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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.

Piston rings are large contributors to friction losses in internal combustion engines. To achieve higher engine efficiency, low friction ring packs that can maintain good sealing performance must be designed. To support this effort, simulation tools have been developed to model the performance of piston rings during engine operation. However, the challenge of predicting oil consumption, blow by, and ring pack friction with sufficient accuracy remains. This is mostly due to the complexity of this system. Ring dynamics, deformation, interaction with liner and piston, gas and lubricant flow must all be studied together to make relevant predictions. In this paper, a new curved beam finite element model of piston rings is proposed. Ring structural deformation and contact with the liner are treated on two separate grids. A comparison with ring models in the literature and analytical solutions shows that it can provide accurate results efficiently.

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.

During an ExtraVehicular Activity (EVA), both the heat generated by the astronaut's metabolism and that produced by the Portable Life Support System (PLSS) must be rejected to space. The heat sources include the heat of adsorption of metabolic CO2, the heat of condensation of water, the heat removed from the body by the liquid cooling garment, the load from the electrical components and incident radiation. Although the sublimator hardware to reject this load weighs only 1.58 kg (3.48 lbm), an additional 3.6 kg (8 lbm) of water are loaded into the unit, most of which is sublimated and lost to space, thus becoming the single largest expendable during an eight-hour EVA. Using a radiator to reject heat from the astronaut during an EVA can reduce the amount of expendable water consumed in the sublimator. Radiators have no moving parts and are thus simple and highly reliable. However, past freezable radiators have been too heavy.

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.

After several decades of human spaceflight, the community of space-faring nations has accumulated a diverse and sometimes harrowing history of toxicological events that have plagued human space endeavors almost from the very beginning. Some lessons have been learned in ground-based test beds and others were discovered the hard way - when human lives were at stake in space. From such lessons one can build a risk-management framework for toxicological events to minimize the probability of a harmful exposure, while recognizing that we cannot predict all possible events. Space toxicologists have learned that relatively harmless compounds can be converted by air revitalization systems into compounds that cause serious harm to the crew.

In the design of a new space suit it is necessary to have requirements that define what mobility space suit joints should be capable of achieving in both a system and at the component level. NASA elected to divide mobility into its constituent parts -- range of motion (ROM) and torque -- in an effort to develop clean design requirements that limit subject performance bias and are easily verified. Unfortunately, the measurement of mobility can be difficult to obtain. Current technologies, such as the Vicon motion capture system, allow for the relatively easy benchmarking of range of motion (ROM) for a wide array of space suit systems. The ROM evaluations require subjects in the suit to accurately evaluate the ranges humans can achieve in the suit. However, when it comes to torque, there are significant challenges for both benchmarking current performance and writing requirements for future suits.

A model has been developed for estimating the oil vaporization rate from the cylinder liner of a reciprocating engine. The model uses input from an external cycle simulator and an external liner oil film thickness model. It allows for the change in oil composition and the change in oil film thickness due to vaporization. It also estimates how the passage of the compression and scraper rings combine with the vaporization to influence the steady-state composition of the oil layer in the upper ring pack. Computer model results are presented for a compression-ignition engine using a range of liner temperatures, several engine speeds, and two different oils. Vaporization is found to be highly dependent on liner temperature and steady-state oil composition. The steady-state oil composition near the top of the cylinder is found to be significantly different than the composition of the oil near the bottom of the cylinder.

An aerodynamic model of the entrainment of the head wall quench layer during blowdown and exhaust of an internal combustion engine has been developed. The model may be used to calculate the time resolved concentration and mass flowrate of hydrocarbons (HC) in the exhaust, from a knowledge of engine geometry and operating conditions. It predicts that the area As from which HC are swept will be proportional to the cube root of the ratio of the quench layer thickness δq to the thickness of the viscous boundary layer δv. Since the mass of HC emitted is proportional to the product of the HC density ρHC, the area As and the thickness δq, the HC emissions will be proportional to the product ρHC δq4/3 and this is the most important factor determining the emissions.

Homogenous Charge Compression Ignition (HCCI) engine operation has been demonstrated using both residual trapping and residual re-induction. A number of production valve train technologies can accomplish either of these HCCI modes of operation. Wide-scale testing of the many valve timing and duration options for an HCCI engine is both time and cost prohibitive, thus a modeling study was pursued to investigate optimal HCCI valve-train designs using the geometry of a conventional gasoline Port-Fuel-Injected (PFI) Spark-Ignition (SI) engine. A commercially available engine simulation program (WAVE), as well as chemical kinetic combustion modeling tools were used to predict the best approaches to achieving combustion across a wide variety of valve event durations and timings. The results of this study are consistent with experimental results reported in the literature: both residual trapping and residual re-induction are possible strategies for HCCI combustion.

Multi-target recognition technology plays an important role in the field of intelligent driving. In this paper, we propose a novel multi-target recognition algorithm with high accuracy and efficiency. We design a time series based recurrent neural network that integrates historical appearance information on the timeline, which can effectively improve the recognition accuracy. The target appearance characteristics extracted from the feature fusion network are then sent to the recursive neural network with the function of long-term and short-term memory for prediction, extending the learning and analysis of the neural network to the space-time domain. After the LSTM interprets advanced visual features, time series based regression is used as an appearance model to regress features to a particular visual element position through preliminary position inference. We evaluate our proposed algorithm on the KITTI data set and a large number of real scene experiments.

As the piston pin works under significant mechanical load, it is susceptible to wear, seizure, and structural failure, especially in heavy duty internal combustion engines. It has been found that the friction loss associated with the pin is comparable to that of the piston, and can be reduced when the interface geometry is properly modified. However, the mechanism that leads to such friction reduction, as well as the approaches towards further improvement, remain unknown. This work develops a piston pin lubrication model capable of simulating the interaction between the pin, the piston, and the connecting rod. The model integrates dynamics, solid contact, oil transport, and lubrication theory, and applies an efficient numerical scheme with second order accuracy to solve the highly stiff equations. As a first approach, the current model assumes every component to be rigid.

This paper presents a numerical model of the rotational and lateral dynamics of the piston (secondary motion) and piston slap in mixed lubrication. Piston dynamic behavior, frictional and impact forces are predicted as functions of crank angle. The model considers piston skirt surface waviness, roughness, skirt profile, thermal and mechanical deformations. The model considers partially-flooded skirt and calculates the pressure distributions and friction in the piston skirt region for both hydrodynamic and boundary lubrication. Model predictions are compared with measurements of piston position using gap sensors in a single-cylinder engine and the comparison between theory and measurement shows remarkable agreement.

A twin-land oil control ring (TLOCR) model is used to evaluate TLOCR friction and the results are compared to the experiment measurement in a single cylinder floating liner engine under motoring condition. The model is based on a correlation between the hydrodynamic pressure and film thickness, which is generated using a deterministic model. The well-known three-regime lubrication is predicted with the model for ring with different ring tensions under various engine running conditions. A good match is found for the model and experiment results.

The increasingly stringent regulations for fuel economy and emissions require better optimization and control of oil consumption. One of the primary mechanisms of oil consumption is vaporization from the liner; we consider this as the “minimum oil consumption (MOC).” This paper presents a physical-mathematical cycle model for predicting the MOC. The numerical simulations suggest that the MOC is markedly sensitive to oil volatility, liner temperature, engine load and speed but less sensitive to oil film thickness. A one-line correlation is proposed for quick MOC estimations. It is shown to have <15% error compared to the cycle MOC computation. In the “dry region” (between top ring and OCR at the TDC), oil is depleted due to high heat and continual exposure to the combustion chamber.

A complete one-dimensional mixed lubrication model has been developed to predict oil film thickness and friction of the piston ring-pack. An average flow model and a roughness contact model are used to consider the effects of surface roughness on both hydrodynamic and boundary lubrication. Effects of shear-thinning and liner temperature on lubricant viscosity are included. An inlet condition is applied by considering the unsteady wetting location at the leading edge of the ring. A ‘film non-separation’ exit condition is proposed to replace Reynolds exit condition when the oil squeezing becomes dominant. Three lubrication modes are considered in the model, namely, pure hydrodynamic, mixed, and pure boundary lubrication. All of these considerations are crucial for studying the oil transport, asperity contact, and friction especially in the top dead center (TDC) region where the oil control ring cannot reach.

Over the last couple decades, there has been a growing interest in incorporating commercial off-the-shelf (COTS) technologies and open standards in the design of human-rated spacecraft. This approach is intended to reduce development and upgrade costs, lower the need for new design work, eliminate reliance on individual suppliers, and minimize schedule risk. However, it has not traditionally been possible for COTS solutions to meet the high reliability and fault tolerance requirements of systems implementing critical spacecraft functions. Byzantine faults are considered particularly dangerous to such systems because of their ability to escape traditional means of fault containment and disrupt consensus between system components. In this paper, we discuss the design of a voting protocol using Time-Triggered Ethernet capable of achieving data integrity in the presence of a single Byzantine fault.

A fuel volatility model based on the major species present in the fuel has been formulated. The model accurately predicts the ASTM distillation curves and Reid Vapor Pressure for hydrocarbon fuels. The model may be used to assess the fuel effects on the extent of evaporation and the vapor composition in the mixture preparation process.