Production of zero trans Iranian vanaspati using chemical transesterification and blending techniques from palm olein, rapeseed and sunflower oils

Chemical transesterification and blending techniques were used for producing zero trans fats suitable for use as Iranian vanaspati. Triple blends of palm olein (POo), rapeseed (RSO) and sunflower oil (SFO) were subjected to two different treatments: (i) blending and then transesterification (BT) and (ii) transesterification of pure POo before blending with RSO and SFO (TB). The changes in slip melting point (SMP), solid fat content (SFC), carbon number (CN) triacylglycerol (TAG) composition, induction period (IP) of oxidation at 120 °C and IP of crystallisation at 20 °C of blends before and after treatments were investigated. Both BT and TB methods resulted in an increase in the CN48 TAG molecules, SMP and SFC, and a decrease in the IP of oxidation and crystallisation of initial blends. Samples made by TB method had higher CN48 TAG content, SMP, SFC and IP of oxidation, and lower IP of crystallisation than those made by BT method. Correlation between SFC at 20 °C and saturated fatty acid (SFA) content of the treated blends indicated that the SFA must be higher than 33.1% and 26.8% for BT and TB methods, respectively, to obtain fats suitable for use as vanaspati.     

Implementing of the multi-objective particle swarm optimizer and fuzzy decision-maker in exergetic, exergoeconomic and environmental optimization of a benchmark cogeneration system

Multi-objective optimization for design of a benchmark cogeneration system namely as the CGAM cogeneration system is performed. In optimization approach, Exergetic, Exergoeconomic and Environmental objectives are considered, simultaneously. In this regard, the set of Pareto optimal solutions known as the Pareto frontier is obtained using the MOPSO (multi-objective particle swarm optimizer). The exergetic efficiency as an exergetic objective is maximized while the unit cost of the system product and the cost of the environmental impact respectively as exergoeconomic and environmental objectives are minimized. Economic model which is utilized in the exergoeconomic analysis is built based on both simple model (used in original researches of the CGAM system) and the comprehensive modeling namely as TTR (total revenue requirement) method (used in sophisticated exergoeconomic analysis). Finally, a final optimal solution from optimal set of the Pareto frontier is selected using a fuzzy decision-making process based on the Bellman-Zadeh approach and results are compared with corresponding results obtained in a traditional decision-making process. Further, results are compared with the corresponding performance of the base case CGAM system and optimal designs of previous works and discussed.     

Aquifers Management through Evolutionary Bayesian Networks: The Altiplano Case Study (SE Spain)

An approach for the integration of Object-Oriented Bayesian Networks (OOBNs) and Evolutionary Multiobjective Optimization (EMO) is proposed for integrated water resource management and decision support. Bayesian Networks (BNs) offer a novel and powerful tool for modelling complex water systems, facilitating the use of hierarchical modelling by improving the efficiency and communication between the different parts of a model. EMO offers a range of non-dominated optimal management solutions on a Pareto front that facilitate the identification of tradeoffs among conflicting criteria regarding stakeholder’s preferences. The integrated tool provides new possibilities for undertaking an integrated analysis where stakeholder participation can play an important role. It is used for simultaneously analysing the whole water system, characterising uncertainty as probabilities and evaluating different management options. The tool is applied to an overexploited water system located in Southern Spain that is supplied totally by groundwater. In this study, a complex model based on BNs is designed and used as the core of the study. The transition to Evolutionary Bayesian networks (EOBNs) allows stakeholder involvement to be utilized more effectively for designing and evaluating the model’s consistency, and taking into account their conflicting interests.     

Self-adaptive fitness formulation for constrained optimization

A self-adaptive fitness formulation is presented for solving constrained optimization problems. In this method, the dimensionality of the problem is reduced by representing the constraint violations by a single infeasibility measure. The infeasibility measure is used to form a two-stage penalty that is applied to the infeasible solutions. The performance of the method has been examined by its application to a set of eleven test cases from the specialized literature. The results have been compared with previously published results from the literature. It is shown that the method is able to find the optimum solutions. The proposed method requires no parameter tuning and can be used as a fitness evaluator with any evolutionary algorithm. The approach is also robust in its handling of both linear and nonlinear equality and inequality constraint functions. Furthermore, the method does not require an initial feasible solution.     

Multidisciplinary design of a small satellite launch vehicle using particle swarm optimization

In the present paper, particle swarm optimization, a relatively new population based optimization technique, is applied to optimize the multidisciplinary design of a solid propellant launch vehicle. Propulsion, structure, aerodynamic (geometry) and three-degree of freedom trajectory simulation disciplines are used in an appropriate combination and minimum launch weight is considered as an objective function. In order to reduce the high computational cost and improve the performance of particle swarm optimization, an enhancement technique called fitness inheritance is proposed. Firstly, the conducted experiments over a set of benchmark functions demonstrate that the proposed method can preserve the quality of solutions while decreasing the computational cost considerably. Then, a comparison of the proposed algorithm against the original version of particle swarm optimization, sequential quadratic programming, and method of centers carried out over multidisciplinary design optimization of the design problem. The obtained results show a very good performance of the enhancement technique to find the global optimum with considerable decrease in number of function evaluations.     

State of SuDS delivery in the United Kingdom

Sustainable drainage systems (SuDS) have become a key tool in the design of water sensitive cities, due to their capacity to store and attenuate surface water, and to treat runoff. SuDS implementation requires a complex alignment of planning frameworks, engineering designs, construction practices, maintenance processes, community buy‐in and ownership agreements. To understand this alignment, and build an evidence base on the implementation and management of UK SuDS, a questionnaire was distributed to 50 000 industry professionals by the Chartered Institution of Water and Environmental Management. The findings suggested that SuDS are beginning to become the norm, although ‘harder’ solutions tend to prevail. Additionally, design and construction remain weakly regulated, and there is a lack of clear legal framework on SuDS ownership and maintenance. Expert practitioners supported the need for a single adoption method, coordinated by the local authority and suggested policy changes to make SuDS obligatory.     

An analytical model of delay in multi-hop wireless ad hoc networks

Several analytical models of different wireless networking schemes such as wireless LANs and meshes have been reported in the literature. To the best of our knowledge, all these models fail to address the accurate end-to-end delay analysis of multi-hop wireless networks under unsaturated traffic condition considering the hidden and exposed terminal situation. In an effort to gain deep understanding of delay, this paper firstly proposes a new analytical model to predict accurate media access delay by obtaining its distribution function in a single wireless node. The interesting point of having the media access delay distribution is its generality that not only enables us to derive the average delay which has been reported in almost most of the previous studies as a special case but also facilitates obtaining higher moments of delay such as variance and skewness to capture the QoS parameters such as jitters in recently popular multimedia applications. Secondly, using the obtained single node media access delay distribution, we extend our modeling approach to investigate the delay in multi-hop networks. Moreover, probabilities of collisions in both hidden and exposed terminal conditions have been calculated. The validity of the model is demonstrated by comparing results predicted by the analytical model against those obtained through simulation experiments.