Radar Track Acquisition Range

The track acquisiton range of a track-while-scan radar is defined as the range at which the cumulative probability of M detections in N scans is 90 percent. Track acquisition ranges for 2 out of 3, 2 out of 4, and 3 out of 4 detection criteria are presented for Swerling 0, 1, and 3 target models.     

Simple Expressions for Determining Radar Detection Thresholds

The threshold value required to obtain a specified false-alarm probability, when postdetection integration follows a square-law or an envelope detector, is frequently needed in theoretical and practical studies of radar signal processor performance. The determination of such threshold values requires a substantial numerical computational effort. In this correspondence, simple expressions are presented with which these thresholds can be determined with excellent accuracy using only a scientific calculator.     

Heat transfer enhancement in combined cooling of the turbine blade leading edge

This paper reports the results of an experimental study of heat transfer using a model of the internal cooled surface of the turbine blade leading edge. We investigated a joint action of air jets and hemispherical protrusions on heat transfer from the concave surface of the leading edge model to air.     

Analysis of the effect of stiffener profile on buckling strength in composite isogrid stiffened shell under axial loading

In this paper, the buckling behavior of thin-walled GFRP cylindrical shells with triangular lattice patterned reinforcements formed by helical and circumferential ribs under axial force is analyzed. In this analysis, various models of composite isogrid stiffened cylindrical shells with outer diameter of 150 millimeters, shell thickness of 0.5 millimeters and height of 280 millimeters, stiffened with 6 helical and 2 circumferential ribs and all with the same material properties of shell and ribs are used. Ribs have constant section areas but different shapes and cross section profiles. The effects of these differences on buckling strengths of structures under axial load are studied. For analysis and modeling of structures, Finite Element Analysis method and ANSYS software were used. The results (elastic buckling load) for each model were derived and based on these results, ratio of buckling strengths to weight parameters were calculated for each model and were compared to results obtained from other models. The effect of profile of the ribs on the buckling of shells under axial loading can be concluded from the results. Results showed that stiffening the shells increased the buckling load from 10% up to 36% while decreased the buckling load to weight ratio to 42% up to 52% of an unstiffened shell.     

Technique of physical modeling of lightning strike effects on aircraft

This paper considers the issue of direct and indirect effects of lightning strikes on aircraft. It is proposed to study electromagnetic fields and interferences that affect aircraft instruments based on the theory of large-scale experiment.     

Methods for investigating the unmanned aerial vehicle electric actuator performance in aeroelasticity tasks

Theoretical and experimental methods of investigating the performance of an electric actuator of maneuverable unmanned aerial vehicle (UAV) is considered in order to solve the aeroelasticity tasks. Models of the stability analysis for the rudder–actuator system as well as the examples of numerical and experimental studies of this system performance are given.     

The Performance of Adaptive Array in a Dynamic Environment

The performance of adaptive arrays for jamming cancellation isdegraded due to relative angular movements between the arrayelements and the signal sources in space. We consider small angularvariations about the steady state of a linear (power inversion) arraycaused by either 1) a discrete angular jump, or 2) a continuousangular movement with constant angular velocity. Performancedegradation is assessed in terms of the resulting increase in the totaloutput power relative to its steady-state (minimum) value. Theresults reported are independent of the algorithm used to minimizethe output mean square error (MSE) and are supported bycomputer simulations.     

ENGINE SENSOR FAULT DIAGNOSIS USING MAIN AND DECENTRALIZED NEURAL NET WORKS

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