Strength and fatigue properties in medium carbon duplex steels

The effect of microstructure on strength and fatigue properties has been investigated in two medium carbon alloy steels (BS 817M40 and BS 835M30) by developing dual-phase, ferritic-martensitic microstructures. Hardness-strength relationships and fatigue resistance at comparatively high strength levels were investigated by producing various microstructures. Conventional quenching and tempering, intercritical annealing and step quenching were used to vary the proportion, morphology and distribution of the ferrite and martensite phases. The results of the present study show that both hardness and strength increase with increasing proportion of martensite and/or hardness of the second phase. The relationship between hardness or strength and martensite percent is not in good agreement with a simple “law of mixtures” but is compatible with a more rapid strength increase at high martensite contents. The dual phase microstructures from the present study show superior near threshold ΔK_TH values than normal tempered martensite. The results also show a high degree of correlation between Paris equation m values and fracture toughness K_IC, showing that for high m values K_IC is low and vice versa. The present experiments show that although crack initiation resistance in dual-phase steels is excellent crack propagation rates are higher than in quenched and tempered microstructures for a given ΔK.     

Estimation of emission of hydrocarbons and filling losses in storage containers using intelligent models

The emission of hydrocarbon plays a key role in the oil and gas production industries and can pose a danger. In the current cooperation, two intelligent simple tools, namely, support vector machine (SVM) and adaptive network based fuzzy inference system (ANFIS), have been developed to predict the amount of filling loss in storage tanks at vapor pressures ranging between 0 and 101 KPa and working pressures ranging between 101.325 and 251.325 KPa. Based on statistical analysis, estimations by the SVM approach show better accuracy than the ANFIS method. The proposed models are easy to apply and would be of great assistance to engineers, particularly those dealing with the design and applications of storage tanks. The efforts in this study will cover the manner for making precise estimations of the filling losses in storage tanks, which can help researchers and engineers control the operational conditions.     

Evaluation of dike-type causeway impacts on the flow and salinity regimes in Urmia Lake,Iran

Urmia Lake, located in a closed basin in north-west Iran, is the largest lake (5000–6000 km²) in the Middle East. It is very saline with total dissolved salts reaching 200 g/l compared with a normal seawater salinity of about 35 g/l. The construction of a causeway, which was initiated in 1979 but then abandoned until the early 2000s, is near completion and will provide road access between the western and eastern provinces. The causeway has an opening 1.25 km long and divides Urmia Lake into a northern and southern basin and restricts water exchange. The flow and salinity regimes are affected by the presence of this new causeway, and there are concerns over the well being of the Artemia population. This study investigates the effects of the construction of the causeway on flow and salinity regimes, considers remedial actions, and examines the effects of climatic variability on salinity and flow. Flow and salinity regimes were numerically simulated by using a commercially available two and three-dimensional (2D and 3D) MIKE model. The validity of the numerical model was assessed through sensitivity analysis of the model and comparing the simulated results against field measurements; the 3D model provided the higher correlation between simulated and actual data. Wind input was the main climatic and hydrologic factor influencing flow regime while river discharge, evaporation and rainfall were the key parameters affecting salinity distribution in the lake models. The 3D model was subsequently used to predict lake conditions in typical dry, wet and normal climates, to examine the environmental impacts from the new causeway, and to evaluate possible improvements that some remedial measures may provide.     

Estimation of the CO2-oil minimum miscibility pressure for enhanced oil recovery

The authors' aim was to present new models based on artificial neural network (ANN) and two optimization algorithms including cuckoo optimization algorithm (COA) and teaching learning based optimization (TLBO) to predict the pure and impure CO₂ MMP. Thirty-four and 11 training and testing data sets were used to develop these models with following inputs: reservoir temperature, the mole percent of volatile oil components (C₁ and N₂), mole percent of intermediate oil components (C₂-C₄, CO₂, and H₂S), molecular weight of C₅₊ fraction in oil phase (MW_C5+) and mole percentage of CO₂, N₂, C₁, C₄, and H₂S in the injected gas. Statistical comparisons show that although two models yield acceptable results, the ANN-TLBO model has better performance with the lower mean absolute percentage error (2.6%) and standard deviation (3.37%) and the higher coefficient of determination (0.993). Moreover, among the available correlations, the Cronquist's (1978 Cronquist, C. (1978). Carbon dioxide dynamic miscibility with light reservoir oils. Fourth Annual U.S. DOE Symposium, Tulsa, Oklahoma. [Google Scholar]; corrected by Sebastian et al., 1985 Sebastian, H. M., Wenger, R. S., and Renner, T. A. (1985). Correlation of minimum miscibility pressure for impure CO2 streams. J. Pet. Technol. 37:2076–2082.[Crossref] , [Google Scholar]) correlations have better performance. Finally, the sensitivity analysis on the ANN-TLBO showed that MW_C5+ and reservoir temperature are the most influential parameters in determining the CO₂ MMP, respectively.     

Silicon Nanoparticles and Methyl Jasmonate Improve Physiological Response and Increase Expression of Stress-related Genes in Strawberry cv. Paros Under Salinity Stress

Silicon - Salinity is one of the most crucial abiotic stresses, which is the consequence of an increase in the concentration of NaCl ions, influencing the plant’s growth, development, and...