SDNews: December 2024

Newsletter summary:

???[Software] Navigation through multi-dimensional data with Iiplot

???[Software] Modal analysis DoE navigation

??[Expertise] Mode classification using clusters

This month, we focus on illustrating some of SDT's interactivity tools.

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???[Software] Navigation through multi-dimensional data with Iiplot

?? Data navigation is an essential feature for engineering projects, what can be done?

?? An efficient tool should provide an interactive and flexible display strategy, with formatting and capturing capabilities.

?? ?? Come Iiplot, our versatile curve navigation and signal processing tool. It is dedicated to 2D or 3D representation of multidimensional curves with an accent on navigation, display customization and formatting for report integration.

?The following video demonstrates Iiplot navigation features, handling multiple dimensions, sampling value ranges in some directions, and switching channels with context.

?? Curious about the illustrative test case? The data is part of our tutorials for parametric experimental modal analysis on the GARTEUR test case with temperature dependency. The test being MIMO, the transfers span a frequency band, outputs, inputs, and several temperatures, making it a 4D database. With a focus on the influence of temperature, many displays can be devised for assessment. The video showcases an interactive navigation case in this regard.

??? [Software] Modal analysis DoE navigation

?? Understanding a model sensitivity to various parameters is key to controlling quality (verification and validation), assessing modelling refinement or simplification possibilities, and getting project engineering insights.

??? ?? DoE study display strategy must thus provide a comprehensive interactivity to allow browsing in the results that can feature many indicators and observing associated model response.

?In the following video, we demonstrate our solutions to an interactive modal analysis DoE display.

??For those curious about the context, our example is a parametrized brake squeal complex eigenvalue analysis output. In this framework, self-excited friction induced vibrations are characterized by unstable complex modes (negative damping ratio) linked to the steady sliding condition between the liners and disc. Unstable modes are thus of particular interest.

??The damping ratio not being linked to the attainable vibration amplitude; other indicators can be evaluated to assess their criticality.

Equivalent radiated power is here used to approach noise propensity, this indicator is best used when evaluated on exposed surfaces such as the brake disc!

??[Expertise] Mode classification using clusters

?? Modern computing and storage capabilities allow performing large design of experiments, numerically and/or experimentally. ?? During a project, one can thus be led to analyze overwhelmingly large amounts of modal data, hundreds or even thousands of modes extracted from different parametric configurations around a baseline.

?? Without appropriate tools ?? the task becomes hazardous as soon as significant mode variation happens.

?? At SDTools, we have developed mode classification solutions to enable a thorough analysis of such large dataset. Using modal subspace distances, clustering techniques can be employed. The unfathomable pile of modes is then sorted into a few representative mode classes ?. Besides the simplification, associated parameter distributions are also available!

?The following video illustrates how to analyze large amounts of parametric modal analysis

??Check our latest post on the subject in our website

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