This paper describes an analysis of pulsed lasers micro-drilling of different metals. Study focuses to an optodynamic phenomenon which appears as thermal effects induced by laser light pulses and ...leads to dynamic process manifested as ultrasonic shock waves propagating into the sample material. The shock waves are detected by a non-contact optical method by using arm compensated Michelson. Monitoring of the main parameters of the micro drilling such as material ablation rate and efficiency was realized by analysis of the optodynamic signals. The process is characterized by decreasing ablation rate that leads to the finite hole depth. The experimental part of study comprehends a comparison between various metals. In order to describe decreasing ablation rate a theoretical model based on the energy balance is proposed. It considers the energy/heat transfer from the laser beam to the material and predicts a decreasing drilling rate with an increasing number of successive laser pulses. According to the proposed model, the finite depth of the hole appears as a consequence of the increasing surface area through which the energy of the laser beam is conducted away to the material around the processed area. Decreasing ablation rate and the finite hole depth predicted by model were in good agreement with the experimental results.
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•A micro packed-bed reactor was theoretically and experimentally characterized.•A residence time distribution (RTD) was predicted by lattice Boltzmann method.•Numerical simulations ...were in good agreement with biosensor-based RTD experiments.•A reactor with immobilized lipase B was very efficient for selected esterification.•Very efficient scale-up of the packed-bed reactor enabled high productivities.
A micro packed-bed reactor (µPBR) based on two-parallel-plates configuration with immobilized Candida antarctica lipase B in the form of porous particles (Novozym® 435) was theoretically and experimentally characterized. A residence time distribution (RTD) within µPBRs comprising various random distributions of particles placed in one layer was computationally predicted by a mesoscopic lattice Boltzmann (LB) method. Numerical simulations were compared with measurements of RTD, obtained by stimulus-response experiment with a pulse input using glucose as a tracer, monitored by an electrochemical glucose oxidase microbiosensor integrated with the reactor. The model was validated by a good agreement between the experimental data and predictions of LB model at different conditions. The developed µPBR was scaled-up in length and width comprising either a single or two layers of Novozym® 435 particles and compared regarding the selected enzyme-catalyzed transesterification. A linear increase in the productivity with the increase in all dimensions of the µPBR between two-plates demonstrated very efficient and simple approach for the capacity rise. Further characterization of µPBRs of various sizes using the piezoresistive pressure sensor revealed very low pressure drops as compared to their conventional counterparts and thereby great applicability for production systems based on numbering-up approach.
In this paper, we present a comparison of tribological behaviour between conventional gas nitrided and PVD CrN coated extrusion dies used in industrial production. We found that PVD CrN coated dies ...proved to be superior to nitrided ones.
Intelligent systems are process coupled with robotics in industrial usually settings, though they may be used as diagnostic systems connected only to passive sensors. In this paper we use a new ...method which combines an intelligent genetic algorithm and multiple regression to predict the hardness of hardened specimens. The hardness of a material is an important mechanical property affecting mechanical properties of materials. The Microstructures of the hardened specimens are very complex and cannot be described them with the classical Euclidian geometry. Thus, we use a new method, i.e. fractal geometry. By using the method intelligent-system, genetic programming and multiple regression, improved production the process laser-hardening increases because of the decreased time of the process and, the improved increased topographical property of the used materials. The genetic-programming modelling results show a good agreement with teh measured hardness of the hardened specimens.
The porous structure of a material is an important mechanical property that affects the hardness of materials. We cannot apply Euclidian geometry to describe the porosity of hardened specimens ...because porosity is very complex. Here we use fractal geometry to describe the porosity of robot laser-hardened specimens, hi this paper, we describe how the parameters (speed and temperature) of the robot laser cell affect porous metal materials using a new method, fractal geometry. We describe a new technological process of hardening, which can decrease the porosity of hardened specimens. The new process uses robot laser hardening with an overlapping laser beam. First, we hardened specimens using different velocities and temperatures and then repeated the process, hi addition, we present how the speed and temperature affect the porosity in two different processes of robot laser hardening. Furthermore, we present the improved results after hardening with the overlap process. To analyse the results, we used one method of intelligent system, neural networks and a relationship was obtained by using a four-layer neural network. We compare both processes.
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