A computer code, based on Euler Equations in generalized curvilinear coordinates, has been developed to resolve binary perfect gas mixture flows. The capability of modeling various mixture effects is built in the algorithm and the computer code. The Roe's numerical scheme is used to discretize the convective terms of the governing fluid flow equations, while a simple upwinding method is applied for the equation of continuity of species. Some applications of binary gas mixture flows, including nozzle cooling and thrust vectoring, are investigated and the role of mixing phenomenon in these flows is classified. Additionally, the influences of using different gases on flow fields are evaluated, especially in two-dimensional thrust vectoring problems.

By application of Cone Penetration Test (CPT) data for shallow foundation (footing) design, the problems of providing representative undisturbed samples and, rather, \varphi-N coefficient relations will be eliminated. An analytical model, based on a general shear failure mechanism of the logarithm spiral type, has been developed for calculating, directly, the bearing capacity of footings, q_ult from cone resistance, q_c. The transform of the failure mechanism from a shallow to a deep foundation and the scale effect have been considered in the proposed method. Six current CPT direct methods for determining the bearing capacity of footings have been investigated. The proposed method and others were compared to the measured capacity, ranging from 1.7 to 15 kg/cm^2, of 28 footings compiled in a database with a range of diameter from 0.3 to 3 m located in different soils. The graphical and cumulative probability approaches for the validation of the methods indicates optimistic results for the bearing capacity estimation of the proposed method, which is simple and routine.

In this paper, a genetic algorithm is developed for the optimal design of storm water networks. The nodal elevations of the sewer network are taken as the decision variables. A steady state simulation code is used to analyze the trial solutions provided by the GA optimizer. The performance of the four selection schemes namely, conventional roulette wheel, roulette wheel selection with linear scaling, roulette wheel selection with ranking and, finally, roulette wheel selection with power law scaling, is studied by applying the model to some benchmark examples in the literature. The conventional roulette wheel selection scheme produced superior results compared to other methods. The results produced by the proposed model are either comparable or superior to existing results in the literature.

When velocities in the piping systems change rapidly, spectacular accidents occur, due to transient-state pressures where the elastic properties of the pipe and liquid must be considered. This hydraulic transient is commonly known as water hammer. A conventional widely-used technique for analyzing this phenomenon is the Method Of Characteristic (MOC), in which, by introducing the characteristic lines, two ordinary differential equations, in lieu of the governing partial differential equations, are produced. In the undisturbed form of the equations, the energy dissipation is evaluated by the steady or quasi-steady approximation. But, there is experimental and theoretical evidence which shows that the velocity profiles in unsteady-flow conditions have greater gradients and, thus, greater shear stresses, than corresponding values in steady-flow. Moreover, the numerical integration of the friction loss is based on the values at the previous time step. This paper employs the External Energy Dissipator, Karney's method, to apply the boundary conditions in a network. To investigate the effect of the unsteady friction formula, the cross characteristic mesh, based on the Vitkovsky formulation, is completely derived and incorporated in the network. At last, the effect of the weighting term in the integration of the friction-loss term is examined. The paper shows that if the maximum head rise were to be practically considered, it would not need the unsteady friction term to be taken into account. Moreover, the weighting integration constant has the slightest effect on the text network.

In this paper, the numerical results of hydrodynamic modeling of primary settling tanks are presented. The flow field is assumed to be incompressible and non-buoyant. The effects of two different types of turbulence model, standard k-\varepsilon and RNG, are compared with each other. The effects of an inlet baffle on the hydrodynamics of settling tanks are also studied. Results are obtained for the primary settling tank of the city of Sarnia, Ontario, Canada. The effects of the existence and position of another interior baffle in the settling tanks are also studied. Results in the different parts are compared with experimental and numerical data and showed good agreement. Comparison between two models of turbulence shows that the numerical results of the flow field, especially the streamline curvature, are not the same, in spite of having nearly equal results in the streamwise velocity component.

The change of gait pattern and muscular activity following amputation is thought to be responsible for the higher incidence of joint degenerative disorders observed in amputees. Considering the lack of consistent data in the literature, the purpose of the present study was to measure and analyze the spatio-temporal variables, the kinematics and, particularly, the net joint moments of the intact and prosthetic limbs of above knee amputee subjects during walking and to compare the results with those of normals. The gait characteristics of five transfemoral amputees and five normal subjects were measured using videography and a force platform. The human body was modeled as a 2-D sagittal plane linkage consisting of 8 rigid segments and analyzed using rigid body kinematics and inverse dynamics approaches. The results, including the joints flexion angles and normalized net moments, were statistically analyzed. There was a significant difference between the spatio temporal variables of the normal subjects and intact and prosthetic limbs of amputee subjects, but, the difference between the intact and prosthetic limbs of amputees was not statistically significant. The kinematics of the intact limb of the amputee subjects was close to that of the normals, but the prosthetic limb had a much more limited angular motion. The intact limbs of the amputee subjects experienced larger than normal extension hip moment (with a maximum value of 2.08 compared to 1.68 Nm/kg) and flexion knee moment (with a maximum value of 1.84 compared to 1.14 Nm/kg)

this is believed to contribute to the articular cartilage lesions. The hip joint of the prosthetic limb of the amputee subjects, on the other hand, experienced lower than normal joint moments (with a maximum value of 0.97 compared to 1.67 Nm/kg), which might contribute to the osteoporosis found in the remainder of the femur.

This paper presents an effective approach for kinematic and dynamic modeling of high mobility Wheeled Mobile Robots (WMR). As an example of these robots, the method has been applied to the CEDRA rescue robot, which is a complex, multibody mechanism. The model is derived for 6-DOF motions, enabling movements in x, y and z directions, as well as for roll, pitch and yaw rotations. Forward kinematics equations are derived using the Denavit Hartenberg method and Jacobian matrices for the wheels. Moreover, the inverse kinematics of the robot are obtained and solved for the wheel velocities and steering commands, in terms of the desired velocity, heading and measured link angles. Finally, the dynamics of the rover mechanism have been thoroughly studied and analyzed. Due to the complexity of this multi-body system, especially on rough terrain, Kane's method of dynamics has been used to model this problem. The proposed approach and method can easily be extended to other mechanisms and rovers.

In this paper, a Genetic-Based Neural Network (GBNN) is employed to predict the soil-water characteristic curve of unsaturated soils. A three-layer network has been trained by genetic algorithm and its topology is determined by trial and error. The network has five input neurons, namely, initial void ratio, initial gravimetric water content, logarithm of suction normalized with respect to air pressure, clay fraction and silt content. The network has five neurons in the hidden layer and the only output neuron is the gravimetric water content corresponding to the assigned input suction. Results from pressure plate tests carried out on clay, silty clay, sandy loam and loam, compiled in SoilVision software, was adopted as a database for training and testing the network. For this purpose, and after data digitization, a computer program coded in visual basic was developed and used for the analysis. Finally, neural network simulations are compared with the experimental results, as well as models proposed by other investigators. The comparison indicates the superior performance of the proposed method for predicting the soil-water characteristic curve.

In this paper, an improved Ant Colony Optimization (ACO) algorithm is proposed for reservoir operation. Through a collection of cooperative agents called ants, the near-optimum solution to the reservoir operation can be effectively achieved. To apply the proposed ACO algorithm, the problem is approached by considering a finite horizon with a time series of inflow, classifying the reservoir volume to several intervals and deciding for releases at each period, with respect to a predefined optimality criterion. Pheromone promotion, explorer ants and a local search are included in the standard ACO algorithm for a single reservoir, deterministic, finite-horizon problem and applied to the Dez reservoir in Iran. The results demonstrate that the proposed ACO algorithm provides improved estimates of the optimal releases of the Dez reservoir, as compared to traditional state-of-the-art Genetic Algorithms. It is anticipated that further tuning of the algorithmic parameters will further improve the computational efficiency and robustness of the proposed method.

This paper presents results of an experimental study of the behavior of the stress variation at the flange and attached pipe section of a gasketed flanged pipe joint during both the bolt up (pre-loading) procedure and under operating (internal pressure loading) conditions. Stress variations showing flange yielding, flange rotation, effects of a joint tightening sequence, identification of the mode of response to loading (static or dynamic) and the effects of retightening are discussed in detail. Additionally, the importance of high quality bolting with proper surface treatment and the use of proper tooling to reduce the magnitude of overall flange stress variation are also discussed.

Electrical Capacitance Tomography (ECT) is an imaging technique that maps the electrical permittivity contrast of the object. This paper studies an image and a shape reconstruction method for ECT. For image reconstruction, a regularized Gauss-Newton method has been implemented, based on the inverse finite element technique. For shape reconstruction, a narrowband level set method has been developed. Using experimental ECT data, a comparative study of these two techniques is the main objective of this paper.

A numerical model has been developed for the determination of liquid flow permeability through columnar dendrite during growth and segregation in Al-Si alloys. Therefore, in the present work, two separate computational models of grain growth and interdendritic liquid flow are coupled for modeling of the permeability in partly solid alloy. Grain growth is simulated, using a Cellular Automation Finite Difference (CAFD) for a 2D dendrite and fluid flow by using a Computational Fluid Dynamic (CFD) model for determining permeability. A new model has been presented for calculation and modification of dendrite permeability in high solid fractions. Simulation results show which Si concentration variations, at each time step, could transform the dendrite shape. Also, dendrite morphology could alert the interdendritic permeability factor.