Calculation of maximum surface settlement induced by EPB shield tunnelling and introducing most effective parameter

This study aims to predict ground surface settlement due to shallow tunneling and introduce the most affecting parameters on this phenomenon.Based on data collected from Shanghai LRT Line 2 project undertaken by TBM-EPB method,this research has considered the tunnel's geometric,strength,and operational factors as the dependent variables.At first,multiple regression(MR) method was used to propose equations based on various parameters.The results indicated the dependency of surface settlement on many parameters so that the interactions among different parameters make it impossible to use MR method as it leads to equations of poor accuracy.As such,adaptive neuro-fuzzy inference system(ANFIS),was used to evaluate its capabilities in terms of predicting surface settlement.Among generated ANFIS models,the model with all input parameters considered produced the best prediction,so as its associated R~2 in the test phase was obtained to be 0.957.The equations and models in which operational factors were taken into consideration gave better prediction results indicating larger relative effect of such factors.For sensitivity analysis of ANFIS model,cosine amplitude method(CAM) was employed; among other dependent variables,fill factor of grouting(n) and grouting pressure(P) were identified as the most affecting parameters.     

Optimization of a Three-Component Green Corrosion Inhibitor Mixture for Using in Cooling Water by Experimental Design

Factors such as inhibitor concentration, solution hydrodynamics, and temperature influence the performance of corrosion inhibitor mixtures. The simultaneous studying of the impact of different factors is a time- and cost-consuming process. The use of experimental design methods can be useful in minimizing the number of experiments and finding local optimized conditions for factors under the investigation. In the present work, the inhibition performance of a three-component inhibitor mixture against corrosion of St37 steel rotating disk electrode, RDE, was studied. The mixture was composed of citric acid, lanthanum(III) nitrate, and tetrabutylammonium perchlorate. In order to decrease the number of experiments, the L16 Taguchi orthogonal array was used. The “control factors” were the concentration of each component and the rotation rate of RDE and the “response factor” was the inhibition efficiency. The scanning electron microscopy and energy dispersive x-ray spectroscopy techniques verified the formation of islands of adsorbed citrate complexes with lanthanum ions and insoluble lanthanum(III) hydroxide. From the Taguchi analysis results the mixture of 0.50 mM lanthanum(III) nitrate, 0.50 mM citric acid, and 2.0 mM tetrabutylammonium perchlorate under the electrode rotation rate of 1000 rpm was found as optimum conditions.     

Effect of basalt,silica sand and fly ash on the mechanical properties of quaternary polymer concretes

The aim of this study is to manufacture quaternary polymer concretes (PCs) and optimize the weight percentages of the epoxy resin, ultrafine fly ash, silica sand and basalt aggregates. For this, we first manufactured binary PCs of epoxy/basalt, epoxy/silica sand and epoxy/fly ash and then studied the mechanical properties such as compressive, flexural and splitting tensile strength. The mixture design method was used as an approach for design of experiment to reduce the number of tests and optimize the mechanical strength of the PC. The best weight percentages of the PC components were 25 (epoxy), 5 (fly ash), 52.5 (silica sand) and 17.5 (basalt). The compressive, flexural and splitting tensile strength of the quaternary PC were equal to 94.1, 39.0 and 11.8, which were 3.76, 11.1 and 6.5 times higher than those of ordinary Portland cement, respectively. Finally, a scanning electron microscopy test was implemented to study the microstructure of the PC.     

A novel adaptive fuzzy predictive control for hybrid systems with mixed inputs

This paper proposes a new adaptive nonlinear model predictive control (NMPC) methodology for a class of hybrid systems with mixed inputs. For this purpose, an online fuzzy identification approach is presented to recursively estimate an evolving Takagi–Sugeno (eTS) model for the hybrid systems based on a potential clustering scheme. A receding horizon adaptive NMPC is then devised on the basis of the online identified eTS fuzzy model. The nonlinear MPC optimization problem is solved by a genetic algorithm (GA). Diverse sets of test scenarios have been conducted to comparatively demonstrate the robust performance of the proposed adaptive NMPC methodology on the challenging start-up operation of a hybrid continuous stirred tank reactor (CSTR) benchmark problem.     

Band structure effect on the electron current oscillation in ultra-scaled GaSb Schottky MOSFET: tight-binding approach

This paper explores band structure effect on the quantum transport of a low-dimensional GaSb Schottky MOSFET (SBFET) for the implementation of III–V transistor with a low series resistance. Precise treatment of the full band structure is employed applying sp ³ d ⁵ s ^? tight-binding (TB) formalism. A remarkable distinction between the thickness dependent effective masses extracted from the TB and the bulk values imply that the quantum confinement modifies the device performance. Strong transverse confinement leads to the effective Schottky barrier height increment. Owing to the adequate enhanced Schottky barriers at low drain voltages, a double barrier gate modulated potential well is formed along the channel. The double barrier profile creates a longitudinal quantum confinement and induces drain current oscillation at low temperatures. Significant factors that may affect the current oscillation are thoroughly investigated. Current oscillation is gradually smoothed out as the gate length shrinks down in ultra scaled structure. The results in this paper are paving a way to clarify the feasibility of this device in nanoscale regime.     

Effect of nanoparticles on the morphology and thermal properties of self-healing poly(urea-formaldehyde) microcapsules

The preparation of microcapsules with adequate performance is required for the fabrication of self-healing composites. Self-healing microcapsules with improved morphology as well as thermal and water resistance were prepared by introducing either single-walled carbon nanotubes (SWCNTs) or aluminum oxide nanoparticles (nano-alumina) into a urea–formaldehyde resin (which acts as the wall material). The prepared microcapsules were studied using various characterization techniques, including Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), optical microscopy (OM), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), and contact-angle measurements. Based on comparisons with traditional poly(urea–formaldehyde) microcapsules, the modified microcapsules exhibited a smoother surface. Our results indicate that the presence of the nanoparticles did not affect the core content of the microcapsules, which was approximately 78 wt.%. The average size of the traditional microcapsules was reduced from 168 μm to 115 and 95 μm for the SWCNT- and nano-alumina-modified microcapsules, respectively. In addition, the thermal resistance of the microcapsules was improved after modifying the capsule walls. After the microcapsules had been modified with SWCNTs, the water resistance of the capsules improved, and the contact angle increased from 44° to 50°.     

Impact of gate sidewall angle on the electrical characteristics of V-shaped gate III-nitride HEMTs: An investigation into self-heating and geometrical effects

Journal of Computational Electronics - Variation of gate sidewall angle in V-shaped gate HEMTs impacts the device electrical performance, including self-heating effects, high-frequency operation...