MODELLING AND SIMULATION
and help understand the entire system’s behaviour. ‘Using MBD, engineers could understand how fast the robot can go, how much payload it can handle, and how to optimise the design given the operating conditions,’ says Harduwar.
Challenging times Engineers are still faced with challenges when running MBD simulations. Methodically constructing very large models where potentially hundreds of components may move separately from each other is one such issue. Ryan explains: ‘It is quite easy and
A simulation of landing gear
increased the capacity of its washing machines by 35 per cent, improved the energy factor by 24 per cent and water factor by 52 per cent, while simultaneously reducing the cost per cubic foot by 10 per cent and the product development cycle time by 25 per cent. EnginSoft’s RecurDyn solution also helped Toyota’s Forklift division, which was having difficulties predicting the behaviour of the vehicle when carrying loads and driving through obstacles. The truck was modelled in RecurDyn, including flexible bodies to model the forks and the built-in tyre module, to accurately predict the behaviour of a fully-loaded truck driving over obstacles. Danujan Sivanesan, a Senior Project Engineer specialising in multibody dynamics at Enginsoft, says: ‘RecurDyn reliably analysed the critical conditions normally understood during the testing phase and computed the dynamic loads between the forks and the loads accurately using RecurDyn Geo-contact technology. This helped the customer reduce their product development time, enabling them to iterate through multiple designs and improve the performance and quality of their product.’ This range of applications and
interested industries continues to constantly expand. ‘Markets are starting to adopt this type of technology now to design better products and have not traditionally been operating in this space before,’ according to Chris Harduwar, VP of Business Development at Maplesoft. ‘[Engineers are] exploring rigid and
flexible multibody dynamics as a way to assess the interactions on components such as loads, tensions and torques and develop the specifications and limitations for a machine to operate,’ he says. ‘At Maplesoft, our customers often work to improve performance with components
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that fit into a larger machine or address issues that span multiple domains. All industries have ‘some common
and representative problems that can be addressed and solved through the use of MBD simulations,’ according to Jim Ryan, VP of Model-Based Systems Solutions at Altair. ‘MBD can really help improve the positioning to make sure that parts move as intended – one example is with those systems involving precisely controlled movements such as active suspensions and precise pointing systems such as telescopes and radar.’ MBD simulations can also help
”Using MBD, engineers could understand how fast the robot can go, how much payload it can handle, and how to optimise the design given the operating conditions”
engineers calculate the sizing forces and torques needed to move the system with the correct actuators. You can also manage accelerations and peak forces, reduce wear and avoid friction- or contact- induced damage or calculate loads to minimise stresses, fatigue and, ultimately, failed operations or broken products. MapleSim, for example, is used to
develop high-speed robotics, including custom components between the joints or using motors that have not been defined yet. Engineers need to understand the torques and forces that are applied to those motors across the full design and including the interaction of the movement of all the components. MapleSim was recently used to design a six-degree-of-freedom cable robot
common to model such connections incorrectly, in which case the simulation might not proceed, or it might proceed but yield incorrect results, consistent with the CAE engineer’s much-used axiom: garbage in, garbage out’!’ The easy re-use of pre-constructed
CAD assemblies (3D geometries) to retain the relative starting positions of all the components in a multibody system, together with all the mass and inertia properties, is another challenge to accurately predicting the motion. ‘Even though multibody dynamics modelling has improved across several decades, it can still be challenging for engineers using MBD to properly model 100 per cent of the complex physics involved, due to such phenomena as part- to-part contacts and friction, especially involving flexible bodies and elastic parts of the system like belts, ropes and cables,’ adds Ryan. Mounting system complexity puts engineers in a difficult position when it comes to MBD simulations. Harduwar says: ‘The engineers are inevitably left with a trade-off between the level of realism or fidelity of a model, compared to the computational and human engineering effort of defining the elements within the simulation.’ The motion control of the manipulators
in a robotic arm, for example, is ‘particularly challenging’ to simulate, according to Harduwar. ‘This is where system-level modelling becomes more effective – where equations of all the systems and components are combined and handled by a simulation tool.’ As product complexity continues to
increase, this situation will continue to impact engineers in the near-term where trade-offs are often made. Harduwar explains: ‘The challenge is doing something at the right fidelity level that will take the appropriate amount of time to get the right level of results.’ This is where system-level modelling using MBD has advantages over finite
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