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.     

Application of several non-linear prediction tools for estimating uniaxial compressive strength of granitic rocks and comparison of their performances

Uniaxial compressive strength (UCS) of rock is crucial for any type of projects constructed in/on rock mass. The test that is conducted to measure the UCS of rock is expensive, time consuming and having sample restriction. For this reason, the UCS of rock may be estimated using simple rock tests such as point load index (I _s(50)), Schmidt hammer (R _n) and p-wave velocity (V _p) tests. To estimate the UCS of granitic rock as a function of relevant rock properties like R _n, p-wave and I _s(50), the rock cores were collected from the face of the Pahang–Selangor fresh water tunnel in Malaysia. Afterwards, 124 samples are prepared and tested in accordance with relevant standards and the dataset is obtained. Further an established dataset is used for estimating the UCS of rock via three-nonlinear prediction tools, namely non-linear multiple regression (NLMR), artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS). After conducting the mentioned models, considering several performance indices including coefficient of determination (R ²), variance account for and root mean squared error and also using simple ranking procedure, the models were examined and the best prediction model was selected. It is concluded that the R ² equal to 0.951 for testing dataset suggests the superiority of the ANFIS model, while these values are 0.651 and 0.886 for NLMR and ANN techniques, respectively. The results pointed out that the ANFIS model can be used for predicting UCS of rocks with higher capacity in comparison with others. However, the developed model may be useful at a preliminary stage of design; it should be used with caution and only for the specified rock types.     

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.     

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.     

Coating of stainless steel and titanium bipolar plates for anticorrosion in PEMFC: A review

Anticorrosion coating for stainless steel (SS) and titanium bipolar plates were evaluated to improve the corrosion resistance and electrical conductivity in PEMFC. The PEMFC offers clean and environmentally friendly usage in electrical power systems. The bipolar plates contribute 60%–80% of the total components of PEMFC stack with electrical conductivity >100 S cm^?1. Therefore, high conductivity and corrosion resistance are observed for long-term operations in PEMFC. Recent works has developed the cost-effective and feasible alternative materials to replace graphite bipolar plates. Metallic materials, such as SS and titanium, possess good electrical conductivity but poor corrosion resistance. Coating of SS and titanium bipolar plates can improve the corrosion resistance of metallic bipolar plates. Excellent performance of bipolar plates was recorded by using NbC coating for stainless steel materials. The ICR value using plasma surface alloying method was 8.47 mΩ cm² with a low current density (I_corr) between 0.051 and 0.058 μA cm^?2. The criteria for both current densities (<1 μA cm^?2) and electrical conductivity (<10 mΩ cm²) met the DOE's 2020 technical targets. In addition, conventional air brush method can be used for fabricating multilayer coatings onto substrates because it is self-cleaning, low cost and offers high volume and large area production. Vapor deposition method, a highly advanced coating technology using PVD, suitable for coating bipolar plates because it is environmentally friendly and can be used in high temperatures, producing materials with good impact strength and excellent abrasion resistance. PEMFC cost is still too high for large scale commercialization, which is the cost of raw material and processing to allow fabrication of thinner plates contributes substantially to the total PEMFC cost. Some future works on fuel cell anticorrosion research with reasonable coating method is suggested to reduce the cost in order to facilitate the move toward commercialization especially for SS and titanium bipolar plates.