Strength evaluation of granite block samples with different predictive models

Over the last decade, application of soft computing techniques has rapidly grown up in different scientific fields, especially in rock mechanics. One of these cases relates to indirect assessment of uniaxial compressive strength (UCS) of rock samples with different artificial intelligent-based methods. In fact, the main advantage of such systems is to readily remove some difficulties arising in direct assessment of UCS, such as time-consuming and costly UCS test procedure. This study puts an effort to propose four accurate and practical predictive models of UCS using artificial neural network (ANN), hybrid ANN with imperialism competitive algorithm (ICA–ANN), hybrid ANN with artificial bee colony (ABC–ANN) and genetic programming (GP) approaches. To reach the aim of the current study, an experimental database containing a total of 71 data sets was set up by performing a number of laboratory tests on the rock samples collected from a tunnel site in Malaysia. To construct the desired predictive models of UCS based on training and test patterns, a combination of several rock characteristics with the most influence on UCS has been used as input parameters, i.e. porosity (n), Schmidt hammer rebound number (R), p-wave velocity (V_p) and point load strength index (Is(50)). To evaluate and compare the prediction precision of the developed models, a series of statistical indices, such as root mean squared error (RMSE), determination coefficient (R²) and variance account for (VAF) are utilized. Based on the simulation results and the measured indices, it was observed that the proposed GP model with the training and test RMSE values 0.0726 and 0.0691, respectively, gives better performance as compared to the other proposed models with values of (0.0740 and 0.0885), (0.0785 and 0.0742), and (0.0746 and 0.0771) for ANN, ICA–ANN and ABC–ANN, respectively. Moreover, a parametric analysis is accomplished on the proposed GP model to further verify its generalization capability. Hence, this GP-based model can be considered as a new applicable equation to accurately estimate the uniaxial compressive strength of granite block samples.

     

Improved ionic conductivity of nitrile rubber/ionic liquid composites

Polymer electrolytes with high ionic conductivity and good elasticity were prepared by mixing nitrile rubber (poly(acrylonitrile-co-butadiene) rubber; NBR) with ionic liquid, N-ethylimidazolium bis(trifluoromethanesulfonyl)imide (EImTFSI). The NBR/EImTFSI composites were obtained as homogeneous and transparent films when the ionic liquid content was less than 60 wt%. Raman spectroscopy suggested the interaction between nitrile group of NBR and TFSI anion. Sample with ionic liquid content of 50 wt% showed the ionic conductivity of 1.2×10⁻⁵ S cm⁻¹ at 30 °C. Addition of lithium salt to this NBR/EImTFSI composite further enhanced the ionic conductivity to about 10⁻⁴ S cm⁻¹ without spoiling mechanical properties. DSC studies showed two glass transition temperatures for composites indicating microphase separation.     

Increasing selective pressure towards the best compromise in evolutionary multiobjective optimization: The extended NOSGA method

Most current approaches in the evolutionary multiobjective optimization literature concentrate on adapting an evolutionary algorithm to generate an approximation of the Pareto frontier. However, finding this set does not solve the problem. The decision-maker still has to choose the best compromise solution out of that set. Here, we introduce a new characterization of the best compromise solution of a multiobjective optimization problem. By using a relational system of preferences based on a multicriteria decision aid way of thinking, and an outranked-based dominance generalization, we derive some necessary and sufficient conditions which describe satisfactory approximations to the best compromise. Such conditions define a lexicographic minimum of a bi-objective optimization problem, which is a map of the original one. The NOSGA-II method is a NSGA-II inspired efficient way of solving the resulting mapped problem.     

Influence of nitrogen doping on carbon nanotubes towards the structure,composition and oxygen reduction reaction

Nitrogen-doped carbon nanotubes (NCNTs) as noble-metal free catalysts were synthesised via chemical vapour deposition using iron (II) phthalocyanine as a metal catalyst for growth of the nanotubes. The synthesis process was performed in one step in a tube furnace using different chemical precursors (aniline, diethylamine and ethylenediamine) as nitrogen sources. The NCNT samples were physically characterised using scanning electron microscopy, transmission electronic microscopy and X-ray photoelectron spectroscopy. Cyclic voltammetry measurements were conducted to investigate the oxygen reduction reaction (ORR), and they showed that the electrocatalytic activities depend on the structural and morphological changes in the NCNTs. The results showed that NCNTs synthesised from ethylenediamine precursors exhibit an ORR scheme proceed via indirect four electron transfer process in acidic media, which implies that these NCNTs are a candidate for serving as the cathodic catalyst in PEMFCs. The highly active NCNTs possess unique characteristics, including a high concentration of surface defects with high pyridinic-N and pyridinic-N-oxides configurations that serve as active sites for ORR activity in acidic media.     

Acerola and cashew apple as sources of antioxidants and dietary fibre

Several tropical fruits have been described as natural sources of dietary fibre (DF) and phenolic compounds, associated with different health effects. The aim of this work was to ascertain the DF, phenolic compounds content (including non‐extractable polyphenols, mostly associated with DF) and antioxidant capacity in acerola fruits and cashew apples from selected clones. ‘BRS 236’ acerola fruits presented a high antioxidant capacity because of the combination of both extractable polyphenols and l ‐ascorbic acid (providing together a Folin value of 170 kg^?1 g d.m.). ‘CCP 76’ cashew apples contained 28 g kg^?1 d.m. of extractable polyphenols and 13 g kg^?1 d.m. of ascorbic acid as well as a high amount of non‐extractable condensed tannins (52 g kg^?1 d.m.). DF content was of 260 g kg^?1 d.m. in acerola fruit and of 209 g kg^?1 d.m. in cashew apple. Acerola fruits and cashew apple should therefore be considered as new natural sources of DF and phenolic compounds.     

Cytochemical characterization and structural approach to Prosopis juliflora (Sw) D.C. seed gum extraction

Mesquite seed is a good gum source. In this work seed structure was characterized in order to help seed gum extraction. Seed gum was located between cotyledon and seed coat. Milling process yielded, basically, two fractions: endosperm and seed coat plus gum. This fact was supported by the cytochemical observation of a dense layer near the seed coat and a loose layer near the endosperm. Cells containing seed gum had thick cell walls and a proteic core. Seed gum extraction implications are discussed. Copyright © 2005 Society of Chemical Industry     

Addition of cashew tree gum to maltodextrin-based carriers for spray drying of cashew apple juice

This study involved an attempt to totally or partially replace maltodextrin DE10 (MD10) by cashew tree gum (CTG) as a drying aid agent in spray drying of cashew apple juice. The objective was to evaluate the impact of drying aid/cashew apple juice dry weight ratio (D/C, ranging from 3 to 5) and degree of replacement of MD10 with CTG (CTG_R, ranging from 0% to 100%) on ascorbic acid retention (AAR), hygroscopicity, flowability and water solubility of spray dried cashew apple juice powder. AAR was increased from 72.90% to 95.46% by increasing D/C from 3 to 5. CTG was shown as a promising maltodextrin replacer, being more effective than the latter to decrease powder hygroscopicity. The most adequate drying conditions (D/C = 5, CTG_R≥50%) resulted in more than 90% of AAR, and produced a powder with good flowing properties and water solubility.     

Synthesis of polymer/MWCNT nanocomposite catalyst supporting materials for high-temperature PEM fuel cells

In this study, the polymer/MWCNT nanocomposites were synthesized from the pristine MWCNT and polymer binders using functionalization with solution processing methods. The synthesized polymer/MWCNT nanocomposites exhibited high specific surface areas than the pristine MWCNT. The MWCNT/Nafion nanocomposite attributed to the maximum peak current at 5.795 × 10^?5 (A) while the peak current of MWCNT/PBI was obtained at 3.662 × 10^?5 (A). Moreover, polymer/MWCNT based electrocatalysts performed better electrochemical activity because of polymers binders can assist electrochemical interaction using the high surface areas of the catalyst supporting material. Also, the MEAs fabricated using the hot pressing method, while the acid doped PBI membrane sandwiched between the electrodes. The fabricated MEAs were successfully demonstrated in a single cell and found capable of measuring a maximum power density of 112.10 mW/cm² under 150 °C temperature. In conclusion, the synthesized catalyst-supporting materials enhanced the electrochemical activity and catalyst stability which fulfilling the main objective of this study.