ALBERT

Description: Imperial College of Science and Technology, Department of Mechanical Engineering, Fluids Section, London SW7 2BX Detailed measurements are reported of mean-flow and turbulence characteristics of opposed jets discharging normally intoa cross-flowing stream. They were obtained with pitch-to-diameter ratios of two and four, and for the limiting case of single opposed jets and for a separation of four jet diameters. Results are presented at downstream distances from two diameters from the plane of the jet centres. The results for the symmetrically arranged jets show that the jets retain their identity for a velocity ratio of unity and pitch-to-diameter ratios of four and infinity. With a velocity ratio of 1.8, the single opposed jets bifurcate about a vertical plane to form two symmetric cores of mixed jet fluid. With the pitch-to-diameter ratio of two, the individual jets retain their identity and, in contrast with the results for a pitch-to-diameter ratio of four, where each jet divides to form two cores, only one core is formed for each jet. In general, the turbulence characteristics are determined by the mean flow, which is controlled largely by pressure forces. © 1982, Cambridge University Press. All rights reserved.

Description: SUMMARYDelineating site-specific management zones within fields can be helpful in addressing spatial variability effects for adopting precision farming practices. A 3-year (2008/09 to 2010/11) field study was conducted at the Postgraduate Agricultural Research Station, University of Agriculture, Faisalabad, Pakistan, to identify the most important soil and landscape attributes influencing wheat grain yield, which can be used for delineating management zones. A total of 48 soil samples were collected from the top 300 mm of soil in 8-ha experimental field divided into regular grids of 24 × 67 m prior to sowing wheat. Soil and landscape attributes such as elevation, % of sand, silt and clay by volume, soil electrical conductivity (EC), pH, soil nitrogen (N) and soil phosphorus (P) were included in the analysis. Artificial neural network (ANN) analysis showed that % sand, % clay, elevation, soil N and soil EC were important variables for delineating management zones. Different management zone schemes ranging from three to six were developed and evaluated based on performance indicators using Management Zone Analyst (MZA V0·1) software. The fuzziness performance index (FPI) and normalized classification entropy NCE indices showed minimum values for a four management zone scheme, indicating its appropriateness for the experimental field. The coefficient of variation values of soil and landscape attributes decreased for each management zone within the four management zone scheme compared to the entire field, which showed improved homogeneity. The evaluation of the four management zone scheme using normalized wheat grain yield data showed distinct means for each management zone, verifying spatial variability effects and the need for its management. The results indicated that the approach based on ANN and MZA software analysis can be helpful in delineating management zones within the field, to promote precision farming practices effectively.