S.m. Seyed-Hosseini, M. Sabzehparvar, S. Nouri ,
Volume 18, Issue 3 (International Journal of Engineering 2007)
Abstract
Abstract: This paper presents an exact model and a genetic algorithm for the multi-mode resource constrained project scheduling problem with generalized precedence relations in which the duration of an activity is determined by the mode selection and the duration reduction (crashing) applied within the selected mode. All resources considered are renewable. The objective is to determine a mode, the amount of continuous crashing, and a start time for each activity so that all constraints are obeyed and the project duration is minimized. Project scheduling of this type occurs in many fields for instance, predicting the resources and duration of activities in software development projects. A key feature of the model is that none of the typical models can cope with the continuous resource constraints. Computational results with a set of 100 generated instances have been reported and the efficiency of the proposed model has been analyzed.
N. M. Nouri, A. Eslamdoost , M. Shienejad,
Volume 19, Issue 5 (IJES 2008)
Abstract
In the present paper, partial cavitation over various head-forms was studied numerically to predict the shape of the cavity. Navier-Stokes equations in addition to an advection equation for vapor volume fraction were solved. Mass transfer between the phases was modeled by a sink term in vapor equation in the numerical analysis for different geometries in wide range of cavitation numbers. The re-entrant jet formation, which is the main cause for the cavitation cloud separation, was modeled very well with a modification of turbulent viscosity. In regions with higher vapor volume fractions (lower mixture densities) a modification of the turbulence model was made by artificially reducing the turbulent viscosity of mixture. Computed shapes of cavities were found to be in good agreement with those of the reported experiments. Simulation results also compared well with those obtained from analytical relations.
Mohsen Nourizadeh, Moharram Habibnejad Korayem, Hami Tourajizadeh,
Volume 36, Issue 1 (IJIEPR 2025)
Abstract
The purpose of this paper is to optimal control a dual-stage cable robot in a predefined path and to determine the maximum load-carrying capacity of this robot as a tower crane. Also, to expand the workspace of the robot two stages are employed. Today, cable robots are extensively used in load handling. Positive cable tension and collision-free cable control are the most important challenges of this type of robot. The high ratio of transposable loads to weight makes these robots very attractive for use as tower cranes. Dynamic Load Carrying Capacity (DLCC) is the maximum load that can be carried along a predefined path without violating the actuators and allowable accuracy constraints. State-Dependent Riccati Equation (SDRE) is employed to control the end-effector within the path to achieve the maximum DLCC. This approach is chosen since it can optimize the required motors' torque which consequently leads us to the maximum DLCC. In addition, the constraint of cables’ collision together is also checked along the predetermined path using the non-interference algorithm. The correctness of modeling is verified by comparing the results with previous research and the efficiency of the proposed optimal controlling strategy toward increasing the DLCC is investigated by conducting some comparative simulations. it is shown that the proposed cable robot by the aid of the designed optimal controller can increase the load carrying capacity successfully along any desired path using the allowable amount of motors' torque.
