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Concord, MA, United States

Herrin D.W.,University of Kentucky | Liu J.,University of Kentucky | Martinus F.,Trane Inc. | Kato D.J.,Cambridge Collaborative Inc. | Cheah S.,Cummins Power Generation
Noise Control Engineering Journal

The inverse boundary element method (BEM) is a numerical procedure whereby sound pressure measurements in the near field are used to predict the vibration on a vibrating surface. After the vibration on the surface (or particle velocity in the case of an opening) is determined, the sound pressure in the far field can be predicted using a forward BEM analysis. This paper will examine the applicability of the inverse BEM to predicting sound pressure in the far field on two examples; an engine cover and generator set.The results indicate that the inverse BEM can be used to accurately predict far field sound pressure. Additionally, it is demonstrated that a partial or patch BEM model of a surface can be utilized successfully in some instances as a means of reducing the computation time. © 2009 Institute of Noise Control Engineering. Source

Musser C.T.,Cambridge Collaborative Inc. | Da Silva M.M.,Ford Motor Company | Kempt R.,Ford Motor Company
41st International Congress and Exposition on Noise Control Engineering 2012, INTER-NOISE 2012

SEA (Statistical Energy Analysis) for automotive NVH development has been employed for more than 20 years. SEA is uniquely suited to providing predictions of main noise contribution paths and overall interior noise due to individual or combined airborne or structureborne noise sources at higher frequencies. Existing SEA vehicle models may be easily adapted for acoustic design studies for new vehicle programs, allowing fast design study predictions at the first stages of vehicle design before test hardware or mature FEA models are available. For greater confidence in the model and results a model validation from laboratory test data is recommended. This paper discusses an SEA model validation process using hemi-anechoic laboratory test data with artificial acoustic sources and a windowing methodology employing blocker parts on the flanking paths to study and validate the contribution of the dominant individual noise transfer paths. Testing strategy, methodology, main results, and lessons learned are presented. Key SEA modeling input parameters and validation approach are discussed. Comparison of test data to correlated model and representative NVH design sensitivity results are shown. Conclusions about the testing, model correlation, and use of the correlated model to support future vehicle program design are given. Source

Musser C.,Cambridge Collaborative Inc. | Marques Da Silva M.,MSX International Do Brazil | Lima Alves P.S.,Ford Motor Company
SAE Technical Papers

For purposes of reducing development time, cost and risk, the majority of new vehicles are derived strongly or at least generally from a surrogate vehicle, often of the same general size or body style. Previous test data and lessons learned can be applied as a starting point for design of the new vehicle, especially at early phases of the design before definite design decisions have been finalized and before prototype of production test hardware is available. This is true as well of vehicle NVH development where most new vehicles being developed are variants of existing vehicles for which the main noise transfer paths from sources of interest are already understood via test results and existing targets. The NVH targets for new vehicles are defined via benchmarking, market considerations, and other higher-level decisions. The objective is then to bridge the gap between test data from surrogate vehicles to direct support of the NVH development of new vehicle programs. Because of its strength in providing analysis predictions of the effect of design changes on vehicle NVH at higher frequencies, Statistical Energy Analysis (SEA) is an established tool for using available test data to correlate an SEA model that can be adapted for early design phase NVH development of new vehicles. The effect of changes to materials, gage thickness, sound package, source levels, or geometry changes on the interior noise levels can be predicted by SEA with good accuracy to support design decisions that must be made early in the program. This paper illustrates with a concrete example an idealized implementation of this process. The main test plan design considerations for a baseline surrogate vehicle are discussed. Some key test results and their uses are presented. The updating and correlation of an SEA model representing the baseline vehicle are shown. The objective methods for determining the effectiveness of the correlation are given using this vehicle as an example. Finally, the use of a correlated SEA model to effectively support the NVH development of several variant vehicle programs at an early phase of the design process is presented along with suggestions for the best use of this design tool, its advantages and limitations, and the most effective roles it can serve to support the overall vehicle design cycle. Copyright © 2013 SAE International. Source

Cambridge Collaborative Inc. | Date: 2005-06-28

Computer software program which analyzes dynamic systems by calculating vibration and acoustic levels for all types of structures and acoustics spaces.

Shen M.,Corning Inc. | Musser C.T.,Cambridge Collaborative Inc. | Manning J.E.,Cambridge Collaborative Inc.
41st International Congress and Exposition on Noise Control Engineering 2012, INTER-NOISE 2012

The interior noise of passenger vehicles is often dominated at higher frequencies by transmission through the glasses. One of the main reasons this occurs is that a conventional sound package cannot be applied to the glasses. The sound package is used on other vehicle subassemblies such as the dash, floor, and doors. Also, turbulent flows have prominent reattachment regions downstream from the cowl, side mirrors, and pillars that create locally high source levels that are directly transmitted as noise into the vehicle interior through the glasses. Use of multilayer laminated glasses has been shown to provide a great benefit in reducing passenger vehicle noise. When paths other than the glasses are dominant, as is the case at lower frequencies, the total weight of the glasses can also be reduced while avoiding significant interior noise increases. This paper presents the results from analytical studies of the potential for the application of lower surface density glass laminate versus the resulting interior noise performance for different glass laminate designs. The analytical modeling approach is based on Statistical Energy Analysis (SEA) and the correlation test data are described. Copyright © (2012) by the Institute of Noise Control Engineering (INCE). Source

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