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All around the world, steps are being taken to improve the quality of our environment. Prominent among these are the definition, implementation, and attainment of increasingly stringent emissions regulations for all types of engines, including off-highway diesels. These rigorous regulations have driven use of technologies like after-treatment, advanced air systems, and advanced fuel systems. Fuel dispensed off-highway is routinely and significantly dirtier than fuel from on-highway outlets. Furthermore, fuels used in developing countries can be up to 30 times dirtier than the average fuels in North America. Poor fuel cleanliness, coupled with the higher pressures and performance demands of modern fuel systems, create life challenges greater than encountered with cleaner fuels. This can result in costly disruption of operations, loss of productivity, and customer dissatisfaction in the off-highway market.

Temporal light modulation (TLM), colloquially known as “flicker,” is an issue in almost all lighting applications, due to widespread adoption of LED and OLED sources and their driving electronics. A subset of LED/OLED lighting systems delivers problematic TLM, often in specific types of residential, commercial, outdoor, and vehicular lighting. Dashboard displays, touchscreens, marker lights, taillights, daytime running lights (DRL), interior lighting, etc. frequently use pulse width modulation (PWM) circuits to achieve different luminances for different times of day and users’ visual adaptation levels. The resulting TLM waveforms and viewing conditions can result in distraction and disorientation, nausea, cognitive effects, and serious health consequences in some populations, occurring with or without the driver, passenger, or pedestrian consciously “seeing” the flicker.

It is generally agreed that adequate resolution is required to reproduce the structure of spray and gas jets in numerical computations. It has not been clarified what this resolution should be although it would appear reasonable to assume that it should be such that the physical scales of the problem are resolved. In the case of a jet, this implies that near the orifice, the jet diameter has to be resolved since this is the appropriate length scale. It is shown in this work that if such a resolution is not used in computing transient jets, the structure of the jet is not reproduced with adequate accuracy. In fact, unexpected, erroneous and misleading dependence on ambient turbulence length and time scales will be predicted when the initial ambient turbulence diffusivity is small relative to the jet diffusivity. When the ambient turbulence diffusivity is of the same order as the jet diffusivity or greater, entrainment rates are significantly underpredicted.

Autonomous vehicles have the potential to transform lives by providing transportation to a wider range of users. However, with this new method of transportation, user acceptance and comfort are critical for widespread adoption. This exploratory study aims to investigate what makes passengers uncomfortable in existing vehicles to inform the design of future autonomous vehicles. In order to predict what may impact user acceptance for a diverse rider population for future autonomous vehicles, it is important to understand what makes a broad range of passengers uncomfortable today. In this study, interviews were conducted for a total of 75 participants from three diverse groups, including 20 automotive engineering graduate students who are building an autonomous concept vehicle, 21 non-technical adults, and 34 senior citizens. The results revealed both topics which made different groups of passengers uncomfortable as well as how these varied between the groups.

Financial planners are always anxious to assist engineers and scientists in making retirement decisions. Many engineers, especially Industrial Engineers (IE), have had courses that provide the knowledge to make these retirement financial plans themselves. This paper will provide a method of estimating retirement needs utilizing Excel software and IE college coursework.

The purpose of this research is to characterize the wear resistance of wheel treads made of polymeric woven and non-woven fabrics. Experimental research is used to characterize two wear mechanisms: (1) external wear due to large sliding between the tread and rocks, and (2) external wear due to small sliding between the tread and abrasive sand. Experimental setups include an abrasion tester and a small-scale merry-go-round where the tread is attached to a deformable rolling wheel. The wear resistance is characterized using various measures including, quantitatively, by the number of cycles to failure, and qualitatively, by micro-visual inspection of the fibers’ surface. This paper describes the issues related to each experiment and discusses the results obtained with different polymeric materials, fabric densities and sizes. The predominant wear mechanism is identified and should then be used as one of the criteria for further design of the tread.

In the next 20 years fully autonomous vehicles are expected to be in the market. The advance on their development is creating paradigm shifts on different automotive related research areas. Vehicle interiors design and human vehicle interaction are evolving to enable interaction flexibility inside the cars. However, most of today’s vehicle manufacturers’ autonomous car concepts maintain the steering wheel as a control element. While this approach allows the driver to take over the vehicle route if needed, it causes a constraint in the previously mentioned interaction flexibility. Other approaches, such as the one proposed by Google, enable interaction flexibility by removing the steering wheel and accelerator and brake pedals. However, this prevents the users to take control over the vehicle route if needed, not allowing them to make on-route spontaneous decisions, such as stopping at a specific point of interest.

In recent years, Nearfield Acoustical Holography (NAH) has been used to identify stationary vehicle exterior noise sources. However that application has usually been limited to individual components. Since powertrain noise sources are hidden within the engine compartment, it is difficult to use NAH to identify those sources and the associated partial field that combine to create the complete exterior noise field of a motor vehicle. Integrated Nearfield Acoustical Holography (INAH) has been developed to address these concerns: it is described here. The procedure entails sensing the sources inside the engine compartment by using an array of reference microphones, and then calculating the associated partial radiation fields by using NAH. In the second part of this paper, the use of farfield arrays is considered. Several array techniques have previously been applied to identify noise sources on moving vehicles.

New techniques have been developed to visualize soot deposition in both traditional and new diesel particulate filter (DPF) substrate materials using a modified cyanoacrylate fuming technique. Loading experiments have been conducted on a variety of single channel DPF substrates to develop a deeper understanding of soot penetration, soot deposition characteristics, and to confirm modeling results. Early results indicate that stabilizing the soot layer using a vaporized adhesive (Cynoacrylate) may allow analysis of the layer with new methods.

Artificial intelligence (AI) enhanced control system deployments are emerging as a viable substitute to more traditional control system. In particular, deep learning techniques offer an alternate approach to tune the ever increasing sets of control system parameters to extract performance. However, the systematic verification and validation (to establish the reliability and robustness) of deep learning based controllers in actual deployments remains a challenge. This is exacerbated by the need to evaluate and optimize control systems embedded within an operational environment (with its own sets of additional unknown or uncertain parameters). Existing literature comparisons of deep learning against traditional controllers, where they may exist, do not offer structured approaches to comparative performance evaluation and improvement. It is also crucial to develop a standardized controlled test environment within which various controllers are evaluated against a common metric.

Improving passenger safety inside vehicle cabins requires continuously monitoring vehicle seat occupancy statuses. Monitoring a vehicle seat’s occupancy status includes detecting if the seat is occupied and classifying the seat’s occupancy type. This paper introduces an innovative non-intrusive technique that employs capacitive sensing and an occupancy classifier to monitor a vehicle seat’s occupancy status. Capacitive sensing is facilitated by a meticulously constructed capacitance-sensing mat that easily integrates with any vehicle seat. When a passenger or an inanimate object occupies a vehicle seat equipped with the mat, they will induce variations in the mat’s internal capacitances. The variations are, in turn, represented pictorially as grayscale capacitance-sensing images (CSI), which yield the feature vectors the classifier requires to classify the seat’s occupancy type.

Vehicle safety remains a significant concern for consumers, government agencies, and automotive manufacturers. One critical type of vehicle accident results from the right or left side tires leaving the road surface and then returning abruptly due to large steering wheel inputs (road runoff and return). A subset of runoff road crashes that involve a steep hard shoulder has been labeled shoulder induced accidents. In this paper, a limited authority real time steering controller has been developed to mitigate shoulder induced accidents. A Kalman Filter based tire cornering stiffness estimation technique has been coupled with a feedback controller and driver intention module to create a safer driving solution without excessive intervention. In numerical studies, lateral vehicle motion improvements of 30% were realized for steering intervention. Specifically, the vehicle crossed the centerline after 1.0 second in the baseline case versus 1.3 seconds with steering assistance at 60 kph.

The destruction of low concentrations (<600 ppm) of nitric oxide using a low-temperature, dielectric barrier/packed-bed corona reactor has been studied. We compare the chemistry and energy efficiencies observed using various packing materials in warm moist air under oxidative (lean-burn) conditions. Measurements of NO and NOx removal in the effluent gas were made as a function of energy dissipated in the reactor. Changes in the observed fate of NO as a function of the packing material are discussed.

Computational Fluid Dynamics (CFD) modeling was used to investigate the effects of the direct injection of wet ethanol at various injection timings during the intake stroke in a diesel engine with a shallow bowl piston. Thermally Stratified Compression Ignition (TSCI) has been proposed to expand the operating range of Low Temperature Combustion (LTC) by broadening the temperature distribution in the cylinder prior to ignition. TSCI is accomplished by injecting either water or a water-fuel mixture with a high latent heat of vaporization like wet ethanol. This current study focuses on isolating the effects that injecting such a high heat of vaporization mixture during the intake stroke has on the distribution of temperature and equivalence ratio in the cylinder before the onset of combustion. A CONVERGE 3-D CFD model of a single cylinder diesel research engine using Reynolds Averaged Naiver Stokes (RANS) turbulence modeling was developed and validated against experimental data.

Image segmentation has historically been a technique for analyzing terrain for military autonomous vehicles. One of the weaknesses of image segmentation from camera data is that it lacks depth information, and it can be affected by environment lighting. Light detection and ranging (LiDAR) is an emerging technology in image segmentation that is able to estimate distances to the objects it detects. One advantage of LiDAR is the ability to gather accurate distances regardless of day, night, shadows, or glare. This study examines LiDAR and camera image segmentation fusion to improve an advanced driver-assistance systems (ADAS) algorithm for off-road autonomous military vehicles. The volume of points generated by LiDAR provides the vehicle with distance and spatial data surrounding the vehicle.

A full calibration exercise of a diesel engine air path can take months to complete (depending on the number of variables). Model-based calibration approach can speed up the calibration process significantly. This paper discusses the overall calibration process of the air-path of the Cat® C7.1 engine using statistical machine learning tool. The standard Cat® C7.1 engine's twin-stage turbocharger was replaced by a VTG (Variable Turbine Geometry) as part of an evaluation of a novel air system. The changes made to the air-path system required a recalculation of the air path's boost set point and desired EGR set point maps. Statistical learning processes provided a firm basis to model and optimize the air path set point maps and allowed a healthy balance to be struck between the resources required for the exercise and the resulting data quality.

Most airline maintenance human factors training programs miss the mark when it comes to producing optimal behavioral and procedural changes among participating maintenance professionals. While there are many causes for training outcomes which are less than desired and anticipated, principal among these are the failure of most programs to address the pragmatic learning needs of those technicians as adult learners. Attention to andragogical principles such as clear learning goals, readily apparent relevance and direct applicability of material, immediate feedback, learner directed inquiry and self assessment can contribute greatly to achieving optimal results. A program currently under development at Purdue University utilizes a combination of classroom instruction, group discussion, and learner participation in aviation maintenance scenarios as a method for improving human factors education.

The authors relate their experience in teaching a senior level Computer-Aided Design (CAD) course in Mechanical Engineering using advanced Computer-Aided Engineering software. The course balances the theory and the need for hands-on experience with commercial CAD software in solving practical design problems. Students are given assignments ranging from simple 3D modeling exercises and 2D finite element analyses to an optimization project requiring more advanced 3D modeling and analysis. Where possible, analytical solutions are found and compared to the finite element results. The software allows the students to explore much more complex problems than would have otherwise been possible.

Previous research has shown that the homogeneous charge compression ignition (HCCI) combustion concept holds promise for reducing pollutants (i.e. NOx, soot) while maintaining high thermal efficiency. However, it can be difficult to control the operation of the HCCI engines even under steady state running conditions. Power density may also be limited if high inlet air temperatures are used for achieving ignition. A methodology using a small pilot quantity of diesel fuel injected during the compression stroke to improve the power density and operation control is considered in this paper. Multidimensional computations were carried out for an HCCI engine based on a CAT3401 engine. The computations show that the required initial temperature for ignition is reduced by about 70 K for the cases of the diesel pilot charge and a 25∼35% percent increase in power density was found for those cases without adversely impacting the NOx emissions.

The application of virtual engineering methods can streamline the product design process through improved collaboration opportunities among the technical staff and facilitate additive manufacturing processes. A product digital twin can be created using the available computer-aided design and analytical mathematical models to numerically explore the current and future system performance based on operating cycles. The strategic decision to implement a digital twin is of interest to companies, whether the required financial and workforce resources will be worthwhile. In this paper, two metrics are introduced to assist management teams in evaluating the technology potential. The usefulness and time savings metrics will be presented with accompanying definitions. A case study highlights the usefulness metric for the “Deep Orange” prototype vehicle, an innovative off-road hybrid vehicle designed and fabricated at Clemson University.