The ATV BEM & FEM solver sets up and launches an acoustic BEM or FEM model to compute and store acoustic transfer vectors (ATV). The resulting database is used in a standard ATV-based final response sequence, either seamlessly from the ATV computation or at a later time. The vibration response simulation results are then combined with an ATV set to efficiently calculate the noise radiated from a vibrating surface. Up to a 100-fold speed increases can be obtained compared to conventional acoustic simulation methods. Using the ATV tool, a machinery noise signature can be simulated within a day rather than weeks and results can be post-processed using the LMS Virtual.Lab Acoustics graphical tools
This solver helps the acoustic solution to occur on multiple nodes, such as multi-CPUs or multiple computers in a network. As an ideal way to solve large models quickly, this solution is applicable to a variety of configurations including frequency level, matrix level, thread level or a combination.
Using the Modification Prediction module, users can very quickly analyze modified designs and simulate acoustic behavior for a large number of design options in a limited time. The module applies the design modification on the structural modes and assesses the influence of structural changes on the overall noise performance without resolving the complete structural or acoustic equations.
Using advanced singular value decomposition techniques, this module accounts for the random nature of certain noise and vibration characteristics typically found in the aeronautics and aerospace industry. This includes high acoustical random excitations induced by jets or rockets that cause random vibrations of the fairing and spacecraft itself.
Traditionally, fatigue damage is associated with time-dependent loading; however, there are often situations in which loading time signals cannot easily be determined, like the wind load on a wind turbine. In this case, random vibration fatigue power spectral densities define the loads. In other cases, loads are deterministic, but defined in frequency. For efficiency reasons, it is desirable to perform the complete simulation in the frequency domain. With Vibration Fatigue, LMS integrates its cutting-edge knowledge in durability assessment methods. Users can benefit from an easy and consistent set-up and highly efficient analysis methods, including real multi-axial load and local stress behavior as well as the seam and spot welds.
This innovative mesh coarsening technique for exterior meshing can be compared to wrapping the structure with a rubber sheet: small surface features are smoothed to dramatically reduce model size. Model features that have a significant impact on the acoustic response remain in place to preserve the quality and accuracy of the acoustic simulation. A simple user interface requests the obtainable frequency range from the structural mesh and then performs the necessary wrapping. Using this meshing approach, users can create complex acoustic models in hours.
The cavity meshing tool helps users to generate a high-quality HEXA-dominant mesh directly from the structural model, ensuring close proximity between the two. A mechanism for detecting and repairing holes and thus defining the cavity is employed before a high-quality mesh is created automatically. The required automation level can be determined by the user that allows either the entire vehicle cavity or just specific volumes to be meshed. The meshing algorithm can competently handle sharp and smooth features, seats and footprints using the adaptive mesh feature.
The CFD General Notation System (CGNS) provides a general standard interface, which is used to import computational fluid dynamics (CFD) analysis data into LMS Virtual.Lab. This makes it possible to interface with all CFD vendors that support the CGNS export functionality. This data is used as an input source for aero-acoustic simulations.
Virtual.Lab Optimization provides a set of powerful capabilities for single and multi-attribute optimization. Through design of experiments (DOE) and response surface modeling (RSM) techniques, engineers gain rapid insight into all possible design options that meet specific requirements. Using advanced optimization routines including Six Sigma manufacturing, LMS Virtual.Lab automatically selects the optimal design, taking into account real-world variability while meeting the strictest robustness, reliability and quality criteria.
