Multibody System Dynamics: what it is and why it matters | Aki Mikkola
In computational dynamics, a number of formalisms have been introduced to analyze the dynamics of mechanical systems. Among these, Multibody System Dynamics (MSD) has become a reliable and easy-to-use tool to analyze the dynamics of mechanical systems. MSD is a systematic approach that applies to a wide range of problems. As the word “multibody” implies, the method was developed, in particular, to describe systems comprising multiple bodies, which are the key components from which the system under investigation can be effectively represented.
Multibody System Dynamics targets and is most effective at analyzing the dynamics of bodies that interact through mechanical joints. They control and limit relative motion between the interconnected bodies. The movement of one body influences the movement of other bodies based on the joint interconnection types.
Since system bodies can undergo substantial rotation, the kinematic description of a multibody system is generally nonlinear. As a result, the equations of motion describing it are nonlinear, and analytical solutions are generally not available. Instead, the equations of motion need to be solved using a numerical time-integration scheme. The nonlinear equations of motion can be constructed in many ways, i.e., formulations. In general, multibody formulations can be categorized to approaches based on global coordinates such like augmented formulation or method based on coordinate partitioning and approaches based on relative coordinate that make the use of system topology such like semi-recursive formulation. Each has advantages and disadvantages. Since the performance of a multibody formulation must be evaluated in conjunction with a time-integration scheme, the multibody formulation and time-integration scheme chosen determines how well a dynamic simulation performs.
Practical Relevance of Multibody System Dynamics
The multibody approach can be applied in a wide variety of engineering fields including robotics, aerospace applications, vehicle dynamics, biomechanics, and rotating structures. Optimization and sophisticated design tools are often required for these applications.
To satisfy increasingly demanding customer expectations, today’s machine products are becoming increasingly complex. Accordingly, multibody analysts are faced with the task of seamlessly integrating a variety of complex subsystems provided by multidisciplinary development teams to reliably determine overall system performance. In practical analysis work, this challenge can be addressed by combining multibody system dynamics, which describes the behaviors of the interacting mechanical components, with other computational models such as those that predict the performance of hydraulic or pneumatic actuators. Judicious application of monolithic or co-simulation procedures makes it possible to integrate the different computer model types. With the resulting multiphysical models, multibody system dynamics can provide machine developers with a significantly improved understanding of system performance as a whole and more importantly the myriad of internal interactions that characterize the system.
Multibody system simulation has proven to be an effective and powerful tool when implemented throughout the product development process. Understanding how the dynamic behavior of a system is affected by variations in design variables is important, and this understanding can be gained with considered application of a good computer simulation model. Moreover, because simulation can in many cases replace physical prototyping, it can significantly shorten the product development cycle.
Multibody system dynamics clearly plays an important and fast-growing role in product development. However, it also offers unique features that can enhance other product-related processes such as sales and marketing, the exploration of new business opportunities, and the service business.
For sales and marketing, MSD can be used to highlight a proposed new product’s technical features. For example, it can demonstrate the dynamic performance of a new mobile crane or a vehicle suspension system. If this is done in real time, the demonstrations are more interesting, and the customer can be more engaged. With a simulator, the customer can even experience product performance hands-on and get a feel for how custom features will affect the operator experience.
Similarly, realtime multibody system dynamics can be used to study new business opportunities. With the aid of accurate physics-based realtime simulation, potential customers can readily be given the opportunity to experience and evaluate new innovations or radically enhanced products.
Aki Mikkola received a Ph.D. degree in the field of machine design in 1997. Since 2002, he has been working as a Professor in the Department of Mechanical Engineering at LUT University, Finland. Currently, Mikkola leads the research team of the Laboratory of Computational Dynamics. He has been awarded five patents, has contributed to more than 130 peer-reviewed journal papers and has presented more than 50 conference articles. His major research activities are related to flexible multibody dynamics, real-time simulation, and biomechanics.
Together with Jorge Ambrosio he is editor in chief of the journal Multibody System Dynamics. https://www.springer.com/journal/11044
The journal explores theoretical and computational methods in rigid and flexible multibody systems, their applications and experimental procedures used to validate the theoretical foundations. Multibody applications include, but are not limited to, vehicle dynamics, aerospace technology, robotics and mechatronics, soil models, machine dynamics, crashworthiness, and biomechanics.