Bench-scale and pilot plant preparation of chemically modified polyester resins

The laboratory preparation procedure of a recently developed unsaturated polyester resin was followed to prepare the resin on a large scale (10- and 200-L pilot plant reactors). The process heating rate, reaction temperature, and agitator tip speed were kept constant on scale-up. The resin was successfully reproduced and its properties were unchanged upon scale-up. The effects of reaction temperature and inert gas flow rate on the polyesterification reaction rate were investigated. It was found that a 10°C increase in temperature or a 50% increase in the gas flow rate results in a 50% increase in the reaction rate.     

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.

     

New Approaches to Routing in Mobile Ad hoc Networks

Worldwide Interoperability for Microwave Access (Wimax) is power station through which mobile network, commonly known as A Mobile Ad-hoc Network (MANET) is used by the people. A MANET can be described as an infrastructure-less and self-configure network with autonomous nodes. Participated nodes in MANETs move through the network constantly causing frequent topology changes. Designing suitable routing protocols to handle the dynamic topology changes in MANETs can enhance the performance of the network. In this regard, this paper proposes four algorithms for the routing problem in MANETs. First, we propose a new method called Classical Logic-based Routing Algorithm for the routing problem in MANETs. Second is a routing algorithm named Fuzzy Logic-based Routing Algorithm (FLRA). Third, a Reinforcement Learning-based Routing Algorithm is proposed to construct optimal paths in MANETs. Finally, a fuzzy logic-based method is accompanied with reinforcement learning to mitigate existing problems in FLRA. This algorithm is called Reinforcement Learning and Fuzzy Logic-based (RLFLRA) Routing Algorithm. Our proposed approaches can be deployed in dynamic environments and take four important fuzzy variables such as available bandwidth, residual energy, mobility speed, and hop-count into consideration. Simulation results depict that learning process has a great impact on network performance and RLFLRA outperforms other proposed algorithms in terms of throughput, route discovery time, packet delivery ratio, network access delay, and hop-count.

     

Transforming Vulnerability Indexing for Saltwater Intrusion into Risk Indexing through a Fuzzy Catastrophe Scheme

Mapping vulnerability to Saltwater Intrusion (SWI) in coastal aquifers is studied in this paper using the GALDIT framework but with a novelty of transforming the concept of vulnerability indexing to risk indexing. GALDIT is the acronym of 6 data layers, which are put consensually together to invoke a sense of vulnerability to the intrusion of saltwater against aquifers with freshwater. It is a scoring system of prescribed rates to account for local variations; and prescribed weights to account for relative importance of each data layer but these suffer from subjectivity. Another novelty of the paper is to use fuzzy logic to learn rate values and catastrophe theory to learn weight values and these together are implemented as a scheme and hence Fuzzy-Catastrophe Scheme (FCS). The GALDIT data layers are divided into two groups of Passive Vulnerability Indices (PVI) and Active Vulnerability Indices (AVI), where their sum is Total Vulnerability Index (TVI) and equivalent to GALDIT. Two additional data layers (Pumping and Water table decline) are also introduced to serve as Risk Actuation Index (RAI). The product of TVI and RAI yields Risk Indices. The paper applies these new concepts to a study area, subject to groundwater decline and a possible saltwater intrusion problem. The results provide a proof-of-concept for PVI, AVI, RAI and RI by studying their correlation with groundwater quality samples using the fraction of saltwater (f_sea), Groundwater Quality Indices (GQI) and Piper diagram. Significant correlations between the appropriate values are found and these provide a new insight for the study area.

     

Influence of slip length on filtration performance of fine particles

Fine particle filtration has been known to become progressively inefficient as the filter cake builds up owing to restricted movement of liquid through the small cavities formed in the cake. In different chemical industries, this restricts higher throughput rates and also results in higher transportation costs due to increase in moisture content. This paper discusses the influence of using a surfactant, DAH (dodecylamine hydrochloride), in enhancing the filtration rate of a finely ground particles and the reduction of moisture content in the cake. The observed enhanced filtration rate has been attributed to a reduction in the resistance to liquid flow due to the increase in hydrophobicity at the particle surface. The resulting enhanced filtration rate has been modelled by superimposing a slip velocity at the boundary of the capillaries formed in the cake. The model evaluates the cake and medium resistances by incorporating a slip length into the filtration equation which varies with the concentration of hydrophobic reagent and the effective size of capillaries. The increase in filtration rate is more pronounced for finer particle slurries. Also, it has been observed that the moisture content of the filter cakes formed was reduced.     

An enhanced beam search algorithm for the Shortest Common Supersequence Problem

The Shortest Common Supersequence Problem asks to obtain a shortest string that is a supersequence of every member of a given set of strings. It has applications, among others, in data compression and oligonucleotide microarray production. The problem is NP-hard, and the existing exact solutions are impractical for large instances. In this paper, a new beam search algorithm is proposed for the problem, which employs a probabilistic heuristic and uses the dominance property to further prune the search space. The proposed algorithm is compared with three recent algorithms proposed for the problem on both random and biological sequences, outperforming them all by quickly providing solutions of higher average quality in all the experimental cases. The Java source and binary files of the proposed IBS_SCS algorithm and our implementation of the DR algorithm and all the random and real datasets used in this paper are freely available upon request.