Comprehensive review of water management and wastewater treatment in food processing industries in the framework of water-food-environment nexus

Food processing is among the greatest water-consuming industries with a significant role in the implementation of sustainable development goals. Water-consuming industries such as food processing have become a threat to limited freshwater resources, and numerous attempts are being carried out in order to develop and apply novel approaches for water management in these industries. Studies have shown the positive impact of the new methods of process integration (e.g., water pinch, mathematical optimization, etc.) in maximizing water reuse and recycle. Applying these methods in food processing industries not only significantly supported water consumption minimization but also contributed to environmental protection by reducing wastewater generation. The methods can also increase the productivity of these industries and direct them to sustainable production. This interconnection led to a new subcategory in nexus studies known as water-food-environment nexus. The nexus assures sustainable food production with minimum freshwater consumption and minimizes the environmental destructions caused by untreated wastewater discharge. The aim of this study was to provide a thorough review of water-food-environment nexus application in food processing industries and explore the nexus from different aspects. The current study explored the process of food industries in different sectors regarding water consumption and wastewater generation, both qualitatively and quantitatively. The most recent wastewater treatment methods carried out in different food processing sectors were also reviewed. This review provided a comprehensive literature for choosing the optimum scenario of water and wastewater management in food processing industries.     

Short-term wind power forecasting using ridgelet neural network

Rapid growth of wind power generation in many countries around the world in recent years has highlighted the importance of wind power prediction. However, wind power is a complex signal for modeling and forecasting. Despite the performed research works in the area, more efficient wind power forecast methods are still demanded. In this paper, a new prediction strategy is proposed for this purpose. The forecast engine of the proposed strategy is a ridgelet neural network (RNN) owning ridge functions as the activation functions of its hidden nodes. Moreover, a new differential evolution algorithm with novel crossover operator and selection mechanism is presented to train the RNN. The efficiency of the proposed prediction strategy is shown for forecasting of both wind power output of wind farms and aggregated wind generation of power systems.     

Robust stability of hybrid Roesser models against parametric uncertainty: a general approach

This paper aims at proposing a general framework for the establishement of LMI conditions to analyse the robust stability of a singular hybrid Roesser model subject to parametric uncertainties. The uncertain parameters are involved through implicit Linear Fractional Representations (LFR). Special focus is put on the influence of the number of uncertain parameters and the dimensionality of the model. More precisely it is shown that each dimension can nearly be regarded as an uncertain parameter and the other way around. Therefore, their influence on the conservatism of the obtained condition is very similar.     

Corrosion control in underground concrete structures using double waterproofing shield system (DWS)

High level of structural and waterproofing stability leads to long-term service life in underground infrastructures. Interaction between aggressive groundwater with tunnel causes corrosion and damage in concrete structure due to steel reinforcement corrosion and concrete cracks. This study introduces a double waterproofing shield system (DWS) as an innovative solution to waterproofing and structural failures in underground concrete structures. In this method, ordinary shotcrete mixture replaces by an organic polymer concrete (OPC) to construct a water-resistant temporary support right after each partial excavation. Two groups of specimens including reference concrete and OPC specimens were provided and tested in accordance with ASTM C 642. Waterproofing parameters including porosity, pore volume, permeability and hydraulic conductivity have been determined. Results show a remarkable reduction in mentioned parameters for OPC compared with ordinary concrete. Improvement in waterproofing performance of temporary support corresponds to a healthy final lining and increase in service life of the structure.     

基于规则与统计相结合的藏文文本自动查错方法研究

针对目前藏文文本自动查错方法的不足,该文提出了一种基于规则和统计相结合的自动查错方法.首先以藏文拼写文法为基础,结合形式语言与自动机理论,构造37种确定型有限自动机识别现代藏文字;然后利用查找字典的方法识别梵音藏文字;最后利用互信息和t-测试差等统计方法查找藏语词语搭配错误和语法错误等真字词错误,实现藏文文本的自动查错...     

Comment on Chen et al. "Fabrication and photovoltaic conversion enhancement of graphene/n-Si Schottky barrier solar cells by electrophoretic deposition", Electrochimica Acta, 2014

In a recent article, Chen et al. [Electrochimica Acta, 2014, 130: 279] presented their fabrication and characterization results on a graphene/n-Si solar cell where the Au nanoparticles were inserted in graphene to increase its optical and electrical properties. The higher efficiency of the device was attributed to increased conductivity of graphene after doping with Au nanoparticles. However, the knowledge in the field of Schottky diode solar cells relates this to increased band bending at the junction. Also, to explain the instability behaviour, they concluded that the growth of silicon oxide on the Si surface or oxygen adsorption on the window layer resulted in the device performance increasing initially and decreasing in the end. However, this instability seems to be due to variation in series resistance reduced at the beginning because of slightly lowered Fermi level and increased at the end by the self-compensation by deep in-diffusion of Au nanoparticles into n-Si layer. We also propose that inserting a very thin p-type layer at the junction will enhance the carrier collection and performance of this device.     

Low pressure mercury–argon electrodeless fluorescent lamp simulation using the finite volume method

A finite volume model of a low pressure Ar–Hg electrodeless lamp with external coils is established. The physical configuration is similar to the OSRAM/ENDURA 70 W lamp. A Maxwellian energy distribution is assumed. Two dimensional behaviors of the most important plasma parameters such as the electron density, the electron temperature and the most important mercury states are discussed. Results are in good agreement with former studies and the general understanding in this area. Also, the influence of the argon pressure is studied. Based on the simulation, the population of the main resonance state, Hg (6³P₁ ) depends on the argon pressure and the optimized value is about 300 mTorr.     

The Temperature Effect on the Compressive Behavior of Closed-Cell Aluminum-Alloy Foams

In this research, the mechanical behavior of closed-cell aluminum (Al)-alloy foams was investigated at different temperatures in the range of 25-450 °C. The main mechanical properties of porous Al-alloy foams are affected by the testing temperature, and they decrease with the increase in the temperature during uniaxial compression. From both the constant/serrated character of stress–strain curves and macro/microstructural morphology of deformed cellular structure, it was found that Al foams present a transition temperature from brittle to ductile behavior around 192 °C. Due to the softening of the cellular structure at higher temperatures, linear correlations of the stress amplitude and that of the absorbed energy with the temperature were proposed. Also, it was observed that the presence of inherent defects like micropores in the foam cell walls induced further local stress concentration which weakens the cellular structure’s strength and crack propagation and cell-wall plastic deformation are the dominant collapse mechanisms. Finally, an energy absorption study was performed and an optimum temperature was proposed.     

Using fuzzy controller for improvement of power decoupling performance in PV systems

ABSTRACT

In photovoltaic systems in order to ensure the stable operation of the module, ripple value of the input voltage should be mitigated to a small value; for this purpose, the power decoupling circuit can be used. In this work, considering the four-switch-based power decoupling circuit developed, the conventional Proportional-Integral (PI) controller has been replaced with well-known fuzzy controller, which enjoys a wide range of control gain variation, both linear and nonlinear rules' capability, robustness and more flexibility. The operating modes of the circuit are addressed and accordingly the space state model is derived. Then, the proposed controller has been replaced and the performance of the system will be analysed. The power decoupling circuit along with the proposed controller is implemented by MATLAB/Simulink software. The simulation results show the ability of the proposed fuzzy controller to improve the performance of the system in comparison to the conventional PI controller. A deeper comparison of two controllers confirms that the system would experience more accuracy, faster response and lower total harmonic distortion (THD) in presence of the proposed fuzzy controller.