Numerical Simulation of Thermal Stresses in Prismatic Concrete Beams Reinforced with FRP Bars under Low Temperatures

The thermal properties of fiber reinforced polymer (FRP) bars particularly in the transverse direction are higher than those of hardened concrete and steel bars. The difference in transverse thermal characteristics between FRP bar and concrete generates radial tensile stresses within concrete at the interface of FRP bars/concrete under low temperatures. These thermal stresses may cause circumferential cracks in concrete at the interface and eventually the reduction of the bond that can affect significantly the serviceability of reinforced concrete structures. This paper presents a nonlinear numerical simulation of thermal stresses in prismatic concrete beams reinforced with glass FRP (GFRP) bars submitted to low temperatures when the confining action of concrete is asymmetric. The non linear numerical analysis shows that the first circumferential cracks start to develop within concrete at FRP bar/concrete interface at a temperature decrease DTcr varied between -30°C and -25°C for prismatic concrete beams reinforced with GFRP bars having a ratio of concrete cover thickness to FRP bar diameter (c/db) varied from 1.0 to 3.2. Furthermore, the depths of circumferential cracks propagated from the interface through the concrete cover increase with the decrease of the thermal load DT (from -25 °C to -50 °C). These depths did not reach the outer surface of the concrete cover under low temperatures up to -50 °C. Also, the radial tensile stress at FRP bar/concrete interface increases with the increase in the ratio c/db. The cracking thermal loads and thermal stresses predicted from nonlinear finite element model are compared to those evaluated with analytical models. Comparisons between numerical and analytical results in terms of cracking thermal loads and thermal stresses are presented

Identification and Antibiosis of a Novel Actinomycete Strain RAF-11 Isolated From Iraqi Soil.

A total of 35 actinomycetes strains were isolated from and around Baghdad, Iraq, at a depth of 5-10 m, by serial dilution agar plating method

Estimation of Properties of Liquid-Vapor Mixture of Some Refrigerants at High Pressure for Solar-Photovoltaic Refrigeration

Abstract. In this work, a hybrid method based on neural network and particle swarm optimization is applied to literature data to develop and validate a model that can predict with precision vapor-liquid equilibrium data for the binary systems (hexafluoroethane (R116(1)), 1,1,1,2-tetrafluoroethane (R134a) and R1234ze) . ANN was used for modelling the non-linear process. The PSO was used for two purposes: replacing the standard back propagation in training the ANN and optimizing the process. The training and validation strategy has been focused on the use of a validation agreement vector, determined from linear regression analysis of the predicted versus experimental outputs, as an indication of the predictive ability of the neural network model. Statistical analysis of the predictability of the optimized neural network model shows excellent agreement with experimental data (coefficient of correlation equal to 0.998). Furthermore, the comparison in terms of average relative deviation (AARD%) between, the predicted results for the whole temperature and pressure range shows that the ANN-PSO model can predict far better the mixture properties than cubic equations of state

Screening for genes coding for putative antitumor compounds, antimicrobial and enzymatic activities from haloalkalitolerant and haloalkaliphilic bacteria strains of Algerian Sahara soils

Extreme environments may often contain unusual bacterial groups whose physiology is distinct from those of normal environments. To satisfy the need for new bioactive pharmaceuticals compounds and enzymes, we report here the isolation of novel bacteria from an extreme environment. Thirteen selected haloalkalitolerant and haloalkaliphilic bacteria were isolated from Algerian Sahara Desert soils. These isolates were screened for the presence of genes coding for putative antitumor compounds using PCR based methods. Enzymatic, antibacterial, and antifungal activities were determined by using cultural dependant methods. Several of these isolates are typical of desert and alkaline saline soils, but, in addition, we report for the first time the presence of a potential new member of the genus Nocardiawith particular activity against the yeast Saccharomyces cerevisiae. In addition to their haloalkali character, the presence of genes coding for putative antitumor compounds, combined with the antimicrobial activity against a broad range of indicator strains and their enzymatic potential, makes them suitable for biotechnology applications

Real-time implementation of an interconnected observer design for p-cells chopper

This paper deals with an observer design for a p-cell chopper. The goal is to reduce drastically the number of sensors in such system by using an observer in order to estimate all the capacitor voltages. Furthermore, considering an instantaneous model of a p-cell chopper, an interconnected observer is designed in order to estimate the capacitor voltages. This is realized by using only the load current measurement. Simulation results are given in order to illustrate the performance of such observer. To demonstrate the validity of our approach, experimental results based on Digital Signal Processor (DSP) are presented