Determination of discharge coefficient for flow over one cycle compound trapezoidal plan form labyrinth weir

Weirs are common structure to regulate discharge and flow control inwater conveyance channels and hydraulic structures. Labyrinth weirsconsidered one of economical and effective methods to increase the efficiency of weirs that crest length of weirs increase without a related increase in structure width. Therefore, flow discharge will be increased. Compared to use compound weir, there are some benefits including the simultaneous passage of floating materials such as wood, ice, etc. Also, sedimentations are pass through compound weir. The trapezoidal Labyrinth weir is one of the combined models. In present study 15 physical models that discussion effect changes sidewall angle of labyrinth weir on discharge coefficient of flow over and through the compound trapezoidal one cycle Labyrinth weir. Also, it is developed design curves with various shapes and configurations. The researchshowed here mainly objectives at determining the coefficient of discharge for flow-over trapezoidal labyrinth weir by performing tests at wide range of values of side wall angles (α) from 6° to 35° and compound linear weir to be compared.

Steric control over molecular structure and supramolecular association exerted by tin- and ligand-bound groups in diorganotin carboxylates

Structural data (X-ray and solution and solid-state ^₁₁₉Sn NMR) show that skew-trapezoidal-bipyramidal diorganotin compounds of 2-quinaldate are invariably monomeric, owing to the steric bulk of the carboxylate ligand. In contrast, most of the analogous compounds of 2-picolinate (2-pic) can increase their coordination number by polymerization or the incorporation of solvent in their coordination sphere in the solid state. The exceptional compound is tBu₂Sn(2-pic)₂ (3), for which no increase in coordination number is apparent, a result that is correlated with the bulky tert-butyl groups. Thus, judicious choice of tin or ligand substituents can be exploited to dictate coordination number and/or the degree of supramolecular aggregation in the investigated systems.

Effect of mean stress on multiaxial ratcheting life: a simplified life prediction model based on average equivalent stress amplitude

This article proposes a model to predict uniaxial and multiaxial ratcheting life by addressing the three primary parameters that influence failure life: fatigue damage, ratcheting damage and the multiaxial loading path. These three factors are addressed in the present model by (a) the stress amplitude for fatigue damage, (b) mean stress-dependent Goodman equation for ratcheting damage and (c) an inherent weight factor based on average equivalent stress to account for the multiaxial loading. The proposed model requires only two material constants which can be easily determined from uniaxial symmetric stress-controlled fatigue tests. Experimental ratcheting life data collected from the literature for 1025 and 42CrMo steel under multiaxial proportional and nonproportional constant amplitude loading ratcheting with triangular sinusoidal and trapezoidal waveform (i.e. linear, rhombic, circular, elliptical and square stress paths) have shown good agreement with the proposed model.

Portfolio selection under higher moments using fuzzy multi-objective linear programming

Since asset returns have been recognized as not normally distributed, the avenue of research regarding portfolio higher moments soon emerged. To account for uncertainty and vagueness of portfolio returns as well as of higher moment risks, we proposed a new portfolio selection model employing fuzzy sets in this paper. A fuzzy multi-objective linear programming (MOLP) for portfolio optimization is formulated using marginal impacts of assets on portfolio higher moments, which are modelled by trapezoidal fuzzy numbers. Through a consistent centroid-based ranking of fuzzy numbers, the fuzzy MOLP is transformed into an MOLP that is then solved by the maximin method. By taking portfolio higher moments into account, the approach enables investors to optimize not only the normal risk (variance) but also the asymmetric risk (skewness) and the risk of fat-tails (kurtosis). An illustrative example demonstrates the efficiency of the proposed methodology comparing to previous portfolio optimization models.