Improving the interfacial adhesion in a new renewable resource-based biocomposites from biofuel coproduct and biodegradable plastic

Biocomposites of a biopolymer and the coproduct of corn bioethanol industry, dried distillers’ grains with solubles (DDGS), were produced by reactive melt extrusion and injection molding. The biopolymer matrix was a blend of polyhydroxy(butyrate-co-valrerate), PHBV, and poly(butylene adipate-co-terphthalate), PBAT. The effect of compatibilizer, polymeric methylene diphenyl diisocyanate (PMDI), and corn oil lubricant was studied. The change in melt processing force suggested the occurrence of chemical reactions during the processing. This hypothesis was further investigated by infrared spectroscopy by which the formation of urethane and urea bonds between DDGS and polymeric matrix was approved. Dynamic mechanical analysis confirmed the occurrence of crosslinks at PBAT–PHBV interface showing that the tan δ curves for PBAT and PHBV of the matrix shifted slightly towards each other. Moreover, the calculated parameter of interaction, A, from tan δ curves admitted the stronger bond at the DDGS–matrix interface as a result of addition of PMDI compatibilizer. Also, scanning electron microscopy images revealed improved interfacial adhesion at the DDGS–matrix interface as well as PBAT–PHBV interface within the matrix itself. The obtained crosslinked interfaces resulted in improvement in the strength, modulus, and elongation-at-break of biocomposites. Moreover, a synergism of PMDI and corn oil effects led to a dramatic improvement in impact strength of this biocomposite system so that the respective value for the prepared DDGS biocomposite increased from 75 to 212 J/m with addition of 1 % of PMDI and 3 % of corn oil.     

Supply chain network optimization considering assembly line balancing and demand uncertainty

In supply chain optimisation problems, determining the location, number and capacity of facilities is concerned as strategic decisions, while mid-term and short-term decisions such as assembly policy, inventory levels and scheduling are considered as the tactical and operational decision levels. This paper addresses the optimisation of strategic and tactical decisions in the supply chain network design (SCND) under demand uncertainty. In this respect, a two-stage stochastic programming model is developed in which strategic location decisions are made in the first-stage, while the second-stage contains SCND problem and the assembly line balancing as a tactical decision. In the solution scheme, the combination of sample average approximation and Latin hypercube sampling methods is utilised to solve the developed two-stage mixed-integer stochastic programming model. Finally, computational experiments on randomly generated problem instances are presented to demonstrate the performance and power of developed model in handling uncertainty. Computational experiments showed that stochastic model yields better results compared with deterministic model in terms of objective function value, i.e. the sum of the first-stage costs and the expected second-stage costs. This issue proved that uncertainty would be a significant and fundamental element of developed model and improve the quality of solutions.     

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.     

Joint market clearing in a stochastic framework considering power system security

This paper presents a new stochastic framework for provision of reserve requirements (spinning and non-spinning reserves) as well as energy in day-ahead simultaneous auctions by pool-based aggregated market scheme. The uncertainty of generating units in the form of system contingencies are considered in the market clearing procedure by the stochastic model. The solution methodology consists of two stages, which firstly, employs Monte–Carlo Simulation (MCS) for random scenario generation. Then, the stochastic market clearing procedure is implemented as a series of deterministic optimization problems (scenarios) including non-contingent scenario and different post-contingency states. The objective function of each of these deterministic optimization problems consists of offered cost function (including both energy and reserves offer costs), Lost Opportunity Cost (LOC) and Expected Interruption Cost (EIC). Each optimization problem is solved considering AC power flow and security constraints of the power system. The model is applied to the IEEE 24-bus Reliability Test System (IEEE 24-bus RTS) and simulation studies are carried out to examine the effectiveness of the proposed method.     

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.