Modelling of discontinuities through dipole distribution

An indirect boundary element method using dipole distribution is employed in order to model discontinuities inside the flow region. The problem of flow under a dam is treated with a sheet-pile in its foundation. The discontinuity across the sheet-pile is demonstrated, a general boundary element procedure for a mixed problem is outlined and the coefficients of the linear system are given in analytical form. Very good agreement with existing analytical results is obtained.     

Solubilities of cinnamic acid esters in binary mixtures of ionic liquids and organic solvents

The solubilities of three cinnamic acid esters, namely, methyl ferulate, methyl p-coumarate, and methyl sinapate, have been measured in mixed solvent systems of tert-butanol with 1-butyl-3-methyl-imidazolium hexafluorophosphate ([BMIM][PF₆]), 1-butyl-3-methyl-imidazolium tetrafluoroborate ([BMIM][BF₄]) and 1-methyl-3-octyl-imidazolium tetrafluoroborate ([OMIM][BF₄]) at 303.15 and 321.15 K, and in mixed solvent systems of ethyl acetate with [BMIM][BF₄] and [OMIM][BF₄] at 303.15 K. In eight cases, out of the 22 data sets, an additive behaviour of the solubility was observed, positive deviations from additivity were observed in six cases, a positive synergistic effect in five cases, and, finally, negative deviations from additivity in the remaining three cases. Prediction of the solubilities of the solutes in the various ternary systems was performed with the NRTL and UNIQUAC activity coefficient models. The binary interaction parameters of the models between solute and solvent molecules were taken from the literature. When the parameters between the solvent molecules are fitted to literature data, satisfactory predictions are not always obtained. On the other hand, very good predictions are obtained when only one of the two interaction parameters between the two solvent molecules is fitted to one single point of the solubility isotherm and the other interaction parameter is set equal to zero.     

Genetic algorithms and cellular automata in aquifer management

A groundwater management problem is presented involving pumping cost minimization with both well discharges and well locations as decision variables. A grid of candidate well locations is set up and optimal arrangements of wells are sought within this discrete space. A genetic algorithm approach is presented with the following particular features: (a) A suitable scaling is applied to the objective function in order to alleviate its regionally flat behavior. (b) No penalty functions are involved in constraint handling. Instead, the feasible region is transformed into a rectangular domain. The transformation introduced is proved to be bijective. (c) A binary representation of well configurations is presented and compared to a combinatorial one. The binary representation necessitates the introduction of specially designed genetic operators. Besides purely genetic algorithms, the concept of cellular automaton is introduced as the basis of an alternative formulation of the optimization problem. The lattice of the cellular automaton provides the discrete set of candidate well positions. The well configuration is represented by a group of agents occupying an equal number of lattice sites. The agents change positions as dictated by the structure of the automaton and, also, by an associated genetic algorithm, which directs the evolution of the whole scheme toward an optimal configuration. An improved performance of this approach is noted and discussed in comparison to the purely genetic algorithm schemes of the present work. A simulated annealing approach is also applied to the same problem for comparison purposes. Finally, a new and more efficient hybrid annealing–genetic approach is introduced and discussed.     

Combined land-use and water allocation planning

A general framework for a combined land use and water management is described. An optimization problem is formulated that combines combinatorial and spatial characteristics. The aim of the planning is to maximize economic benefit, while minimizing water extraction and transportation cost under ecological constraints. A genetic algorithm is employed endowed with a new neighborhood operator. This operator acts on a local level, but it produces global results. Although the computational scheme does not include compactness as a separate objective, compact patterns are produced as emergent results. The algorithm is tested on a fictive area represented as a grid with 15×15 land blocks and, also, on a real-world case study.     

Influence of thermal degradation in the physicochemical properties of fish oil

Physicochemical and thermal analyses were undertaken to evaluate the influence of the temperature on the oxidation of sea fish oil once its polyunsaturated fatty acids deteriorate rapidly. Fish oil displayed four decomposition steps in synthetic air atmosphere and only one step in nitrogen atmosphere. The first step started at 189 and 222 °C for oxidizing and inert atmospheres, respectively. An OIT value of 53 min was measured at 100 °C. After the degradation process the peroxide index and the iodine index reduced from 35.38 to 9.85 meq × 1000 g^?1 and from 139.79 to 120.19 gI₂ × 100 g^?1, respectively. An increase of the free fatty acids amount from 0.07 to 0.17% was observed while viscosity increased from 57.2 to 58.0 cP. Absorption at 272 nm also increased. The thermogravimetric and spectroscopic techniques are reproducible and versatile being an option for characterization of edible oil oxidation.     

Vapor liquid equilibrium modeling of alkane systems with Equations of State: “Simplicity versus complexity”

Two types of Equations of State (EoS), which are characterized here as “simple” and “complex” EoS, are evaluated in this study. The “simple” type involves two versions of the Peng–Robinson (PR) EoS: the traditional one that utilizes the experimental critical properties and the acentric factor and the other, referred to as PR-fitted (PR-f), where these parameters are determined by fitting pure compound vapor pressure and saturated liquid volume data. As “complex” EoS in this study are characterized the EoS derived from statistical mechanics considerations and involve the Sanchez–Lacombe (SL) EoS and two versions of the Statistical Associating Fluid Theory (SAFT) EoS, the original and the Perturbed-Chain SAFT (PC-SAFT).

The evaluation of these two types of EoS is carried out with respect to their performance in the prediction and correlation of vapor liquid equilibria in binary and multicomponent mixtures of methane or ethane with alkanes of various degree of asymmetry. It is concluded that for this kind of systems complexity offers no significant advantages over simplicity. Furthermore, the results obtained with the PR-f EoS, especially those for multicomponent systems that are encountered in practice, even with the use of zero binary interaction parameters, indicate that this EoS may become a powerful tool for reservoir fluid phase equilibria modeling.     

A LES-CMC formulation for premixed flames including differential diffusion

A finite volume large eddy simulation–conditional moment closure (LES-CMC) numerical framework for premixed combustion developed in a previous studyhas been extended to account for differential diffusion. The non-unity Lewis number CMC transport equation has an additional convective term in sample space proportional to the conditional diffusion of the progress variable, that in turn accounts for diffusion normal to the flame front and curvature-induced effects. Planar laminar simulations are first performed using a spatially homogeneous non-unity Lewis number CMC formulation and validated against physical-space fully resolved reference solutions. The same CMC formulation is subsequently used to numerically investigate the effects of curvature for laminar flames having different effective Lewis numbers: a lean methane–air flame with Le_eff = 0.99 and a lean hydrogen–air flame with Le_eff = 0.33. Results suggest that curvature does not affect the conditional heat release if the effective Lewis number tends to unity, so that curvature-induced transport may be neglected. Finally, the effect of turbulence on the flame structure is qualitatively analysed using LES-CMC simulations with and without differential diffusion for a turbulent premixed bluff body methane–air flame exhibiting local extinction behaviour. Overall, both the unity and the non-unity computations predict the characteristic M-shaped flame observed experimentally, although some minor differences are identified. The findings suggest that for the high Karlovitz number (from 1 to 10) flame considered, turbulent mixing within the flame weakens the differential transport contribution by reducing the conditional scalar dissipation rate and accordingly the conditional diffusion of the progress variable.     

A new multi-objective self-organizing optimization algorithm (MOSOA) for spatial optimization problems

Spatial planning is an important and complex activity. It includes land use planning and resource allocation as basic components. An abundance of papers can be found in the literature related to each one of these two aspects separately. On the contrary, a much smaller number of research reports deal with both aspects simultaneously. This paper presents an innovative evolutionary algorithm for treating combined land use planning and resource allocation problems. The new algorithm performs optimization on a cellular automaton domain, applying suitable transition rules on the individual neighbourhoods. The optimization process is multi-objective, based on non-domination criteria and self-organizing. It produces a Pareto front thus offering an advantage to the decision maker, in comparison to methods based on weighted-sum objective functions. Moreover, the present multi-objective self-organizing algorithm (MOSOA) can handle both local and global spatial constraints. A combined land use and water allocation problem is treated, in order to illustrate the cellular automaton optimization approach. Water is allocated after pumping from an aquifer, thus contributing a nonlinearity to the objective function. The problem is bi-objective aiming at (a) the minimization of soil and groundwater pollution and (b) the maximization of economic profit. An ecological and a socioeconomic constraint are imposed: (a) Groundwater levels at selected places are kept above prescribed thresholds. (b) Land use quota is predefined. MOSOA is compared to a standard multi-objective genetic algorithm and is shown to yield better results both with respect to the Pareto front and to the degree of compactness. The latter is a highly desirable feature of a land use pattern. In the land use literature, compactness is part of the objective function or of the constraints. In contrast, the present approach renders compactness as an emergent result.