Thermomechanical material parameters characterization of the superalloy PN 3601669-7 under low-velocity impacts

This work concerns the characterization of the thermodynamic behavior of the superalloy Airsist 215 (PN 3601669-7) containing cobalt. Such superalloys are used in aeronautical construction, in the hot parts of the turbine. They are frequently used for the production of the paddles. The parts in service are subjected to dynamic solicitations and thermal fluctuations over the course of time. They are responsible for modification and degradation of material properties. This can lead to the appearance of cracks and, in the long term, to the rupture of these parts. In this paper, a preliminary physical study is made on the appearance of the cracks, followed by experiments using shocks at ambient temperature and under a heating situation which simulates combustion. It is found that these dynamic loads have a significant impact on the development of the cracks that appear on the segments of the turbine nozzle. The study is devoted to the elastic shock of Hertz-Boussinesq extended to viscoelastic bodies by direct convolution of Riemann-Stielges. The interest resides in the local convolution and the distribution of stresses in the contact zone. The shock excitation method includes a deduced force in the load and disload phases. This force is an impulse which approaches a Dirac function. The sample can be modeled approximately by a system of one degree of freedom for natural frequency, damping and transfer function. The spectral response of the specified shock allows calculation of the damping. Every point of this spectrum gives the response for the linear system of the transfer function. Then, viscoelastic shock parameters are deduced.     

Work stealing with private integer–vector–matrix data structure for multi‐core branch‐and‐bound algorithms

In this paper, the focus is put on multi‐core branch‐and‐bound algorithms for solving large‐scale permutation‐based optimization problems. We investigate five work stealing (WS) strategies with a new data structure called integer–vector–matrix (IVM). In these strategies, each thread has a private IVM allowing the local management of a set of subproblems enumerated using a factorial system. The WS strategies differ in the way the victim thread is selected and the granularity of stolen work units (intervals of factoradics). To assess the efficiency of the private IVM‐based WS approach, the five WS strategies have been extensively experimented on the flowshop scheduling permutation problem and compared with their conventional linked‐list‐based counterparts. The obtained results demonstrate that the IVM‐based WS outperforms the linked‐list‐based one in terms of CPU time, memory usage and number of performed WS operations. Copyright © 2016 John Wiley & Sons, Ltd.     

Analysis and prediction of tool wear, surface roughness and cutting forces in hard turning with CBN tool

The main of the present study is to investigate the effects of process parameters (cutting speed, feed rate and depth of cut) on performance characteristics (tool life, surface roughness and cutting forces) in finish hard turning of AISI 52100 bearing steel with CBN tool. The cutting forces and surface roughness are measured at the end of useful tool life. The combined effects of the process parameters on performance characteristics are investigated using ANOVA. The composite desirability optimization technique associated with the RSM quadratic models is used as multi-objective optimization approach. The results show that feed rate and cutting speed strongly influence surface roughness and tool life. However, the depth of cut exhibits maximum influence on cutting forces. The proposed experimental and statistical approaches bring reliable methodologies to model, to optimize and to improve the hard turning process. They can be extended efficiently to study other machining processes.     

Graphics processing unit‐accelerated bounding for branch‐and‐bound applied to a permutation problem using data access optimization

Branch‐and‐bound (B&B) algorithms are attractive methods for solving to optimality combinatorial optimization problems using an implicit enumeration of a dynamically built tree‐based search space. Nevertheless, they are time‐consuming when dealing with large problem instances. Therefore, pruning tree nodes (subproblems) is traditionally used as a powerful mechanism to reduce the size of the explored search space. Pruning requires to perform the bounding operation, which consists of applying a lower bound function to the subproblems generated during the exploration process. Preliminary experiments performed on the Flow‐Shop scheduling problem (FSP) have shown that the bounding operation consumes over 98% of the execution time of the B&B algorithm. In this paper, we investigate the use of graphics processing unit (GPU) computing as a major complementary way to speed up the search. We revisit the design and implementation of the parallel bounding model on GPU accelerators. The proposed approach enables data access optimization. Extensive experiments have been carried out on well‐known FSP benchmarks using an Nvidia Tesla C2050 GPU card. Compared to a CPU‐based single core execution using an Intel Core i7‐970 processor without GPU, speedups higher than 100 times faster are achieved for large problem instances. At an equivalent peak performance, GPU‐accelerated B&B is twice faster than its multi‐core counterpart. Copyright © 2013 John Wiley & Sons, Ltd.     

Finished surface morphology,microstructure and magnetic properties of selective laser melted Fe-50wt% Ni permalloy

This work focuses on the structure and magnetic properties of Fe-50wt% Ni permalloy manufactured from the pre-alloyed powder by selective laser melting (SLM). The selective laser melted (SLMed) alloys were characterized by a 3D profilometer,optical microscope, scanning electron microscope, X-ray diffraction, etc. The effects of the volume energy density of laser(LVED) on structure, and magnetic properties with coercivity ( H _c ), remanence ( B _r ), and power losses ( P     

A parallel bi-objective hybrid metaheuristic for energy-aware scheduling for cloud computing systems

In this paper, we investigate the problem of scheduling precedence-constrained parallel applications on heterogeneous computing systems (HCSs) like cloud computing infrastructures. This kind of application was studied and used in many research works. Most of these works propose algorithms to minimize the completion time (makespan) without paying much attention to energy consumption.We propose a new parallel bi-objective hybrid genetic algorithm that takes into account, not only makespan, but also energy consumption. We particularly focus on the island parallel model and the multi-start parallel model. Our new method is based on dynamic voltage scaling (DVS) to minimize energy consumption.In terms of energy consumption, the obtained results show that our approach outperforms previous scheduling methods by a significant margin. In terms of completion time, the obtained schedules are also shorter than those of other algorithms. Furthermore, our study demonstrates the potential of DVS.     

Prediction of Tool Wear in the Turning Process Using the Spectral Center of Gravity

The recent increase in machining productivity is closely related to longer tool life and good surface quality. In the present study, an experimental technique is proposed to evaluate the performance of a cemented carbide inset during the machining of AISI D3 steel. The aim of this technique is to find a relationship between the vibratory state of the cutting tool and the corresponding wear during machining in order to detect the beginning of the transition period to excessive wear. A spectral indicator named spectral center of gravity, SCG, is proposed to highlight the three phases of tool wear using the spectra of the accelerations measured. Very promising results are obtained which can be used to underpin an industrial monitoring system capable of detecting the onset of transition to excessive wear and alerting the user of the end of the tool’s life. The purpose of this study is to review the vibration analysis techniques and to explore their contributions, advantages and drawbacks in monitoring of tool wear.     

New upgrading options of heavy oil fractions from Algerian refineries

The global demand for petroleum products is increasing year by year quantitatively and qualitatively. Besides the clear products supplied by the fractionation of crude oil, there are a number of heavy petroleum products obtained from the secondary treatment, which are not the proper use; they are often used as components of fuel oil. Now, all the refineries are equipped by hydrotreating facilities aimed to transform these fractions heavy in market value of products most important. Consequently, the choice of adequate processes is a major challenge for oil refineries. The objective of this work is to value these heavy cuts by the catalytic cracking process, which is the most suitable method and is the only one existing in Algeria.