Probabilistic Event Based Rainfall-Runoff Modeling Using Copula Functions

Multivariate probability analysis of hydrological elements using copula functions can significantly improve the modeling of complex phenomena by considering several dependent variables simultaneously. The main objectives of this study were to: (i) develop a stand-alone and event-based rainfall-runoff (RR) model using the common bivariate copula functions (i.e. the BCRR model); (ii) improve the structure of the developed copula-based RR model by using a trivariate version of fully-nested Archimedean copulas (i.e. the FCRR model); and (iii) compare the performance of the developed copula-based RR models in an Iranian watershed. Results showed that both of the developed models had acceptable performance. However, the FCRR model outperformed the BCRR model and provided more reliable estimations, especially for lower joint probabilities. For example, when joint probabilities were increased from 0.5 to 0.8 for the peak discharge (q_p) variable, the reliability criteria value increased from 0.0039 to 0.8000 in the FCRR model, but only from 0.0010 to 0.6400 in the BCRR model. This is likely because the FCRR considers more than one rainfall predictor, while the BCRR considers only one.

     

Magnetic field analysis of a 9–6 without permanent magnet brushless DC motor by using 3-D finite element method

This paper presents characteristic analysis of without permanent magnet brushless DC (WPMBLDC) motor by using three-dimensional (3-D) finite element method (FEM). The paper describes the complex magnetic structure and principle of the presented WPMBLDC motor in detail. The magnetic field distribution of the presented motor is numerically computed by 3-D FEM. The primary characteristics of the motor including magnetic flux density, flux linkage and inductance profile are obtained. A prototype WPMBLDC machine has also been built and tested; additionally, the accuracy of 3-D FE analysis is verified by comparing the calculated results with the experimental measured values.     

Coupled particle swarm optimization method with genetic algorithm for the static–dynamic performance of the magneto-electro-elastic nanosystem

As a first attempt, Fourier series expansion (FSE), particle swarm optimization (PSO), and genetic algorithm (GA) methods are coupled for analysis of the static–dynamic performance and propagated waves in the magneto-electro-elastic (MEE) nanoplate. The FSE method is presented for solving the motion equations of the MEE nanoplate. For increasing the performance of genetic algorithms for solving the problem, the particle swarm optimization technique is added as an operator of the GA. Accuracy, convergence, and applicability of the proposed mixed approach are shown in the results section. Also, we prove that for obtaining the convergence results of the PSO and GA, we should consider more than 16 iterations. Finally, it is shown that if designers consider the presented algorithm in their model, the results of phase velocity of the nanosystem will be increased by 27%. A useful suggestion is that there is a region the same as a trapezium in which there are no effects from magnetic and electric potential of the MEE face sheet on the phase velocity of the smart nanoplate, and the region will be bigger by increasing the wavenumber.

     

Fault‐tolerant control of distributed systems by information pattern reconfiguration

Given a fault‐tolerance strategy and a distributed control system, the set of recoverable faults depends on the information pattern that is implemented. This paper shows that fault‐tolerance can be achieved, when possible, by the reconfiguration of the information pattern. A necessary and sufficient recoverability condition is provided, and sub‐optimal solutions are developed for actuator and sensor faults under system reconfiguration. Copyright © 2014 John Wiley & Sons, Ltd.     

Statistical analysis of the performance of a bi-functional catalyst under operating conditions of LPDME process

Liquid phase direct synthesis of dimethyl ether (LPDME™) under various operating conditions (temperature, H₂/CO molar ratio of feed) was conducted in a mechanically agitated slurry reactor system. Each run was monitored for 60 h time on stream (TOS) in order to confirm the high activity and long-term stability of a bi-functional catalytic system (CuO–ZnO–Al₂O₃/H-MFI-90). Statistical experimental design was applied for determining the optimum operating conditions under which the catalytic system shows the highest performance. A significant improvement in the performance of the bi-functional catalyst was observed when the temperature and H₂/CO molar ratio of feed were increased from 200 to 240 °C and 1 to 2, respectively at a constant pressure of 35 bar and GHSV equal to 1100 mLn/(g-cat h). CO conversion was increased from 9.1 mol% at T = 200 °C and H₂/CO = 1 to 79.6 mol% at T = 240 °C and H₂/CO = 2 and the yield and selectivity of DME also increased from 7.11% to 47.05% and 41.57% to 59.96%, (molar basis) respectively. No significant deactivation has been observed during 60 h TOS at different operating conditions. Furthermore, from the main effect plots and response table results, it was concluded that the most effective factor on activity and stability of bi-functional catalytic system is temperature.