ANFIS-based prediction of the compressive strength of geopolymers with seeded fly ash and rice husk–bark ash

In the present work, compressive strength of geopolymers made from seeded fly ash and rice husk–bark ash has been predicted by adaptive network-based fuzzy inference systems (ANFIS). Different specimens, made from a mixture of fly ash and rice husk–bark ash in fine and coarse forms and a mixture of water glass and NaOH mixture as alkali activator, were subjected to compressive strength tests at 7 and 28 days of curing. The curing regimes were different: one set of the specimens were cured in water at room temperature until 7 and 28 days and the other sets were oven-cured for 36 h at the range of 40–90°C and then cured at room temperature until 7 and 28 days. A model based on ANFIS for predicting the compressive strength of the specimens has been presented. To build the model, training and testing using experimental results from 120 specimens were conducted. The used data as the inputs of ANFIS models are arranged in a format of six parameters that cover the percentage of fine fly ash in the ashes mixture, the percentage of coarse fly ash in the ashes mixture, the percentage of fine rice husk–bark ash in the ashes mixture, the percentage of coarse rice husk–bark ash in the ashes mixture, the temperature of curing, and the time of water curing. According to these input parameters in the ANFIS models, the compressive strength of each specimen was predicted. The training and testing results in ANFIS models showed a strong potential for predicting the compressive strength of the geopolymeric specimens.     

Thermocapillary instability of an infinite Prandtl number fluid with negligible gravitational effects

Summary Finite amplitude fluid motion is investigated in a horizontal layer of an infinite Prandtl number fluid with an upper free surface for the case where thermocapillary effects are significant and gravitational effects are negligible. It is found that subcritical instability exists and that two-dimensional rolls and down-hexagons (where motion is downward at the cells' centers) are always unstable. But up-hexagons (where motion is upward at the cells' centers) are stable for sufficiently small amplitude , while both uphexagons and squares are stable in a range of larger where hysteresis effects exist.With 1 Figure     

Predicting the effects of nanoparticles on compressive strength of ash-based geopolymers by gene expression programming

In the present work, the effect of SiO₂ and Al₂O₃ nanoparticles on compressive strength of ash-based geopolymers with different mixtures of rice husk ash, fly ash, nanoalumina and nanosilica has been predicted by gene expression programming. The models were constructed by 12 input parameters, namely the water curing time, the rice husk ash content, the fly ash content, the water glass content, NaOH content, the water content, the aggregate content, SiO₂ nanoparticle content, Al₂O₃ nanoparticle content, oven curing temperature, oven curing time and test trial number. The value for the output layer was the compressive strength. According to the input parameters in gene expression programming models, the data were trained and tested, and the effects of SiO₂ and Al₂O₃ nanoparticles on compressive strength of the specimens were predicted with a tiny error. The results indicate that gene expression programming model is a powerful tool for predicting the effect of nanoparticles on compressive strength of the geopolymers in the considered range.     

Permeability prediction and construction of 3D geological model: application of neural networks and stochastic approaches in an Iranian gas reservoir

Determination of petrophysical parameters by using available data has a specific importance in exploration and production studies for oil and gas industries. Modeling of corrected permeability as a petrophysical parameter can help in decision making processes. The objective of this study is to construct a comprehensive and quantitative characterization of a carbonate gas reservoir in marine gas field. Artificial neural network is applied for prediction of permeability in accordance with other petrophysical parameters at well location. Correlation coefficient for this method is 84 %. In the study, the geological reservoir model is developed in two steps: First, the structure skeleton of the field is constructed, and then, reservoir property is distributed within it by applying new stochastic methods. Permeability is modeled by three techniques: kriging, sequential Gaussian simulation (SGS) and collocated co-simulation using modeled effective porosity as 3D secondary variable. This paper enhances the characterization of the reservoir by improving the modeling of permeability through a new algorithm called collocated co-simulation. Kriging is very simple in modeling the reservoir permeability, and also, original distribution of the data changes considerably in this model. In addition, the SGS model is noisy and heterogeneous, but it retains the original distribution of the data. However, the addition of a 3D secondary variable in third method resulted in a much more reliable model of permeability.     

Abrasion resistance of concrete containing SiO2 and Al2O3 nanoparticles in different curing media

In the present study, abrasion resistance and compressive strength of concrete specimens containing SiO₂ and Al₂O₃ nanoparticles which are cured in different curing media have been investigated. Portland cement was partially replaced by up to 2.0 wt.% SiO₂ and Al₂O₃ nanoparticles and mechanical properties of the produced specimens were measured. Increasing the nanoparticles content have found to increase the abrasion resistance of the specimens which were cured in water and saturated limewater, while this condition was not observed for compressive strength in both curing media. The enhancement of abrasion resistance was more for the specimens containing SiO₂ nanoparticles in both curing media. Since, abrasion resistance and compressive strength of the specimens follow a similar regime by increasing the nanoparticles content when they are cured in saturated limewater, some experimental relationships has been presented to correlate these two properties of concrete for this curing medium. On the whole, it has been concluded that the abrasion resistance of concrete does not only depend on the corresponding compressive strength.     

In Vitro Rescue of the Bile Acid Transport Function of ABCB11 Variants by CFTR Potentiators

ABCB11 is responsible for biliary bile acid secretion at the canalicular membrane of hepatocytes. Variations in the ABCB11 gene cause a spectrum of rare liver diseases. The most severe form is progressive familial intrahepatic cholestasis type 2 (PFIC2). Current medical treatments have limited efficacy. Here, we report the in vitro study of Abcb11 missense variants identified in PFIC2 patients and their functional rescue using cystic fibrosis transmembrane conductance regulator potentiators. Three ABCB11 disease-causing variations identified in PFIC2 patients (i.e., A257V, T463I and G562D) were reproduced in a plasmid encoding an Abcb11-green fluorescent protein. After transfection, the expression and localization of the variants were studied in HepG2 cells. Taurocholate transport activity and the effect of potentiators were studied in Madin–Darby canine kidney (MDCK) clones coexpressing Abcb11 and the sodium taurocholate cotransporting polypeptide (Ntcp/Slc10A1). As predicted using three-dimensional structure analysis, the three variants were expressed at the canalicular membrane but showed a defective function. Ivacaftor, GLP1837, SBC040 and SBC219 potentiators increased the bile acid transport of A257V and T463I and to a lesser extent, of G562D Abcb11 missense variants. In addition, a synergic effect was observed when ivacaftor was combined with SBC040 or SBC219. Such potentiators could represent new pharmacological approaches for improving the condition of patients with ABCB11 deficiency due to missense variations affecting the function of the transporter.     

Qualitative analysis of ganoderic acids in Ganoderma lucidum from Iran and China by RP-HPLC and electrospray ionisation-mass spectrometry (ESI-MS)

Ganoderma lucidum is used as a health food and medicine in Far East and produces different ganoderic acids which are well known for their valuable bioactivities. In this study, two different strains of G. lucidum from Iran and China were investigated for ganoderic acids, using reversed phase HPLC (RP-HPLC) in combination with UV and electrospray ionisation-mass spectrometry (ESI-MS). The results showed a relatively low intensity ganoderic acid C2 peak in the chromatogram of the Iranian sample. However, three high intensity peaks attributed to the well known ganoderic acids including ganoderic acids T, Me and H from the Chinese strain. These findings clearly indicated that different strains of G. lucidum could posses a range of active compounds and hence, bioactivities. Moreover, the variation in the triterpenoid components encourages more studies on the rest of bioactive molecules, and also different strains grown in a variety of climatic and geographical conditions.     

Reliability analysis and inspection updating by stochastic response surface of fatigue cracks in mixed mode

The analysis of engineering structures under fatigue crack growth aims at ensuring an appropriate reliability level over the entire operational lifetime. This paper deals with a new approach, namely the Stochastic Response Surface, to couple finite element analysis and reliability methods. The stochastic collocation method provides an explicit expression of the limit state function related to fatigue failure. This expression is used in first and second order reliability methods in order to compute the failure probability at a given structural age. When inspection is carried out, the structural reliability can be easily updated in terms of the observed crack length. Two numerical applications dealing with fatigue crack growth are presented to illustrate the proposed method, showing its performance in terms of numerical efficiency and accuracy.     

Wall Smoke Deposition from a Hot Smoke Layer

Smoke deposition from a hot smoke layer onto wall surfaces was studied in a hood apparatus using polymethylmethacrylate, polypropylene, and gasoline as fuels. Based upon prior analysis by Butler and Mulholland, the smoke deposition was expected to be dominated by thermophoresis. The deposited smoke samples were collected on glass filter paper attached to the hood wall and the mass per unit area of smoke deposited was measured gravimetrically. Measurements were made of quantities required for the prediction of thermophoretic smoke deposition. The smoke deposition measured in the experimental program was well predicted by the thermophoretic smoke deposition equation. The thermophoretic smoke deposition equation was found to be suitable for predicting smoke deposition onto wall surfaces exposed to fire environments.     

On nonlinear evolution of convective flow in an active mushy layer

We consider the nonlinear effect of convective flow in a horizontal mushy layer during solidification. The mushy layer that we consider has a permeable mush–liquid interface and is treated as an active porous medium with variable permeability. The nonlinear partial differential equations involved in this system are conservation equations for flow momentum, mass, temperature, and concentration. Numerical solutions to the resulting weakly nonlinear equations are obtained using a fourth-order Runge–Kutta integration scheme via a shooting technique. An evolution equation of Landau type is derived in terms of linear and first-order solutions by introducing an adjoint operator. The Landau constant is calculated for both cases: constant permeability and variable permeability. The analysis reveals that there is a slow transition of the flow to a steady state with smaller amplitude for an active mushy layer.