Abstract: Networks can be utilized to represent project planning problems, using nodes for activities and arcs to indicate precedence relationship between them. For fixed activity duration, a simple algorithm calculates the amount of time required to complete a project, followed by the activities that comprise the critical path. Program Evaluation and Review Technique (PERT) generalizes the above model by incorporating uncertainty, allowing activity durations to be random variables, producing nevertheless a relatively crude solution in planning problems. In this paper, based on the findings of the relevant literature, which strongly suggests that a Beta distribution can be employed to model earthmoving activities, we utilize Monte Carlo simulation, to estimate the project completion time distribution and measure the influence of skewness, an element inherent in activities of modern technical projects. We also extract the activity criticality index, with an ultimate goal to produce more accurate planning estimations.
Abstract: In general, classical methods such as maximum
likelihood (ML) and least squares (LS) estimation methods are used
to estimate the shape parameters of the Burr XII distribution.
However, these estimators are very sensitive to the outliers. To
overcome this problem we propose alternative robust estimators
based on the M-estimation method for the shape parameters of the
Burr XII distribution. We provide a small simulation study and a real
data example to illustrate the performance of the proposed estimators
over the ML and the LS estimators. The simulation results show that
the proposed robust estimators generally outperform the classical
estimators in terms of bias and root mean square errors when there
are outliers in data.
Abstract: This study is concerned with the visualization of monotone data using a piecewise C1 rational trigonometric interpolating scheme. Four positive shape parameters are incorporated in the structure of rational trigonometric spline. Conditions on two of these parameters are derived to attain the monotonicity of monotone data and othertwo are leftfree. Figures are used widely to exhibit that the proposed scheme produces graphically smooth monotone curves.
Abstract: The concept of adaptive shape parameters (ASP) has been presented for solution of incompressible Navier Strokes equations using mesh-free local Radial Basis Functions (RBF). The aim is to avoid ill-conditioning of coefficient matrices of RBF weights and inaccuracies in RBF interpolation resulting from non-optimized shape of basis functions for the cases where data points (or nodes) are not distributed uniformly throughout the domain. Unlike conventional approaches which assume globally similar values of RBF shape parameters, the presented ASP technique suggests that shape parameter be calculated exclusively for each data point (or node) based on the distribution of data points within its own influence domain. This will ensure interpolation accuracy while still maintaining well conditioned system of equations for RBF weights. Performance and accuracy of ASP technique has been tested by evaluating derivatives and laplacian of a known function using RBF in Finite difference mode (RBFFD), with and without the use of adaptivity in shape parameters. Application of adaptive shape parameters (ASP) for solution of incompressible Navier Strokes equations has been presented by solving lid driven cavity flow problem on mesh-free domain using RBF-FD. The results have been compared for fixed and adaptive shape parameters. Improved accuracy has been achieved with the use of ASP in RBF-FD especially at regions where larger gradients of field variables exist.
Abstract: In this paper, the estimation of the stress-strength
parameter R = P(Y < X), when X and Y are independent and both
are Lomax distributions with the common scale parameters but
different shape parameters is studied. The maximum likelihood
estimator of R is derived. Assuming that the common scale parameter
is known, the bayes estimator and exact confidence interval of R are
discussed. Simulation study to investigate performance of the
different proposed methods has been carried out.
Abstract: Medical applications are among the most impactful
areas of microrobotics. The ultimate goal of medical microrobots is
to reach currently inaccessible areas of the human body and carry out
a host of complex operations such as minimally invasive surgery
(MIS), highly localized drug delivery, and screening for diseases at
their very early stages. Miniature, safe and efficient propulsion
systems hold the key to maturing this technology but they pose
significant challenges. A new type of propulsion developed recently,
uses multi-flagella architecture inspired by the motility mechanism of
prokaryotic microorganisms. There is a lack of efficient methods for
designing this type of propulsion system. The goal of this paper is to
overcome the lack and this way, a numerical strategy is proposed to
design multi-flagella propulsion systems. The strategy is based on the
implementation of the regularized stokeslet and rotlet theory, RFT
theory and new approach of “local corrected velocity". The effects of
shape parameters and angular velocities of each flagellum on overall
flow field and on the robot net forces and moments are considered.
Then a multi-layer perceptron artificial neural network is designed
and employed to adjust the angular velocities of the motors for
propulsion control. The proposed method applied successfully on a
sample configuration and useful demonstrative results is obtained.
Abstract: Heterogeneous catalysis is vital for a number of
chemical, refinery and pollution control processes. The use of
catalyst pellets of hollow cylindrical shape provide several distinct
advantages over other common shapes, and can therefore help to
enhance conversion levels in reactors. A better utilization of the
catalytic material is probably most notable of these features due to
the absence of the pellet core, which helps to significantly lower the
effect of the internal transport resistance. This is reflected in the
enhancement of the effectiveness factor. For the case of the first order
irreversible kinetics, a substantial increase in the effectiveness factor
can be obtained by varying shape parameters. Important shape
parameters of a finite hollow cylinder are the ratio of the inside to the
outside radii (κ) and the height to the diameter ratio (γ). A high value
of κ the generally helps to enhance the effectiveness factor. On the
other hand, lower values of the effectiveness factors are obtained
when the dimension of the height and the diameter are comparable.
Thus, the departure of parameter γ from the unity favors higher
effectiveness factor. Since a higher effectiveness factor is a measure
of a greater utilization of the catalytic material, higher conversion
levels can be achieved using the hollow cylindrical pellets possessing
optimized shape parameters.
Abstract: For smaller mechatronic device, especially for micro
Electronic system, a micro machining is a must. However, most
investigations on vibration of a mill have been limited to the
traditional type mill. In this article, vibration and dynamic
characteristics of a micro mill were investigated in this study. The
trend towards higher precision manufacturing technology requires
producing miniaturized components. To improve micro-milled
product quality, obtain a higher production rate and avoid milling
breakage, the dynamic characteristics of micro milling must be
studied. A stepped pre-twisted mill is used to simulate the micro mill.
The finite element analysis is employed in this work. The flute length
and diameter effects of the micro mill are considered. It is clear that
the effects of micro mill shape parameters on vibration in a micro mill
are significant.