Stress distribution in thick-walled cylinder due to non-uniform radial pressure on the example of reinforcement corrosion in concrete

This paper presents an analytical solution to the non-uniform pressure on thick-walled cylinder. The formulation is based on the linear elasticity theory (plain strain) and stress function method. As an example, the proposed solution is used to model the stress distribution due to non-uniform steel reinforcement corrosion in concrete. The model is formulated considering different scenarios of corrosion pressure distribution. It is validated against the finite element model for different cases of non-uniform pressure distributions. The results show that the corrosion-induced cracks are likely to start just beyond the anodic zone. This is confirmed by the experimental tests on concrete cylinder exposed to non-uniform accelerated corrosion of steel reinforcement. The model can be effectively used to calculate the distribution of corrosion-induced stresses in concrete.     

Schedule-Based Cooperative Multi-agent Reinforcement Learning for Multi-channel Communication in Wireless Sensor Networks

Wireless sensor networks (WSNs) have become an important component in the Internet of things (IoT) field. In WSNs, multi-channel protocols have been developed to overcome some limitations related to the throughput and delivery rate which have become necessary for many IoT applications that require sufficient bandwidth to transmit a large amount of data. However, the requirement of frequent negotiation for channel assignment in distributed multi-channel protocols incurs an extra-large communication overhead which results in a reduction of the network lifetime. To deal with this requirement in an energy-efficient way is a challenging task. Hence, the Reinforcement Learning (RL) approach for channel assignment is used to overcome this problem. Nevertheless, the use of the RL approach requires a number of iterations to obtain the best solution which in turn creates a communication overhead and time-wasting. In this paper, a Self-schedule based Cooperative multi-agent Reinforcement Learning for Channel Assignment (SCRL CA) approach is proposed to improve the network lifetime and performance. The proposal addresses both regular traffic scheduling and assignment of the available orthogonal channels in an energy-efficient way. We solve the cooperation between the RL agents problem by using the self-schedule method to accelerate the RL iterations, reduce the communication overhead and balance the energy consumption in the route selection process. Therefore, two algorithms are proposed, the first one is for the Static channel assignment (SSCRL CA) while the second one is for the Dynamic channel assignment (DSCRL CA). The results of extensive simulation experiments show the effectiveness of our approach in improving the network lifetime and performance through the two algorithms.

     

Photothermoelectric (PTE) Versus Photopyroelectric (PPE) Detection of Phase Transitions

The photopyroelectric (PPE) technique is one of the photothermal (PT) methods mostly used for phase transitions investigations. In this paper, we want to compare the PPE results with those obtained using another, recently developed PT method [the photothermoelectric (PTE) calorimetry] for the same purpose of detecting phase transitions. The well-known ferro-paraelectric phase transition of TGS, taking place at a convenient temperature (about \(49\, {}^{\circ }\hbox {C}\)), has been selected for demonstration. A comparison of the two PPE and PTE methods, both in the back detection configuration (in the special case of optically opaque sample and thermally thick regime for both sensors and sample) shows that they are equally suitable for phase transitions detection. Performing a proper calibration, the amplitude and phase of the signals can be used in order to obtain the critical behaviour of all sample’s static and dynamic thermal parameters.     

On the accurate determination of thermal diffusivity of liquids by using the photopyroelectric thickness scanning method

An enhanced accurate method of measuring the thermal diffusivity of liquids by the sample's thickness scan of the phase of the photopyroelectric signal is presented. The method, making use of the absolute values of the phase and sample thickness, leads to very accurate results for the room temperature values of thermal diffusivity (about +/-0.3%). The high accuracy of the method is due to a very precise control of the sample's thickness variation (0.1 microm step), to a proper localization of the thickness scan range, and to a new procedure of data analysis. The high accuracy of the method recommends it for the study of processes associated with small changes of the thermal parameters.     

Improvement of corrosion protection of steel by incorporation of a new phosphonated fatty acid in a phosphorus-containing polymer coating obtained by UV curing

Six formulations containing diacrylate monomers (from 89 to 92.5% (w/w)) as well as a phosphonated methacrylate monomer (from 1 to 10% (w/w)) were prepared. All formulations were UV-cured and the corrosion performance of the resulting coatings applied onto a steel substrate was assessed by electrochemical impedance spectroscopy (EIS). It was first shown that the coatings containing phosphonic acid methacrylate (MAPC1(OH)₂) instead of methacrylate phosphonic dimethyl ester (MAPC1) presented higher corrosion protection related to the strong adhesive properties of phosphonic acid on the metal substrate. A minimum MAPC1(OH)₂ content of 2.5% was determined to provide the highest impedance values (best efficiency). Then, a new bio-based compound, i.e. phosphonic acid-bearing oleic acid (phosphonated fatty acid), was synthesized and added as an inhibitor to the formulations. In the presence of this compound, the corrosion protection was notably improved. The beneficial effect of phosphonated fatty acid was explained by its inhibitive action at the steel/coating interface and by the improvement of the barrier properties.     

An improved radial impulse turbine for OWC

Traditionally, wells turbines have been widely used in OWC plants. However, an alternative has been studied over recent years: a self-rectifying turbine known as an impulse turbine. We are interested in the radial version of the impulse turbine, which was initially proposed by M. McCormick. Previous research was carried out using CFD (FLUENT^®), which aimed to improve knowledge of the local flow behavior and the prediction of the performance for this kind of turbine. This previous work was developed with a geometry taken from the literature, but now our goal is to develop a new geometry design with a better performance. To achieve this, we have redesigned the blade and vane profiles and improved the interaction between them by means of a new relation between their setting angles. Under sinusoidal flow conditions the new design improves the turbine efficiency by up to 5% more than the geometry proposed by Professor Setoguchi, in 2002. In this paper, the design criteria we have used is described, and the flow behavior and the performance of this new design are compared with the previous one.     

HVOF sprayed WC–Co coatings: Microstructure,mechanical properties and friction moment prediction

This study aims at gaining a better understanding of the microstructural features that control the mechanical and the tribological performances of WC–12 wt.% Co coatings under High Velocity Oxygen Fuel (HVOF) spraying conditions. This paper looks at the influences of the HVOF process parameters for WC–12Co material on the microstructural and the tribological behaviours of the coatings. The correlation between the coating microstructure and the wear behaviour is investigated by observing and analysing the microstructure and by studying the friction moment using enhanced statistical tool based on neural computations. According to the experimental and the numerical results, it has been shown that the spray parameters affect the phase composition, hardness and porosity of HVOF sprayed WC–12Co coatings and the correlations with HVOF process parameters are fully predictable in the steady-state regime.     

Effect of pressure on the structural and elastic properties of ZnS and MgS alloys in the B3 and B1 phases

From the first-principles calculations, we have investigated the elastic stiffness coefficients C₁₁, C₁₂, C₄₄ and the bulk modulus B of the II-VI semiconductors ZnS and MgS under hydrostatic pressure. The calculations are based on the density functional theory within the generalized gradient approximation (GGA) for exchange-correlation interaction. For the structural properties we have shown that ZnS adopt the rocksalt (NaCl or B1) structure over 11.87 GPa pressure, the same character is adopted by MgS over 0.8 GPa. The elastic coefficients have the same behavior for the different structures of alloys; they increase with increasing pressure values. Our results for the structural parameters and equilibrium phase elastic constants are in good agreement with the available theoretical and experimental data.     

Maintainability defects detection and correction: a multi-objective approach

Software defects often lead to bugs, runtime errors and software maintenance difficulties. They should be systematically prevented, found, removed or fixed all along the software lifecycle. However, detecting and fixing these defects is still, to some extent, a difficult, time-consuming and manual process. In this paper, we propose a two-step automated approach to detect and then to correct various types of maintainability defects in source code. Using Genetic Programming, our approach allows automatic generation of rules to detect defects, thus relieving the designer from a fastidious manual rule definition task. Then, we correct the detected defects while minimizing the correction effort. A correction solution is defined as the combination of refactoring operations that should maximize as much as possible the number of corrected defects with minimal code modification effort. We use the Non-dominated Sorting Genetic Algorithm (NSGA-II) to find the best compromise. For six open source projects, we succeeded in detecting the majority of known defects, and the proposed corrections fixed most of them with minimal effort.