MODELLING AND SIMULATION g
element analysis (FEA) or computational fluid dynamics (CFD) analysis. Using system-level modelling and multibody dynamics, different types of equations are used where each component and the interactions between components are described. This is a more efficient way for engineers to understand the behaviour of certain systems in response to the force acting upon it. Barral explains: ‘These integrated
capabilities enable designers and engineers to collaborate on replicating real-world scenarios and analysing multiple design options quickly and accurately. MBD simulations can help engineers study sub [systems] and complete systems, optimise critical components and systems earlier in the development cycle, avoid costly last- minute changes during physical testing and achieve overall efficiency and performance goals.’
As such, MBD is not only a more
computationally efficient way to simulate a dynamic system, but also to simulate the rate at which engineers can get answers on a whole system when using system-level modelling.
Visualisation matters Visualisation tools are vital for MBD simulations; enabling engineers to analyse results quicker, thanks to the animations generated. Ryan says: ‘People expect to see full 3D geometries realistically moving on their screens – and they can with MBD. And in the spirit of ‘a picture can be worth a thousand words’, it is also true that ‘an animation can be worth 1e6 pictures’.’ Visual animations, for example, can help engineers understand rates of change for the system as it moves. ‘Especially when limits or targets are involved, it could be essential to know if actual values for velocities or accelerations are exceeding those limits or targeted values – for example, with a cruise-control system in a car that is set to make sure the car doesn’t exceed 100kph,’ Ryan explains. Plot and graphs are helpful, while
complementary visualisation aids are ‘essential in those cases where motion- related quantities cannot easily be perceived or even accurately measured
”People expect to see full 3D geometries realistically moving on their screens – and they can with MBD”
28 Scientific Computing World Summer 2022
VTD and Adams - truck sensor perception as cab tilts and oscillates
through animations alone,’ according to Ryan. ‘For instance, an animation typically will not show the time-history of specific forces in the system to enable an engineer to spot the peak value of a force and also the time at which it occurs... which could be vitally important to the product’s design.’
Future motion Advancing electrification will continue to impact mechanical simulations and MBD is helping ease this transition. Ryan explains: ‘For years, as the products that companies make have continually grown – and accelerated – in complexity, we have seen an increased need to perform simulations of smarter electro- mechanical products involving all kinds of logic and feedback control systems.’ This is ‘especially applicable’ to
systems in motion, according to Ryan. “This is to help ensure that they move as intended – especially when safety considerations are important such as when developing something like antilock braking systems (ABS) and traction control systems (TCS) for different types of ground vehicles.’ MBD is also increasingly being used earlier in the design and development lifecycle. Previously, control system engineers and multibody dynamics engineers would develop their separate systems in isolation and then try to put them together at some point later in the development cycle – maybe as late as the first prototype stage. But this is still ‘much later than
desired,’ according to Ryan, who adds: ‘Fortunately, we are now able to help companies break down the silos that have long existed between engineers and engineering teams who are focused on different disciplines – electrical
versus mechanical versus controls, for instance. These streamlined workflows are now helping companies to minimise bottlenecks in their product development cycle so that they can continue to accelerate time-to-market.’ AI and machine learning are
complementary technologies that are really finding their feet in the MBD realm. Ryan says: ‘Leveraging artificial intelligence/machine learning (AI/ML), especially using neural networks to create reduced order models (ROMs) of subsystems to accelerate simulation throughput, is another trend.’ ‘We’re also seeing greater interest in digital twins in general and finding VR and AR applications to manage and monitor real-time operations of fleets of machines,’ Harduwar adds. Environmental concerns will continue
to push MBD simulation adoption, a trend that will affect not just MBD but the entire simulation landscape. Barral explains: ‘Trends in sustainability,
green energy and autonomous – and driver-assisted – vehicles are really important factors in the increased use of multibody simulation. ‘Moreover, industries are subject to
irreversible ‘trends’ such as climate- change mitigation redefining operations. Climate issues are accelerating quickly and, with global regulation pushing for a more circular economy in line with market expectations, aligning to the sustainability agenda won’t be easy. ‘However, the first step to reaching this goal is creating products in a fully collaborative, virtual environment. Once you have all of this information available in a single immersive experience, it becomes so much easier to visualise your data in the right context and then apply it for the best results.’
@scwmagazine |
www.scientific-computing.com
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