Abstract: For those who have lost the ability to move their hand, going through repetitious motions with the assistance of a therapist is the main method of recovery. We have been developed a robotic assistive device to rehabilitate the hand motions in place of the traditional therapy. The developed assistive device (RAD-HR) is comprised of four degrees of freedom enabling basic movements, hand function, and assists in supporting the hand during rehabilitation. We used a nonlinear computed torque control technique to control the RAD-HR. The accuracy of the controller was evaluated in simulations (MATLAB/Simulink environment). To see the robustness of the controller external disturbance as modelling uncertainty (±10% of joint torques) were added in each joints.
Abstract: Currently, there are few user friendly Weigh-in-
Motion (WIM) data analysis softwares available which can produce
traffic input data for the recently developed AASHTOWare pavement
Mechanistic-Empirical (ME) design software. However, these
softwares have only rudimentary Quality Control (QC) processes.
Therefore, they cannot properly deal with erroneous WIM data. As
the pavement performance is highly sensible to the quality of WIM
data, it is highly recommended to use more refined QC process on
raw WIM data to get a good result. This study develops a userfriendly
software, which can produce traffic input for the ME design
software. This software takes the raw data (Class and Weight data)
collected from the WIM station and processes it with a sophisticated
QC procedure. Traffic data such as traffic volume, traffic distribution,
axle load spectra, etc. can be obtained from this software; which can
directly be used in the ME design software.
Abstract: This study investigates how the site specific traffic
data differs from the Mechanistic Empirical Pavement Design
Software default values. Two Weigh-in-Motion (WIM) stations were
installed in Interstate-40 (I-40) and Interstate-25 (I-25) to developed
site specific data. A computer program named WIM Data Analysis
Software (WIMDAS) was developed using Microsoft C-Sharp (.Net)
for quality checking and processing of raw WIM data. A complete
year data from November 2013 to October 2014 was analyzed using
the developed WIM Data Analysis Program. After that, the vehicle
class distribution, directional distribution, lane distribution, monthly
adjustment factor, hourly distribution, axle load spectra, average
number of axle per vehicle, axle spacing, lateral wander distribution,
and wheelbase distribution were calculated. Then a comparative
study was done between measured data and AASHTOWare default
values. It was found that the measured general traffic inputs for I-40
and I-25 significantly differ from the default values.