Metamodels Resulting from Two Different Geometry Morphing Approaches Are Suitable to Direct the Modification of Structure-Born Noise Transfer in the Digital Design Phase

Abstract

Noise vibration and harshness (NVH) development often takes place in the later development phases. Shifting the optimization to the early digital development phase enables more parameters to participate in the optimization and leads to a more holistic development process. Digital NVH development often modifies system and component frequency response functions (FRFs) using finite element (FE) simulation. Currently, the often manual process of creating new FE models for modified designs makes a systematic evaluation of many designs difficult and time-consuming. In this paper, we take on these difficulties and use both a Direct Morphing approach and a Box Morphing approach to automatically adopt the first existing FE models to modified designs. We use the generated simulation results to fit metamodels describing the correlation between geometrical parameters and characteristic FRF values. These metamodels provide an easy and fast to use tool for designers to consider NVH demands. In a simulation example, we demonstrate the capabilities by modifying the kinematic hard points of a vehicle suspension and using them to modify the noise transfer sensitivity. We show that the metamodels can lead the digital design process to intuitively and specifically reduce characteristic component FRF values by changing the location of the component hard points.

Generating Component Designs for an Improved NVH Performance by Using an Artificial Neural Network as an Optimization Metamodel

“…The component under investigation is the knuckle of a vehicle suspension. The same knuckle was also used as an example in a previous publication [27].…”

“…In Figure 1, all five hard points including their attachment surfaces and the flange surface including the wheel center point are visualized. In the previous publication [27], we only used the coordinate of the hard point for the track rod (labeled P in Figure 1) as a variable geometry parameter. In this article, we use all 5 hard point coordinates.…”

“…For each of the 500 parameter sets we automatically create an FE model of the knuckle. This is performed by morphing an initial component FE model using the free form morphing algorithm presented in earlier publications [14,27]. In one of them, we present an example of the FE mesh [27].…”

“…This is performed by morphing an initial component FE model using the free form morphing algorithm presented in earlier publications [14,27]. In one of them, we present an example of the FE mesh [27]. The initial component FE model represents the metal part of the component and consists of approximately 100,000 FE nodes and 50,000 FE elements.…”

“…In a holistic and fast development process the optimization should be based on fast calculating metamodels that represent the behavior of the FE model [13,18,[21][22][23][24][25][26]. In a previous publication, we showed polynomial metamodels to be capable of a targeted reduction in specific frequency bands of a component FRF [27]. Polynomial metamodels perform well for simple, continuous, and differentiable phenomena (p. 48, ref.…”