The steadily increasing performance of modern computer systems is having a large influence on simulation technologies. It enables increasingly detailed simulations of larger and more comprehensive simulation models. Increasingly large amounts of numerical data are produced by these simulations.

This thesis presents several contributions in the field of mechanical system simulation and visualisation. The work described in the thesis is of practical relevance and results have been tested and implemented in tools that are used daily in the industry i.e., the BEAST (BEAring Simulation Tool) tool box. BEAST is a multibody system (MBS) simulation software with special focus on detailed contact calculations. Our work is primarily focusing on these types of systems.

focusing on these types of systems. Research in the field of simulation modelling typically focuses on one or several specific topics around the modelling and simulation work process. The work presented here is novel in the sense that it provides a complete analysis and tool chain for the whole work process for simulation modelling and analysis of multibody systems with detailed contact models. The focus is on detecting and dealing with possible problems and bottlenecks in the work process, with respect to multibody systems with detailed contact models.

The following primary research questions have been formulated:

• How to utilise object-oriented techniques for modelling of multibody systems with special reference tocontact modelling?
• How to integrate visualisation with the modelling and simulation process of multibody systems withdetailed contacts.
• How to reuse and combine existing simulation models to simulate large mechanical systems consistingof several sub-systems by means of co-simulation modelling?

Unique in this work is the focus on detailed contact models. Most modelling approaches for multibody systems focus on modelling of bodies and boundary conditions of such bodies, e.g., springs, dampers, and possibly simple contacts. Here an object oriented modelling approach for multibody simulation and modelling is presented that, in comparison to common approaches, puts emphasis on integrated contact modelling and visualisation. The visualisation techniques are commonly used to verify the system model visually and to analyse simulation results. Data visualisation covers a broad spectrum within research and development. The focus is often on detailed solutions covering a fraction of the whole visualisation process. The novel visualisation aspect of the work presented here is that it presents techniques covering the entire visualisation process integrated with modeling and simulation. This includes a novel data structure for efficient storage and visualisation of multidimensional transient surface related data from detailed contact calculations.

Different mechanical system simulation models typically focus on different parts (sub-systems) of a system. To fully understand a complete mechanical system it is often necessary to investigate several or all parts simultaneously. One solution for a more complete system analysis is to couple different simulation models into one coherent simulation. Part of this work is concerned with such co-simulation modelling. Co-simulation modelling typically focuses on data handling, connection modelling, and numerical stability. This work puts all emphasis on ease of use, i.e., making mechanical system co-simulation modelling applicable for a larger group of people. A novel meta-model based approach for mechanical system co-simulation modelling is presented. The meta-modelling process has been defined and tools and techniques been created to fully support the complete process. A component integrator and modelling environment are presented that support automated interface detection, interface alignment with automated three-dimensional coordinate translations, and three dimensional visual co-simulation modelling. The integrated simulator is based on a general framework for mechanical system co-simulations that guarantees numerical stability.

In systems engineering and object-oriented design, encapsulation is a key concept to handle complexity. Interfaces are defined for the external interaction of a component, whereas internal details are hidden. Complex systems such as cars or airplanes consist of many components, which, in turn, consist of many components – hierarchically, through many levels. Therefore composition is built into modelling languages such as Modelica. External interfaces must be defined for external interaction, whereas internal components cannot be accessed if they are not available through these interfaces.

However, in 3D mechanical systems modelling and design, it is natural to be able to connect components whose surfaces are externally available. For example, the motor belonging to a car can be externally accessible in the 3D view, even though it can be regarded as an internal component of the car.

In this paper we compare two modelling approaches, one is Modelica used for systems engineering as well as modelling of multi-body systems and the other one is BEAST which is a specialised multi-body systems tool with good support for contact modelling. The current Modelica approach requires strict interfaces with encapsulation of internal components, whereas BEAST allows connections to internal components which are visible in a 3D view, which is often natural from the 3D mechanical systems point of view. For 3D mechanical systems, Modelica might be too strict, whereas BEAST might be too forgiving. Two different solutions are presented and discussed (in the form of possible Modelica extensions) to combine the advantages of both approaches.

A fully functional meta-model co-simulation environment that supports integration of many different simulation tool specific models into a co-simulation is described in this paper.

The continuously increasing performance of modern computer systems has a large influence on simulation technologies. It results in more and more detailed simulation models. Different simulation models typically focus on different parts (sub-systems) of the complete system, e.g., the gearbox of a car, the driveline, or even a single bearing inside the gearbox. To fully understand the complete system it is necessary to investigate several or all parts simultaneously. This is especially true for transient (dynamic) simulation models with several interconnected parts. One solution for a more complete and accurate system analysis is to couple different simulation models into one coherent simulation, also called a co-simulation. This also allows existing simulation models to be reused and preserves the investment in these models.

Existing co-simulation applications are often capable of interconnecting two specific simulators where a unique interface between these tools is defined. However, a more general solution is needed to make co-simulation modelling applicable for a wider range of tools. Any such solution must also be numerically stable and easy to use in order to be functional for a larger group of people.

The presented approach for mechanical system co-simulations is based upon a general framework for co-simulation and meta-modelling [9]. Several tool specific simulation models can be integrated and connected by means of a meta-model. A platform independent, centralised, meta-model simulator is presented that executes and monitors the co-simulation. All simulation tools that participate in the co-simulation implement a single, well defined, external interface that is based on a numerically stable method for force/moment interaction.

This paper describes a rotor-dynamics application, a grinding spindle arrangement, that contains several non-linear components, e.g., two ball bearings supporting the spindles shaft and a control system determining the rotation of the shaft. To be able to study the different parts in detail they should be modelled in specialised simulation tools, i.e., model  control systems in Simulink and multibody systems in MSC.ADAMS.However, to understand the system as a whole it is necessary to investigate all parts simultaneously. This is especially true for transient (dynamic) simulation models with several interdependent parts. One solution for a more complete and accurate system analysis is to couple different simulation models into one coherent simulation, also called a co-simulation. This also allows the reuse of existing simulation models and preserves the investment in these models.

The grinding spindle arrangement has successfully been modelled and simulated using a general framework for co-simulation and  metamodelling. Four simulation models have been connected by means of a meta-model, that contains an MSC.ADAMS spindle model, two BEAST  ball bearings fixing the shaft in the housing, and a Simulink driver that controls the rotation of the shaft. Rotor-dynamics effects, such as, grinding-wheel vibrations and stiffness are presented to verify the results of the simulation.

An integrated visualisation and simulation tool for multibody systems with detailed contact analysis applied to transient dynamics is presented in this case study. Transient multibody simulations focusing on detailed contact analysis put high demands not only on the calculation part but also on data visualisation. This is especially true for multidimensional time-varying data. Typical simulation output data, produced by the simulation tool used for this work, has a large number of time steps, in the order of 103-106. This results in 500 MB to 8 GB of compressed data. The large amount of data and many time steps require data compression. A compression algorithm specially designed for time-varying data is used. Selective data access is required for visualisation of transient data sets. A block based streaming technique with fast selective data access is presented that allows for realistic animations of mechanical system dynamics. Furthermore, different representations of surfaces and surface related data are presented that are used throughout the visualisation process. One contribution of this work is the summarisation and description of the complete visualisation process that includes everything from data storage to image rendering, and also includes user-to-data interaction. Another contribution is a sparse data structure for storage of two dimensional transient data sets. This work has been initiated to investigate and describe what is needed to create a complete multibody visualisation system. The outcome of this work is a full-scale visualisation system that is used daily in the industry.

A general approach for modelling of mechanical system co-simulations is presented that is built upon the previously defined general framework for TLM co-simulations and co-simulation meta-modelling.

Co-simulation is one technique for coupling different simulators into one coherent simulation. Existing co-simulation applications are often capable of interconnecting two specific simulators where a unique interface between these tools is defined. However, a more general solution is needed to make co-simulation modelling applicable for a wider range of tools. Any such solution must also be numerically stable and easy to use to be applicable by a larger group of people.

In this work the concept of meta-modelling is applied to mechanical co-simulation. Several tool-specific simulation models can be integrated and connected by means of a meta-model, where the meta-model  defines the physical interconnections of these models.

A general meta-modelling process is described that represents the basis for this work. A meta-modelling language (MML) has been defined to support the modelling process and store the meta-model structure. Besides elements for physical interconnections, etc., the language also defines graphical elements that can be used for meta-model  visualisation. All proposed solutions are general and simulation tool independent.

A fully functional modelling environment has been created to make meta-modelling applicable. The modelling environment supports easy encapsulation and integration of simulation tool-specific models. Each simulation tool implements a single, well defined co-simulation interface. All interfaces implement a numerically stable method for force/moment interaction. The presented environment features a graphical user  interface for co-simulation modelling with support for three dimensional  visual representation of the co-simulation model including all its components.

Modeling and simulation often require different tools for specialized purposes, which increase the motivation to use co-simulation. Since physical models often are describing enterprises¿ primary know-how, there is a need for a sound approach to securely perform modeling and simulation. This paper discusses different possibilities from a security perspective, with focus on secure distributed co-simulation over wide area networks (WANs), using transmission line modeling (TLM). An approach is outlined and performance is evaluated both in a simulated WAN environment, and for a real encrypted co-simulation between Sweden and Australia. It is concluded that several parameters affect the total simulation time, where especially the network delay (latency) has a significant impact.

A framework for meta-modelling with Transmission Line (TLM) joints is presented. The framework is intended to support transient simulations of mechanical systems using co-simulation of different tools. The expressive power of the Modelica language is used to describe the meta-model in an easy to understand, object oriented way. A ModelicaXML based translator is used to convert Modelica code to an XML document which is accepted as input by the co-simulation engine. The framework prototype for SKF’s BEAST and MSC.ADAMS is presented here. It is designed to be general, so that support for other simulation tools can be easily added. The main focus is on modelling of co-simulation Meta-Models taking advantage of Modelicas graphical and object-oriented modelling capabilities.

Multi-body dynamics describes the physics of motion of an assembly of constrained or restrained bodies. As such it encompasses the behaviour of nearly every living or inanimate object in the universe. "Multi-body dynamics - Monitoring and Simulation Techniques III" includes papers from leading academic researchers, professional code developers, and practising engineers, covering recent fundamental advances in the field, as well as applications to a host of problems in industry. They broadly cover the areas: multi-body methodology; structural dynamics; engine dynamics; vehicle dynamics - ride and handling; and machines and mechanisms. "Multi-body Dynamics" is a unique volume, describing the latest developments in the field, supplemented by the latest enhancements in computer simulations, and experimental measurement techniques. Leading industrialists explain the importance attached to these developments in industrial problem solving.