Kinetic Model for Invertase‐Induced Sucrose Hydrolysis: Initial Time Lag

The kinetics of sucrose hydrolysis by invertase was studied in order to find a comprehensive model for the reaction pathway and mechanism. First, three common models of Michaelis‐Menten (MM), substrate inhibition (S²), and substrate clusters' inhibition (S³(I)) were investigated. The third model was found to better predict the initial sucrose concentration. Then, the S³(I) model was modified to cover the remaining pathway (S³(II)). Finally, a new comprehensive model (S³(III)) was evaluated, which in addition to what is considered in the two previously mentioned models (S³(I) and S³(II)) also involved the initial time lag. The model predictions showed an excellent agreement with the experimental data. The mean absolute error for the MM model is significantly reduced for the S³(III) model.     

Mesoscale finite element prediction of concrete failure

The present paper studies the failure of concrete from the mesoscopic point of view. Biphasic cubic concrete samples containing spherical aggregates embedded in a homogenized mortar have been simulated using standard finite element method. Linear elasticity and damage-plasticity hypotheses are considered for the aggregates and mortar, respectively. Various triaxial loading conditions are assumed for each sample to generate adequate discrete failure points within the stress space. In the next step, the approximated failure surfaces of specimens are constructed using the Delaunay triangulation technique. The effects of mesostructural features such as aggregate grading curve, aggregate volumetric share, and more importantly the controlling parameters of mortar’s damage-plasticity constitutive model have been investigated. Finally, the failure modes of some selected samples have been reported and discussed.     

A FUZZY LOGIC APPROACH TO ESTIMATING HYDRAULIC FLOW UNITS FROM WELL LOG DATA: A CASE STUDY FROM THE AHWAZ OILFIELD, SOUTH IRAN

Porosity-permeability relationships in the framework of hydraulic flow units can be used to characterize heterogeneous reservoir rocks. Porosity is a volumetric parameter whereas permeability is a measure of a rock's flow properties and depends on pore distribution and connectivity. Thus zonation of a reservoir using flow zone indicators and the identification of flow units can be used to evaluate reservoir quality based on porosity-permeability relationships.
In the present study, we attempt to make a quantitative correlation between flow units and well log responses using fuzzy logic in the mixed carbonate-clastic Asmari Formation at the Ahwaz oilfield, South Iran. A hybrid neuro-fuzzy approach was used to verify the results of fuzzy modelling. For this purpose, well log and core data from three wells at Ahwaz were used to make an intelligent formulation between core-derived flow units and well log responses. Data from a separate well was used for evaluation and validation of the results.
The results of this study demonstrate that there is a good agreement between core-derived and fuzzy-logic derived flow units. Fuzzy logic was successful in modelling flow units from well logs at well locations for which no core data was available.     

Performance assessment of decision-making units using an adaptive neural network algorithm: one period case

This study proposes a nonparametric method based on adaptive neural network (ANN) technique for measuring efficiency of decision making units (DMUs) in one period case as a complementary tool for the ANN-based efficiency methods in the previous studies. In previous studies, there are needed to have large volume of data, and so the proposed method in this study is more applicable because it can be used for the cases which have no historical data. In fact, a limitative weakness of the ANN-based efficiency methods about applying them for these cases is removed. So, it can be a competitive method to the other common tools for measuring efficiency. By noting the importance of flexible manufacturing system, this study presents a decision-making model for optimization of operators’ allocation in cellular manufacturing system by computer simulation. The methodology is illustrated through its application on a previously reported dataset. It was found out that ANN provides more robust results and identifies more efficient units than the conventional methods since better performance patterns are explored.     

Predictions of micelle-water partition coefficients and retention in micellar electrokinetic chromatography from solute structure. 2. Fragmental constant approach

The fragmental constant approach (FCA) was used to calculate water-sodium dodecyl sulfate (SDS) micelle partition coefficients, K(mw), for uncharged solutes from their structure. Subsequently, the availability of K(mw) values allows prediction of retention factor, k, in micellar electrokinetic chromatography (MEKC) using the simple relationship k = K(mw)phi, where phi is the phase ratio. The FCA model describes a micelle-water partition coefficient as the sum of the partition coefficients of the constituent atomic/molecular fragments, measured by fragmental constant values, f (i), as well as correction factors to account for various "intramolecular effects" that cause deviations from the predicted partition coefficients as, log K(mw) = sum(n)(i=1)aif i+sum(m)(i=1)kiCm. The fragmental constants for a set of 41 fragments were determined using a training set of 229 aromatic solutes and 198 aliphatic compounds. The K(mw) of the aromatic compounds in the training set were determined by MEKC, while the K(mw) of the aliphatic solutes were estimated using the linear solvation energy relationship (LSER) for the SDS micelles. The fragments consisted of both aromatic fragments (i.e., directly attached to an aromatic ring) and aliphatic fragments. The FCA predictions agree nicely with the observed and LSER partition coefficient values, even for complex molecular structures such as beta-blocker drugs. The results show the great potential of the FCA for a priori prediction of retention behavior in MEKC from solute structure.     

The effect of emulsifiers,sugar, shortening and soya flour on the staling of barbari flat bread

A standard method has been developed to bake barbari flat-type bread. Instron was used to measure the hardness of the crumb of bread samples as a criterion of staling. Different combinations of emulsifiers, sugar, shortening and soya flour were added to the formula of barbari bread to find their effect on the retardation of hardness. Addition of soya flour increased the loaf weight but decreased its total organoleptic score. Added amounts of different additives tried in this experiment improved the hardness approximately to the same level. The best result was obtained by the addition of sodium stearoyl-2-lactylate and shortening.