Synthesis of a Fe3O4-rGO-ZnO-catalyzed photo-Fenton system with enhanced photocatalytic performance

In this work, we designed a magnetically-separable Fe₃O₄-rGO-ZnO ternary catalyst, ZnO anchored on the surface of reduced graphene oxide (rGO)-wrapped Fe₃O₄ magnetic nanoparticles, where rGO, as an effective interlayer, can enhance the synergistic effect between ZnO and Fe₃O₄. The effects of three operational parameters, namely irradiation time, hydrogen peroxide dosage, and the catalyst dosage, on the photo-Fenton degradation of methylene blue and methyl orange were investigated. The results showed that the Fe₃O₄-rGO-ZnO had great potential for the destruction of organic compounds from wastewater using the Fenton chemical oxidation method at neutral pH. Repeatability of the photocatalytic activity after 5 cycles showed only a tiny drop in the catalytic efficiency.     

Effects of Winding Attachment Positions on Output Characteristics of Flux‐Modulating Synchronous Machines

The flux‐modulating synchronous machine (FMSM) is a new type of multipole SM with nonoverlapping concentrated armature and field windings on the stator. This paper compares the output characteristics of two FMSMs through finite element analysis (FEA) and experiments. In both of the FMSMs, the attachment positions of the armature and field windings are swapped. To determine the reason for the discrepancies in their output characteristics, unsaturated inductances were calculated using a d‐‐q equivalent circuit. In addition, the calculated results of the inductances were confirmed through a visualization of the leakage fluxes using FEA. The results of the study show that the synchronous inductance can be reduced by attaching the armature winding to the air‐gap side of the stator teeth and that the reduction leads to an increase in output power.     

Cooling condition dependence on ion etching rate in a softmagnetic metallic glass

Taking into consideration the knock-on cascade mechanism and the free volume theory, the cooling condition dependentR _s (ion etching rate) is investigated for a liquid-quenched Fe-10at%Si-15at%B alloy glass. A highR _s is found in a slow cooled glass.     

A predictive controller based on dynamic matrix control for a non-minimum phase robot manipulator

In this paper a hybrid control strategy is presented based on Dynamic Matrix Control (DMC) and feedback linearization methods for designing a predictive controller of five bar linkage manipulator as a MIMO system (two inputs and two outputs). Analyzing the internal dynamic of robot shows the open loop system is unstable and non-minimum phase, so in order to apply the predictive controller, special modifications are needed. These modifications on non-minimum phase behavior are performed using feedback linearization procedure based on state space realization. The design objective is to track a desirable set point as well as time varying trajectories as a command references with globally asymptotical stabilization. The proposed controller is applied to nonlinear fully coupled model of the typical five bar linkage manipulator with non-minimum phase behavior. Simulation results show that the proposed controller has good efficiency. The step responses of system with and without feedback linearization process illustrated that the mentioned modification for stabilizing is performed properly. After applying the proposed predictive controller, the joint angle of robot tracks the reference input while another input acts as the disturbance and vice versa.     

Sustainable Basin-Scale Water Allocation with Hydrologic State-Dependent Multi-Reservoir Operation Rules

This study extends the PSO-MODSIM model, integrating particle swarm optimization (PSO) algorithm and MODISM river basin decision support system (DSS) to determine optimal basin-scale water allocation, in two aspects. The first is deriving hydrologic state-dependent (conditional) operating rules to better account for drought and high-flow periods, and the second is direct, explicit consideration of sustainability criteria in the model’s formulation to have a better efficiency in basin-scale water allocation. Under conditional operating rules, the operational parameters of reservoir target storage levels and their priority rankings were conditioned on the hydrologic state of the system in a priority-based water allocation scheme. The role of conditional operating rules and policies were evaluated by comparing water shortages associated with objective function values under unconditional and conditional operating rules. Optimal basin-scale water allocation was then evaluated by incorporating reliability, vulnerability, reversibility and equity sustainability indices into the PSO objective function. The extended model was applied for water allocation in the Atrak River Basin, Iran. Results indicated improved distribution of water shortages by about 7.5% using conditional operating rules distinguishing dry, normal and wet hydrologic states. Alternative solutions with nearly identical objective function values were found with sustainability indices included in the model.     

Bidirectional teleportation of a pure EPR state by using GHZ states

In the present paper, a novel bidirectional quantum teleportation protocol is proposed. By using entanglement swapping technique, two GHZ states are shared as a quantum channel between Alice and Bob as legitimate users. In this scheme, based on controlled-not operation, single-qubit measurement, and appropriate unitary operations, two users can simultaneously transmit a pure EPR state to each other, While, in the previous protocols, the users can just teleport a single-qubit state to each other via more than four-qubit state. Therefore, the proposed scheme is economical compared with previous protocols.     

Fuzzy Bayesian system reliability assessment based on Pascal distribution

The main purpose of this paper is to provide a methodology for discussing the fuzzy. Bayesian system reliability from the fuzzy component reliabilities, actually we discuss on the Fuzzy Bayesian system reliability assessment based on Pascal distribution, because the data sometimes cannot be measured and recorded precisely. In order to apply the Bayesian approach, the fuzzy parameters are assumed as fuzzy random variables with fuzzy prior distributions. The (conventional) Bayes estimation method will be used to create the fuzzy Bayes point estimator of system reliability by invoking the well-known theorem called ‘Resolution Identity’ in fuzzy sets theory. On the other hand, we also provide the computational procedures to evaluate the membership degree of any given Bayes point estimate of system reliability. In order to achieve this purpose, we transform the original problem into a nonlinear programming problem. This nonlinear programming problem is then divided into four sub-problems for the purpose of simplifying computation. Finally, the sub problems can be solved by using any commercial optimizers, e.g. GAMS or LINGO.     

A Bayesian approach to design of adaptive multi-model inferential sensors with application in oil sand industry

In the context of process industries, online monitoring of quality variables is often restricted by inadequacy of measurement techniques or low reliability of measuring devices. Therefore, there has been a growing interest in the development of inferential sensors to provide frequent online estimates of key process variables on the basis of their correlation with real-time process measurements. Representation of multi-modal processes is one of the challenging issues that may arise in the design of inferential sensors. In this paper, Bayesian procedures for the development and implementation of adaptive multi-model inferential sensors are presented. It is shown that the application of a Bayesian scheme allows for accommodating the overlapping operating modes and facilitating the inclusion of prior knowledge. The effectiveness of the proposed procedures are first demonstrated through a simulation case study. The efficacy of the method is further highlighted by a successful industrial application of an adaptive multi-model inferential sensor designed for real-time monitoring of a key quality variable in an oil sands processing unit.     

Stress distribution of coated film with a range of coated film thickness and elastic properties under a single EHL operating condition

In recent years, the techniques improving sliding performances have progressed by using coated films possessing superior tribological properties, to reduce the failures of the mechanical elements. Those techniques are often used under severe conditions such as elastohydrodynamic lubrication (EHL). In this paper, numerical three-dimensional analysis of the maximum shear stress applied into the coated film and substrate under a single EHL operating condition was performed with a range of coated film thickness and elastic properties. The strength of coated film as one of those techniques was evaluated numerically, resulting in an optimum design of coated film. As a result, coated films with a larger value of thickness and a smaller modulus of elasticity than that of substrate are preferable.