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

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

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

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

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

Modeling the Relationship Between Estimated Fungicide Use and Disease-Associated Yield Losses of Soybean in the United States I: Foliar Fungicides vs Foliar Diseases

Fungicide use in the United States to manage soybean diseases has increased in recent years. The ability of fungicides to reduce disease-associated yield losses varies greatly depending on multiple factors. Nonetheless, historical data are useful to understand the broad sense and long-term trends related to fungicide use practices. In the current study, the relationship between estimated soybean yield losses due to selected foliar diseases and foliar fungicide use was investigated using annual data from 28 soybean growing states over the period of 2005 to 2015. For national and regional (southern and northern United States) scale data, mixed effects modeling was performed considering fungicide use as a fixed and state and year as random factors to generate generalized R2 values for marginal (R2GLMM(m); contains only fixed effects) and conditional (R2GLMM(c); contains fixed and random effects) models. Similar analyses were performed considering soybean production data to see how fungicide use affected production. Analyses at both national and regional scales showed that R2GLMM(m) values were significantly smaller compared to R2GLMM(c) values. The large difference between R2 values for conditional and marginal models indicated that the variation of yield loss as well as production were predominantly explained by the state and year rather than the fungicide use, revealing the general lack of fit between fungicide use and yield loss/production at national and regional scales. Therefore, regression models were fitted across states and years to examine their importance in combination with fungicide use on yield loss or yield. In the majority of cases, the relationship was nonsignificant. However, the relationship between soybean yield and fungicide use was significant and positive for majority of the years in the study. Results suggest that foliar fungicides conferred yield benefits in most of the years in the study. Furthermore, the year-dependent usefulness of foliar fungicides in mitigating soybean yield losses suggested the possible influence of temporally fluctuating abiotic factors on the effectiveness of foliar fungicides and/or target disease occurrence and associated loss magnitudes

Diameters in preferential attachment models

In this paper, we investigate the diameter in preferential attachment (PA-) models, thus quantifying the statement that these models are small worlds. The models studied here are such that edges are attached to older vertices proportional to the degree plus a constant, i.e., we consider affine PA-models. There is a substantial amount of literature proving that, quite generally, PA-graphs possess power-law degree sequences with a power-law exponent \tau>2. We prove that the diameter of the PA-model is bounded above by a constant times \log{t}, where t is the size of the graph. When the power-law exponent \tau exceeds 3, then we prove that \log{t} is the right order, by proving a lower bound of this order, both for the diameter as well as for the typical distance. This shows that, for \tau>3, distances are of the order \log{t}. For \tau\in (2,3), we improve the upper bound to a constant times \log\log{t}, and prove a lower bound of the same order for the diameter. Unfortunately, this proof does not extend to typical distances. These results do show that the diameter is of order \log\log{t}. These bounds partially prove predictions by physicists that the typical distance in PA-graphs are similar to the ones in other scale-free random graphs, such as the configuration model and various inhomogeneous random graph models, where typical distances have been shown to be of order \log\log{t} when \tau\in (2,3), and of order \log{t} when \tau>3