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Abstract The non-pneumatic tire (NPT) has been widely used due to its advantages of no run-flat, no need for air maintenance, low rolling resistance, and improvement of passenger comfort due to its better shock absorption. It has a variety of applications in military vehicles, earthmovers, the lunar rover, stair-climbing vehicles, etc. Recently, the Unique Puncture-Proof Tire System (UPTIS) NPT has been introduced for passenger vehicles. In this study, three different design configurations, viz., Tweel, Honeycomb, and newly developed UPTIS, have been compared. The effect of polyurethane (PU) material nonlinearity has also been introduced by applying five different nonlinear PU material properties in the spokes. The combined analysis of the PU material nonlinearity and spoke design configuration on the overall tire stiffness and spoke damage prediction is done using three-dimensional (3D) finite element modelling (FEM) simulations performed in ANSYS 16.0.

Abstract This work introduces the concept of a dual-layer specification structure for standards that separate interoperability functions, such as backward compatibility, localization, and deployment, from those essential to reliability, security, and functionality. The latter group of features, which constitute the actual standard, make up the baseline layer for instructions, while all the elements required for interoperability are specified in a second layer, known as a Protocols, Operations, Usage, and Formats (POUF) document. We applied this technique in the development of a standard for Uptane [1], a security framework for over-the-air (OTA) software updates used in many automobiles. This standard is a good candidate for a dual-layer specification because it requires communication between entities, but does not require a specific format for this communication.

Abstract Inspection of Composite panels is vital to the assessment of their ability to be fit for purpose. Conventional methods such as X-ray CT and Ultrasonic scanning can be used, however, these are often expensive and time consuming processes. In this paper we investigate the use of off-the-shelf Non-Destructive Test, NDT, equipment utilizing Fringe projection hardware and open source software to rapidly evaluate a series of composite panels. These results are then verified using destructive analysis of the panels to prove the reliability of the rapid NDT methods for use with carbon composite panels. This process allows us to quickly identify regions of geometric intolerance or formed defects without the use of expensive sub-surface scanning systems, enabling a fast and cost effective initial part evaluation system. The focus of this testing series is on 6mm thick pre-preg carbon-epoxy composite laminates that have been laid up using AFP and formed using TRF.

Abstract Reliability analysis of a large-scale system under random dynamic loads can be a very time-consuming task since it requires repeated studies of the system. In many engineering problems, for example, wave loads on an offshore platform, the excitation loads are defined using a power spectral density (PSD) function. For a given PSD function, one needs to generate many time histories to make sure the excitation load is modeled accurately. Global and local approximation methods are available to predict the system response efficiently. Each way has their advantages and shortcomings. The combined approximations (CA) method is an efficient method, which combines the advantages of local and global approximations. This work demonstrates two methodologies that utilize CA to reduce the cost of crude or separable Monte Carlo simulation (MCS) of linear dynamic systems when the excitation loads are defined using PSD functions.

Abstract On contrast to the qualitative approach used in the majority of researches, an evaluation quantitative approach is introduced not only to depict the plain individual effect of the influence of the high-pressure torsion (HPT) processing conditions on the microstructural and Hv-values of the ultra-hard nanostructured AA6061-15%SiCp composite but also to detect its possible parameters functional interaction and nonlinear trends involved. Experimental data were used to establish many adequate and significant empirical models to detect and to evaluate the mutual functional interrelationships between the Hv-values of the composite, each of HPT processing pressure, and number of revolutions. For each group of interrelated parameters, the preferred selected developed model has been exploited to generate the relevant contours and response surface graphs.

Abstract A key element in an ergonomically designed driver’s seat in a car is the correct identification of driver seating position and posture accommodation. Current practice by the automotive Original Equipment Manufacturer (OEM) is to utilize the Society of Automotive Engineering (SAE) J1517 standard practice as a reference. However, it was found that utilizing such guidelines, which were developed based on the American population, did not fit well with the anthropometry and stature of the Malaysian population. This research seeks to address this issue by comparing the SAE J1517 Model against Malaysian preferred driving position. A total of 62 respondents were involved for the driver seating position and accommodation study in the vehicle driver’s seat buck mockup survey and measurements. The results have shown that the Malaysian drivers prefer to sit forward as compared to the SAE J1517 Model and have shorter posture joint angle.

Abstract Geometric variation stemming from manufacturing can be a limiting factor for the quality and reliability of products. Therefore, manufacturing assessments are increasingly being performed during the early stages of product development. In the aerospace industry, products are complex engineering systems, the development of which require multidisciplinary expertise. In such contexts, there are significant barriers against assessing the effects of geometric variation on the functionality of products. To overcome these barriers, this article introduces a new methodology consisting of a modelling approach linked to a multidisciplinary simulation environment. The modelling approach is based on the parametric point method, which allows point-scanned data to be transferred to parameterised CAD models. In a case study, the methodology is implemented in an industrial setting.

Abstract Aircraft subsystem development involves various combinations of testing and qualification activities to realize a flight-worthy system. The subsystem needs to be verified for a massive number of customer requirements. Power quality (PQ) testing is also an important testing activity carried out as part of the environmental qualification test. It is intended to verify the functionality of subsystems with various kinds of power disturbances and to determine the ability of a subsystem to withstand PQ disturbances. The subsystem being designed should be reliable enough to handle PQ anomalies. A PQ test results in an enormous amount of data for analysis with millions of data samples depending on the test and can be identified as big data. The engineer needs to analyze each set of test data as part of post-processing to ensure the power disturbances during testing are as per the standard requirements and that the functional performance of the subsystem is met.

Abstract The development of automated driving systems (ADS) necessitates procedures to validate system safety. The reliability of an ADS’s environment perception provided by lidar, radar, and camera sensors is of special interest in this context, because perception errors can be safety-critical. In this article, we formalize the reliability-based validation of environment perception for safe automated driving and discuss associated challenges. We describe a potential solution to a perception reliability validation by deriving performance requirements at the sensor level. We then summarize statistical methods to learn sensor perception reliabilities in field tests, on proving grounds, and through virtual simulations. With the developed safety validation framework, we show that, potentially, one can validate the safety of an ADS with feasible test effort.

Abstract Autonomous vehicles (AVs) are being rapidly introduced into our lives. However, public misunderstanding and mistrust have become prominent issues hindering the acceptance of these driverless technologies. The primary objective of this study is to evaluate the effectiveness of a driving simulator to help the public gain an understanding of AVs and build trust in them. To achieve this aim, we built an integrated simulation platform, designed various driving scenarios, and recruited 28 participants for the experiment. The study results indicate that a driving simulator effectively decreases the participants’ perceived risk of AVs and increases perceived usefulness. The proposed methodologies and findings of this study can be further explored by auto manufacturers and policymakers to provide user-friendly AV design.

Abstract Climate change has necessitated the development of “green” alternatives to replace existing materials. This focus has resulted in the push toward fabricating natural fiber-reinforced polymer composites. This research work looks at the surface roughness (SR) of natural fibers like rice husk ash (RHA) and groundnut shell ash (GSA) reinforced in nine different concentrations into an epoxy matrix to form composites. Composite samples are fabricated using various concentrations of natural fibers and measures and optimizes for the SR through the implementation of genetic algorithms (GA). It was found that a minimum SR of 1.422 μm can be obtained for an epoxy/hardener ratio of 3:1 and without the addition of any reinforcements. This optimization was achieved within 102 generations. In addition to GA optimization, another optimization implementation was done through the Taguchi method.

Abstract Accelerated durability testing of automotive components has become a major interest for the ground vehicle Industries. This approach can predict the life characteristics of the vehicle by testing fatigue failure at higher stress level within a shorter period of time. Current tradition of laboratory testing includes a rigid fixture to mount the component with the shaker table. This approach is not accurate for the durability testing of most vehicle components especially for those parts connected directly with the tire and suspension system. In this work, the effects of the elastic support on modal parameters of the tested structure, such as natural frequencies, damping ratios and mode shapes, as well as the estimated structural fatigue life in the durability testing were studied through experimental testing and numerical simulations.

Abstract Uncertainties in design represent a considerable industrial stake. Controlling the reliability and robustness of a mechanical system at the level of design has become necessary in order to control these uncertainties. Using the theory of probabilistic design optimization, the present work reports on the application of the concept of reliability-based robustness on minimizing the weight of a planetary gear train (PGT). The optimum combination of reliability and robustness for the minimum weight of the PGT was found using an optimization algorithm based on Particle Swarm Optimization (PSO) and Monte Carlo Simulation (MCS). The algorithm was developed by combining the propagation of uncertainties with the optimization of the function objective within a single probabilistic model. The results show that a reliability-based robust design offers a better alternative to the traditional deterministic design models.

Abstract Welding is a dominant joining process employed in fabrication industries, especially in critical areas such as boiler, pressure vessels, and marine structure manufacturing. Online monitoring of welding processes using sensors and intelligent models is increasingly used in industries for predicting weld conditions. Studies are conducted in a Shielded Metal Arc Welding (SMAW) process using sound, current, and voltage sensors to predict the weld conditions. Sensor signatures are acquired from the good weld and defective weld conditions established in this study. Signal processing is carried out, and time-domain statistical features are extracted. Statistical features are also extracted from the power waveform derived from the current and voltage data for all the weld conditions. Classification And Regression Tree (CART) and Support Vector Machine (SVM) algorithms are used to build the statistical models to predict the weld conditions.

Abstract The dimensional quality of the car body is built on quality management of form, fitment, and functional requirements. Each of these attributes reflects the final product quality and, therefore, needs to be ascertained quantitatively. Design intent and functionality conformance with specifications are paramount to performance, and thus quality. It is accomplished through optimal Geometric Dimensioning and Tolerancing of parts (GD&T), datum/Primary Locating Points (PLP) strategy, tricks/levers, and assembly design. Challenges stem from the complexity involved in the datum layout strategy and its optimization for desired deviations. Incorrect datum schemes in design prompt underconstrained fixtures, redundant datum, the sensitivity of datum layout, etc. and induce defects in later stages. The end effect is smoothing out the variation issues leading to compromise in quality.

Abstract Wheel alignment audit systems are used in vehicle service environments to identify vehicles which may benefit from a comprehensive evaluation on a precision static alignment measurement system. Non-contact dynamic wheel alignment audit systems acquire measurement data from vehicles in motion passing between sensors in an inspection lane. The dynamic nature of the moving vehicles introduces variables which are not present when auditing wheel alignment on a static vehicle. Measurement results are affected by changes in vehicle velocity, steering movement, suspension movement, floor surface conditions, tire sidewall profiles, and driver presence, as well as other variables.

Abstract Increasing the strength of materials is effective in reducing weight and boosting structural part performance, but there are cases where the residual strain generated during the process of manufacturing of high-strength materials results in a decline of durability. It is therefore important to understand how the residual strain in a manufactured component changes due to processing conditions. In the case of a connecting rod, because the strain load on the connecting rod rib sections is high, it is necessary to clearly understand the distribution of strain in the ribs. However, because residual strain is generally measured by using X-ray diffractometers or strain gauges, measurements are limited to the surface layer of the parts. Neutron beams, however, have a higher penetration depth than X-rays, allowing for strain measurement in the bulk material.

Abstract The increasingly important need to design simpler structures, reducing the number of constituent components, has motivated the approach outlined in this article, which proposes an effective reengineering example of a product belonging to the automotive industry, combining the advantages offered by the compliant mechanisms with production opportunities linked to the use of additive manufacturing. Taking advantage of compliant mechanisms makes it possible to significantly improve the component’s production phase, leading to undoubted benefits on the supply chain and on product’s time to market, benefits made possible by exploiting the outstanding characteristic of additive manufacturing to produce already assembled multi-material structures.

Corrigendum - The word "Differ" in the title should be corrected to "Different". The correct title is: Rapid Methodology to Simultaneous Quantification of Different Antioxidants in Biodiesel Using Infrared Spectrometry and Multivariate Calibration.

Abstract The aim of this work is to quantify three different antioxidants in biodiesel - Santoflex, baynox, and tocopherol-using Middle Infrared (MIR) spectroscopy and chemometrics. For the construction of the models, 28 samples containing an antioxidant in the range of 0.1 to 500 mg/kg in biodiesel were used. We developed three models based on PLS 1 multivariate calibration method to quantify each of the three antioxidants separately and a model based on PLS 2 method to quantify simultaneously all the antioxidants. All models were compared to the values of root mean square error of calibration (RMSEC) and validation (RMSEP). For the baynox, santoflex, and tocopherol antioxidants quantification using PLS 1, the values of RMSEC and RMSEP were 37.2, 18.8, 9.0 mg/kg, and 26.7, 21.1, 68.6 mg/kg, respectively.