Optimisation of the fuelling of hydrogen vehicles using cascade systems and ejectors

The present study investigates the replacement of expansion valves, used in the cascade system of hydrogen fuelling stations, by a series of ejectors. The major advantage of using ejectors is to recover part of the kinetic energy lost during the expansion of a high-pressure primary flow, in order to entrain a lower pressure secondary flow; thus resulting in a more efficient fuelling.Firstly, a quasi-steady 1-D simulation model of the ejector was calibrated using computational fluid dynamics in terms of the main geometry and pressure conditions.Secondly, the quasi-steady 1-D model of the ejector was used in a dynamic model of the hydrogen fuelling station, in order to investigate the influence of its geometry on the transient fuelling performances. Different fuelling scenarios were explored with varying number of buffer tanks in the cascade system of the fuelling station, and different initial pressures in the vehicle's tank. The results show that the replacement of the expansion valve by an ejector may reduce the energy consumption for hydrogen compression by up to 6.5% using two buffer tanks in the cascade system. On the other hand, increasing the number of buffer tanks reduces the energy savings as the driving pressure ratio decreases.     

Airfoil optimisation for vertical‐axis wind turbines with variable pitch

To advance the design of a multimegawatt vertical‐axis wind turbine (VAWT), application‐specific airfoils need to be developed. In this research, airfoils are tailored for a VAWT with variable pitch. A genetic algorithm is used to optimise the airfoil shape considering a balance between the aerodynamic and structural performance of airfoils. At rotor scale, the aerodynamic objective aims to create the required optimal loading while minimising losses. The structural objective focusses on maximising the bending stiffness. Three airfoils from the Pareto front are selected and analysed using the actuator cylinder model and a prescribed‐wake vortex code. The optimal pitch schedule is determined, and the loadings and power performance are studied for different tip‐speed ratios and solidities. The comparison of the optimised airfoils with similar airfoils from the first generation shows a significant improvement in performance, and this proves the necessity to properly select the airfoil shape.     

Chaos embedded krill herd algorithm for optimal VAR dispatch problem of power system

Chaotic krill herd algorithm (KHA) (CKHA) is proposed in this paper to solve the optimal VAR dispatch problem of power system considering either minimization of real power loss or that of absolute value of total voltage deviation or improvements of voltage profile as an objective while satisfying all the equality and the inequality constraints of the power system network. Detailed studies of different chaotic maps are illustrated. Among these, Logistic map is considered in the proposed technique to improve the performance of the basic KHA. The performance of the proposed CKHA is implemented, successfully, on standard IEEE 14- and IEEE 118-bus test power systems in which the control of bus voltages, tap position of transformers and reactive power sources are involved. The results offered by the proposed CKHA are compared to other evolutionary optimization based techniques surfaced in the recent state-of-the-art literature. Simulation results indicate that the proposed CKHA approach yields better optimization efficacy over some other recent popular techniques in terms of results offered, effectiveness, quality of solution and convergence speed.     

Reducing CO2 emission from exhaust gases using molten carbonate fuel cells: a new approach

The aim of this study is to couple molten carbonate fuel cell (MCFC) stack with integrated gasification combined cycle fed by refinery residues, to remove CO₂ from gas turbine exhaust gases that have CO₂ emission rate of 14,200 ton/year. By applying multi-objective optimisation (MOO) using genetic algorithm, the optimal values of operating load and the corresponding values of objective functions are obtained. The MOO of the MCFC system regarding two scenarios is performed. The first scenario is minimisation of cost of electricity (COE) and CO₂ emission rate. Objective functions of the second scenario are the same as in the first scenario while CO₂ tax is taken into account. Results show that the second scenario has 29.5% lower average optimal COE and 2.5% lower average emission rate in comparison with the first scenario. A sensitivity analysis is also performed to study the effect of fuel price and CO₂ tax variations on optimal solutions.     

Process optimisation and physicochemical characterisation of enzymatic hydrolysates of proteins from co‐products of Atlantic Salmon (Salmo salar) and Yellowtail Kingfish (Seriola lalandi)

The aim of this study was to develop an enzymatic hydrolysis process of protein co‐products for two major commercial fish species in Australia: Atlantic salmon (AS) and Yellowtail kingfish (YTK). The outcomes are to produce high protein recovery of fish protein hydrolysates within controlled molecular weight ranges that display enhanced physicochemical properties of oil binding and emulsification. Three enzymes (Flavourzyme, Neutrase and Alcalase) were applied to processing co‐products. Protein recovery and physicochemical properties were evaluated with increasing hydrolysis time from 30 min to 180 min and ratio of enzyme to substrate (E/S) from 0.5% to 3.0%. In order to achieve a product with optimum emulsifying capacity (50 ± 0.6 m² g^?1), an E/S ratio of 0.6–1.3% Flavourzyme was applied for 30–111 min with a protein recovery of 55%; in order to achieve a product with optimum oil‐binding capacity (8.3 ± 0.3 g oil g hydrolysates^?1), an E/S ratio of 2.3–3.0% Flavourzyme was applied for 25–64 min with a protein recovery of 70%. YTK protein hydrolysates were further membrane‐fractionated into five fractions (>100 kDa, 50–100 kDa, 30–50 kDa, 10–30 kDa and <10 kDa), and of these, the 10–30 kDa exhibited the best properties of oil binding (19 ± 0.3 g oil g hydrolysates^?1) and emulsification (57 ± 0.7 m² g^?1). These results demonstrate the importance of enzymatic hydrolysis of seafood co‐products into high‐value ingredients for food products and processing.     

A comparative study on optimised and non‐optimised axial flow,spherical reactors in naphtha reforming process

In this study, the operating conditions of an axial flow spherical reactor have been optimised using a reliable optimisation technique and the results are compared with the results of non‐optimised conditions. The dynamic behaviour of the reactor has been considered in the optimisation process and orthogonal collocation method has been used in order to solve the obtained equations from mathematical modelling of the process. The goal of this study is to maximise the aromatics and hydrogen production rate. Therefore, the objective function is the combination of two terms which include the production rate of the mentioned components. The catalyst distribution for each reactor, the inlet pressure of the system, Length per radius for each reactor, the naphtha feed molar flow rate and the hydrogen mole fraction in the recycle stream as well as the inlet temperature of each reactor have been optimised in this study. © 2011 Canadian Society for Chemical Engineering     

Robust eigenstructure clustering by non-smooth optimisation

We extend classical eigenstructure assignment to more realistic problems, where additional performance and robustness specifications arise. Our aim is to combine time-domain constraints, as reflected by pole location and eigenvector structure, with frequency-domain objectives such as the H₂, H_∞ or Hankel norms. Using pole clustering, we allow poles to move in polydisks of prescribed size around their nominal values, driven by optimisation. Eigenelements, that is poles and eigenvectors, are allowed to move simultaneously and serve as decision variables in a specialised non-smooth optimisation technique. Two aerospace applications illustrate the power of the new method.     

Scheduling of open-pit phosphate mine extraction

Open-pit deposits are often characterised by a stack of layers of different geological nature. Some layers are worthless while the ore of the others is of a varying economic value depending on grade. To reach a layer, it is necessary to have first removed the upper layers above the extraction zone. This action results in uncovering the layer in this particular place and in facilitating access to the layers below. This extraction process involves a series of 2–7 basic operations; each one is performed by a machine, some of which are able to perform up to three different operations. Ensuring the consistency of mining extraction scheduling over a few months, in order to meet known or forecast demand, is a challenging task. A mining extraction model based on mathematical programming is proposed but it is hardly usable, due to its size. Therefore, a model based on a Discrete Event Simulation, is created to test how ore supplies are affected by the tactical and operational decisions relating to the choice of parcels to be processed and to the allocation of machines to the different basic operations.     

Thermal buckling optimisation of composite plates using firefly algorithm

Abstract

Composite plates play a very important role in engineering applications, especially in aerospace industry. Thermal buckling of such components is of great importance and must be known to achieve an appropriate design. This paper deals with stacking sequence optimisation of laminated composite plates for maximising the critical buckling temperature using a powerful meta-heuristic algorithm called firefly algorithm (FA) which is based on the flashing behaviour of fireflies. The main objective of present work was to show the ability of FA in optimisation of composite structures. The performance of FA is compared with the results reported in the previous published works using other algorithms which shows the efficiency of FA in stacking sequence optimisation of laminated composite structures.     

Optimisation of maintenance strategy for rural road network using genetic algorithm

The objective of this paper is to develop an optimised maintenance strategy for the rural road network of Kerala state. This is accomplished with the development of a bi-objective deterministic optimisation model which simultaneously satisfies the objectives of both minimisation of total maintenance cost and maximisation of performance of the road network. The model is capable of planning the maintenance activities over a multi-year planning period. The performance of the road network is accounted using the composite index, namely Pavement Condition Index. The constraint-based genetic algorithm was used as the optimisation tool since it very well takes care of the combinatorial nature of the network-level pavement maintenance programming. The applicability of the model is illustrated using a case study for the rural road network of Kerala state in India. The effort made through this research work to develop a suitable Pavement Maintenance and Management System for rural road network can lead to the proper maintenance and upkeep of the rural roads, thereby triggering a positive impact on the Indian economy.