Matrix analysis of nonlinear trusses using Prandtl-2 Neural Networks

A new method, based on the concepts of matrix analysis as well as the learning capabilities of neural networks, for the analysis of nonlinear trusses under dynamic loading is presented. The method can be applied to static trusses too. While there have been attempts in the past to use neural networks to identify and model different structures based on data measured on structural response directly, the main feature and advantage of this new method is in its capability to model a nonlinear truss by assembling the data collected on the response of its members. The basics of the method are: (1) for each truss member, a neural network is trained to learn and simulate its load-response behavior, (2) the member neural networks are then assembled to build another neural network which can simulate the load-response behavior of the whole truss. Noticing test at member level is generally easier than at structure level, this can make the building of a neural network to simulate the response of the truss more affordable. Also this has potential application when it is hard to find a mathematical model from experimental data to describe the internal force vector for a truss, as well as identification and control of trusses where precise modeling of the structure is a key point to the success of the application. Prandtl Neural Network, developed recently by the authors for modeling of nonlinear hysteretic materials, has been improved and used in this study too. The improved version has been called Prandtl-2 Neural Network (PNN2) in this paper. The method has been applied to the static and dynamic analysis of a 3-bar and a 10-bar benchmark truss successfully, the results of which are reported in this paper.     

Fabrication, characterization, and measurement of viscosity of α-Fe2O3-glycerol nanofluids

Magnetic nanofluids, ferrofluids, are a special category of smart nanomaterials, consisting of stable dispersion of magnetic nanoparticles in different fluids. In this study, magnetic nanoparticles of hematite, α-Fe₂O₃, were prepared by solvothermal method using Fe(NO₃)₃ as a starting material. The nanoparticles were characterized by X-ray diffraction (XRD) and transmission electronic microscope (TEM).To the best of our knowledge, this is the first research on the rheological properties of nanofluids of α-Fe₂O₃ nanoparticles and glycerol. The experimental results showed that the viscosity of α-Fe₂O₃-glycerol nanofluids increases with increasing the particle volume fraction and decreases with increasing temperature. Our results clearly showed that the α-Fe₂O₃-glycerol nanofluids are non-Newtonian shear-thinning and their shear viscosity depends strongly on temperature. The experimental data were compared with some theoretical models. The measured values of the effective viscosity of nanofluids are underestimated by the theoretical models.     

Note on new solutions of LR fuzzy linear systems using ranking functions and ABS algorithms

Recently, Ghanbari and Mahdavi-Amiri focused on solving LR fuzzy linear systems by use of ranking functions. They applied a ranking function introduced by Cheng, which is based on the centroid point, to illustrate their method. Also, they presented an important lemma using the centroid formulae provided by Cheng, to determine the centroid point for a class of fuzzy numbers. Unfortunately, they didn’t consider that the formulae are incorrect and have led to some misapplications as pointed out by Wang and his colleagues. Therefore, in this paper, we first show that Lemma 19 of Ghanbari and Mahdavi-Amiri’s paper is not true and then correct it using the centroid formulae suggested by Wang. Finally, we correct the results obtained in Ghanbari and Mahdavi-Amiri’s paper for a special example.     

An experimental investigation of creaming phenomenon using a novel optical method: A case study of mineral oil-in-water emulsion

The present study elucidates the creaming phenomenon of mineral oil-in-water macroemulsion using a new noninvasive method based on turbidimetry. Additionally, microscopic observation of the phenomenon is carried out to derive an in-depth understanding of the mechanisms. Accumulation of the particles in the emulsions under the formed cream is monitored during a relatively prolonged period of time. Backflow of continuous and dispersed phases in temporary channels is observed at the proximity of the cream. In addition to the backflow, a high traffic density of the dispersed particles and deflocculation of the cream are the main reasons for the accumulation of the dispersed phase particles and a temporary stability against creaming. The deflocculation hinders cream growth and increases the stratification of the cream. A low concentration zone of the dispersed phase with the width of ～100?µm is observed under the cream.     

The first report on the catalytic oxidation of urazoles to their corresponding triazolinediones via in situ catalytic generation of Br using periodic acid or oxone/KBr system

A combination of periodic acid or oxone^® and a catalytic amount of KBr in the presence of few drops of water, were used for the catalytic oxidation of urazoles and bis-urazoles to their corresponding triazolinediones under mild and heterogeneous conditions with moderate to excellent yields.     

Distance-regular Cayley graphs with least eigenvalue $$$$

We classify the distance-regular Cayley graphs with least eigenvalue \(-2\) and diameter at most three. Besides sporadic examples, these comprise of the lattice graphs, certain triangular graphs, and line graphs of incidence graphs of certain projective planes. In addition, we classify the possible connection sets for the lattice graphs and obtain some results on the structure of distance-regular Cayley line graphs of incidence graphs of generalized polygons.     

Resource allocation based on cost efficiency

In this paper, we consider a resource allocation (RA) problem and develop an approach based on cost (overall) efficiency. The aim is to allocate some inputs among decision making units (DMUs) in such way that their cost efficiencies improve or stay unchanged after RA. We formulate a multi-objective linear programming problem using two different strategies. First, we propose an RA model which keeps the cost efficiencies of units unchanged. This is done assuming fixed technical and allocative efficiencies. The approach is based on the assumption that the decision maker (DM) may not have big changes in the structure of DMUs within a short term. The second strategy does not impose any restrictions on technical and allocative efficiencies. It guarantees that none of the cost efficiencies of DMUs get worse after RA, and the improvement for units is possible if it is feasible and beneficial. Two numerical examples and an empirical illustration are also provided.     

Theoretical determination of the differential polarizability and anisotropy of alkaline earth oxide nanoclusters (BeO)n [n = 2–9]: The basis set and electron correlation effects

As an important lineage of metal oxides, alkaline earth oxides have attracted significant interest due to their unique properties and potential applications in material science and industry. In this article, we present the first ab initio (HF, MP2, and CCSD(T)) and density functional theory (TPSSh functional) investigation on the optical properties such as polarizabilities per atom (PPA), differential polarizability per unit (DPPU), and anisotropies of (BeO)_n [n = 2–9] nanoclusters as an illustrative example of alkaline earth oxides nanostructures. Basis set augmentation effects on the studied properties of BeO nanoclusters have been explored by using basis sets of triple‐zeta quality starting from 6‐311G with increasing completeness of the diffuse and polarization functions to the 6‐311+G(3df) basis. Checking carefully the basis set effects, it is shown that the 6‐311+G(3d) basis set provides the best compromise between the accuracy and computational cost. We found a decreasing trend for PPA values of BeO nanoclusters using all considered methods, indicating the strong electron delocalization with increasing cluster size. Moreover, in accordance with the energetic analysis of stability of BeO nanoclusters, the values of PPA show that the (BeO)₄ and (BeO)₆ clusters are the most stable magic numbers compared to the neighbors, satisfying the minimum polarizability principle. The computed values of DPPU demonstrate a strong binding effect in BeO nanoclusters. Taking into account the electron correlation correction (ECC), it is observed that the variations of ECC on dipole polarizabilities are almost smooth for clusters under study. © 2013 Wiley Periodicals, Inc.     

Effect of composition,solvent exchange liquid and drying method on the porous structure of phenol–formaldehyde gels

Organic gels have been synthesized by sol–gel polycondensation of phenol (P) and formaldehyde (F) catalyzed by sodium carbonate (C). The effect of synthesis parameters such as phenol/catalyst ratio (P/C), solvent exchange liquid and drying method, on the porous structure of the gels have been investigated. The total and mesopore volumes of the PF gels increased with increasing P/C ratio in the range of P/C ≤ 8, after this both properties started to decrease with P/C ratio for P/C > 8 and the gel with P/C = 8 showed the highest total and mesopore volumes of 1.281 and 1.279 cm³ g⁻¹ respectively. The gels prepared by freeze drying possessed significantly higher porosities than the vacuum dried gels. The pore volume and average pore diameter of the freeze dried gels were significantly higher than those of the vacuum dried gels. T-butanol emerged as the preferred solvent for the removal of water from the PF hydrogel prior to drying, as significantly higher pore volumes and specific surface areas were obtained in the corresponding dried gels. The results showed that freeze drying with t-butanol and lower P/C ratios were favourable conditions for the synthesis of highly mesoporous phenol–formaldehyde gels.