Abstract: Background: Maintaining the correct body balance is
essential in the prevention of falls in the elderly, which is especially
important for women because of postmenopausal osteoporosis and
the serious consequences of falls. One of the exercise methods which
is very popular among adults, and which may affect body balance in
the positive way is the Pilates method. The aim of the study was to
evaluate the effect of regular Pilates exercises on the ability to
maintain body balance in static conditions in adult healthy women.
Material and methods: The study group consisted of 20 healthy
women attending Pilates twice a week for at least 1 year. The control
group consisted of 20 healthy women physically inactive. Women in
the age range from 35 to 50 years old without pain in musculoskeletal
system or other pain were only qualified to the groups. Body balance
was assessed using MatScan VersaTek platform with Sway Analysis
Module based on Matscan Clinical 6.7 software (Tekscan Inc.,
U.S.A). The balance was evaluated under the following conditions:
standing on both feet with eyes open, standing on both feet with eyes
closed, one-leg standing (separately on the right and left foot) with
eyes open. Each test lasted 30 seconds. The following parameters
were calculated: estimated size of the ellipse of 95% confidence, the
distance covered by the Center of Gravity (COG), the size of the
maximum shift in the sagittal and frontal planes and load distribution
between the left and right foot, as well as between rear- and forefoot.
Results: It was found that there is significant difference between the
groups in favor of the study group in the size of the confidence
ellipse and maximum shifts of COG in the sagittal plane during
standing on both feet, both with the eyes open and closed (p
Abstract: Series of experimental tests were conducted on a
section of a 660 kW wind turbine blade to measure the pressure
distribution of this model oscillating in plunging motion. In order to
minimize the amount of data required to predict aerodynamic loads
of the airfoil, a General Regression Neural Network, GRNN, was
trained using the measured experimental data. The network once
proved to be accurate enough, was used to predict the flow behavior
of the airfoil for the desired conditions.
Results showed that with using a few of the acquired data, the
trained neural network was able to predict accurate results with
minimal errors when compared with the corresponding measured
values. Therefore with employing this trained network the
aerodynamic coefficients of the plunging airfoil, are predicted
accurately at different oscillation frequencies, amplitudes, and angles
of attack; hence reducing the cost of tests while achieving acceptable
accuracy.
Abstract: The aerodynamic stall control of a baseline 13-percent
thick NASA GA(W)-2 airfoil using a synthetic jet actuator (SJA) is
presented in this paper. Unsteady Reynolds-averaged Navier-Stokes
equations are solved on a hybrid grid using a commercial software to
simulate the effects of a synthetic jet actuator located at 13% of the
chord from the leading edge at a Reynolds number Re = 2.1x106 and
incidence angles from 16 to 22 degrees. The experimental data for the
pressure distribution at Re = 3x106 and aerodynamic coefficients at
Re = 2.1x106 (angle of attack varied from -16 to 22 degrees) without
SJA is compared with the computational fluid dynamic (CFD)
simulation as a baseline validation. A good agreement of the CFD
simulations is obtained for aerodynamic coefficients and pressure
distribution.
A working SJA has been integrated with the baseline airfoil and
initial focus is on the aerodynamic stall control at angles of attack
from 16 to 22 degrees. The results show a noticeable improvement in
the aerodynamic performance with increase in lift and decrease in
drag at these post stall regimes.