, nozzle perimeter plates, and alternate nose fan exit hubs. Tests were conducted at four model heights (H/D = 0.95, 1.53, 3.06 and 6.45, where D is the average nozzle exit diameter equal to 0.997 m.) Results are presented and discussed

Ground test of the D shaped vented thrust vectoring nozzle

Static ground tests of a large scale lift/cruise thrust vectoring nozzle were conducted to establish: (1) vectoring performance 'in' and 'out' of ground effect; (2) thrust spoilage capability; (3) compatibility of the nozzle with a turbotip fan; and (4) the nozzle structural temperature distribution. Vectoring performance of a short coupled, vented nozzle design on a large scale, (60%) basis was compared with small scale (4.5%) test nozzle results. The test nozzle was a "boilerplate" model of the MCAIR "D" vented nozzle configured for operation with the LF336/J85 turbotip lift fan system. Calibration of the LF336/J85 test fan with a simple convergent nozzle was performed with four different nozzle exit areas to establish reference thrust, nozzle pressure ratio, and nozzle corrected flow characteristics for comparison with the thrust vectoring nozzle data. Thrust vectoring tests with the 'D' vented nozzle were conducted over the range of vector angles between 0 and 117 deg for several different nozzle exit areas

Radiation cooled MPD arc thruster

Radiation-cooled magnetohydrodynamic arc thruste

Severe risk for Stewart\u27s disease

Stewart\u27s disease of corn, also known as Stewart\u27s wilt, is caused by the bacterium Pantoea stewartii. The 2000 growing season is predicted to be a very severe year for this disease, largely because of six successive winters with above-average monthly temperatures that have favored the survival of the insect vector for this disease, the corn flea beetle (Chaetocnema pulicaria). There are commonly two stages to the disease. Initially, leaf lesions that are off-green to yellow extend along the leaf veins, followed by mild-to-severe early seedling blight symptoms

Advancing agricultural research using machine learning algorithms

Rising global population and climate change realities dictate that agricultural productivity must be accelerated. Results from current traditional research approaches are difficult to extrapolate to all possible fields because they are dependent on specific soil types, weather conditions, and background management combinations that are not applicable nor translatable to all farms. A method that accurately evaluates the effectiveness of infinite cropping system interactions (involving multiple management practices) to increase maize and soybean yield across the US does not exist. Here, we utilize extensive databases and artificial intelligence algorithms and show that complex interactions, which cannot be evaluated in replicated trials, are associated with large crop yield variability and thus, potential for substantial yield increases. Our approach can accelerate agricultural research, identify sustainable practices, and help overcome future food demands

Meta-analysis of the linear relationship between soybean yield loss and rust severity from uniform fungicide trials.

To quantify yield loss in soybean as affected by rust severity, meta-analysis was used to examine data from uniform fungicide trials (UFTs) conducted across 25 locations and 5 years (2003?2008) in the main soybean production regions of Brazil. Trials (n = 81) were selected based on predefined criteria and examined for the linear relationships between soybean yield loss (%) and rust severity (%) at the R6 growth stage. Slopes of the yield loss × severity relationship were estimated by linear regression. The influence of potential moderator variables on slopes was examined by a random effects model. Forty-one trials were excluded due to the presence of influential observations in the negative linear relationship between yield and severity. There was considerable variation among slope estimates for the increase in yield loss with respect to the change in soybean rust severity (0.31?1.81 p.p./p.p.). A significant and positive relationship between soybean rust severity and yield loss was found. For every increase of 1 p.p. in soybean rust severity, the average increase in yield loss was 0.71 p.p. (95% CI = 0.60?0.82 p.p.). The moderator variable timing of disease onset and severity class accounted for 17 and 16% of the overall and between-trial variability of slopes, respectively. This study provides an approach for quantitative risk assessments of rust-related soybean yield loss, an important step for an economic evaluation of alternative rust management strategies.Edição do Proceedings of the National Soybean Rust Symposium, New Orleans, 2009

Study of arc-jet propulsion devices Final report, 20 Nov. 1964 - 19 Dec. 1965

Energy transfer mechanisms in radiation, water, and regeneratively cooled, and MPD arc jet propulsion device

Dissecting the Economic Impact of Soybean Diseases in the United States over Two Decades

Soybean (Glycine max L. Merrill) is an economically important commodity for United States agriculture. Nonetheless, the profitability of soybean production has been negatively impacted by soybean diseases. The economic impacts of 23 common soybean diseases were estimated in 28 soybean-producing states in the U.S., from 1996 to 2016 (the entire data set consisted of 13,524 data points). Estimated losses were investigated using a variety of statistical approaches. The main effects of state, year, pre- and post-discovery of soybean rust, region, and zones based on yield, harvest area, and production, were significant on “total economic loss” as a function of diseases. Across states and years, the soybean cyst nematode, charcoal rot, and seedling diseases were the most economically damaging diseases while soybean rust, bacterial blight, and southern blight were the least economically damaging. A significantly greater mean loss (51%) was observed in states/years after the discovery of soybean rust (2004 to 2016) compared to the pre-discovery (1996 to 2003). From 1996 to 2016, the total estimated economic loss due to soybean diseases in the U.S. was $95.48 billion, with$80.89 billion and $14.59 billion accounting for the northern and southern U.S. losses, respectively. Over the entire time period, the average annual economic loss due to soybean diseases in the U.S. reached nearly$4.55 billion, with approximately 85% of the losses occurring in the northern U.S. Low yield/harvest/production zones had significantly lower mean economic losses due to diseases in comparison to high yield/harvest/production zones. This observation was further bolstered by the observed positive linear correlation of mean soybean yield loss (in each state, due to all diseases considered in this study, across 21 years) with the mean state wide soybean production (MT), mean soybean yield (kg ha-1), and mean soybean harvest area (ha). Results of this investigation provide useful insights into how research, policy, and educational efforts should be prioritized in soybean disease management