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Although structural intensity was introduced in the 80's, this concept never found practical applications, neither for numerical nor experimental approaches. Quickly, it has been pointed out that only the irrotational component of the intensity offers an easy interpretation of the dynamic behavior of structures by visualizing the vibration energy flow. This is especially valuable at mid and high frequency where the structure response understanding can be challenging. A new methodolodgy is proposed in order to extract this irrotational intensity field from the Finite Element Model of assembled structures such as Bodies In White. This methodology is hybrid in the sense that it employs two distinct solvers: a dynamic solver to compute the structural dynamic response and a thermal solver to address a diffusion equation analogous to the thermal conduction built from the previous dynamic response.

Water management in PEMFC power generation systems is a key point to guarantee optimal performances and durability. It is known that a poor water management has a direct impact on PEMFC voltage, both in drying and flooding conditions: furthermore, water management entails phenomena from micro-scale, i.e., formation and water transport within membrane, to meso-scale, i.e., water capillary transport inside the GDL, up to the macro-scale, i.e., water droplet formation and removal from the GFC. Water transport mechanisms through the membrane are well known in literature, but typically a high computational burden is requested for their proper simulation. To deal with this issue, the authors have developed an analytical model for the water membrane content simulation as function of stack temperature and current density, for fast on-board monitoring and control purposes, with good fit with literature data.

The present study discusses about the determination of the Seal drag force in the application where elastomeric seal is used with metallic interface in the presence of different fluids. An analytical model was constructed to predict the seal drag force and experimental test was performed to check the fidelity of the analytical model. A Design of Experiment (DoE) was utilized to perform experimental test considering different factors affecting the Seal drag force. Statistical tools such as Test for Equal Variances and One way Analysis of Variance (ANOVA) were used to draw inferences for population based on samples tested in the DoE test. It was observed that Glycol based fluids lead to lubricant wash off resulting into increased seal drag force. Additionally, non-lubricated seals tend to show higher seal drag force as compared to lubricated seals. Keywords: Seal Drag, DoE, ANOVA

Bio-composites have gained significant attention within the aerospace industry due to their potential as a sustainable solution that addresses the demand for lightweight materials with reduced environmental impact. These materials blend natural fibers sourced from renewable origins, such as plant-based fibers, with polymer matrices to fabricate composite materials that exhibit desirable mechanical properties and environmental friendliness. The aerospace sector's growing interest in bio-composites originates from those composites’ capacity to mitigate the industry's carbon footprint and decrease dependence on finite resources. This study aims to investigate the suitability of utilizing plant derived flax fabric/PLA (polylactic acid) matrix-based bio-composites in aerospace applications, as well as the recyclability potential of these composites in the circular manufacturing economy.

A typical high-pressure hose assembly consists of hose made with synthetic polymer braids and Teflon tube crimped with metallic fittings. These hose assemblies are mainly used for aircraft landing gear application considering its high-pressure sustenance and better flexibility. The proposed study investigates the effect of thermo-mechanical stress generated due to cyclic soaking and flexibility testing at thermostatic subzero (-65°F) and high temperature (+275°F) on performance of high-pressure hose assembly. This effect is further studied through hose tear-down which was envisioned to investigate the hose layer degradation and focused on changes in inner PTFE tube, which ultimately leads to product performance issues. Keywords: braids, tear down analysis, thermo-mechanical, inter-layer abrasion.

In this paper, experimental studies were conducted to examine the mechanical behavior of a polymer composite material called polyamide with glass fiber (PA6-GF), which was fabricated using the three-dimensional (3D) fusion deposition modeling (FDM) technique. FDM is one of the most well-liked low-cost 3D printing techniques for facilitating the adhesion and hot melting of thermoplastic materials. PA6 exhibits an exceptionally significant overall performance in the families of engineering thermoplastic polymer materials. By using twin-screw extrusion, a PA6-GF mixed particles made of PA6 and 20% glass fiber was produced as filament. Based on literature review, the samples have been fabricated for tensile, hardness, and flexural with different layer thickness of 0.08 mm, 0.16 mm, and 0.24 mm, respectively. The composite PA6-GF behavior is characterized through an experimental test employing a variety of test samples made in the x and z axes.

This specification covers nitrile-butadiene elastomer in the form of molded sheet and shapes, color coded yellow per ARP1527.

This specification covers a nitrile (NBR) rubber in the form of sheet, strip, tubing, extrusions, and molded shapes.

This specification covers a nitrile (NBR) rubber in the form of sheet, strip, tubing, extrusions, and molded shapes.

For intelligent vehicles, a robust perception system relies on training datasets with a large variety of scenes. The architecture of federated learning allows for efficient collaborative model iteration while ensuring privacy and security by leveraging data from multiple parties. However, the local data from different participants is often not independent and identically distributed, significantly affecting the training effectiveness of autonomous driving perception models in the context of federated learning. Unlike the well-studied issues of label distribution discrepancies in previous work, we focus on the challenges posed by scene heterogeneity in the context of federated learning for intelligent vehicles and the inadequacy of a single scene for training multi-task perception models. In this paper, we propose a federated learning-based perception model training system.

Fracture characterization of automotive metals under simple shear deformation is critical for the calibration of advanced fracture models employed in forming and crash simulations. In-plane shear fracture tests of high ductility materials have proved challenging since the sample edge fails first in uniaxial tension before the fracture limit in shear is reached at the center of the gage region. Although through-thickness machining is undesirable, it appears required to promote higher strains within the shear zone. The present study seeks to adapt existing in-plane shear geometries, which have otherwise been successful for many automotive materials, to have a local shear zone with a reduced thickness. It is demonstrated that a novel shear zone with a pocket resembling a “peanut” can promote shear fracture within the shear zone while reducing the risk for edge fracture. An emphasis was placed upon machinability and surface quality for the design of the pocket in the shear zone.

Fracturing in a tight radius during bending is one of the major manufacturing issues in forming Advanced High Strength Steels (AHSS). The study investigated the bendability of AHSS under two forming conditions: bending with and without stretched over the die radius. The bendability was evaluated by conducting modified Bending Under Tension (BUT) test for stretch bending and 90o v bend test for bending without stretch. The study also examined the effect of material properties on the limiting bend ratio. Various strength high strength steels, range from 420 MPa to 1700 MPa tensile strength, were selected in the study. Results indicated that critical radius-to-thickness ratios between the two tests are different but correlated in a relationship which was depicted in the bendability diagram.

Multiple hybrid bead designs were investigated in this study to control the springback on DP780 samples using post-stretching technique. The performance of the four different hybrid bead designs was evaluated by measuring the minimum blank-lock tonnage required to control the springback during a U-channel stamping process. A finite element (FE) model of the U-channel stamping process was developed to simulate the process and predict the minimum blank-lock tonnage required for springback control using each of the hybrid bead designs. It is shown that the developed FE model predicts both the required minimum blank-lock tonnage for post-stretching, and the springback profile, with good accuracy.

During the vehicle lifecycle, customers are able to directly perceive the outer panel stiffness of vehicles in various environmental conditions. The outer panel stiffness is an important factor for customers to perceive the robustness of the vehicle. In the real test of outer panel stiffness after prototype production, evaluators manually press the outer panel in advance to identify vulnerable areas to be tested and evaluate the performance only in those area. However, when developing the outer panel stiffness performance using FEA (Finite Element Analysis) before releasing the drawing, it is not possible to filter out these areas, so the entire outer panel must be evaluated. This requires a significant amount of computing resources and manpower. In this study, an approach utilizing artificial intelligence was proposed to streamline the outer panel stiffness analysis and improve development reliability.

One of the five major performances of vehicles, NVH(Noise, Vibration, Harshness), has recently emerged in electric vehicles, again. And, front loading NVH simulation is essential to respond nimbly to automotive industry these days. However, the two components of the simulation, mathematical sound absorption modeling equation, and the acoustic parameters, the input factor, is requiring improvement because of lack of robustness. In this study, we tried to strengthen, standardize, and refine the connectivity between micro (fine structure) and macro (acoustic parameter-related physical properties) characteristics, and improve the consistency with actual NVH performance. As a porous polymer material, polyurethane foam, which is widely used for the interior and exterior of automobiles, is treated as a target material.

Multiple experimental studies were performed on galling intiation for variety of tooling materials, coatings and surface treatments, sheet materials with various surface textures and lubrication. Majority of studies were performed for small number of samples in laboratory conditions. In this paper, the methodology of screening experiment using different combinations of tooling configurations and sheet material in the lab followed by the high volume small scale U-bend performed in the progressive die on the mechanical press is discussed. The experimental study was performed to understand the effect of the interface between the sheet metal and the die surface on sheet metal flow during stamping operations. Aluminum sheet AA5754 2.5mm thick was used in this experimentation. The sheet was tested in laboratory conditions by pulling between two flat insert with controllable clamping force and through the drawbead system with variable radii of the female bead.

Roller offsetting is an incremental forming technique used to generate offset stiffening or mating features in sheet metal parts. Compared to die forming, roller offsetting utilizes generic tooling to create versatile designs at a relatively lower forming speed, making it well-suited for low volume productions in automotive and other industries. However, more significant distortion can be generated from roller offset forming process resulting from springback after forming. In this work, we use particle swarm optimization to identify the tool path and resulting feature geometry that minimizes distortion. In our approach, time-dependent finite element simulations are adopted to predict the distortion of each candidate tool path using a quarter symmetry model of the part. A multi-objective fitness function is used to both minimize the distortion measure while constraining the minimal radius of curvature in the tool path.