Sharif Digital Repository

The long-term deactivation of a commercial K-promoted Fe2O3 catalyst used in the dehydrogenation of ethylbenzene to styrene monomer was investigated using 30 mo of operating data of three industrial SM radial fixed bed adiabatic reactors. The Langmuir-Hinshelwood, Hougen-Watson model was used for reaction kinetics modeling. The kinetics of coking from ethylbenzene and styrene and the short-term deactivation function due to the quick coke formation were considered in the model. The kinetics of long-term deactivation of the catalyst for ethylbenzene dehydrogenation to styrene at 550°-630°C were determined. Unknown parameters of the long-term activity function, related to the slow loss of... 

Long-term deactivation of a commercial K-promoted Fe 2O 3 catalyst used in the dehydrogenation of ethylbenzene to styrene monomer was studied using 30 months of operating data of three industrial SM radial fixed bed adiabatic reactors. The Langmuir-Hinshelwood, Hougen-Watson model (LHHW) was used for reaction kinetics modeling. The kinetics of coking from ethylbenzene and styrene and the short-term deactivation function due to the quick coke formation were also considered in the model. The kinetics of long-term deactivation of the catalyst for ethylbenzene dehydrogenation to styrene between 550 and 630 °C were determined by allowing the effects of temperature and time on the catalyst... 

Tolerance analysis is essential for estimation of final error of key product characteristic (KPC) in a mechanical assembly caused by errors in production and assembly of individual parts. Many mechanical assemblies, especially in automotive and aerospace industries, include sheet metal parts with a small ratio of thickness to width or length. Such parts are substantially flexible and thus, are prone to large errors due to elastic deformations during assembly production. Phenomena such as deformation due to fixture force, spring back, welding distortion and so on are common to such parts. Unlike tolerance analysis of rigid parts, here, the elastic deformation of the parts plays a significant... 

Many real-world networks have a modular structure, and their component may undergo random errors and/or intentional attacks. More devastating situations may happen if the network components have a limited load capacity; the errors and attacks may lead to a cascading component removal process, and consequently, the network may lose its desired performance. In this brief, we investigate the tolerance of cascading errors and attacks in modular small-world networks. This brief studies the size of the largest connected component of the networks when cascading errors or attacks occur. The robustness of the network is tested as a function of both the intermodular connection and intramodular... 

In this article, a resilient, adaptive event-triggered distributed Nash equilibrium seeking algorithm is investigated for a class of multimicrogrid systems. Since the strategy of each microgrid affects others' costs through total generation cost, such interaction among microgrids is modeled as a noncooperative game. To reduce unnecessary signal transmission among the aggregators, an adaptive algorithm, where threshold parameters are adjusted based on the behavior of the estimated signals in the last two iterations, is proposed. It is observed that when false data is injected into an agent, its estimated signals begin to diverge from the equilibrium point, and as a result, the threshold value... 

In this paper, a mathematical model is proposed to assess the flow distribution based on the traffic criterion. In the mathematical model, the resilience and stability criteria are developed based on the concepts of control engineering and optimal control. The results show that the route stability is dependent on the traffic parameter. Then, considering several factors including stability, safety, resilience, risk-averse investment, the environment and noise, a decision-making model is presented to evaluate the performance of the flow distribution routes during crises. Goal programming and data-oriented modelling are used to solve the mathematical model. Data envelopment analysis (DEA) is... 

An efficient hierarchical hybrid delivery (EHHD) model is proposed by integrating a location-allocation optimisation model with a dynamic data envelopment analysis (DEA) model in this paper. The proposed model is characterised by having a periodic measurement assessing customer behaviour using the dynamic DEA, as well as developing a hierarchical connection among home delivery, the pickup point and the locker station options. The developed model considers uncertain conditions for transportation costs and customer behaviour. To solve this model, a meta-goal programming approach has been used. Based on the results of the numerical experiments, the developed model has a better performance than... 

In this paper, an algorithm has been developed to evaluate the performance of omni channel distribution network configurations based on data envelopment analysis (DEA) models and consensus formation. At first, bi-objective input- and output-oriented simultaneous DEA models are developed to evaluate the configurations with respect to two common criteria, i.e., the service and cost, and the transparency criterion which is defined based on the blockchain technology. Then, a consensus is formed on the evaluation results, based on a risk-based optimisation model. The proposed models are solved by fuzzy goal programming. In addition, the application of the proposed models is demonstrated through a... 

This work aims to design a sustainable two-echelon supply chain not only based on the widely used cost perspective, but also based on the efficient use and preservation of limited resources. For this purpose, a branch and efficiency (B&E) algorithm is developed, which includes an optimization model and an evaluation model. The proposed tri-objective optimization model simultaneously minimizes the total cost of the supply chain, maximizes the sustainability score, and minimizes inequity among customers. The solutions obtained from the optimization model are then evaluated by extended data envelopment analysis (EDEA) models based on common criteria (i.e., cost and service) and traffic... 

Location and allocation problems in supply chain networks are considered as strategic decisions; because they both require investment and have long-term effects. On the other hand, the supply chain network is not protected against disruptions in the real world. In this paper, a branch and efficiency (B&E) algorithm is developed which integrates a multi-objective optimization model used for designing the supply chain network with an extended data envelopment analysis (EDEA) model. Through this integration, efficient solutions are obtained that lead to minimization of the costs. The objective functions of the optimization model include the operational costs, resilience costs and inequality in... 

As an outcome of economies of scale, demand growth can benefit companies in various ways. However, demand fulfillment and management are just not possible in a supply chain whose managers focus only on cost minimization. For this reason, the present paper proposes a sustainable, efficient, customer-centered and resilient closed-loop supply chain network. Limited access to labor during the Covid-19 pandemic, traffic congestion due to transportation of products, as well as transparency through the Blockchain technology are some of the key considerations in our supply chain network design. To the best of our knowledge, this is the first attempt where such a supply chain network is designed,... 

The production and distribution planning problem, where incomplete information from the manufacturer factories is available to the distributor, is prevalent in the real world. Yet, researchers have not focused sufficiently on this field of research. Therefore, our paper offers a two-level multi-objective optimization of production and distribution planning for the two-stage supply chain based on the Data Envelopment Analysis method, which minimizes both the cost and the traffic congestion caused by the establishment of distributor warehouses. In addition, transparency through the blockchain technology and uncertain conditions through stochastic and fuzzy programming are considered in the... 

In this paper, the vibration and primary resonance of electrostatically actuated microbridges are investigated, with the effects of electrostatic actuation, axial stress, and mid-plane stretching considered. Galerkin's decomposition method is adopted to convert the governing nonlinear partial differential equation to a nonlinear ordinary differential equation. The homotopy perturbation method (a special case of homotopy analysis method) is then employed to find the analytic expressions for the natural frequencies of predeformed microbridges, by which the effects of the voltage, mid-plane stretching, axial force, and higher mode contribution on the natural frequencies are studied. The primary... 

Since the advent of conventional activated sludge biological treatment plants, their low efficiency in nitrogen and phosphorus removal has become a significant concern. Therefore, in this study, the performance of microalgal-activated sludge membrane bioreactor (MAS-MBR) as a self-biological treatment or as a post-treatment for conventional biological treatments was investigated. A continuous MAS-MBR with two ratios of algae/sludge (only microalgae and 5:1) was used to treat raw and treated wastewater. The optimum case was achieved with the cultivation of mixed algae/sludge in raw wastewater (R2 case). In this case, the ammonium and phosphorus removal efficiencies were 94.36 ± 3.5 and 88.37... 

In this paper, a fast phoneme recognition system is introduced based on sparse representation. In this approach, the phoneme recognition is fulfilled by Viterbi decoding on support vector machines (SVM) output probability estimates. The candidate classes for classification are adaptively pruned by a k-dimensional (KD) tree search followed by a sparse representation (SR) based class selector with adaptive number of classes. We applied the proposed approach to introduce a phoneme recognition system and compared it with some well-known phoneme recognition systems according to accuracy and complexity issues. By this approach, we obtain competitive phoneme error rate with promising computational... 

In this paper, the dissolution and mobilization of non-aqueous phase liquid (NAPL) blobs in the Surfactant-Enhanced Aquifer Remediation (SEAR) process were upscaled using dynamic pore network modeling (PNM) of three-dimensional and unstructured networks. We considered corner flow and micro-flow mechanisms including snap-off and piston-like movement for two-phase flow. Moreover, NAPL entrapment and remobilization were evaluated using force analysis to develop the capillary desaturation curve (CDC) and predict the onset of remobilization. The corner diffusion mechanism was also applied in the modeling of interphase mass transfer to represent NAPL dissolution as the dominant mass transfer... 

In this study, a submerged membrane was installed in a bioreactor to treat N-riched wastewater and obtain high biomass productivity. Chlorella vulgaris was cultivated under mixotrophic, heterotrophic, and photoautotrophic conditions in different kinds of nitrogen sources (nitrate and ammonium) to compare the microalgae growth and nutrient removal in a membrane bioreactor. Further, the respirometric and photosynthetic activities of microalgae were investigated to evaluate the viability of microalgae in different conditions. The highest biomass productivity was obtained under mixotrophic cultivation in ammonium source (0.230 ± 0.009 gr/L d). Moreover, with this type of cultivation and nitrogen... 

Satisfying customer demand is one of the growing concerns of supply chain managers. On the other hand, the development of internet communications has increased online demand. In addition, the COVID-19 pandemic has increased the demand for online shopping. One of the useful concepts that help to address this concern is the omni-channel strategy, which integrates online and traditional channels with the aim of improving customer service level. For this purpose, this paper proposes an algorithm for evaluating Omni-channel Distribution Network Configurations (OCDNCs). The algorithm applies an extended Data Envelopment Analysis (DEA) model to evaluate OCDNCs based on cost, service, transparency,... 

With the development of communication infrastructure, the design of supply chains has changed significantly. Blockchain technology, as one of the most cutting-edge technologies, can promote transparency among members of the supply chain network. To the best of our knowledge, this is the first study that tries to develop a novel bi-objective optimization model to integrate the transparency resulting from the use of blockchain for designing a three-level supply chain network. The first objective function is to minimize total cost while the second objective function seeks to maximize transparency based on the application of blockchain technology. Moreover, it is worth noting that it is the...