Browse Topic: Logistics
This specification covers a synthetic rubber in the form of sheet, strip, tubing, extrusions, and molded shapes. This specification should not be used for molded rings, compression seals, O-ring cords, and molded in place gaskets for aeronautical and aerospace applications without complete consideration of the end use prior to the selection this material.
Due to the spot weld and mechanical fastener share the similar characteristics to join sheets together with differences in deformation behavior around joint region, a novel spot joint element (user-defined element) consists of regular Mindlin shell elements and equations for different kinematic constraints is proposed to simplify the spot joint representation in lightweight automotive structures. The novel spot joint element can not only provide accurate deformation behavior around joint region but also output mesh-insensitive structural stresses at virtual nodes with the use of traction-based structural stress method for fatigue failure analysis. In this investigation, the structural stress distributions around joint circumference in the lap-shear specimens with spot weld or fastener are first calculated to validate the accuracy of the novel spot joint element. Then, the structural stresses along different cross-sections emanating from joint are also calculated for the specimens with
The automotive industry is undergoing a fundamental transformation in Electrical/Electronic (E/E) architecture, evolving from traditional distributed and domain-based designs toward zonal configurations. The rapid growth of software-defined functionality, cross-domain integration, and centralized computing has exposed inherent limitations of legacy architectures in scalability, wiring complexity, and system integration. Zonal E/E architecture addresses these challenges by consolidating computing and Input/Output (I/O) resources into high-performance controllers distributed across physical zones of a vehicle. This transformation, however, cannot occur instantaneously, as contemporary vehicle designs and E/E system solutions are the result of decades of incremental development based on distributed and domain-based paradigms. Moreover, key enabling technologies for zonal E/E architecture—such as high-performance Central Compute Platform (CCP) and zonal controllers, high-speed automotive
Thermal and lubrication management is critical for the performance characteristics of Electric Drive Units (EDUs) in electrified powertrains. Accurate assessment of lubrication flow, particularly in terms of wetting behavior and churning losses, is essential for optimizing EDU performance across various driving conditions. This study presents a comprehensive numerical investigation of lubrication flow behavior within an EDU using an advanced Smoothed Particle Hydrodynamics (SPH) method. The mesh-free SPH approach provides significant advantages in modeling intricate oil dynamics, such as oil splashing, and the behavior of oil in contact with rotating components. The primary focus of this study is to investigate the phenomena of oil splashing, wetting behavior characterized by the Wetting Fraction(WF), and churning losses within the gearbox environment. Key flow characteristics such as oil distribution, particle trajectories, torque resistance due to fluid drag, and oil volume fraction
Developing efficient fast-charging infrastructure along highway corridors is critical for reducing range anxiety and promoting long-distance electric travel. However, traditional static location approaches often fail to account for the stochastic interactions between continuous traffic flows and the stochastic variability of remaining driving ranges. To address these methodological gaps, this study develops a demand-driven optimization framework that integrates an improved Genetic Algorithm with the flow-capturing location-allocation model (GA-FCLM). Unlike static facility location approaches, the flow-capturing location-allocation component is specifically selected to maximize the interception of continuous traffic flows under strict range constraints, while the genetic algorithm efficiently navigates the high-dimensional discrete search space of simultaneous siting and sizing decisions. By synthesizing segment-level traffic flows with Monte Carlo simulations of state of charge (SOC
A computational study based on a conjugate heat transfer (CHT) method in SimericsMP+ was performed to predict the winding temperatures in an X76 emotor. In this study, the thermal load was represented in the simulation through the solution of electromagnetic equations in SimericsMP+, where heat generation was driven by root-mean-square (RMS) current, while liquid cooling was applied at flow rates ranging from 1 LPM to 6 LPM. Simulations were conducted to measure the temperature on three thermocouple locations on each side of the winding crown and weld regions under steady operation. The computational strategy employed a loosely coupled approach. A fluid-only simulation was first carried out to establish stable flow conditions, followed by coupling with solid conduction where the winding acted as the heat source. The predicted temperature distributions were then compared with test data. Results obtained show good agreement, with differences remaining within an acceptable range, thereby
This study introduces a novel in-cabin health monitoring system leveraging Ultra-Wideband (UWB) radar technology for real-time, contactless detection of occupants' vital signs within automotive environments. By capturing micro-movements associated with cardiac and respiratory activities, the system enables continuous monitoring without physical contact, addressing the need for unobtrusive vehicle health assessment. The system architecture integrates edge computing capabilities within the vehicle's head unit, facilitating immediate data processing and reducing latency. Processed data is securely transmitted via HTTPS to a cloud-based backend through an API Gateway, which orchestrates data validation and routing to a machine learning pipeline. This pipeline employs supervised classifiers, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Random Forest (RF) to analyze features such as temporal heartbeat variability, respiration rate stability, and heart rate. Empirical
In heavy-duty tippers, where challenging conditions demand high torque, planet carriers play a crucial role by enabling efficient load distribution and torque transmission while supporting gear ratio and speed variation in space-constrained systems such as automatic transmissions, hybrid drivetrains, and electric vehicles. This paper focuses on the comprehensive durability performance assessment of planet carrier housing (PCH) using duty cycles derived from road load data acquisition (RLDA) measurements for a heavy-duty tipper gearbox development program. The existing Design Validation Plan (DVP) for the planet carrier considers first gear utilization of 10-15% at 40% vehicle overload, in line with historical data. However, recent trends in mining applications revealed vehicle overloads of 55-65%, leading to an increase in first gear utilization (25-35%). This shift presents challenges for original equipment manufacturer (OEM) to enhance design durability while incorporating additional
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