Browse Topic: CAD, CAM, and CAE
A passenger vehicle's front-end structure's structural integrity and crashworthiness are crucial to ensure compliance with various frontal impact safety standards (such as those set by Euro NCAP & IIHS). For a new front-end architecture, design targets must be defined at a component level for crush cans, longitudinal, bumper beam, subframe, suspension tower and backup structure. The traditional process of defining these targets involves multiple sensitivity studies in CAE. This paper explores the implementation of Physics-Informed Neural Networks (PINNs) in component-level target setting. PINNs integrate the governing equations into neural network training, enabling data-driven models to adhere to fundamental mechanical principles. The underlying physics in our model is based upon a force scheme of a full-frontal impact. A force scheme is a one-dimensional representation of the front-end structure components that simplifies a crash event's complex physics. It uses the dimensional and
In area of modern manufacturing, ensuring product quality and minimizing defects are utmost important for maintaining competitive advantage and customer satisfaction. This paper presents an innovative approach to detect defect by leveraging Artificial Intelligence (AI) models trained using Computer-Aided Design (CAD) data. Traditional defect detection methods often rely on physical inspection, which can be time-consuming and prone to human error. The conventional method of developing an AI model requires a physical part data, By utilizing CAD data, the time to develop an AI model and implementing it to production line station can be saved drastically. This approach involves the use of AI algorithms trained on CAD models to detect and classify defects in real-time. The field trial results demonstrate the effectiveness of this approach in various industrial applications, highlighting its potential to revolutionize defect detection in manufacturing.
Automotive OEMs can derive significant cost savings by reducing the quantity of physical crash tests and thereby accelerate product development, when they follow the Euro NCAP Virtual Testing procedure. It helps in optimizing the overall vehicle development process via more efficient simulations, as well as facilitates in early adoption of new safety regulations. In this pursuit, companies must comply with strict Euro NCAP requirements, which includes transparency and traceability of virtual tests. A major challenge therein is model validation – which requires highly precise detailing and extensive use of data for accurately replicating real physics of the problem. Deploying these workflows into an existing simulation process can be a complicated and time-consuming task, particularly when integrating various simulation and testing methods. A powerful simulation process and data management system (SPDM) can thereby assist companies to automate their entire simulation process, ensures
Simulation-driven product development involves numerous computer aided engineering (CAE) model iterations, where each version represents a critical difference. Usually, these multiple model versions are generated by hundreds of simulation engineers working in teams distributed across the globe, making functional collaboration a key to effective product development. To manage vast amounts of CAE data generated by engineers working simultaneously on a project, it is imperative to have a robust version management system to track changes in the CAE data. A robust version management is the backbone of an effective simulation data management (SDM) system. It involves capturing and documenting model changes at every design iteration. Accurate documentation of the model changes is crucial as it helps in understanding the model evolution and collaboration among engineers. However, documenting is usually considered a boring and tedious task by many engineers. This often leads to bad change
The objective of this paper is to evaluate the thermal performance of the brake discs in the design stage of its life cycle by developing a methodology to replicate dynamometer testing using multi-disciplinary Finite Element Analysis (FEA) methods. A simulation workflow was formulated in which Computational Fluid Dynamics (CFD) was used to create temperature and velocity dependent Heat Transfer Coefficients (HTC) which were in turn used in Computer Aided Engineering (CAE) to do a thermo-mechanical analysis. With this workflow various designs of the brake discs were analyzed. A sensitivity study was done to determine critical design features that affected its thermal performance. A final design was fixed that met both the weight and thermal performance targets. This design was evaluated in dynamometer testing, and 93% correlation was achieved. Thus, the developed simulation workflow ensured that a first-time right brake disc can be finalized in the design stage, which will meet the
The high-pressure steering hose in a hydraulic steering system carries pressurized hydraulic fluid from the power steering pump to the steering gear (or steering rack). Its main function is to transmit the force generated by the pump so that the hydraulic pressure assists the driver in turning the wheels more easily. The high-pressure hydraulic pipeline in the power steering system is a vital component for ensuring optimal performance. During warranty analysis, leakage incidents were observed at the customer end within the warranty period. The primary factors contributing to these failures include pipe material thickness, material composition, mechanical properties, and engine-induced vibrations. This study investigates fatigue-related failures through detailed material characterization and Computer-Aided Engineering (CAE) based on real world usage road load data collected. The objective is to identify the root causes by examining the influence of varying pipe thickness on fatigue life
In pursuit of a distinct sporty interior sound character, the present study explores an innovative strategy for designing intake systems in passenger vehicles. While most existing literature primarily emphasizes exhaust system tuning for enhancing vehicle sound quality, the current work shifts the focus toward the intake system’s critical role in shaping the perceived acoustic signature within the vehicle cabin. In this research work, target cascading and settings were derived through a combination of benchmark and structured subjective evaluation study and aligning with literature review. Quantitative targets for intake orifice noise was defined to achieve the desired sporty character inside cabin. Intake orifice targets were engineered based on signature and sound quality parameter required at cabin. Systems were designed by using advanced NVH techniques, Specific identified acoustic orders were enhanced in the intake system to reinforce the required signature in acceleration as well
In response to increasing environmental awareness and the automotive industry's push for sustainability, the development of lightweight and robust components has become a key area of focus. This paper presents a multidisciplinary approach to the design and optimization of an aluminum parking brake lever, leveraging advanced structural optimization techniques to enhance performance while meeting stringent environmental standards. Traditional manufacturing processes for automotive components, such as stamping, often rely on steel due to its strength and ease of processing. However, the high density of steel can significantly impact the overall weight of the vehicle, leading to increased fuel consumption and emissions. In contrast, aluminum’s superior strength-to-weight ratio offers a promising alternative. This study employs Finite Element Analysis (FEA) to model the initial stress history of the lever, followed by the application of structural optimization tools to refine its geometry
The concept of “quality feel” in automotive interiors relates to how consumers perceive a product’s quality through touch and feel. While subjective, it’s crucial for satisfaction and differentiation and is defined by engineering requirements like displacement, especially for interior components. Assessing this early in development is vital. Traditionally, this evaluation happens virtually using Computer Aided Engineering (CAE) simulations, which measure displacement and stiffness. However, conventional simulation methods, like Finite Element Method (FEM), can be time-consuming to set up. This work presents two case studies where the evaluation of an interior panel’s quality feel, using structural numerical simulations combined with the Simulation Driven Design (SDD) method was performed. SDD is an iterative process where simulation results guide design modifications, optimizing the component until it meets quality criteria, which are based on simulated human touch and resulting
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