Fastener experts believe that upwards of 95% of all fastener failures are the result of either the wrong fastener for the job or improper installation. Whether this shocking figure is accurate or not, it is irrefutable that threaded fasteners are poorly misunderstood by many in both the fastener and user communities. In October 1990 the USS Iwo Jima suffered a catastrophic steam valve accident minutes after leaving port following repairs to its steam plant. In one of the single most deadly events of Operation Desert Storm, ten of the eleven crewmen present in the engine compartment would lose their lives.
Finite Element Analysis (FEA) is a powerful and well recognized tool used in the analysis of heat transfer problems. However, FEA can only analyze solid bodies and, by necessity thermal analysis with FEA is limited to conductive heat transfer. The other two types of heat transfer: convection and radiation must by approximated by boundary conditions. Modeling all three mechanisms of heat transfer without arbitrary assumption requires a combined use of FEA and Computational Fluid Dynamics (CFD).
RMS (Reliability-Maintainability-Safety-Supportability) engineering is emerging as the newest discipline in product development due to new credible, accurate, quantitative methods. Weibull Analysis is foremost among these new tools. New and advanced Weibull techniques are a significant improvement over the original Weibull approach. This workshop, originally developed by Dr. Bob Abernethy, presents special methods developed for these data problems, such as Weibayes, with actual case studies in addition to the latest techniques in SuperSMITH® Weibull for risk forecasts with renewal and optimal component replacement.
Finite Element Analysis (FEA) has been used by engineers as a design tool in new product development since the early 1990's. Until recently, most FEA applications have been limited to static analysis due to the cost and complexity of advanced types of analyses. Progress in the commercial FEA software and in computing hardware has now made it practical to use advanced types as an everyday design tool of design engineers. In addition, competitive pressures and quality requirements demand a more in-depth understanding of product behavior under real life loading conditions.
We are currently in the age of developing Autonomous Vehicles (AV). Never before in history, the environment has been as conducive as today for these developments to come together to deliver a mass produced autonomous car for use by general public on the roads. Several enhancements in hardware, software, standards and even business models are paving the way for rapid development of AVs, bringing them closer to production reality. Safety is an indispensable consideration when it comes to transportation products, and ground vehicle development is no different. We have several established standards. When it comes to Autonomous Vehicle development, an important consideration is ISO 26262 for, Automotive Functional Safety. Going from generic frameworks such as Failure Mode and Effects Analyses (FMEA) and Hazard and operability study (HAZOP) to Functional Safety, Safety of Intended Functionality, and Automotive Safety Integrity Levels specific is a natural progression.
Rapidly enhancing engineering techniques to manufacture components in quick turnaround time have gained importance in recent time. Manufacturing strategies like Additive Manufacturing (AM) are a key enabler for achieving them. Unlike traditional manufacturing techniques such as injection molding, casting etc., AM unites advanced materials, machines, and software which will be critical for Industry 4.0. Successful application of AM involves a specific combination and understanding of these three key elements. In this paper the AM approach used is Fused Deposition Modelling (FDM). Since material costs contribute to 60% of the overall FDM costs, it becomes a necessity to optimize the material consumption of the produced parts. This paper reports case studies of 3D printed parts used in an Automobile plant’s production aids, which utilize computational methods(CAE), topology optimization and FDM constrains (build directions) to manufacture the part in the most optimal way.
RESEARCH OBJECTIVE Accelerated artificial weathering performance has been always observed as critical and most important factor for durability prediction of colour and resin for a coating system. Photo oxidation of resin is the phenomenon behind coating’s ageing. Though accelerated weathering tests protocols are widely used in industry, they are very costly and still very time consuming. One automotive grade accelerated testing can go as long as 8 months duration. METHODOLOGY (maximum 150 words) Photo oxidation value (POV) is proportionate to the degradation of the resin material used in coating. During the accelerated weathering POV is measured for the coating at stipulated interval during initial phase and trend is plotted for deterioration verses weathering test duration. POV can be analysed with the help of FTIR analysis to observe bond absorption energy and bond separation energy in the resin system. This trend can be extrapolated to predict the weathering performance of coating.
Automotive safety is the primary concern in the current world. In order to develop safe and crashworthy vehicles, phenomena behind the energy absorption characteristics of every automotive component must be known. Steering wheel is one of the key players which could cause severe injuries to the driver if sufficient safety measures are not considered. This research focuses on the crash performance of commercial vehicle steering as per head form and body block test prescribed in ECE R12. Detailed FE (Finite Element) model of the steering wheel including armature, horn pad was developed using nonlinear material properties. The model was first validated using the test results. Comparisons between experimental results and finite element analysis results were conducted and correlated using load versus displacement profiles over the duration of impact. A good relationship between test and FE results was found which allows for investigation into the energy analysis of the steering components.
Objective: In ground vehicle industry, strain life approach is commonly used for predicting fatigue life. This approach requires use of fatigue material properties such as fatigue strength coefficient (σf'), fatigue strength exponent (b), fatigue ductility coefficient (εf'), fatigue ductility exponent (c), cyclic strength coefficient (K′) and cyclic strain hardening exponent (n′). These properties are obtained from stable hysteresis loop of constant amplitude strain-controlled uniaxial fatigue tests. Usually fatigue material properties represent 50th percentile experimental data and doesn't account possible material variation in the fatigue life calculation. However, for robust design of vehicle components, variation in material properties need to be taken into account. In this paper, methodology to develop 5th percentile (B5), 10th percentile (B10) and 20th percentile (B20) fatigue material properties are discussed.
These days backhoe loader have become main part of construction equipment vehicles. The main function of backhoe is to dig ditches to lay pipes and underground cable, set up foundations for buildings and create drainage systems. During these operations, many failures are observed in backhoe loader structure/parts. With the help of Accelerated structural durability testing, life of backhoe loader & its part can be estimated; through which we can understand different failure modes. The real time data was collected during various operations which includes pit digging, duck walk, ditch climbing, levelling, dozing, piling, truck loading etc. We have used software based approach to process the strain, displacement and other data collected during real time operation to create the duty cycle. The same duty cycle was simulated in the lab condition using servo hydraulic actuators.
To control air pollution in urban areas and to reduce carbon print in the cities, nowadays EV’s are preferred over IC engine vehicles. Earlier Electric vehicles used DC motor and Induction motors. But Brushless Permanent Magnet motors are preferred over Induction motor for EV’s due to their High Torque density, high-power density and highly efficiency. Prevalent Electric vehicles today have Brushless DC motors. Compared to BLDC, PMSM motor have smoother control and negligible torque ripplesThus, PMSM motor is preferred over BLDC for Electric Vehicle, because of its sinusoidal back emf which results in smoother control, and results into smoother and more comfortable driving experience to users. Methodology Sensor based field-oriented control (FOC) is implemented in 48 V 5kW Interior PMSM motor. . To start the Synchronous motor initial position of the rotor magnetic field should be known.
The SRM is gaining much interest for EVs due to its rare-earth-free characteristic and excellent performance. SRM possess several advantages such as low cost, high efficiency, high power density, fault-tolerant and it can produce extended constant power region, and this makes SRM as viable alternative over conventional PM drives. Objective: The objective of this paper is to establish proof of theoretical concepts related to SRM. The key to achieve an effective SRM modeling is to use a methodology that allow the nonlinearity of its magnetic characteristics to be represented while maximizing the simulation speed. This paper represents how magnetization data obtained from FEA in the form of look up tables is most appropriate way to represent SRM model. In this paper, performance analysis of SRM is done with the help of Open loop and Closed loop MATLAB simulations. These dynamic simulations of SRM will assist in understanding behavior of SRM in various loading and speed conditions.
Objective / Question: Is it possible to extend the envelope of simulation driven design and its advantages to development of complex dynamic systems viz. traction motor drives? The objective that then follows is how to enable OEM/Tier-1s to reduce wastes in the process of traction motor controller design, development, optimization and implementation. Motor control design to validation process is time consuming and tricky! Additionally, the requirement of software knowledge to write code to implement drive engineer's control ideas. The challenges here are - to name a few - algorithm for real time, addressing memory constraints, debugging, comprehending mathematical overflows, portability & BOM cost. These introduces wastes in parameters like time, cost, performance, efficiency and reliability. Methodology: Developing a new traction motor controller for E Mobility takes 18 - 24 months typically. 2 distinct activities take place in a loop.
Title Development of a Graphical User Interface (GUI) Based Tool for Vehicle Dynamics Evaluation Authors Mr. Shubham Kedia, Dr. Divyanshu Joshi, Dr. Muthiah Saravanan Mahindra Research Valley, Mahindra & Mahindra, Chennai Objective Objective metrics for evaluation of major vehicle dynamics performance attributes i.e. ride, handling and steering are required to compare, validate and optimize dynamic behavior of vehicles. Some of these objective metrics are recommended and defined by ISO and SAE, which involve data processing, statistical analysis and complex mathematical operations on acquired data, through simulations or experimental testing. Due to the complexity of operations and volume of data, evaluation is often time consuming and tedious. Process automation using existing tools such as MS Excel, nCode, Siemens LMS, etc. includes several limitations and challenges, which make it cumbersome to implement.
A virtual 'model' is generally a mathematical surrogate of a physical system and when well correlated, serves as a basis for understanding the physical system in part or in entirety. Drive Quality defines a driver's 'experience' of a blend of controlled responses to an applied input. The 'experience' encompasses physical, biological and bio-chemical perception of vehicular motion by the human body. In the automotive domain, many physical modeling tools are used to model the sub-components and its integration at the system level. Physical Modeling requires high domain expertise and is not only time consuming but is also very 'compute-resource' intensive. In the path to achieving 'vDQP (Virtual Drive Quality Prediction)' goal, one of the requirements is to establish 'well-correlated' virtual environments of high fidelity with respect to standard test maneuvers. This helps in advancing many developmental activities from a Controls and Calibration aspect.
In the current commercial vehicles market, ride-comfort and handling are crucial parameters for the customer and end user. There are various aspects which determine the vehicle behaviour. One of aspects is the structural rigidity of the vehicle, which has its own effect on vehicle dynamics. To meet the required stiffness of the main structural component of the vehicle i.e. chassis frame, FEA analysis has to be done in current methodology. The number of iterations have to be done to build an appropriate model with low weight, which can meet the design requirements. At first, conceptual design mock-up unit is to be developed then FEA (CAE) analysis to be done on it. If any design criteria are not met, then this cycle repeats again until it fulfils the required stiffness. Today, the direct stiffness procedure is the basic principle of almost every FEA software package.
Several people die every year due to vehicle accidents. Federal Motor Vehicle Safety Standards (FMVSS) are U.S. federal regulations stating design, structure, performance, and durability necessities for vehicles. The objective of a crash test for FMVSS No. 208 is to measure how well a passenger vehicle would protect its occupants in the event of a frontal crash. FMVSS 208 consists of series of tests including different impact surface type as well as occupant sizes. It also covers the belted and unbelted occupant behavior at the time of front impact. Each test scenario has different ways to injure the occupant. Airbags are the part of passive safety equipment family in any automobile and play an imperative role to reduce the occupant head and chest injuries at the time of crash or accidents. This study covers the evaluation of airbag performance in all FMVSS 208 load cases using validated Finite Element Methodology (FEM).
Sleeper buses are increasingly used as connectivity between cities and remote areas with sleeping comfort for passengers. During the normal operation, the bus body is subjected to several loads, external loads from the road (i.e. crossing over a speed bump, breaking & cornering). Moreover, there is a substantial possibility that these loads may lead to a structural failure. Hence, it is necessary to determine stresses occurred in the bus body to ensure its integrity under these driving scenarios. During the accident, rollover/front/rear/side impact, energy absorbing capacity of bus body structure is crucial for safety of passengers. The objective of this study is to reduce weight of bus structure while maintaining cost & safety as constraint. 3D Model prepared in NX and finite element model created in hypermesh ,LS-dyna/optistruct used as solver and post processing done in hyperview. In this study, fully loaded bus with passengers as well as maximum language mass, considered.