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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.

Improving the verification and certification process of the high lift system by introduction of virtual testing is one of the approaches to counter the challenges related to testing of future aircraft, in terms of performing more tests of more complex systems in less time. The quality of the applied modelling methods itself and the guarantee of a completely traceable simulation lifecycle management along the aircraft development are essential. The presentation shows how existing processes for the management of all test related data have to be extended to cover the specifics of using multi body simulation models for virtual tests related to high lift failure cases. Based on a demonstrator, MSC Software GmbH and Airbus developed and are still refining the SimManager based “High Lift System Virtual Test Portal”. This portal has to fulfil on the one side global requirements like data management, data traceability and workflow management.

CAE capabilities have long been used for performing static and dynamic structural analysis during the seat design process. More recently, the soft parts of the seat including foams, trim and suspension have also been modeled with CAE. The purpose of this modeling is to better understand the physical phenomena which are involved in the sitting process, to enhance seat design knowledge, and to replace as much physical testing during the design process with virtual, CAE testing. This paper presents the first part of a multi-phased, both experimental and numerical project. The aim of this first stage is to assess the capabilities of a CAE methodology to predict FMVSS 202a backset. Based on CAD data, a finite element mesh of the seat was built. The mechanical behavior of all parts was characterized through experiments on material samples.

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.

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.

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.

Insufficient chip extraction often leads to disruptions of automated drilling processes and will have a negative impact on the surface qualities. One opportunity to avoid chip accumulation is based on a kinematically enforced chip breakage caused by sinusoidal axial oscillations of the drilling tool. Recent investigations have shown that the quality of chip extraction is, amongst others, considerably depending on the chip shape and mass which are defined by the cutting parameters feed, amplitude and frequency. So far only mechanical systems in the form of tool holders have been available on the market, which are restricted to a fixed frequency (oscillation frequency is coupled to the spindle speed). In the present study a spindle with magnetic bearings was used which allows to adjust the oscillation frequency independent of the spindle speed and therefore enables all opportunities to affect the generated chip shapes.

Pulsed assembly lines are providing an enormous potential to the aviation industry, especially in terms of reduced lead times, optimized asset utilization and an increased ratio of value adding processes. As it comes near to flow manufacturing the realization of a pulsed assembly line leads to special requirements to the use of NC programs for automated drilling and fastening processes, especially as a result of the unique part positions upon each pulse and concerning the balancing of the work onto several serialized fastening machines. The key to those challenges are versatile NC part programs that eliminate the need for any additionally written NC programs by self-adapting onto the concrete situation within the working areas of the production line.

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).

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.

Statistical Energy Analysis (SEA) is widely used for modeling the vibro-acoustic response of large and complex structures. SEA makes simulations practical thanks to its intrinsic statistical approach and the lower computational cost compared to FE-based techniques. However, SEA still requires underlying models for subsystems and junctions to compute the SEA coefficients which appear in the power balance equations of the coupled system. Classically, such models are based on simplified descriptions of the structures to allow analytical or semi-analytical developments. To overcome this limitation, the authors have proposed a general approach to SEA which only requires the knowledge of impedances of the structures to compute SEA coefficients. Such impedances can always be computed from an accurate FE model of each component of a coupled system.

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.

“Smart” refers to tools that are “specific, measurable, achievable, reasonable/realistic, and time bound.” Smart assembly tools are used in many industries, including automotive, aerospace, and space for measuring, inspecting, gauging, drilling, and installing all existing fastening systems. Inside the Industry 4.0 environment, these tools have a huge influence on Information and Communication Technology (ICT), assembly cost reduction, process control, and even the product and process quality. These four domains—and their undefined nature—are the focus of this SAE EDGE™ Research Report. The technical issues identified here need to be discussed, the goals clarifying the scope of the industry-wide need to be aligned, and the issues requiring standardization need prioritized. NOTE: SAE EDGE Research Reports are intended to identify and illuminate key issues in emerging, but still unsettled, technologies of interest to the mobility industry.

Increased production rates and cost reduction are affecting manufacturing in all mobility industry sectors. One enabling methodology that could achieve these goals in the burgeoning “Industry 4.0” environment is the optimized deterministic assembly (DA) approach. It always forms the same final structure and has a strong link to design-for-assembly and design-for-automation. The entire supply chain is considered, with drastic savings at the final assembly line level through recurring costs and lead-time reduction. Unsettled Technology Areas in Deterministic Assembly Approaches for Industry 4.0 examines the evolution of previous assembly principles that lead up to and enable the DA approach, related simulation methodologies, and undefined and unsolved links between these domains. Click here to access the full SAE EDGETM Research Report portfolio.

In response to the ice crystal icing hazard identified twenty years ago, aviation industry, regulation authorities, and research centers joined forces into the HAIC-HIWC international collaboration launched in 2012. Two flight campaigns were conducted in the high ice water content areas of tropical mesoscale convective systems in order to characterize this environment conducive to ice crystal icing. Statistics on cloud microphysical properties, such as Ice Water Content (IWC) or Mass Median Diameter (MMD), derived from the dataset of in situ measurements are now being used to support icing certification rulemaking and anti-icing systems design (engine and air data probe) activities. This technical paper focuses on methodological aspects of the derivation of MMD. MMD are estimated from PSD and IWC using a multistep process in which the mass retrieval method is a critical step.

Glaciated icing conditions potentially leading to in-service event are often encountered in the vicinity of deep convective clouds. Nowcasting of these conditions with space-borne observations would be of a great help for improving flight safety and air-traffic management but still remains challenging. In the framework of the HAIC (High Altitude Ice Crystals) project, methods to detect and track regions of high ice water content from space-based geostationary and low orbit mission are investigated. A first HAIC/HIWC field campaign has been carried out in Australia in January-March 2014 to sample meteorological conditions potentially leading to glaciated icing conditions. During the campaign, several nowcasting tools were successfully operated such as the Rapid Development Thunderstorm (RDT) product that detects the convective areas from infrared geostationary imagery.

In its entirety, automation is part of an integrated, multi-disciplinary product development process including the design, process, production, logistics, and systems approach—it depends on all these areas, but it also influences them as well. Automation in aerospace manufacturing is present throughout the entire supply chain, from elementary part manufacturing at suppliers up to final assembly, and a clear understanding of all the benefits (and drawbacks) of automation would help designers and engineers select the right designs for and levels of automation. The Right Level of Automation Within Industry 4.0 examines all impacts of automation that should be known by designers, manufacturers, and companies before investments in automation-related decisions are made—regardless of the which industry they work in. The process and the set of criteria discussed in this report will help decision makers select the right level of automation.

The presented paper describes the software complex developed in St. Petersburg Polytechnical University for AIRBUS aimed at simulation of aircraft assembly process. Previous version of this complex was described in [1].

This study presents the results of the ICE GENESIS 2021 Swiss Jura Flight Campaign in a way that is readily usable for ice accretion modelling and aims at improving the description of snow particles for model inputs. 2D images from two OAP probes, namely 2D-S and PIP, have been used to extract 3D shape parameters in the oblate spheroid assumption, as there are the diameter of the sphere of equivalent volume as ellipsoid, sphericity, orthogonal sphericity, and an estimation of bulk density of individual ice crystals through a mass-geometry parametrization. Innovative shape recognition algorithm, based on Convolutional Neural Network, has been used to identify ice crystal shapes based on these images and produce shape-specific mass particle size distributions to describe cloud ice content quantitatively in details. 3D shape descriptors and bulk density have been extracted for all the data collected in cloud environments described in the regulation as icing conditions.

Measurements in snow conditions performed in the past were rarely initiated and best suited for pure and extremely detailed quantification of microphysical properties of a series of microphysical parameters, needed for accretion modelling. Within the European ICE GENESIS project, a considerable effort of natural snow measurements has been made during winter 2020/21. Instrumental means, both in-situ and remote sensing were deployed on the ATR-42 aircraft, as well as on the ground (ground station at ‘Les Eplatures’ airport in the Swiss Jura Mountains with ATR-42 overflights). Snow clouds and precipitation in the atmospheric column were sampled with the aircraft, whereas ground based and airborne radar systems allowed extending the observations of snow properties beyond the flight level chosen for the in situ measurements.