Abstract: Heavy rainfall greatly affects the aerodynamic performance of the aircraft. There are many accidents of aircraft caused by aerodynamic efficiency degradation by heavy rain.
In this Paper we have studied the heavy rain effects on the aerodynamic efficiency of cambered NACA 64-210 and symmetric
NACA 0012 airfoils. Our results show significant increase in drag and decrease in lift. We used preprocessing software gridgen for creation of geometry and mesh, used fluent as solver and techplot as postprocessor. Discrete phase modeling called DPM is used to model the rain particles using two phase flow approach. The rain particles are assumed to be inert.
Both airfoils showed significant decrease in lift and increase in drag in simulated rain environment. The most significant difference between these two airfoils was the NACA 64-210 more sensitivity than NACA 0012 to liquid water content (LWC). We believe that the results showed in this paper will be useful for the designer of the commercial aircrafts and UAVs, and will be helpful for training of the pilots to control the airplanes in heavy rain.
Abstract: A climate dependent model is proposed to simulate
the population of Aedes aegypti mosquito. In developing the model,
average temperature of Shah Alam, Malaysia was used to determine
the development rate of each stage of the life cycle of mosquito.
Rainfall dependent function was proposed to simulate the hatching
rate of the eggs under several assumptions. The proposed transition
matrix was obtained and used to simulate the population of eggs,
larvae, pupae and adults mosquito. It was found that the peak of
mosquito abundance comes during a relatively dry period following a
heavy rainfall. In addition, lag time between the peaks of mosquito
abundance and dengue fever cases in Shah Alam was estimated.
Abstract: In recent years, many researches to mine the exploding Web world, especially User Generated Content (UGC) such as
weblogs, for knowledge about various phenomena and events in the physical world have been done actively, and also Web services
with the Web-mined knowledge have begun to be developed for
the public. However, there are few detailed investigations on how accurately Web-mined data reflect physical-world data. It must be
problematic to idolatrously utilize the Web-mined data in public Web services without ensuring their accuracy sufficiently. Therefore,
this paper introduces the simplest Web Sensor and spatiotemporallynormalized
Web Sensor to extract spatiotemporal data about a target
phenomenon from weblogs searched by keyword(s) representing the
target phenomenon, and tries to validate the potential and reliability of the Web-sensed spatiotemporal data by four kinds of granularity
analyses of coefficient correlation with temperature, rainfall, snowfall,
and earthquake statistics per day by region of Japan Meteorological
Agency as physical-world data: spatial granularity (region-s population
density), temporal granularity (time period, e.g., per day vs. per week), representation granularity (e.g., “rain" vs. “heavy rain"), and
media granularity (weblogs vs. microblogs such as Tweets).