On the dynamics of inertial drives of vibrating machines – effects of energy and frequency pulsation

In this paper, we describe a simulation combined with genetic algorithm for job shop scheduling problems in mechanical manufacturing and engineering. In first phase of the scheduling and real-time control system, optimization algorithms for scheduling will reduce drastically the computational burden on simulation, while in second phase, simulation can provide a problem free execution of the predictive plans and can be used to check the validity of the schedule, and most importantly, to improve or fine tune the schedule in mechanical manufacturing area. Therefore combination with genetic algorithm and optimization algorithm for job shop scheduling has significance for guiding the practical mechanical manufacturing.KeywordsJob shop schedulingGenetic algorithmExtendSimModeling and simulationMechanical manufacturing

Constrained optimization problems in mechanical engineering are very difficult for the optimization algorithm. In 2013, an improved version of constrained differential evolution, named ArATM-ICDE was proposed to optimize the constrained optimization problem. An archiving-based adaptive trade-off model (ArATM) was constructed to handle the constraints; resulting in an algorithm referred to as ArATM-ICDE. This paper applies ArATM-ICDE to solve constraint optimization problems in mechanical engineering. We also combine the penalty technique for constraint handling into the ICDE, named Penalty-ICDE; which compares the abilities of the constraint handling techniques. Our experiments were conducted on ten widely used constraint engineering optimization problems. The experiment results proved the ArATM-ICDE to be more reliable than the Penalty-ICDE. Additionally, ArATM-ICDE consumed a lesser number of function calls than Penalty-ICDE. This paper further compared the effectiveness of ArATM-ICDE and Penalty-ICDE with eight state-of-the-art algorithms, which revealed that ArATM-ICDE and Penalty-ICDE produced solutions of higher quality than those produced by the comparative algorithms. The ArATM-ICDE also consumed less effort in its process.

There is an industrial trend of increasing technological effectiveness of production and growing autonomy of factories, resulting in generation of huge amounts of raw data that can be used to improve efficiency and continuity of industrial plants operation. Big data collection, processing and analysis technologies are already being actively implemented. Further use of big data will help with a variety of tasks, such as optimization and process monitoring, quality control of equipment and produced parts, modeling and forecasting of the facility operation and other mechanical engineering challenges. A new method of creation of a two-level neural network structure is proposed, designed to solve a number of problems by training individual neural networks for each subset of data used in the task at hand. This method combines two levels of information processing: the first level of the neural network classifier and the second level, which includes several neural network analyzers. Depending on the specific subject area and the data sets available, it is possible to use the method to solve various problems in mechanical engineering. The method allows to add new neural network analyzers and expand the scope of application. The practical application of the method in solving the problem of text message sentiment analysis is shown and an example of the Python programming language software implementation of the two-level structure is given. Use cases for the two-level structure method in mechanical engineering tasks are proposed. In addition, the proposed method can be used as a part of the hybrid intelligent information system that includes mivar expert systems. Combining neural networks with mivar expert systems as part of a hybrid intelligent information system is a promising direction for the development of artificial intelligence for mechanical engineering.

In the current research, problems in engineering are becoming more and more prominent. One of the classes of engineering problems in engineering design problems, where a set of variables is calibrated in order for the optimization function to have a minimal or maximal value. This function considers energy efficiency, cost efficiency, and production efficiency in engineering design. One of the ways such problems are solved is metaheuristics. In this paper, we demonstrate how Dingo Optimization Algorithm (DOA) can be used to solve certain optimization problems in mechanical engineering. Firstly, a brief review of the DOA and its biological inspiration is given, along with the most important formulae. The pseudo-code for this algorithm was written using MATLAB R2020a software suite. Dingo Optimization Algorithm (DOA) was used to optimize engineering problems, such as pressure vessel optimization, stepped cantilever beam, car side-impact, and cone clutch optimization. The results presented in this paper show that the DOA can produce relevant results in engineering design problems.

Numerical methods are described as techniques by which several mathematical problems are formulated, because they may be easily solved with arithmetic operations. These methodologies have a great impact on the current development of finite element theory and other areas. We have given a short study of numerical methodologies applied in fluid flow and heat and mass transfer problems in mechanical engineering which includes finite difference method, Finite element method, Boundary value problems (general), Lattice Boltzmann’s methods, Crank-Nicolsan scheme methods, boundary integral method, Runge-Kutta method, Taylor series method and so on. We have discussed some phenomena taking place in fluids such as surface tension, coning, water scattering, Stokes law, gravity-capillary, and unsteady free-surface flows, swirling, and so on. We have also analyzed boundary value problems on boundary problems, eigenvalue problems and found a numerical way to solve these problems. We have presented different numerical methods applied to different fundamental modeling approaches in heat transfer and the performance of the mechanisms (modes) vary concerning the methods applied. The paper is dedicated to demonstrating how the methods are beneficial in solving real-life heat transfer problems in engineering applications. Results of the parameters like thermal conductivity, energy flux, entropy, temperature, etc. have been compared with the existing methods

A genetic algorithm (GA) is hybridized with an artificial immune system (AIS) as an alternative to tackle constrained optimization problems in engineering. The AIS is inspired in the clonal selection principle and is embedded into a standard GA search engine in order to help move the population into the feasible region. The procedure is applied to mechanical engineering problems available in the literature and compared to other alternative techniques.

A genetic algorithm (GA) is hybridized with an artificial immune system (AIS) as an alternative to tackle constrained optimization problems in engineering. The AIS is inspired in the clonal selection principle and is embedded into a standard GA search engine in order to help move the population into the feasible region. The procedure is applied to mechanical engineering problems available in the literature and compared to other alternative techniques.

A great deal of problems in engineering, but for example also in physics, biology or sociology deals with equilibrium solutions of nonlinear equations and their stability. By equilibrium solutions one can understand steady state solutions or time periodic solutions. However to be more specific we want to concentrate on the case which seems to be of greatest practical importance namely the case of loss of stability of a stable steady State equilibrium position. Some arbitrarily choosen examples in the above mentioned fields are in engineering buckling phenomena in structural mechanics ([24]) or the onset of a hunting motion of a railvehicle ([20]). In biology the change in the behavior of an animal from backing up into an attacking mode ([35]) or in sociology the sudden readiness of the whole population of a democratically governed country to go to war. In physics a good example is the behavior of a fluid layer heated from below ([11]). To all these examples it is common that a distinguished parameter is varied and that at a critical parameter value a qualitative change in the behavior of a system takes place, i.e. the original equilibrium looses its stability. The special parameter is for the buckling problem the magnitude of loading, for the railvehicle the speed, for the animal it could be a measure of the closeness of an invader to its nest, for the country getting ready to start a war it could be the amount of humiliation suffered from a dictatory regime and for the fluid layer it is the temperature difference between the lower and the upper surface of the layer.

Obituary

Because of its magnificent mechanical and chemical effects, acoustic cavitation plays an important role in a broad range of biomedical, chemical and mechanical engineering problems. Particularly, irradiation of the multiple frequency acoustic wave could enhance the effects of cavitation. The advantages of employment of multi-frequency ultrasonic field include decreasing the cavitation thresholds, promoting cavitation nuclei generation, increasing the mass transfer and improving energy efficiency. Therefore, multi-frequency ultrasonic systems are employed in a variety of applications, e.g., to enhance the intensity of sonoluminenscence, to increase efficiency of sonochemical reaction, to improve the accuracy of ultrasound imaging and the efficiency of tissue ablation. Compared to single-frequency systems, a lot of new features of bubble dynamics exist in multi-frequency systems, such as special properties of oscillating bubbles, unique resonances in the bubble response curves, and unusual chaotic behaviours. In present paper, the underlying mechanisms of the cavitation effects under multi-frequency acoustical excitation are also briefly introduced.

The article discusses a new scientific field — cybernetical neuroscience — which studies mathematical models adopted in computational neuroscience using methods from cybernetics (the science of control and communication in living organisms, machines, and society). It also examines the practical application of results obtained from research on mathematical models. Key tasks, methods, and results in cybernetical neuroscience are outlined. As an example some results in neurointerface control and machine learning methods from the Institute for Problems in Mechanical Engineering, Russian Academy of Sciences (IPME RAS) are presented.

An extensive investigation into a fully pulsed jet has been performed with a single wire hotwire anemometer operated in a constant temperature mode to study the influences of varying mean exit velocity of the jet and pulsing frequency on the velocity field and turbulence quantities. The results of radial profile test across the jet show that the pulsed jet is axisymmetric. The test of jet centerline location demonstrates that the jet follows a straight line trajectory to propagate downstream. From the axial measurements, it is shown that the pulsed jet behaves like a steady jet after the pulsation effects have diminished towards furthest downstream locations, hence the existence of two distinct regions namely the pulsed dominated region and the high turbulence steady jet region is proved. However, the existence of the two distinct regions is strongly dependent on the mean exit velocity and pulsing frequency. At a high mean exit velocity and a low pulsing frequency, the high turbulence steady jet region can not be identified displaying no transition region. Moreover, at high mean exit velocities with a constant pulsing frequency, the aggregate turbulence intensity decreases more slowly along the downstream positions. Amplifications of the root-mean-square level of centerline-aggregate turbulence associated with an increasing mean exit velocity contribute to this case. At higher pulsing frequencies with a constant mean exit velocity, the aggregate turbulence intensity decreases more rapidly along the downstream positions as a result of the attenuations of the root-mean-square level of centerline-aggregate turbulence. Skewness and flatness along the downstream positions depart from the symmetry value of 0 and Gaussian value of 3, respectively as the mean exit velocity increases with a constant pulsing frequency. At higher pulsing frequencies with a constant mean exit velocity, skewness and flatness become lower in which approach the symmetry value of 0 and Gaussian value of 3, respectively. From the radial measurements, at an increasing pulsing frequency with a constant mean exit velocity the radial profile of mean axial velocity becomes narrower. As the mean exit velocity is increased at a constant pulsing frequency, narrower radial profiles result. Also, the radial distribution of aggregate turbulence intensity has smaller levels as the pulsing frequency is increased at a constant mean exit velocity. As the jet propagates downstream the levels of radial distribution of the aggregate turbulence intensity across the jet reduce gradually. At a constant pulsing frequency, amplification of the root-mean-square level of aggregate turbulence occurs as the mean exit velocity is increased which leads to the higher levels of radial distribution of aggregate turbulence intensity. Moreover, the radial profile of relative turbulence energy becomes broader as the pulsing frequency is increased at a constant mean exit velocity. However, there is some evidence demonstrating the narrower radial profiles as the pulsing frequency increases. As the mean exit velocity is increased at a constant mean exit velocity, a broader radial profile is produced. The levels of triple-products across the jet reduce as the pulsing frequency is increased at a constant mean exit velocity but the levels increase as a result of an increasing mean exit velocity at a constant pulsing frequency. Skewness and flatness in the radial direction are relatively lower at an increasing pulsing frequency with a constant mean exit velocity whereas at an increasing mean exit velocity with a constant pulsing frequency their values become higher. Furthermore, the jet volume flow rate relative to that at the jet exit significantly reduces as the Reynolds number increases. The jet growth and normalized volume flow rates are found to be higher than that of steady jets even up to further downstream position associated with the broadening radial profiles of mean axial velocity. At the low mean exit velocity of 13.7 m/s, the jet growth and jet volume flow rate at the low pulsing frequency of 10 Hz are higher than those at the high pulsing frequency of 25 Hz. However, as compared with the jet growth and volume flow rate phenomena at the low mean exit velocity of 13.7 m/s, a striking issue appears at the high mean exit velocity of 34.4 m/s demonstrating that the jet growth and jet volume flow rate at the low pulsing frequency are lower than those at the high pulsing frequency.

Inertial microfluidics leverages hydrodynamic forces to manipulate and separate particles at high flow speeds. Benefiting from its simplicity, high throughput, and accurate manipulation, inertial microfluidics has been extensively studied for processing particle and cellular samples. Most research in the field has focused on steady flows, where the flow speed and direction are constant. In real-world applications, pumping systems are never perfect and often experience flow variations due to device vibration, tubing compliance, or pressure fluctuations. Understanding the influence of flow pulsation on particle inertial focusing and separation is of great importance. Therefore, this work investigates the effects of flow pulsation on inertial focusing and separation in a sinusoidal microchannel. First, we analyzed the dynamic characteristics of the microfluidic system using a hydraulic-electric analogy and determined the critical frequency of the system (fc) as ∼9 Hz. Next, we experimentally investigated the effects of pulsatile flows on the inertial focusing of microparticles and compared them with steady flows. Additionally, the effects of pulsation amplitude and frequency were studied, and the particle distribution in the time domain was also examined. Finally, we evaluated the influence of flow pulsation on the separation of a binary particle mixture. While particle focusing and separation remained stable at pulsation frequencies above the critical frequency of the system, they were negatively affected at lower frequencies. At 5 Hz, the purity decreased notably for 15 μm particles (from 94% to 71%) and slightly for 10 μm particles (from 99% to 94%), while at 10 Hz, purities remained close to the steady flow values. The results showed that the pulsation frequency was a more critical parameter than the pulsation amplitude for particle inertial focusing and separation performance.

Heat transfer in a pulsed bubbling fluidized bed

An object-oriented knowledge based system has been implemented to solve simple quantitative problems in engineering. In this system, knowledge consists of the laws of engineering represented by Formulae as found in a text book, linked to the data on corresponding quantities. The Object-Oriented Paradigm has successfully provided a natural and uniform representation of this kind of quantitative knowledge and facilitated problem solving. This has been achieved using the Problem Decomposition strategy, representing the problem space as an AND/OR tree. The Depth-first Recursive Search was then used to retrieve the formulae and data in the correct sequence to solve the problem. The system has been implemented on a Sun Spare station using the C++ development environment, Objectworks. It has been used to solve a number of simple problems in mechanical and electrical engineering.