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.

     

On the application of Harris hawks optimization (HHO) algorithm to the design of microchannel heat sinks

Engineering with Computers - A novel Harris hawks optimization algorithm is applied to microchannel heat sinks for the minimization of entropy generation. In the formulation of the heat transfer...     

Microstructure and Sliding Wear Behaviour of Ni(Cr)-TiB_2 Coatings Deposited by HVOF Spraying of SHS Powders

THERMAL SPRAYING provides a large range ofcoatings,which increase the wear resistance ofsubstrates[1].One of the major coating families is thecermet,composed of hard ceramic particles with ametallic binder.The most commonly used cermetcoatings in industrial applications are based on eitherthe WC-Co or the Cr3C2-Ni(Cr)systems with WC-17wt%Co and Cr3C2-25wt%Ni(Cr)being typicalcompositions[2,3].Although WC-Co deposits are hardand wear resistant at ambient temperatures their rangeof ap…     

Towards improved parallelism through order reduction of accessing data in nD matrices

This paper encompasses the presentation of an enhanced approach with the capacity to reduce the time complexity of accessing nodes in m-dimensional matrices from \(O(n^m)\) to \(O(n\log n)\) . The accomplishment of this process is attained by the serialization of nD (nD) matrices to single-dimensional arrays followed by the access of nodes accordingly. Linear representation of nD matrix data structure induces a superior parallelism of matrix calculations over dense, parallel core micro-architecture computers, including NVIDIA GPGPU Supercomputing and Intel Xeon Phi processing boards. This approach is feasibly implemented as the core of matrix data representation in Math software such as Matlab, Mathematica and Maple, in IDEs for more optimized code generation and in Parallel Computing Libraries such as CUBLAS and Magma.     

A robust optimization approach for pollution routing problem with pickup and delivery under uncertainty

Organizations have recently become interested in applying new approaches to reduce fuel consumptions, aiming at decreasing green house gases emission due to their harmful effects on environment and human health; however, the large difference between practical and theoretical experiments grows the concern about significant changes in the transportation environment, including fuel consumptions, carbon dioxide (CO₂) emissions cost and vehicles velocity, that it encourages researchers to design a near-reality and robust pollution routing problem. This paper addresses a new time window pickup-delivery pollution routing problem (TWPDPRP) to deal with uncertain input data for the first time in the literature. For this purpose, a new mixed integer linear programming (MILP) approach is presented under uncertainty by taking green house emissions into consideration. The objective of the model is to minimize not only the travel distance and number of available vehicles along with the capacity and aggregated route duration restrictions but also the amount of fuel consumptions and green house emissions along with their total costs. Moreover, a robust counterpart of the MILP is introduced by applying the recent robust optimization theory. Computational results for several test problems indicate the capability and suitability of the presented MILP model in saving costs and reducing green house gases concurrently for the TWPDPRP problem. Finally, both deterministic and robust mathematical programming are compared and contrasted by a number of nominal and realizations under these test problems to judge the robustness of the solution achieved by the presented robust optimization model.     

Effect of stepped‐impedance resonators on rectangular metamaterial unit cells

In this article, effect of the stepped‐impedance resonator (SIR) miniaturization technique on rectangular metamaterial unit cells is investigated and the influence of the method's structural parameters on the characteristic impedance and the distance between higher resonance modes is discussed. According to the results, the ideal unit cell for this method should be thick enough and have an impedance ratio greater than one. Furthermore, the SIR technique is applied on a conventional two‐turn spiral metamaterial unit cell and a new compact spiral unit cell is introduced. The effect of this method on the unit cell parameters is investigated and the new unit cell is compared to the conventional spiral. According to the results, a miniaturization factor of 0.75 can be achieved with the new unit cell. To validate the results, a two dimensional array of the unit cell is fabricated and its S‐parameters are measured using the free space method. © 2015 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:582–590, 2015.     

Soft computing based on new interval-valued fuzzy modified multi-criteria decision-making method

In this paper, a new interval-valued fuzzy modified TOPSIS (IVFM-TOPSIS) method is proposed that can reflect both subjective judgment and objective information in real life situations. This proposed method is based on concepts of the positive ideal and negative ideal solutions for solving multi-criteria decision-making (MCDM) problems in a fuzzy environment. The performance rating values and weights of criteria are linguistic variables expressed as triangular interval-valued fuzzy numbers. Furthermore, we appraise the performance of alternatives against both subjective and objective criteria with multi-judges for decision-making problems. Finally, for the purpose of proving the validity of the proposed method a numerical example is presented for a robot selection problem.     

The solution and duality of imprecise network problems

Duality properties have been investigated by many researchers in the recent literature. They are introduced in this paper for a fully fuzzified version of the minimal cost flow problem, which is a basic model in network flow theory. This model illustrates the least cost of the shipment of a commodity through a capacitated network in terms of the imprecisely known available supplies at certain nodes which should be transmitted to fulfil uncertain demands at other nodes. First, we review on the most valuable results on fuzzy duality concepts to facilitate the discussion of this paper. By applying Hukuhara’s difference, approximated and exact multiplication and Wu’s scalar production, we exhibit the flow in network models. Then, we use combinatorial algorithms on a reduced problem which is derived from fully fuzzified MCFP to acquire fuzzy optimal flows. To give duality theorems, we utilize a total order on fuzzy numbers due to the level of risk and realize optimality conditions for providing some efficient combinatorial algorithms. Finally, we compare our results with the previous worthwhile works to demonstrate the efficiency and power of our scheme and the reasonability of our solutions in actual decision-making problems.     

Investigation of deep drawing concept of multi-point forming process in terms of prevalent defects

Multi-point forming is a novel flexible process that is economically suitable for both rapid prototyping and batch production of sheet metal parts. This technique is established based on altering rigid dies by matrices of adjustable punch elements. In this paper, the basic principle of this technique is implemented on deep drawing process. A reconfigurable die was constructed to investigate the multi-point deep drawing process. AA 2024-O Aluminum alloy was designated as test material. The formed specimens were evaluated in terms of dimpling defect, rupture, thickness distribution and dimensional accuracy. The onset of rupture was predicted by integrating the forming limit diagram of employed material with finite element Code. The predicted results were in a reasonable agreement with the experimental tests. It was found that for complete elimination of dimpling defect and acquiring maximum drawing depth, the proper allocation of elastic layer parameters such as thickness and hardness was crucial. The conducted investigations indicated that, in general, dimensional accuracy of formed parts was acceptable. However, for areas with sharp changes in geometry such as corners and side walls, deviation from desired geometry was evident. This phenomenon was remarkably dominant for manufactured parts utilizing softer elastic layer.     

Effects of Fe/SDS and Au nanoparticles on P. aeruginosa bacterial growth and biosurfactant production

The aim of this study was to evaluate the effects of iron (Fe)/SDS and gold (Au) nanoparticles on growth and biosurfactant production of Pseudomonas aeruginosa PBCC5. The concentrations of the nanoparticles used were 1, 500 and 1000 mg/l. In this research, the surface tension of biosurfactant, dry weight of biosurfactant and biomass, emulsification indexes (E₂₄) were measured and transmission electron microscopy analysis was used to monitor the nanoparticles. The test results showed that the effect of nanoparticles on the bacterial growth and biosurfactant production varied corresponding to the type and concentration of nanoparticles. Fe/SDS nanoparticles showed no bacterial toxicity when the concentration of nanoparticles was 1 mg/ml and increased the growth and biosurfactant production, 23.21 and 20.73%, respectively. While at higher concentrations (500, 1000 mg/l), the nanoparticles suppressed bacterial growth as well as biosurfactant production. Similarly, Au nanoparticles had no bacterial toxicity and also increased bacterial growth and biosurfactant production. The surface tensions of all samples decreased from 72 of distiled water to 32–35 mN/m.Inspec keywords: nanoparticles, iron, gold, nanofabrication, nanomedicine, surfactants, biomedical materials, surface tension, renewable materials, transmission electron microscopy, microorganismsOther keywords: Au nanoparticles, P. aeruginosa bacterial growth, biosurfactant production, Pseudomonas aeruginosa PBCC5, surface tension, biomass, emulsification indexes, dry weight, transmission electron microscopy, Fe‐SDS nanoparticles, distiled water, Fe, Au