Determination of pile failure mechanism under pullout test in loose sand

Estimating the deformation of soil around the pile contributes to reliable design of structures under pullout force. This work presents the results of a series of small-scale physical modelling tests designed to investigate the uplift resistance of piles with diameter of 5 cm and slenderness ratios of 1, 2, 3 and 4 in loose sand. Close photogrammetric technique and particle image velocimetry(PIV) were employed to observe the failure patterns due to uplift force on piles. The results show that the shear zones curve slightly outward near the ground surface. After peak resistance, the shear strain concentrates into a pair of narrow shear bands,then a flow around mechanism is formed accompanied by a reduction in the uplift resistance. The results from the laboratory tests were verified by analytical method proposed by Chattopadhyay and PLAXIS 2D and 3D finite element method software. It is found that the depth and width of the failure surface increase with the increment of the slenderness ratio. A good agreement is observed among the measured bearing capacity and obtained failure surface of the models and the results of numerical modelling. Finally, the maximum deformation of loose and dense sand respectively with densities of 25% and 75% were compared in the stage of fully removing pile. The results shows that the deformation of the soil is related to its density, therefore it depends on its dilatancy.     

Application of Spatial Analysis Techniques to Select the Most Suitable Areas for Flood Spreading

This study addressed potential areas for flood spreading by evaluating the Boolean Logic, Overlay Index and Fuzzy Clustering techniques for spatial analysis. We applied these techniques on the artificial recharge criteria of slope, infiltration rate, alluvium thickness, land use and alluvial quality. The above criteria were prepared, classified, weighted and integrated in a GIS environment. The resultant maps were organized into two classes of potentiality, suitable and unsuitable, which expressed two different levels of favorability for site selection of flood spreading in the study area. We used 32 controlling areas to compare the performance of these spatial analysis techniques. By validation of the produced maps, the most suitable areas of flood spreading for each technique were determined: Fuzzy Clustering (14.4 %) Overlay Index (10.84 %) and Boolean Logic (10 %). After land use filtering, 72 %, 70 % and 65 % of the most suitable areas were eliminated in the, Overlay Index, Boolean model and Fuzzy Clustering, respectively. According to our results, the spatial analysis techniques can be powerful tools for selecting the most suitable areas for flood spreading.     

Experimental and modeling study of the kinetics of methane hydrate formation and dissociation

In this work, several experiments were conducted at isobaric and isothermal condition in a CSTR reactor to study the kinetics of methane hydrate formation and dissociation. Experiments were performed at five temperatures and three pressure levels (corresponding to equilibrium pressure). Methane hydrate formation and dissociation rates were modeled using mass transfer limited kinetic models and mass transfer coefficients for both formation and dissociation were calculated. Comparison of results, shows that mass transfer coefficients for methane hydrate dissociation are one order greater than formation conditions. Mass transfer coefficients were correlated by polynomials as relations of pressure and temperature. The results and the method can be applied for prediction of methane production from naturally occurring methane hydrate deposits.     

Dominant role of drivers’ attitude in prevention of road traffic crashes: A study on knowledge,attitude, and practice of drivers in Iran

Objective

Evaluating the relation between Iranian drivers’ knowledge, attitude, and practice (KAP) regarding traffic regulations, and their deterministic effect on road traffic crashes (RTCs).

Setting

Two cities of Tehran and Zahedan, Iran.

Methods

A cross-sectional study was designed. Using a simplified cluster sampling design, 2200 motor vehicle drivers including 1200 in Tehran and 1000 in Zahedan were selected. Sixty locations in Tehran and 50 in Zahedan were chosen. In each pre-identified location, 20 adult drivers were approached consecutively. A questionnaire developed by researchers was filled by each participant. The questionnaire had four sections including items assessing the demographics, knowledge, attitude and practice of drivers toward traffic regulations. Logistic regression analysis was used to evaluate the relationship between the RTCs and KAP variables.

Results

The study sample consisted of 619 (28.1%) occupational and 1580 (71.8%) private drivers. Among them, 86.4% were male. The median age was 33.6 ± 10.83. Drivers in Tehran and Zahedan had no significant differences between their mean scores of KAP items of the questionnaire. Higher knowledge, safer attitude, and safer practice were associated with a decreased number of RTC. After adjusting for possible confounders, increase of one standard deviation in attitude and practice scores (but not knowledge) resulted in 26.4% and 18.5% decrease in RTC, respectively. Finally, considering knowledge, attitude and practice of drivers in one model to assess their mutual effect, it was shown that only attitude is significantly associated with a decrease of RTC (OR = 0.76, P = 0.007).

Conclusion

Increase in attitude and practice accompanied with decreased number of RTCs in Iranian drivers. Specifically, drivers’ attitude had the crucial effect. It is not knowledge and standard traffic education; rather it is how such education is registered as an attitude that translates what is being learned into actions. Without safer attitude, even safer self-reported practice will not result in lower RTCs.     

Fixed-time fault-tolerant control of uncertain MIMO switched interconnected systems subject to state delay,unknown control directions,and quantized nonlinear inputs

This paper investigates design of an adaptive fixed-time fault-tolerant decentralized controller for a class of uncertain multi-input multi-output (MIMO) switched large-scale non-strict interconnected systems under arbitrary switching subject to unknown control directions, quantized nonlinear inputs, actuator failures unknown external disturbances, and unmodeled dynamics. In addition to interconnected terms, time-varying delayed interconnected terms have been considered in the system model which makes it more general than previous works in the literature. The proposed controller can handle switched systems with unknown switching signal and different types of input nonlinearities including, saturation, backlash, and dead-zone. The singularity problem in designing the fixed time controller has been solved. The quantizer and actuators fault parameters are assumed to be unknown. The Razumikhin lemma has been used to deal with the delayed interconnected terms. To cope with the system unknown dynamics, neural networks (NNs) have been applied and by updating the maximum norms of the networks weight vectors the computational load has been reduced. The explosion of complexity occurring in the traditional back-stepping technique has been avoided by applying dynamic surface control (DSC). Finally, by defining an appropriate common Lyapunov function (CLF), fixed-time convergence of system outputs and the closed-loop system stability have been established. The effectiveness of the proposed controller has been shown via simulation study.