A robust learning based evolutionary approach for thermal-economic optimization of compact heat exchangers

This paper presents a robust, efficient and parameter-setting-free evolutionary approach for the optimal design of compact heat exchangers. A learning automata based particle swarm optimization (LAPSO) is developed for optimization task. Seven design parameters, including discreet and continuous ones, are considered as optimization variables. To make the constraint handling straightforward, a self-adaptive penalty function method is employed. The efficiency and the accuracy of the proposed method are demonstrated through two illustrative examples that include three objectives, namely minimum total annual cost, minimum weight and minimum number of entropy generation units. Numerical results indicate that the presented approach generates the optimum configuration with higher accuracy and a higher success rate when compared with genetic algorithms (GAs) and particle swarm optimization (PSO).     

Optimal design of plate-fin heat exchangers by a hybrid evolutionary algorithm

This study explores the first application of a Genetic Algorithm hybrid with Particle Swarm Optimization (GAHPSO) for design optimization of a plate-fin heat exchanger. A total number of seven design parameters are considered as the optimization variables and the constraints are handled by penalty function method. The effectiveness and accuracy of the proposed algorithm is demonstrated through an illustrative example. Comparing the results with the corresponding results using GA and PSO reveals that the GAHPSO can converge to optimum solution with higher accuracy.     

Improvement of palm oil through breeding and biotechnology

The oil palm Elaeis guineensis is the highest oil-yielding crop and has the potential to become the major supplier of both edible oil and renewable industrial feedstock. The oil yield from wild groves is presently less than 0.5 t/ha/y. However, through breeding and selection, the oil yield of commercial plantations could reach as much as 8 t/ha/y. New planting materials also have the capability of better oil yields with high iodine value (IV), slow height increment, and larger kernels. The oil also contains considerable amounts of carotenoids (500–700 ppm), vitamin E (600–1000 ppm), and sterols (250–620 ppm). The oil yield of another oil palm species, E. oleifera, is approximately 0.5 t/ha/y with high contents of carotenoids (700–1500 ppm), vitamin E (700–1500 ppm), and sterols (3500–4000 ppm). The above traits could be improved through breeding and biotechnology. Biotechnological efforts at the Palm Oil Institute of Malaysia are directed toward the production of oil with high IV and high monounsaturated fatty acids for edible purposes and industrial uses. Isolation and manipulation of the genes involved in the biosynthesis of fatty acids are the main focus. The aim is to increase the efficiency of conversion of palmitate (C_16:0) to oleate (C_18:1). Levels of palmitate and oleate are controlled by the enzymes acyl-acyl carrier protein (ACP) thioesterase and β-keto acyl ACP synthase II. The chain termination reactions of C_16:0 and C_18:1 are independent, thus paving the way for the possibility of reducing palmitate levels by switching off the palmitoyl ACP thioesterase gene. Paper presented at the 88th AOCS Annual Meeting & Expo. May 11–14, 1997, Seattle, Washington, USA.     

Physical,microstructure and leaching assessments for pavement road base containing mixed steel slag and cathode ray tube glass

Clean Technologies and Environmental Policy - Use of by-product materials, such as steel slag and cathode ray tube glass, as alternative recycled materials in the construction of roads, could...     

Refinements of Hadamard-type inequalities for quasi-convex functions with applications to trapezoidal formula and to special means

In this paper, some inequalities of Hadamard’s type for quasi-convex functions are given. Some error estimates for the Trapezoidal formula are obtained. Applications to some special means are considered.     

An imperialist competitive algorithm for optimal design of plate-fin heat exchangers

This paper presents the application of imperialist competitive algorithm (ICA) for optimization of a cross-flow plate fin heat exchanger. Minimization of total weight and total annual cost are considered as objectives. Seven design parameters, namely, heat exchanger length at hot and cold sides, fin height, fin frequency, fin thickness, fin-strip length and number of hot side layers are selected as optimization variables. A case study from literature is presented to show the effectiveness of the proposed algorithm. The numerical results reveal that ICA can find optimum configuration with higher accuracy in less computational time when compared to conventional genetic algorithm (GA).     

Self-learning active vibration control of a flexible plate structure with piezoelectric actuator

In this paper, an active vibration control (AVC) incorporating active piezoelectric actuator and self-learning control for a flexible plate structure is presented. The flexible plate system is first modelled and simulated via a finite difference (FD) method. Then, the validity of the obtained model is investigated by comparing the plate natural frequencies predicted by the model with the reported values obtained from literature. After validating the model, a proportional or P-type iterative learning (IL) algorithm combined with a feedback controller is applied to the plate dynamics via the FD simulation platform. The algorithms were then coded in MATLAB to evaluate the performance of the control system. An optimized value of the learning parameter and an appropriate stopping criterion for the IL algorithm were also proposed. Different types of disturbances were employed to excite the plate system at different excitation points and the controller ability to attenuate the vibration of observation point was investigated. The simulation results clearly demonstrate an effective vibration suppression capability that can be achieved using piezoelectric actuator with the incorporated self-learning feedback controller.     

Simulation of forced convection in a channel with nanofluid by the lattice Boltzmann method

This paper presents a numerical study of the thermal performance of fins mounted on the bottom wall of a horizontal channel and cooled with either pure water or an Al₂O₃-water nanofluid. The bottom wall of the channel is heated at a constant temperature and cooled by mixed convection of laminar flow at a relatively low temperature. The results of the numerical simulation indicate that the heat transfer rate of fins is significantly affected by the Reynolds number (Re) and the thermal conductivity of the fins. The influence of the solid volume fraction on the increase of heat transfer is more noticeable at higher values of the Re.