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Photographic and performance studies with a Rapid Compression Machine at the Massachusetts Institute of Technology have been used to develop insight into the role of mixing in diesel engine combustion. Combustion photographs and performance data were analyzed. The experiments simulate a single fuel spray in an open chamber diesel engine with direct injection. The effects of droplet formation and evaporation on mixing are examined. It is concluded that mixing is controlled by the rate of entrainment of air by the fuel spray rather than the dynamics of single droplets. Experimental data on the geometry of a jet in a quiescent combustion chamber were compared with a two-phase jet model; a jet model based on empirical turbulent entrainment coefficients was developed to predict the motion of a fuel jet in a combustion chamber with swirl. Good agreement between theory and experiment was obtained.

A human-centered systems analysis was applied to the adverse aircraft weather encounter problem in order to identify desirable functions of weather and icing information. The importance of contingency planning was identified as emerging from a system safety design methodology as well as from results of other aviation decision-making studies. The relationship between contingency planning support and information on regions clear of adverse weather was investigated in a scenario-based analysis. A rapid prototype example of the key elements in the depiction of icing conditions was developed in a case study, and the implications for the components of the icing information system were articulated.

Future planetary extravehicular activities (EVAs) will go beyond what was experienced during Apollo. As mission duration becomes longer, inevitably, the astronauts on the surface of the Moon and Mars will actively plan and re-plan their own sorties. To design robust decision support aids for these activities, we have to first characterize all the different types of excursions that are possible. This paper describes a framework that organizes parameters and constraints that define a single planetary EVA. We arrived at this framework through case studies: by reviewing the EVA lessons learned during Apollo, conducting an observational study of excursions in a Mars-analog environment, and applying part of the framework to a prototype path planner for human planetary exploration.

Future human space exploration includes returning to the Moon and continuing to Mars. Essential to these missions is each planetary extravehicular activity, or EVA, where astronauts and robotic agents will explore lunar and planetary surfaces. Real-time decision support systems will help these explorers in efficiently planning and re-planning under time pressure sorties. Information and functional requirements for such a system are recommended and are based on on-going human-computer collaboration research.

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.

With the recent advancement in sensing and controller technologies architecture design of an autonomous driving system becomes an important issue. Researchers have been developing different sensors and data processing technologies to solve the issues associated with fast processing, diverse weather, reliability, long distance recognition performance, etc. Necessary considerations of diverse traffic situations and safety factors of autonomous driving have also increased the complexity of embedded software as well as architecture of autonomous driving. In these circumstances, there are almost countless numbers of possible architecture designs. However, these design considerations have significant impacts on cost, controllability, and system reliability. Thus, it is crucial for the designers to make a challenging and critical design decision under several uncertainties during the conceptual design phase.

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.

After treatment (AT) system has evolved over the period of time with ever changing stringent emission norms. Systems are still developing to meet new evolving challenges of diesel engine to meet fuel economy & necessary power to drive the end application. Times have changed when the purpose of AT system was to take care of not only treating engine exhaust but also responsible for attenuation of engine propagated noise. The systems today have become sophisticated and smart enough to work wide range of test conditions & duty cycle to meet the emission norms. Current trend is to meet the performance targets by making these designs compact & less restrictive in terms of backpressure. This creates tradeoff within acoustics attenuation, performance parameters & backpressure offered by these devices. One of the major constraint in development of AT, is available customer packaging space & time to develop these designs in shortest period.

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.

More stringent emission requirements for nonroad diesel engines both in the U.S. and Europe have spurred the development of engines and exhaust aftertreatment technologies. In this study, one such system consisting of a diesel oxidation catalyst, zeolite-based selective catalytic reduction catalyst, and an ammonia oxidation catalyst was evaluated using both nonroad transient and steady-state cycles in order to understand the emission characteristics of this configuration. Criteria pollutants were analyzed and particular attention was given to organic compound and NO2 emissions since both of these could be significantly affected by the absence of a diesel particulate filter that typically helps reduce semi-volatile and particle-phase organics and consumes NO2 via passive soot oxidation. Results are then presented on a detailed speciation of organic emissions including alkanes, cycloalkanes, aromatics, polycyclic aromatic hydrocarbons and their derivatives, and hopanes and steranes.

Lubricant viscosity along the engine cylinder liner varies by an order of magnitude due to local temperature variation and vaporization effects. Tremendous potential exists for fuel economy improvement by optimizing local viscosity variations for specific operating conditions. Methods for analytical estimation of friction and wear in the power-cylinder system are reviewed and used to quantify opportunities for improving mechanical efficiency and fuel economy through lubricant formulation tailored specifically to liner temperature distributions. Temperature dependent variations in kinematic viscosity, density, shear thinning, and lubricant composition are investigated. Models incorporating the modified Reynolds equation were used to estimate friction and wear under the top ring and piston skirt of a typical 11.0 liter diesel engine.

Diesel engines have been identified as contributing to more than half of the transport sectors black carbon (BC) emissions in the US. This large contribution to atmospheric BC concentrations has raised concern about source specific emission rates, including off-highway engines. The European Union has recently implemented more stringent particulate regulations in the form of particle number via the Particle Measurement Programme (PMP) methodology. The PMP method counts the non-volatile fraction of particulate matter (PM) above 23 nm and below 2.5 μm via a condensation particle counter. This study evaluates a surrogate black carbon method which uses the PMP particle count method with a correlation factor to the BC fraction. The transient capable Magee Scientific Aethalometer (AE-33) 880 nm wavelength channel was used to determine the BC fraction.

Tailpipe particle number (PN) emission limits for heavy-duty diesel engines have been introduced as part of the off-highway Stage V standards. To meet the required limits a diesel particulate filter (DPF) with high filtration efficiency is required. The DPF relies on formation of a soot cake layer on the channel walls to achieve this high filtration efficiency. Off highway Stage V certification cycles are significantly higher in temperature than their on-highway counterparts, leading to difficulty in creating and maintaining a soot cake in the DPF. Hence for these applications meeting particle number requirements is challenging. To meet the high filtration efficiency requirements the DPF will have to reduce mean pore size, pore standard deviation, and increase wall thickness, in turn increasing backpressure, which results in a fuel consumption penalty. Another option is to evaluate the impact of temperature stable ash accumulation on DPF filtration efficiency.

Worldwide, regulations continue to drive reductions in brake-specific emissions of nitric oxide (NO) and nitrogen dioxide (NO2) from on-highway and nonroad diesel engines. NOx, formed as a byproduct of the combustion of fossil fuels (e.g., natural gas, gasoline, diesel, etc.), can be converted to dinitrogen (N2) through ammonia (NH3) selective catalytic reduction (SCR). In this study, we closely examine the low-temperature storage, isothermal desorption, reactive consumption, and thermal release of NH3 on commercial Cu-SSZ-13 and V2O5-WO3/TiO2 SCR catalysts. Catalyst core-reactor, N2 adsorption (BET) surface area, and in-situ diffuse reflectance Fourier transform infrared spectroscopy (DRIFTS) experiments are utilized to investigate the fundamental chemical processes relevant to low-temperature (T < 250°C) NH3 SCR.

To meet increasingly stringent diesel engine emission regulations, diesel engines are required to use ultra-low sulfur diesel (ULSD) and are equipped with advanced aftertreatment systems. Cu-SSZ-13 zeolite catalysts are widely used as selective catalytic reduction (SCR) catalysts due to their high NOx reduction and excellent hydrothermal stability. However, active Cu sites of Cu-SSZ-13 catalysts can be poisoned by exposure to engine exhaust sulfur species. This poison effect can be mitigated with the use of ULSD and high temperature exposure from engine operation. On the other hand, ULSD is still not universally available where regulations require it, and vehicles may inadvertently operate with high sulfur diesel fuel (HSD) in some locations. The high concentration of exhaust sulfur species resulting from HSD combustion may rapidly poison the Cu-SSZ-13 SCR catalyst. In this study, the catalytic performance of a sulfur poisoned Cu-SSZ-13 SCR catalyst is analyzed.

Cu-SSZ-13 catalysts are widely used for diesel aftertreatment applications for NOx (NO and NO2) abatement via selective catalytic reaction (SCR) due to their high conversion efficiency and excellent hydrothermal stability. Diesel engine exhaust contains small amounts of SOx due to the combustion of sulfur compounds in diesel fuel. The engine out SOx level mainly depends on the sulfur content in the diesel fuel. The presence of SOx from engine exhaust can deteriorate the SCR performance of Cu-SSZ-13 catalysts in real-world applications. This work is focused on the sulfur-induced deactivation process of a Cu-SSZ-13 catalyst under a range of simulated diesel engine operating conditions. Two catalyst deactivation modes, namely chemical poisoning and physical poisoning, are identified, primarily depending on the operating temperature. Chemical poisoning mainly results from the interaction between SOx and Cu species within the zeolite framework.

Internal combustion engines for plug-in hybrid heavy duty trucks, especially long haul trucks, could play an important role in facilitating use of battery power. Power from a low carbon electricity source could thereby be employed without an unattractive vehicle cost increase or range limitation. The ideal engine should be powered by a widely available affordable liquid fuel, should minimize air pollutant emissions, and should provide lower greenhouse gas emissions. Diesel engines could fall short in meeting these objectives, especially because of high emissions. In this paper we analyze the potential for a flex fuel gasoline-alcohol engine approach for a series hybrid powertrain. In this approach the engine would provide comparable (or possibly greater) efficiency than a diesel engine while also providing 90 around lower NOx emissions than present cleanest diesel engine vehicles. Ethanol or methanol would be employed to increase knock resistance.

Concept of a new decoupled cylinder liner design for internal combustion (IC) engines is presented from the framework of axiomatic design to improve friction and wear characteristics. In the current design, the piston rings fail to satisfy their functional requirements at the two dead centers of the piston stroke where lubrication is poor. It is proposed that by using undulated cylindrical surfaces selectively along the cylinder liner, much of the existing friction and wear problems of IC engines may be solved. The main idea behind undulated surface is to trap wear particles at the piston-cylinder interface in order to minimize plowing, and thus maintain low friction even in areas where lubrication fails to be hydrodynamic. In dry sliding tests using a modified engine motored at low speeds, undulated cylinders operated for significantly longer time than smooth cylinders without catastrophic increase in friction.

Ground impact caused by road debris can result in very severe fire accident of Electric Vehicles (EV). In order to study the ground impact accidents, a Finite Element model of the battery pack structure is carefully set up according to the practical designs of EVs. Based on this model, the sequence of the deformation process is studied, and the contribution of each component is clarified. Subsequently, four designs, including three enhanced shield plates and one enhanced housing box, are investigated. Results show that the BRAS (Blast Resistant Adaptive Sandwich) shield plate is the most effective structure to decrease the deformation of the battery cells. Compared with the baseline case, which adopts a 6.35-mm-thick aluminum sheet as the shield plate, the BRAS can reduce the shortening of cells by more than 50%. Another type of sandwich structure, the NavTruss, can also improve the safety of battery pack, but not as effectively as the BRAS.

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.