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A Lagrangian random vortex-boundary element method has been developed for the simulation of unsteady incompressible flow inside three-dimensional domains with time-dependent boundaries, similar to IC engines. The solution method is entirely grid-free in the fluid domain and eliminates the difficult task of volumetric meshing of the complex engine geometry. Furthermore, due to the Lagrangian evaluation of the convective processes, numerical viscosity is virtually removed; thus permitting the direct simulation of flow at high Reynolds numbers. In this paper, a brief description of the numerical methodology is given, followed by an example of induction flow in an off-centered port-cylinder assembly with a harmonically driven piston and a valve seat situated directly below the port. The predicted flow is shown to resemble the flow visualization results of a laboratory experiment, despite the crude approximation used to represent the geometry.

A novel system for the forming of three dimensional sheet metal parts is described that can form a variety of part shapes without the need for fixed tooling, and given only geometry (CAD) information about the desired part. The central elements of this system are a tooling concept based on a programmable discrete die surface and closed-loop shape control. The former give the process the degrees of freedom to change shape rapidly, and the latter is used to insure that the correct shape is formed with a minimum of forming trials. A 540 kN (60 ton) lab press has been constructed with a 0.3 m (12 in) square pair of discrete tools that can be rapidly re-shaped between forming trials. The shape control system uses measured part shapes to determine a shape error and to correct the tooling shape. This correction is based on a unique “Deformation Transfer Function” approach using a spatial frequency decomposition of the surface.

This paper quantifies the potential of electric propulsion systems to reduce petroleum use and greenhouse gas (GHG) emissions in the 2030 U.S. light-duty vehicle fleet. The propulsion systems under consideration include gasoline hybrid-electric vehicles (HEVs), plug-in hybrid vehicles (PHEVs), fuel-cell hybrid vehicles (FCVs), and battery-electric vehicles (BEVs). The performance and cost of key enabling technologies were extrapolated over a 25-30 year time horizon. These results were integrated with software simulations to model vehicle performance and tank-to-wheel energy consumption. Well-to-wheel energy and GHG emissions of future vehicle technologies were estimated by integrating the vehicle technology evaluation with assessments of different fuel pathways. The results show that, if vehicle size and performance remain constant at present-day levels, these electric propulsion systems can reduce or eliminate the transport sector's reliance on petroleum.

The challenge of developing a robust, real-time driver gaze classification system is that it has to handle difficult edge cases that arise in real-world driving conditions: extreme lighting variations, eyeglass reflections, sunglasses and other occlusions. We propose a single-camera end-toend framework for classifying driver gaze into a discrete set of regions. This framework includes data collection, semi-automated annotation, offline classifier training, and an online real-time image processing pipeline that classifies the gaze region of the driver. We evaluate an implementation of each component on various subsets of a large onroad dataset. The key insight of our work is that robust driver gaze classification in real-world conditions is best approached by leveraging the power of supervised learning to generalize over the edge cases present in large annotated on-road datasets.

Advances in avionics and display technology are significantly changing the cockpit environment in current transport aircraft. The MIT Aeronautical Systems Lab (ASL) has developed a part-task flight simulator specifically to study the effects of these new technologies on flight crew situational awareness and performance. The simulator is based on a commercially-available graphics workstation, and can be rapidly reconfigured to meet the varying demands of experimental studies. The simulator has been successfully used to evaluate graphical microburst alerting displays, electronic instrument approach plates, terrain awareness and alerting displays, and ATC routing amendment delivery through digital datalinks.

The adoption of turbine engines for automotive power plants has been hampered by the high cost, high leakage and high wear rate of present designs of ceramic-matrix regenerators. Proposals are made and analyzed here for design directions to achieve substantial improvements in all three areas. These include lower-cost extruded and pressed matrices; and clamping seals coupled with incremental movement of the rotary-regenerator matrix.

The ability to make accurate decisions concerning early body-in-white architectures is critical to an automaker since these decisions often have long term cost and weight impacts. We address this need with a methodology which can be used to assist in body architecture decisions using process-based technical cost modeling (TCM) as a filter to evaluate alternate designs. Despite the data limitations of early design concepts, TCM can be used to identify key trends for cost-effectiveness between design variants. A compact body-in-white architecture will be used as a case study to illustrate this technique. The baseline steel structure will be compared to several alternate aluminum intensive structures in the context of production volume.

This paper describes the use of a modified quasi-dimensional spark-ignition engine simulation code to predict the extent of cycle-to-cycle variations in combustion. The modifications primarily relate to the combustion model and include the following: 1. A flame kernel model was developed and implemented to avoid choosing the initial flame size and temperature arbitrarily. 2. Instead of the usual assumption of the flame being spherical, ellipsoidal flame shapes are permitted in the model when the gas velocity in the vicinity of the spark plug during kernel development is high. Changes in flame shape influence the flame front area and the interaction of the enflamed volume with the combustion chamber walls. 3. The flame center shifts due to convection by the gas flow in the cylinder. This influences the flame front area through the interaction between the enflamed volume and the combustion chamber walls. 4. Turbulence intensity is not uniform in cylinder, and varies cycle-to-cycle.

Accurately predicting real-world vehicle energy consumption is essential for optimizing vehicle designs, enhancing energy efficiency, and developing effective energy management strategies. This paper presents a data-driven approach that utilizes machine learning techniques and a comprehensive dataset of vehicle parameters and environmental factors to create precise energy consumption prediction models. The methodology involves recording real-world vehicle data using data loggers to extract information from the CAN bus systems for ICE and hybrid electric, as well as hydrogen and battery fuel cell vehicles. Data cleaning and cycle-based analysis are employed to process the dataset for accurate energy consumption prediction. This includes cycle detection and analysis using methods from statistics and signal processing, and then pattern recognition based on these metrics.

Currently, states that are out of compliance with the National Ambient Air Quality Standards must, according to the Clean Air Act Amendments of 1990 (CAAA), develop and implement control strategies that demonstrate specific degrees of reduction in emissions-with the degree of reduction depending upon the severity of the problem. One tool that has been developed to aid regulators in both deciding an appropriate course of action and to demonstrate the desired reductions in mobile emissions is EPA's Mobile 5a emission estimation model. In our study, Mobile 5a has been used to examine the effects of regulatory strategies, as applied to the Northeast United States, on vehicle emissions under worst-case ozone-forming conditions.

MIT Lincoln Laboratory is tasked by the U.S. Federal Aviation Administration to investigate the use of the NEXRAD polarimetric radars* for the remote sensing of icing conditions hazardous to aircraft. A critical aspect of the investigation concerns validation that has relied upon commercial airline icing pilot reports and a dedicated campaign of in situ flights in winter storms. During the month of February in 2012 and 2013, the Convair-580 aircraft operated by the National Research Council of Canada was used for in situ validation of snowstorm characteristics under simultaneous observation by NEXRAD radars in Cleveland, Ohio and Buffalo, New York. The most anisotropic and easily distinguished winter targets to dual pol radar are ice crystals.

Low volume manufacturing has become increasingly important for the automotive industry. Globalization trends have led automakers and their suppliers to operate in developing regions where minimum efficient scales can not always be achieved. With proper maintenance, standard cast iron stamping tools can be used to produce millions of parts, but require large investments. Thus at high production volumes, the impact of the tooling investment on individual piece costs is minimized. However, at low volumes there is a substantial cost penalty. In light of the trends towards localized manufacturing and relatively low demands in some developing markets, low cost stamping tools are needed. Several alternate tooling technologies exist, each of which require significantly lower initial investments, but suffer from greatly reduced tool lives. However, the use of these technologies at intermediate to high volumes requires multiple tool sets thus eliminating their cost advantage.

Rare earths are a group of elements whose availability has been of concern due to monopolistic supply conditions and environmentally unsustainable mining practices. To evaluate the risks of rare earths availability to automakers, a first step is to determine raw material content and value in vehicles. This task is challenging because rare earth elements are used in small quantities, in a large number of components, and by suppliers far upstream in the supply chain. For this work, data on rare earth content reported by vehicle parts suppliers was assessed to estimate the rare earth usage of a typical conventional gasoline engine midsize sedan and a full hybrid sedan. Parts were selected from a large set of reported parts to build a hypothetical typical mid-size sedan. Estimates of rare earth content for vehicles with alternative powertrain and battery technologies were made based on the available parts' data.

The piston skirt is an important contributor of friction in the piston assembly. This paper discusses friction contributions from various aspects of the piston skirt. A brief study of piston skirt patterns is presented, with little gains being made by patterning the piston skirt coating. Next the roughness of the piston skirt coating is analyzed, and results show that reducing piston skirt roughness can have positive effects on friction reduction. Finally, an introductory study into the profile of the piston skirt is presented, with the outcome being that friction reduction is possible by optimizing the skirt profile.

The introduction of new safety critical features using software-intensive systems presents a growing challenge to hazard analysis and requirements development. These systems are rich in feature content and can interact with other vehicle systems in complex ways, making the early development of proper requirements critical. Catching potential problems as early as possible is essential because the cost increases exponentially the longer problems remain undetected. However, in practice these problems are often subtle and can remain undetected until integration, testing, production, or even later, when the cost of fixing them is the highest. In this paper, a new technique is demonstrated to perform a hazard analysis in parallel with system and requirements development. The proposed model-based technique begins during early development when design uncertainty is highest and is refined iteratively as development progresses to drive the requirements and necessary design features.

This paper describes a post-race analysis of team KOMMIT EVT’s electric motorcycle data collected during the 2016 Pikes Peak International Hill Climb (PPIHC). The motorcycle consumed approximately 4 kWh of battery energy with an average and maximum speed of 107 km/h and 149 km/h, respectively. It was the second fastest electric motorcycle with a finishing time of 11:10.480. Data was logged of the motorcycle’s speed, acceleration, motor speed, power, currents, voltages, temperatures, throttle position, GPS position, rider’s heart rate and the ambient environment (air temperature, pressure and humidity). The data was used to understand the following factors that may have prevented a faster time: physical fitness of the rider, thermal limits of the motor and controller, available battery energy and the sprocket ratio between the motor and rear wheel.

A design framework based on the principles of lean manufacturing and axiomatic design was used as a guideline for designing an automotive component manufacturing system. A brief overview of this design decomposition is given to review its structure and usefulness. Examples are examined to demonstrate how this design framework was applied to the design of a gear manufacturing system. These examples demonstrate the impact that low-level design decisions can have on high-level system objectives and the need for a systems-thinking approach in manufacturing system design. Results are presented to show the estimated performance improvements resulting from the new system design.

The windage tray effect on aeration in the engine sump was assessed by replacing much of the windage tray materials with wire meshes of various blockages. The mesh was to prevent direct impact of the oil drops spinning off the crank shaft onto the sump oil, and simultaneously, to provide sufficient drainage so that there was no significant build up of windage tray oil film that would interact with these droplets. Aeration at the oil pump inlet was measured by X-ray absorption in a production V-6 SI engine motoring at 2000 to 6000 rpm. Within experimental uncertainty, these windage tray changes had no effect on aeration. Thus activities in the sump such as the interaction of the oil drops spun from the crank shaft with the sump oil or with the windage tray, and the agitation of the sump oil by the crank case gas, were not major contributors to aeration at the pump inlet.

Two critical milestones that must be achieved during concept design are 1) definition of a product architecture that meets performance, producibility, and strategic objectives, and 2) estimation of the integration risk in each candidate concept. This paper addresses these issues by describing the role played by the producibility members of an Integrated Product Team (IPT) during concept design. Our focus is on the execution of the what we call the “chain method”, which illustrates the structure of function delivery in a concept in a simple pictorial way and helps the IPT to understand the advantages or disadvantages of using a modular or an integral product architecture. The producibility members play a central role in capturing and evaluating the chains for different candidate concepts and decompositions.

Gas-pressurized space suits are highly resistive to astronaut movement, and this resistance has been previously explained by volume and/or structural effects. This study proposed that an additional effect, pressure effects due to compressing/expanding the internal gas during joint articulation, also inhibits mobility. EMU elbow torque components were quantified through hypobaric testing. Structural effects dominated at low joint angles, and volume effects were found to be the primary torque component at higher angles. Pressure effects were found to be significant only at high joint angles (increased flexion), contributing up to 8.8% of the total torque. These effects are predicted to increase for larger, multi-axis joints. An active regulator system was developed to mitigate pressure effects, and was found to be capable of mitigating repeated pressure spikes caused by volume changes.