Sensor nodes are innovative devices that can perform measurements on a large scale and communicate over a network. One of the most significant problems regarding the sensor nodes is how to supply power to a large number of devices. For this reason, they greatly benefit from energy harvesting techniques which can provide energy recovered directly from the environment. A study of the design and the modeling of an autonomous sensor node, powered by a vibrational piezoelectric harvester, is reported here. Subject of the first part of the analysis is a piezoelectric bimorph: an analytical model is proposed in order to estimate the performance, giving particular attention to the optimal mechanical and electrical parameters. The model is then validated through experimental tests, assuming different kinds of real scenarios. Then the results are used to design a device that can benefit from this harvester. In particular a wireless sensor node is developed, for which the energy scavenging ensures energy autonomy and long-term operability. Thanks to a particular harvesting circuit and opportune algorithms for energy management, this system is able to extract energy from vibrations and store it into capacitors. The embedded accelerometer and a wireless module make this device ideal for Structure Health Monitoring purposes.

In this paper, an optimal control strategy (i.e., offset settings system) based on the new Multi-objective Particle Swarm Optimization with Differential Evolution (MOPSO-DE) technique is developed and presented. The MOPSO-DE algorithm is used for calculating the optimal positions (i.e., offset settings) for the cutting tools in lathe machines. This optimal control strategy yields interesting results without a need to go through the complex mathematical modeling of the lathe system. The proposed technique is validated considering a real-world industrial system. This strategy is designed to take an action every 20 pieces, and it takes only 2.5 sec to run the code and optimally calculate the new settings. The control strategy is implemented using two high precision linear stepper motors. By implementing the new optimal control strategy, the estimated number of the defective pieces per day can be reduced by 85%.

Using a coarse time discretisation for saving calculation effort will induce non-uniform heat input within thermal-transient analyses which include translational rigid body motions by the technique of discrete displacement adjustment. We are going to show, why these non-uniformities are generally unavoidable and how a suitable choice of time step size pre-minimizes their consequences. Afterwards, the amount and location of the remaining load-bumps are analytical deduced for an arbitrary motion. With this information, we develop a correction method based on arithmetic calculations to avoid these numerical caused errors. For practical use, the correction is applied as an algorithm to the solution process of analyses with spatial discretized motion partners. We finish by demonstrating the performance of the correction.

Stability of a gantry crane was a challenge in its structure design. A new risk-based stability assessment approach was proposed in this paper. Analytical method was introduced firstly, and then finite element method was adopted to evaluate the stability of square bar. In order to verify the finite element models, results of buckling analysis were compared with the results of analytical method. Secondly, this finite element analysis was applied in stability assessment of a gantry crane, and through parameterized analysis risk elements were identified. Finally, risk-based stability assessment was applied to this gantry crane, and neural network algorithm was adopted to evaluate the risk elements which were defined by finite element analysis. The evaluating results were well consistetent with statistical data, which indicated this risk-based stability assessment approach was reliable which showed a potential in engineering application.

This paper discusses the application of second order mode controls to hydraulic valve-cylinder drives with a special focus on the limitations resulting from nonlinear dynamic effects in flow control valves. Second order sliding mode algorithms appear highly attractive in the successive implementation of sliding mode control, achieving continuous control inputs, while maintaining the main properties of sliding modes. Under certain model assumptions, some of these controllers may even be applied as output feedback controllers. However, intrinsic nonlinear dynamic effects of hydraulic valves such as slew rates and time delays arising in the amplification stages, limits the applicability of such methods, and may lead to partial losses of robustness and limit cycles. These properties are analyzed and experimentally verified, and compensation methods are proposed. The application of the second order sliding algorithm known as the super twisting controller is considered for output feedback control and compared with conventional first order sliding mode control. The controllers under consideration are applied for position tracking control of a hydraulic valve-cylinder drive exhibiting strong variations in inertia- and gravitational loads. Results demonstrate that the super twisting algorithm may be successfully applied for output feedback control of hydraulic valve-cylinder drives, with modifications guaranteeing robust control performance in a small vicinity of the control target.

The paper deals with a project aimed to improve the reliability of a condition monitoring system applied on gearboxes installed on rolling mills. In this context, to properly set up the algorithm, it is necessary to have measurements associated both to standard operating conditions and to malfunctioning. The latter, not being able to be experimentally generated, can be simulated by developing numerical models of the machine under varying conditions. The outputs generated, corresponding to different fault conditions associated with the main common failures of the elements that constitute the transmission, will provide a useful data base to tune the algorithm of condition monitoring.

In this paper, a methodology for real time identification of various singularities for various workspace types of parallel robots is proposed. Python 3D simulation software has been developed to position the moving platform of the robot’s CAD model through pre-defined rules in order to solve specific problems including singularity identification, obstacle avoidance, and path planning. The system is designed to identify the moving platform’s best possible pose. Boolean logic is used to identify valid path trajectory through parametric sweep search method. Joint constraints are checked to validate the platforms’ positions using the actuators’ stroke length, their angles, and any possible collisions. Solutions for any desired pose, based on line collision and mesh model algorithms, are then found. The path, position and workspace data are verified against a kinematic model of the robot, developed in Solid works and Matlab software tools. The simulation system has been successfully tested using various n-dimensional interpolations based on the given case study.

The numerical analysis of heat transfer by finite element method (FEM) has been used widely. It is usually assumed that the parameters relevant to the heat transfer process are accurately known. However, many of these parameters may vary in a random way in reality. The reliability of the heat transfer performance is needed to be evaluated. The paper introduces an accurate, efficient sensitivity analysis method to compute the FEM response with respect to input parameters. Combining this sensitivity analysis, first order reliability method (FORM) algorithm based stochastic finite element method (SFEM) method is used to evaluate the reliability of the limit state for heat conduction of a benchmark plate with input uncertainties.

In this contribution a web-based assessment framework for CAD data is proposed which has been developed based on the experience the authors made giving undergraduate courses at a German university. The framework is the backbone of a hybrid teaching concept combining conventional classroom lessons with e-learning elements. In-between the classroom lessons the students receive instructions on a particular modeling task via a web-interface. The same interface is used to hand in solutions in form of CAD files. Teachers who need to assess these solutions are supported by a semi-automated analysis of the CAD geometry. An algorithm compares each solution with a reference solution in order to reveal typical modeling mistakes. After the assessment is completed the students receive a feedback on their work. A case study on the application of the teaching concept in a course with 691 participants held during summer term 2013 reveals the positive experience the authors made using the system and points to some issues that need to be improved in the future.

Since the 3D printing technology was applied to metallic materials, the conformal cooling channel has been widely utilized for injection mold with a higher cooling efficiency. The conformal cooling channel provides higher degree of freedom in shape and size. It is more effective to apply it to convex core accumulating more heat than the concave side. However, there has not been a standard design method for the conformal cooling channel. Depending upon channel design, the cooling efficiency would not be improved. Sometimes dead flow zones could be made in the channel. Currently every engineer makes the cooling channel design of his own. In this work, we proposed an automated optimum design method for the conformal cooling channel. In the proposed design method, whole product surface is divided into smaller domains with equal thermal energy by Voronoi diagram algorithm. Then cooling channels are installed along the centers of the domains by a binary branching algorithm. The objective of the optimization was the minimization of the product surface temperature deviation. The cooling channels are branching out over the product surface through the evolutionary steps until the objective was satisfied. The injection molding CAE analysis was done by Moldflow, and the optimization by PIAnO. The sample product was an eye-glass lens product.

Todays’ product development process is characterized by an increasing use of embedded software solutions integrated into mechatronic products. The development is more and more translocated into a virtual environment. New software methods and tools have to be developed. Industry 4.0 is an approach to highlight the tendency of modern development. Communication between smart products, communication via internet technologies, cyber-physical systems and the Internet of Things are the basis of Industry 4.0. Owing this development, used project management methodologies have to be adjusted. In special the well-known V-Model is now extended to the W-Model to cope with the new requirements like communications between different disciplines. New approaches in virtual development have to be adapted to modern teaching techniques. Therefore a course for first semester mechanical engineering students is conducted by the department of Computer Integrated Design at the Technische Universität Darmstadt. Industry 4.0 fundamentals are taught as well as the development process underlying the so called W-Model. The students will apply this knowledge while they participate in exercises. A web-based tutorial is provided every week with different learning packages. With these learning packages, the students learn to use the project management techniques as well as software development techniques to solve different tasks. Later complex data structures and algorithms can be coded and are applied. The software development techniques, established in development of information technologies, gets more important in mechanical engineering. Therefore the students learn these aspects. Over three months length the students work in groups and use all their skills to realize a bigger software-project — a digital factory. They use a virtual testing environment (ViTMeS 3.0) to develop their solution. The presented ViTMeS 3.0 is a further development of a virtual testing environment used in last year’s team work. Later they can test their code with a real life example. This example, the digital factory, built with LEGO Mindstorms, is an important part of teaching students the foundations of communication and information techniques as well as software development and programming skills. The last step of the team work is the coding of a graphical user interface for appropriate visualization.

In this paper, we investigate the computational efficiency of explicit and implicit integration schemes for hyperelastic-plastic combined hardening plasticity and examine the influence on the simulated springback in sheet metal forming. Due to the deviatoric character of the evolution equations, the finite strain combined hardening model discussed here is integrated by means of the exponential map algorithm in order to fulfil plastic incompressibility. We focus here on different possibilities of evaluating the exponential tensor functions of the material model. One option is to use the spectral decomposition to evaluate the exponential tensor functions in closed form. Alternatively, the latter functions can be evaluated by Taylor series expansion. Furthermore, we examine the potential of an explicit formulation of elasto-plasticity with combined hardening regarding accuracy and efficiency. The material model equations have been implemented as user material subroutines UMAT and VUMAT for use in the commercial solvers ABAQUS/Standard and ABAQUS/Explicit, respectively. The numerical models are applied to the finite element simulation of draw bending, where the forming step is simulated both in implicit and explicit manner, whereas the ensuing springback step is carried out only implicitly.

This paper summarizes a research project in the field of design and manufacturing of a water brake dynamometer for power testing facilities. In the current study, the design process of a water brake with drilled rotor disks is presented. This process is examined against the development of a water brake for a 4MW gas turbine power measurement at 15,000 RPM speed. The proposed algorithm is based on vital assumptions such as; applying product designing issues and limited modular analysis that urges the disciplinary attitude and leads to the possibility of rapid development, easy maintenance and ease of access. The final scheme is divided into six disciplines with functional classification. These disciplines are rotor, housing, cabs, pedestals, skid and accessories. Accessories, itself, consist of cooling system, lubricating system and control unit. Every discipline has its special function and could be optimized separately. It is possible to change any discipline specification without affecting other disciplines modularity. Using FEM software makes it easy to analyze the mechanical component for static and dynamic load condition regarding complex initial and boundary condition. But it is not wise to analyze whole system for designing a product due to numerical calculation errors. Besides, it is not necessary to use calculation to select machine elements. Rotor dynamics is investigated with modal analysis and related Campbell diagram. Also, transient analysis on housing, rotor and load cell arm is presented. The modal analysis on pedestals and skid is performed to predict the structural behavior under periodic loads caused by rotating unbalance. The process presented in this paper is a method for design of water brake dynamometer. Modularity presented by a product tree and a trend for design cycles associated with computer simulation are the basis of this method. The final product that is designed with this algorithm is successfully manufactured and tested.

In this research, a novel inverse design algorithm called, Elastic Surface Algorithm (ESA), is developed for viscose and inviscid external flow regimes. ESA is a physically based iterative inverse design method that uses flow analysis code to estimate the pressure distribution on the solid structure, i.e. airfoil, and a 2D solid beam finite element code to calculate the deflections due to the difference between the calculated and target pressure distribution. The proposed method is validated through the inverse design of three different airfoils. In addition, two design examples are presented to prove the robustness of the method in various flow regimes. Also, the convergence rate of this method is compared with flexible membrane method (MGM) and Ball-Spine Algorithm (BSA) methods in inviscid flow regime. The results of this study showed that not only the ESA method is an effective method for inverse design of airfoils, but also it can considerably increase the convergence rate in transonic flow regimes.

CFD (Computational Fluid Dynamics) algorithms are nowadays a necessary tool in the aerospace science, as their application allows for the prediction of the aerodynamic characteristics of complete aircraft configurations in a relatively short period of time. A brief presentation and evaluation of such a recently developed academic code, named Galatea, is the main goal of this study. Galatea employs the Reynolds Averaged Navier-Stokes (RANS) equations, discretized with a node-centered finite-volume scheme on three-dimensional unstructured hybrid grids for the simulation of inviscid and viscous compressible fluid flows. For the turbulence prediction appropriate turbulence models (k-ε, k-ω and SST) have been incorporated, while for the acceleration of the solution an agglomeration multigrid scheme along with a suitable parallelization strategy are employed. For the assessment of this algorithm runs over the wing-body and the wing-body-horizontal tail NASA Common Research Model (CRM) configurations were performed, allowing for a comparison in terms of accuracy of the obtained results with the experimental wind tunnel data, as well as with the computational results of corresponding reference solvers.

The diffusion process is very important in many engineering applications. However, there is a shortage of data about diffusion, especially between liquid mixtures (such as water and glycerin, water and salt, etc.), which justifies the search for simple and accurate experimental techniques. Optical techniques are recognized as powerful tools to investigate fluid flow phenomena in transparent media. The aim of this paper is the development of an optical experimental technique, based on Diffractive Optical Element (DOE) Schardin’s schlieren # 2, for measuring liquid diffusion coefficient. This technique is then coupled to a new data treatment, based on correlation algorithms of the Particle Image Velocimetry (PIV) type, allowing the use of displacements recorded in the entire cell rather than just between two points. Principles of the method and preliminary experimental results for the diffusion of a 1.75 M (moles/l) aqueous solution of common salt (NaCl) in pure water are given. These results are in good agreement with the literature.

A quite important topic of structural dynamics is deterministic mechanical systems subjected to stochastic dynamic actions, such as for wind or earthquake. IN such cases structural response have to be properly evaluated by a stochastic approach. Unfortunately for nonlinear mechanical systems only in a very few cases exact solutions are available, and usually simply approximate solutions should be used. A well known one is stochastic equivalent linearization, easy and simple from the conceptual point of view. Moreover it needs of specific numerical techniques to be properly implemented, whose complexity increases in case of non stationary conditions. In this paper a procedure to solve covariance analysis of stochastic linearized systems in case of non stationary excitation is proposed. The no stationary Lyapunov differential matrix covariance equation for the linearized system is solved by using a numerical algorithm that updates linearized system matrix coefficients step by step. This by a predictor-corrector procedure applied to a Euler-implicit integration scheme for the matrix covariance analysis. It is described in details to be simpler implemented by other researchers, and then applied to a typical and important applicative case, that is seismic response of a Bouc Wen Single Degree of Freedom (SDoF) system. Seismic input processes is modeled as linear filtered white noise non stationary separable process. Accuracy and computational costs are analyzed showing the efficiency of the proposed integrating procedure.

Bearing faults detection at the earliest stages is vital in avoiding future catastrophic failures. Many traditional techniques have been established and utilized in detecting bearing faults, though, these diagnostic techniques are not always successful when the bearing faults take place in gearboxes where the vibration signal is complex; under such circumstances it may be necessary to separate the bearing signal from the complex signal. The objective of this paper is to assess the effectiveness of an adaptive filter algorithms compared to a Spectral Kurtosis (SK) algorithm in diagnosing a bearing defects in a gearbox. Two adaptive filters have been used for the purpose of bearing signal separation, these algorithms were Least Mean Square (LMS) and Fast Block LMS (FBLMS) algorithms. These algorithms were applied to identify a bearing defects in a gearbox employed for an aircraft control system for which endurance tests were performed. The results show that the LMS algorithm is capable of detecting the bearing fault earlier in comparison to the other algorithms.

This paper presents a new multi-objective evolutionary algorithm (MOEA) for optimum aerodynamic design of horizontal-axis wind turbines (HAWT). The design problem is set to find the blade shape such that optimizing multi-objective at different airfoil profiles. Combined Blade Element Momentum (BEM) theory and two different algorithms (Genetic (GA) and Enumeration) are used. Flow around subsonic airfoils is analyzed using XFOIL software. WINDMEL III wind turbine is selected to improve its aerodynamic performance with different airfoil profiles technique of National Renewable Energy Laboratory (NREL) family. Employing Genetic Algorithm embodied in Blade Element Momentum theory to calculate power, thrust and starting torque coefficients that are the fitness function. Another method, Enumeration method, is used to enhance evolutionary method results. The optimum solution acquired from combination of Genetic Algorithm and Blade Element Momentum theory of three blades configuration increased power coefficient by (25.8 %) and thrust coefficient by (16.6%). Enumeration method results increased power coefficient by (13.8%), while thrust coefficient decreased by (0.2%) from the original design. In general, the evolutionary method of combined GA and BEM theory with different airfoil profiles technique improved the turbine aerodynamic performance, and the results are in good agreement with other published papers.

The open sump is a typical inlet passage for small to middle-sized pumping station. It is important for the efficiency and safe operation of pumps that the open sump has an optimum design. The flow through the sump and into the pump is calculated using CFD. The incompressible N-S equations are solved by the finite volume method. The RNG k-ε turbulence model and the SIMPLEC algorithm for pressure-velocity coupling are used. Many different designs for the open sump are considered, the results of which are compared based on common criteria to evaluate the sump performance. Design values for the width, the depth of submergence and the bellmouth shape are derived.