ABSTRACT The parameters of a Pitt-Peters dynamic inflow model for a rotor undergoing collective inputs were extracted from experimental measurements on a hovering rotor. The four-bladed rotor of 2 m diameter featured straight, untwisted blades and a solidity of σ = 0.010. The nominal trim condition was CT /σ = 0.07 at a speed of 840 RPM. The rotor wake was measured using phase-resolved, 2D, 3-component particle image velocimetry (PIV) over a large region of interest (0.84 m x 0.77 m), and the integrated rotor aerodynamic forces were obtained from simultaneous hub loads measurements. The frequency response of rotor inflow to rotor thrust was found by measuring the system response to a stepped-sine collective input, which included frequencies of 0.2, 0.3, 0.4, 0.6, and 0.7/rev. The thrust amplitude increased with input frequency, reaching 27.4% of the steady thrust at the highest input frequency. The inflow amplitude was 4.3% of the steady inflow at 0.2/rev and decreased to 2.0

Yu, Daniel, Mortimer, Patrick, Sirohi, Jayant

Moisture Condensation Management in Automotive Headlamp Using Super Hydrophilic Cross-Linked Polymer Composites

2024-26-00841/16/2024

This work aims to develop potential super hydrophilic crosslinked smart polymer composites and condensation management device (CMD) for condensation control in automotive headlamps. Condensation and moisture buildup in the automotive headlamp decrease the visibility to the driver. The superhydrophilic crosslinked polymer composites were prepared with the combination of polyacrylamide-based hydrogels and hygroscopic lithium bromide desiccants. In this work, we have utilized various desiccants such as bromide, chloride and silica gel which is blended together with the polyacrylamide-based hydrogel. The prepared various compositional smart composites were characterized for chemical, thermal and morphological analysis using Fourier Transform Infrared Spectroscopy (FTIR), Differential Scanning Calorimetry (DSC), Polarized Optical Microscopy (POM) & Scanning Electron Microscopy (SEM), respectively. The developed super hydrophilic crosslinked polymer composites were kept into the designed

Chandkoti, Ikhlas, NAIKWADI, AMOL

Real time monitoring and control of engine reliability validation using IOT and AI

2024-26-03471/16/2024

IoT and AI have revolutionized the way we live and work, providing significant benefits across industries. The application of these technologies in engine reliability testing has immense potential as they offer real-time monitoring and analysis of engine performance. Engine reliability testing plays a crucial role in ensuring the safety, efficiency, and longevity of engines. However, traditional engine reliability testing methods can be time-consuming, costly, and often rely on manual inspection and data analysis. This paper presents a series of case studies that demonstrate the potential of IoT and AI tools in engine reliability testing, highlighting their benefits and limitations. This paper offers a comprehensive solution proposal for each use case, outlining the challenges and limitations of current engine reliability testing techniques. After that, the study proposes and evaluates IoT- and AI-based solutions to address these challenges. The study compares the effectiveness of the

Mujtaba, Quadri Syed, Yadav, Sanjay Kumar, kumar, Prabhakar, Verma, Vivek, Srinu, Kuncha

Enhancing Cargo Transportation using Intelligent systems for better Logistics Management

2024-26-01831/16/2024

Efficient cargo transportation plays a crucial role in logistics management and supply chain operations. Accurately detecting and utilizing cargo space within vehicles is vital for maximizing transport capacity, minimizing costs, and optimizing resource allocation and time management. This research paper focuses on enhancing cargo utilization using intelligent systems to improve logistics management. The major research is on developing a system that combines computer vision algorithms and intelligent systems to detect and implement a combination of features for efficient use of cargo space within vehicles and monitor cargo to reduce losses. The proposed approach will use and utilize image processing methods to get relevant features and identify cargo areas. Machine learning models, such as convolutional neural networks (CNNs) and object detection frameworks, will be trained and evaluated on a comprehensive dataset of cargo images to identify the most effective approach for cargo space

JAGTAP, Pramod Prakash, Kale, Shreeja, Mahali, Rakesh

A Machine Learning Approach for Hydrogen Internal Combustion (H2ICE) Mixture Preparation

2024-26-02541/16/2024

The present work discusses the potential benefits of using computational fluid dynamics (CFD) simulation and artificial intelligence (AI) in the design and optimization of hydrogen internal combustion engines (H2ICEs). A Machine Learning (ML) model is developed and applied to the CFD simulation data to identify optimal injection system parameters on the Sandia H2ICE Engine to improve the mixing. This approach can aid in developing predictive ML models to guide the design of future H2ICEs. For the current engine configuration, it is observed that hydrogen (H2) gas injection contributes mixing of H2 with air. If the injector parameters are optimized, mixture preparation is better and eventually combustion. A base CFD model is validated from the Sandia H2ICE engine data against Particle Image Velocimetry (PIV) data for velocity and Planar Laser Induced Fluorescence (PLIF) data for H2 mass fraction. Design of Experiments (DoE) was derived for the injection system parameters to train the ML

Jose, Alen, Probst, Daniel, Biware, Mukul

Utilizing Computed Tomography for Cell Characterization, Quality Assessment, and Failure Analysis

2024-26-01891/16/2024

This abstract presents an experimental study on using Computed Tomography (CT) scan technology for analyzing battery cell failures. Lithium-ion battery cells with known failure modes were subjected to cyclic test under different temperature and C-rates. CT scans provided high-resolution cross-sectional images of internal structures, revealing failure-related features. The advanced image processing techniques quantitatively assessed electrode morphology, active material distribution, and separator integrity. The study demonstrated CT scan's potential in non-destructive analysis, enabling a deeper understanding of failure mechanisms and informing improvements in cell design and manufacturing processes.

Singh, Sathya Prakash, Baidya, Kapil Krishna, ADHALE, Pratik

Unique Optimization Approach of Axle Component and it’s Weld Life Improvement

2024-26-03161/16/2024

Axles are a prominent part of automotive design. Along with a power transmission and differential system, axles support a vehicle’s weight and road-load reactions. Axles carry different attachments such as brakes and suspensions using brackets. Welds play an important role in design and longevity of bracket assemblies. Welds can be susceptible to fractures caused by intrusions akin to cracks and/or discontinuities, compounded by stress concentration due to weld profile and welding processes. Additionally, the simultaneous optimization of both brackets and welds remains a challenge with limited available methods. While topography or shape optimization techniques can enhance bracket robustness by minimizing compliance as the objective, this approach might inadvertently elevate the likelihood of weld fracture if weld dimensions are not concurrently updated. In this endeavor, compliance is used to improve weld life without affecting bracket robustness by using the Vertex Morphing

Wagh, Pranav, Sutar, Mohan, Nilangekar, Abhijit

SAE UNPLUGGED: Is Social Media Hindering AV Advancement?

1341910/25/2023

Today, there is a rush to be the first person to post a video or photo of an autonomous vehicle in a compromising light. But what impact is that having on the advancement of the industry? Many of us don't know the history of aviation and the risks that were taken to advance flight. Autonomous vehicles are having their Wright Brothers moment. When new technologies are developed and commercialized, there's always risk. What makes it worth it is the resulting technology that will decrease road fatalities and put an end to distracted driving. Join Grayson Brulte, Host of SAE Tomorrow Today, as he uses history to explain why society must avoid click-bait coverage of the AV industry to advance autonomy and make our world safer. Have your own thoughts on this topic? We'd love to hear from you! Share your comments, questions or ideas for future topics with Grayson on Twitter or send them to podcast@sae.org.

Hineman, Marcie

Localisation of Ultra-short Sound Emissions from Automotive Components by Using the Sound Field Scanning Method

2025-01-00925/5/2023

Design verification and quality control of automotive components require the analysis of the source location of ultra-short sound events, for instance the engaging event of an electromechanical clutch or the clicking noise of the aluminium frame of a passenger car seat under vibration. State-of-the-art acoustic cameras allow for a frame rate of about 100 acoustic images per second. Considering that most of the sound events introduced above can be far less than 10ms, an acoustic image generated at this rate resembles an hard-to-interpret overlay of multiple sources on the structure under test along with reflections from the surrounding test environment. This contribution introduces a novel method for visualizing impulse-like sound emissions from automotive components at 10x the frame rate of traditional acoustic cameras. A time resolution of less than 1ms eventually allows for the true localization of the initial and subsequent sound events as well as a clear separation of direct from

Rittenschober, Thomas

Hybrid 3D Sound Intensity and Simulation for Optimizing Acoustic Output of Truck Rear Axles

2025-01-01055/5/2023

This study presents a novel methodology for optimizing the acoustic performance of rotating machinery by combining scattered 3D sound intensity data with numerical simulations, focusing on the rear axle of a truck. Using Scan&Paint 3D, sound intensity data is rapidly acquired over a large spatial area with the assistance of a 3D sound intensity probe and infrared stereo camera. The experimental data is then integrated into far-field radiation simulations, enabling detailed analysis of the acoustic behavior and accurate predictions of far-field sound radiation. This hybrid approach offers a significant advantage for assessing complex acoustic sources, allowing for quick and reliable evaluation of noise mitigation solutions. While the current application focuses on the truck's rear axle far-field radiation, the same method can be extended to predict in-cabin sound pressure, providing a versatile solution for many industrial problems.

Fernandez Comesana, Daniel, Vael, Georges, Robin, Xavier, Orselli, Joseph, Schmal, Jared

Suction Cup Quality Predication by Digital Image Correlation

2023-01-0067

4/11/2023

Vacuum suction cups are used as transforming handles in stamping lines, which are essential in developing automation and mechanization. However, the vacuum suction cup will crack due to fatigue or long-term operation or installation angle, which directly affects production productivity and safety. The better design will help increase the cups' service life. If the location of stress concentration can be predicted, this can prevent the occurrence of cracks in advance and effectively increase the service life. However, the traditional strain measurement technology cannot meet the requirements of tracking large-field stains and precise point tracking simultaneously in the same area, especially for stacking or narrow parts of the suction cups. The application must allow multiple measurements of hidden component strain information in different fields of view, which would add cost. In this study, a unique multi-camera three-dimensional digital image correlation (3D-DIC) system was designed

Guo, Bicheng, Zheng, Xiaowan, Fang, Siyuan, Yang, Lianxiang