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This paper presents the second part of a multi-phased, both experimental and numerical project, devoted to the use of Virtual Prototyping techniques for seat design. The aim of this stage is to assess the capabilities of a CAE methodology to predict some comfort-related mechanical parameters, such as overall hardness and plushness, as a base engineering approach to quantify an occupant perception of both long- and short-term comfort. For hardness, a simple human surrogate (SAE AM50 Buttock Form) is applied on the bottom cushion of a fully trimmed, current production FORD seat, following a load cycle. For initial softness, a round probe is indented at different locations of both backrest and bottom cushions, following loading cycles. The resulting load-deflection curves predicted by numerical simulation are in good agreement with the experimental ones.

The Finite Element Method (FEM) and the Statistical Energy Analysis (SEA) are standard methods in the automotive industry for the prediction of vibrational and acoustical response of vehicles. However, both methods are not capable of handling the so called “mid frequency problem”, where both short and long wavelength components are present in the same system. A Hybrid method has been recently proposed that rigorously couples SEA and FEM. In this work, the Hybrid FE-SEA method is used to predict interior noise levels in a trimmed full vehicle due to broadband structure-borne excitation from 200Hz to 1000Hz. The process includes the partitioning of the full vehicle into stiff components described with FE and modally dense components described with SEA. It is also demonstrated how detailed local FE models can be used to improve SEA descriptions of car panels and couplings.

The Hybrid FE-SEA method has been used to create a fast/efficient model to predict structure-borne noise propagation in a fully trimmed vehicle over the frequency range from 200 to 1000 Hz. The method was highlighted along with the modeling process and extensive validation results in previously published papers [1-3]. The use of the model to analyze structure-borne noise in the full vehicle, and to design and evaluate the impact of counter measures was described. In this study, the Hybrid FE-SEA method is used identify potential design changes to improve the acoustic performance. First, results from a noise path analysis are used to identify key contributors to interior noise. Next, potential design strategies for reducing the interior noise are introduced along with implications on the model. Finally, sample prediction results illustrating the impact of design changes on interior noise levels are shown along with experimental validation results.

The most time-consuming step in an external aerodynamics or underhood CFD process is that of generating a usable mesh from CAD data. Conventional mesh generators require a water-tight surface mesh before they can generate the volume mesh. Typical CAD surface data available for mesh generation is far from satisfactory for volume mesh creation: no node-to-node matching between mating parts, minute gaps, overlapping surfaces, overlapping parts, etc. To clean up this kind of data to a level that can be used for volume mesh creation requires a lot of manual work that could take a couple of weeks or more to accomplish. This paper presents a fast and fully automated, Cartesian cell dominated projected mesh generation algorithm used in CFD-VisCART that eliminates the need for CAD data cleaning, thus shaving off weeks worth of time off the design cycle.

Process automation is one of the emerging technologies in the field of computer aided engineering (CAE). A majority of the CAE processes involve repetitive steps during the product development and enhancement phases. An effort is being made to improve the engineer's efficiency by automating the repetitive tasks. The objective of the current study is to demonstrate the capabilities of CAE or FE process automation. Using a CAE process authoring and execution environment, a process was developed for the standard neck pendulum certification for the FE Hybrid III 5th percentile female ATD model. Standard pre-processing tasks for the typical neck pendulum certification simulation such as ATD head/neck replacement and positioning, resolving connections, quality checks, boundary and loading conditions, contact definitions, etc. were defined as process steps. Solver execution and post-processing were also made part of the process automation for the review of results and report generation.

In the framework of noise reduction of HVAC (Heating, Ventilating and Air Conditioning) systems designed for cars, the present study deals with the numerical prediction of aeroacoustics phenomena encountered inside such devices for industrial purposes, i.e. with a reasonable CPU time. It is then proposed in this paper to assess the validity of the chaining, via Lighthill-Curle analogy, of a DES (Detached Eddy Simulation) resulting from the CFD code OpenFOAM (ESI Group) versus a RANS-LES (Large Eddy Simulation) and a BEM calculation resulting from the Vibro/Aeroacoustics software VA One (ESI Group) on an academic case of air passing through a rectangular diaphragm at a low Mach number. The BEM code being parallelized, the performances of DMP (Distributed Memory Processing) solution will also be assessed.

Traditional automotive seat development has relied on a series of physical prototypes that are evaluated and refined in an iterative fashion. Costs are managed by sharing prototypes across multiple attributes. To further manage costs, many OEMs and Tier 1s have, over the past decade, started to investigate various levels of virtual prototyping. The change, which represents a dramatic paradigm shift, has been slow to materialize since virtual prototyping has not significantly reduced the required number of physical prototypes. This is related to the fact virtual seat prototyping efforts have been focused on only selected seat attributes - safety / occupant positioning and mechanical comfort are two examples. This requires that physical prototypes still be built for seat attributes like craftsmanship, durability, and thermal comfort.

To develop future electrical and autonomous cars, it is important to virtually test the car in real driving circumstances, including on wet road or under heavy rain conditions. It is especially critical to check that no water prevents the sensors of the driving assistance systems or autonomous cars from working properly, that water intrusion does not disturb electrical equipment, and that the driver’s visibility remains good under rain condition. ESI Group has introduced the Finite Point Method (FPM) in Virtual Performance Solution (VPS) as a CFD mesh free module in order to simulate the interaction of water with the car structure. It was initially specialized for tank sloshing and water drain applications for car closures and is now extended to other application fields. The objective is to enable a holistic prediction of the car behavior under realistic driving conditions, using a virtual car prototype.

The comfort assessment of seats in the automotive industry has historically been accomplished by subjective ratings. This approach is expensive and time consuming since it involves multiple prototype seats and numerous people in supporting processes. In order to create a more efficient and robust method, objective metrics must be developed and utilized to establish measurable boundaries for seat performance. Objective measurements already widely accepted, such as IFD (Indentation Force Deflection) or CFD (Compression Force Deflection) [1], have significant shortcomings in defining seat comfort. The most obvious deficiency of these component level tests is that they only deal with a seats' foam rather than the system response. Consequently, these tests fail to take into account significant factors that affect seat comfort such as trim, suspension, attachments and other components.

Quality and refinement are of paramount importance for luxury vehicles. The rapid electrification of the automotive industry has increased the contribution of aeroacoustics to the consumer perception of sound quality. The ability to predict whole vehicle aeroacoustic interior noise is essential in the development of vehicles with an extraordinary acoustic environment. This publication summarises the development of a process to combine lattice Boltzmann computational fluid dynamics simulations, with a whole vehicle statistical energy analysis model, to predict the aeroacoustic contribution from all relevant sources and paths. The ability to quantify the relative contribution of glazing panels and path modifications was also investigated. The whole vehicle aeroacoustic interior noise predictions developed, were found to be within 2dB(A) of comparable test vehicle wind tunnel measurements, across a broad frequency range (250-5000 Hz).

Since Statistical Energy Analysis (SEA) is based on lumped parameters, acoustic responses predicted by SEA are spatially discontinuous. However, in many practical applications, the ability to predict spatially continuous energy flow is useful for guiding the design of systems with improved acoustical characteristics. A new approach, utilizing integral equations derived from energy flow concepts, is developed to predict the continuous variation of acoustic field such as sound pressure level in the interior of acoustic domains using structural response predicted by SEA. The computer code developed based on energy flow boundary integral equations is initially validated by analyzing sound propagation in a duct.

In order to assess the seating comfort design of a vehicle seat system, a full finite element occupant model, with anatomically precise features and deformable tissues, has been developed. This paper describes the experiments which were performed in order to assess the biofidelic accuracy of this model. First, static pressure distribution measurements, with human volunteers, have been performed. People of different morphological types were asked to sit on a PU foam cushion with various postures, which were captured by photographs and X-Ray measurements. Pressure sensors were used to determine the corresponding pressure distribution patterns. Then, the FE occupant model was used to simulate the same experiments, and the numerical results were compared to the experimental ones.

Recent developments in the prediction of the contribution of wind noise to the interior SPL have opened a realm of new possibilities in terms of i) how the convective and acoustic sources terms can be identified, ii) how the interaction between the source terms and the side glass can be described and finally iii) how the transfer path from the sources to the interior of the vehicle can be modelled. This paper discusses in detail these three aspects of wind noise simulation and recommends appropriate methods to deliver required results at the right time based on i) simulation and experimental data availability, ii) design stage and iii) time available to deliver these results. Several simulation methods are used to represent the physical phenomena involved such as CFD, FEM, BEM, FE/SEA Coupled and SEA.

One of the major concerns in the vehicle trim part design is the acoustic targets, which are generally defined by absorption area or coefficients, and sound transmission loss (STL) or sound insertion loss (SIL). The breaking down of acoustic targets in vehicle design, which is generally referred to as cascading, is the process of determining the trim part acoustic targets so as to satisfy full vehicle acoustic performance. In many cases, these targets are determined by experience or by subjective evaluation. Simulation based transfer path analysis (TPA), which traces the energy flow from source, through a set of paths to a given receiver, provides a systematic solution of this problem. Guided by TPA, this paper proposes a component level target setting approach that is based on the statistical energy analysis (SEA), an efficient method for vehicle NVH analysis in mid and high frequencies.

Recent developments in the prediction of the contribution of wind noise to the interior SPL have opened a realm of new possibilities. The main physical mechanisms related to noise generation within a turbulent flow and the vibro-acoustic transmission through the vehicle greenhouse is nowadays better understood. Several simulation methods such as CFD, FEM, BEM, FE/SEA Coupled and SEA can be coupled together to represent the physical phenomena involved. The main objective being to properly represent the convective and acoustic component within the turbulent flow to ensure proper computation of the wind noise contribution to the interior SPL of a vehicle.

Wind noise is a major contributor to vehicle noise and a very common consumer complaint for overall vehicle quality [1]. The reduction of wind noise is becoming even more important as powertrain noise is reduced or eliminated (by conversion to hybrid and electric vehicles) and as the importance of quiet interior environment for hands-free device use and voice activation systems becomes more pronounced. In contrast to other noise sources such as tires, engine, intake, exhaust or other component noise whose acoustic loads may be measured in a direct and standardized way with the proper equipment, wind noise is very difficult to predict because the acoustic part of wind noise is a small component of overall fluctuating pressures. It is very challenging to either directly measure or to simulate the acoustic component of fluctuating exterior pressures using CFD (Computational Fluid Dynamics) without a great deal of specialized experience in this area.

This paper presents an integrated simulation process which has been performed in order to assess the riding comfort performance of a vehicle seat system virtually. Present methods of seat comfort design rely on the extensive testing of numerous hardware prototypes. In order to overcome the limitations of this expensive and time-consuming process, and to fasten innovation, simulation-based design has to be used to predict the seat comfort performance very early in the seat design process, leading to a drastic reduction in the number of physical prototypes. The accurate prediction of the seat transfer function by numerical simulation requires a complete simulation chain, which takes into account the successive stages determining the final seat behaviour when submitted to vibrations. First the manufacturing stresses inside the cushion, resulting from the trimming process, are computed.