Suchergebnisse

Modern aircraft are complex systems, equipped with hundreds of embedded sensors that record a wide repertoire of data during flight, such as crucial engine and airframe parameters, status of flight control system, air conditioning system, landing gear, life-saving and emergency systems. The data from the sensors is stored in the Flight Data Recorder. Maintenance personnel routinely transfer this sensor data to a ground terminal device to analyze it for aircraft health and performance monitoring purposes. Manual methods of extracting sensor data can be tedious and error-prone when large fleets of aircraft are involved. This paper presents a novel system to extract sensor data from aircraft to a ground terminal, wirelessly. The wireless system is implemented using unique, configurable wireless transmitter receivers (WTRs) designed for this purpose. The hardware for the wireless transfer of data was designed, interfaced with a modern aircraft's system, and tested with the aircraft on the ground and another flying object. The data from the aircraft's Flight Data Recorder was successfully transmitted and received wirelessly by the ground terminal, over a distance of 50 meters (with aircraft on ground) and 10 Kilometers (with a flying object), in a secure mode with zero packet loss. The WTRs have also qualified the requisite tests for airborne certification.

The planning of flight operations and maintenance is a crucial activity for both commercial and military aircraft. Military aircraft have to be always mission-ready. The task of ensuring this can become quite challenging when several operational requirements and maintenance constraints are to be fulfilled simultaneously. This paper, therefore, addresses the optimisation of flight and maintenance planning (FMP) when several diverse factors such as aircraft flying hours (AFH), flight cycles (FC), calendar life, annual flying requirement (AFR), etc. are to be factored in. Such a problem has not been considered previously. Because the problem can become unwieldy to solve by other methods, two schemes, that is, the genetic algorithm (GA) and modified artificial bee colony (ABC) algorithm for constrained optimisation have been utilised. The objective is to maximise the utilisation rate (UR) of aircraft, while also satisfying other operational and maintenance constraints. The algorithm is tested on a fleet of eight aircraft. In addition to a one-year planning period, a planning horizon of ten years has also been simulated. The results show that both the GA and modified ABC algorithm can be effectively used to solve the FMP problem.

This study investigates gender disparities in inflation expectations in India using data from the Reserve Bank of India's Households' Inflation Expectations Survey (March 2011 to September 2022). To determine these differences, the authors analyze the expectations of future prices for various categories including food products, nonfood products, household durables, housing, and general prices for both a short-term horizon (the next three months) and a long-term horizon (one year ahead). The authors employ independent sample t test, ordinary least square (OLS) regression, and ordinal logistic regression (OLOGIT) models to assess the average inflation expectations disparities between genders. The results demonstrate a significant relationship between gender and inflation expectations, with the findings indicating that, on average, females exhibit higher inflation expectations compared to males.