A B S T R A C T In this paper, the rather complex three-dimensional (3D) fatigue crack growth behaviour in a single-edge notched (SEN) specimen with an inclined plane of the initial crack under torsion loading is investigated with the aid of ADAPCRACK3D programme and by application of a recently developed 3D fracture criterion. It will be shown that the computationally simulated results for fatigue crack growth in the FE model of the specimen are in good agreement with experimental findings for the development of spatially twisted and warped crack faces in the real laboratory test specimen. Consequently, also for this case with a rather complex 3D crack growth behaviour, the functionality of the ADAPCRACK3D programme and the validity of the proposed 3D fracture criterion can be stated.

In this paper the rather complex 3D fatigue crack growth behaviour in a 3PB-specimen with an inclined plane of the initial crack or notch is investigated by the aid of the programme ADAPCRACK3D and by application of a recently developed 3D fracture criterion. It will be shown that the computationally simulated results of fatigue crack growth in the FE-model of the specimen are in good agreement with experimental findings for the development of the spatially twisted crack faces in the real laboratory test-specimen. Consequently, also for this case with a rather complex 3D crack growth behaviour, the functionality of the ADAPCRACK3D-programme and the validity of the proposed 3D fracture criterion can be stated.

In this paper, the dynamical model of the ball juggling robot is presented. The dynamical model takes advantage of the fact that instead of using the camera or vision system, this dynamical model can be used to continuously calculate ball velocity and position during juggling or playing between two robots. In ball juggling or playing robot experiments the most difficult task is to get the position and velocity of the ball during play. This paper deals with calculating the position and velocity of the ball continuously during juggling or playing with the rigid racket. Basic physics reflection laws are used to calculate the outgoing velocity of the ball after each hit. The hitting of the ball on the racket is detected by measuring the distance between the ball contact point and the rigid racket surface. To get the velocity and position of the ball throughout the juggling, the gravitational effect is also incorporated. An overall structure of the stand alone model is also proposed to get the position and velocity continuously. This model is computationally less expensive and gives better insight of the juggling. To validate this dynamical model, experiments are performed on the test bench. The results of this dynamical model are compared and analysed with the results obtained from the RecurDyn simulation and test bench experiment

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When designing complex mechatronic systems, a team of developers will be facing many challenges that can impede progress and innovation if not tackled properly. In meeting them simulation tools play a central role. Yet it is often impossible for a single developer to foresee the overall impact a design decision will have on the system and on the other domains involved. For this task multi-domain simulation tools exists, but because of its complexity and the different levels of detail that are needed, the effort to specify a complete system from scratch is very high. Another challenge is the selection of the most suitable solution elements provided by the manufacturers. Currently they are often chosen manually from catalogues. The development engineer is therefore usually inclined to employ well-known solution elements and suppliers. To tackle both challenges our aim is an increase in efficiency and innovation by means of generally available solution knowledge, such as well-proven solution patterns, ready-to-use solution elements, and established simulation models [1]. Our paper presents a tool-supported, sequential design process. From the outset, the comprehensive functional capability of the designed system is supervised by means of multi-domain simulation. At significant points in the design process, solution knowledge can be accessed as it is stored in ontologies and therefore available via Semantic Web [2]. Thus, one can overcome barriers resulting from different terminologies or referential systems and furthermore infer further knowledge from the stored knowledge. The paper focuses on an early testing in the conceptual design stage and on the subsequent semantic search for suitable solution elements. After the specification of a principle solution for the mechatronic system by combining solution patterns, an initial multi-domain model of the system is created. This is done on the basis of the active structure and of idealized simulation models which are part of a free library and associated with the chosen solution patterns via the ontologies. In further designing the controlled system and its parameters with the completed model, the developer defines additional criteria to be fed into the subsequent semantic search for solution elements. Information on the latter is provided by the manufacturers as well as detailed simulation models, which are used to analyze the functional capability of the concretized system. Therefore, the corresponding idealized models are replaced automatically with the parameterized models of the solution elements containing for example the specific friction model for the chosen motor. We show this process using the concrete example of a dough-production system. In particular, we focus on its transport system. Resulting requirements for the simulation models and their level of detail are expound, as well as the architecture and benefits of the ontologies.