Search Results

Abstract The ASTM D130 was first issued in 1922 as a tentative standard for the detection of corrosive sulfur in gasoline. A clean copper strip was immersed in a sample of gasoline for three hours at 50°C with any corrosion or discoloration taken to indicate the presence of corrosive sulfur. Since that time, the method has undergone many revisions and has been applied to many petroleum products. Today, the ASTM D130 standard is the leading method used to determine the corrosiveness of various fuels, lubricants, and other hydrocarbon-based solutions to copper. The end-of-test strips are ranked using the ASTM Copper Strip Corrosion Standard Adjunct, a colored reproduction of copper strips characteristic of various degrees of sulfur-induced tarnish and corrosion, first introduced in 1954. This pragmatic approach to assessing potential corrosion concerns with copper hardware has served various industries well for a century.

Abstract Additive manufacturing (AM) technologies can produce lighter parts; reduce manual assembly processes; reduce the number of production steps; shorten the production cycle; significantly reduce material consumption; enable the production of prostheses, implants, and artificial organs; and produce end-user products since it is used in many sectors for many reasons; it has also started to be used widely, especially in the field of aerospace. In this study, polylactic acid (PLA) was preferred for the antenna substrate because it is environmentally friendly, easy to recycle, provides convenience in production design with a three-dimensional (3D) printer, and is less expensive compared to other available materials. Copper (Cu) tape and graphene filament were employed for the antenna patch component due to their benefits.

Abstract Regulations limiting GreenHouse Gases (GHG) from Heavy-Duty (HD) commercial vehicles in the United States (US) and European Union will phase in between the 2024 and 2030 model years. These mandates require efficiency improvements at both the engine and vehicle levels, with the most stringent reductions required in the heaviest vehicles used for long-haul applications. At the same time, a 90% reduction in oxides of nitrogen (NOx) will be required as part of new regulations from the California Air Resources Board. Any technologies applied to improve engine efficiency must therefore not come at the expense of increased NOx emissions. Research into advanced engine architectures and components has identified improved turbomachine efficiency as one of the largest potential contributors to engine efficiency improvement. However this comes at the cost of a reduced capability to drive high-pressure Exhaust Gas Recirculation (EGR).

Abstract Deep learning (DL)-based approaches enable unprecedented control paradigms for propulsion systems, utilizing recent advances in high-performance computing infrastructure connected to modern vehicles. These approaches can be employed to optimize diesel aftertreatment control systems targeting the reduction of emissions. The optimization of the Trapped Soot Load (TSL) reduction in the Diesel Particulate Filter (DPF) is such an example. As part of the diesel aftertreatment system, the DPF stores the soot particles resulting from the combustion process in the engine. Periodically, the stored soot is oxidized during a DPF regeneration event. The efficiency of such a regeneration influences the fuel economy, and potentially the service interval of the vehicle. The quality of a regeneration depends on the operating conditions of the DPF, the engine, and the ability to complete the regeneration event.

Abstract The cold crank-start stage, including the first three engine cycles, is responsible for a significant amount of the cold-start phase emissions in a Gasoline Direct Injection (GDI) engine. The engine crank-start is highly transient due to substantial engine speed changes, Manifold Absolute Pressure (MAP) dynamics, and in-cylinder temperatures. Combustion characteristics change depending on control inputs variations, including throttle angle and spark timing. Fuel injection strategy, timing, and vaporization dynamics are other parameters causing cold-start first cycles analysis to be more complex. Hybrid Electric Vehicles (HEVs) provide elevated cranking speed, enabling technologies such as cam phasing to adjust the valve timing and throttling, and increased fuel injection pressure from the first firings.

Abstract With the introduction of advanced lightweight materials with complex microstructures and behaviors, more focus is put on the accurate determination of their forming limits, and that can only be possible through experiments as the conventional theoretical models for the forming limit curve (FLC) prediction fail to perform. Despite that, CAE engineers, designers, and toolmakers still rely heavily on theoretical models due to the steep costs associated with formability testing, including mechanical setup, a large number of tests, and the cost of a stereo digital image correlation (DIC) system. The international standard ISO 12004-2:2021 recommends using a stereo DIC system for formability testing since two-dimensional (2D) DIC systems are considered incapable of producing reliable strains due to errors associated with out-of-plane motion and deformation.

Abstract The hydrocarbons constituting the heavy tail of gasoline are key contributors to particulate matter (PM) emissions from spark-ignition (SI) engines. They are predominantly aromatic and, to a significant degree, bicyclic aromatic. For example, above a boiling point of 400°F, the content of bicyclic compounds in the United States (US) summer E10 regular-grade gasoline exceeds 50%v. Various gasoline parameters, such as the PM Index, Particulate Evaluation Index (PEI), Particulate and Soot Correlation Equation (PASCE), or Threshold Sooting Index (TSI), have been proposed as predictors of PM emissions from SI engines. In particular, the PM Index, whose value is dominated by the content of heavy aromatics and which, so far, has yielded the most predictive PM emissions models, appears to be the best metric to achieve this objective.

Abstract Quantifying exhaust gas composition and temperature in vehicles with internal combustion engines (ICEs) is crucial to understanding and reducing emissions during transient engine operation. This is particularly important before the catalytic converter system lights off (i.e., during cold start). Most commercially available gas analyzers and temperature sensors are far too slow to measure these quantities on the timescale of individual cylinder-firing events, thus faster sensors are needed. A two-color mid-infrared (MIR) laser absorption spectroscopy (LAS) sensor for gas temperature and carbon monoxide (CO) mole fraction was developed and applied to address this technology gap. Two quantum cascade lasers (QCLs) were fiber coupled into one single-mode fiber to facilitate optical access in the test vehicle exhaust. The QCLs were time-multiplexed in order to scan across two CO absorption transitions near 2013 and 2060 cm–1 at 15 kHz.

Abstract Automotive interior coatings for flexible and rigid substrates represent an important segment within automotive coating space. These coatings are used to protect plastic substrates from mechanical and chemical damage, in addition to providing colour and design aesthetics. These coatings are expected to resist aggressive chemicals, fluids, and stains while maintaining their long-term physical appearance and mechanical integrity. Designing such coatings, therefore, poses significant challenges to the formulators in effectively balancing these properties. Among many factors affecting coating properties, the cross-link density (XLD) and solubility parameter (δ) of coatings are the most predominant factors.

Abstract The 2010 Environmental Protection Agency (EPA) Emission Standard for heavy-duty engines required 0.2 g/bhp-hr over certification cycles (cold and hot Federal Test Procedure [FTP]), and the California Air Resources Board (CARB) standards require 0.02 g/bhp-hr for the same cycles leading to a 90% reduction of overall oxides of nitrogen (NOx) emissions. Similar reductions may be considered by the EPA through its Cleaner Trucks Initiative program. In this article, aftertreatment system components consisting of a diesel oxidation catalyst (DOC); a selective catalytic reduction (SCR) catalyst on a diesel particulate filter (DPF), or SCR-F; a second DOC (DOC2); and a SCR along with two urea injectors have been analyzed, which could be part of an aftertreatment system that can achieve the 0.02 g/bhp-hr standard.

Abstract Three-dimensional patterns representing crosshatched plateau-honed cylinder bores based on two-dimensional Fast Fourier Transform (FFT) of measured surfaces were generated and used to calculate pressure flow, shear-driven flow, and shear stress factors. Later, the flow and shear stress factors obtained by numerical simulations for various surface patterns were used to calculate lubricant film thickness and friction force between piston ring and cylinder bore contact in typical diesel engine conditions using a mixed lubrication model. The effects of various crosshatch honing angles, such as 30°, 45°, and 60°, and texture heights on engine friction losses, wear, and oil consumption were discussed in detail. It is observed from numerical results that lower lubricant film thickness values are generated with higher honing angles, particularly in mixed lubrication regime where lubricant film thickness is close to the roughness level, mainly due to lower resistance to pressure flow.

Abstract Heavy-duty (HD) diesel engines are the primary propulsion systems in use within the transportation sector and are subjected to stringent oxides of nitrogen (NOx) and particulate matter (PM) emission regulations. The objective of this study is to develop a robust calibration technique to optimize HD diesel engine for performance and emissions to meet current and future emissions standards during certification and real-world operations. In recent years, California - Air Resources Board (C-ARB) has initiated many studies to assess the technology road maps to achieve Ultra-Low NOx emissions for HD diesel applications [1]. Subsequently, there is also a major push for the complex real-world driving emissions as the confirmatory and certification testing procedure in Europe and Asia through the UN-ECE and ISO standards.

Abstract Stratified lean combustion has proven to be a promising approach for further increasing the thermal efficiency of gasoline direct injection engines in low load conditions. In this work, a new injection strategy for stratified operation mode is introduced. A side and a central-mounted solenoid multi-hole injector are simultaneously operated in a single-cylinder engine. Thermodynamic investigations show that this concept leads to improved stability, faster combustion, reduced particle number emissions, and lower fuel consumption levels compared to using only one injector. Experiments at an optical engine and three-dimensional computational fluid dynamics (CFD) simulations explain the improvements by a more compact mixture and reduced piston wetting with two injectors. Finally, the application of external EGR in combination with the above concept allows NOx emissions to be effectively kept at a low level while maintaining a stable operation.

Abstract Realizing the potential of the gasoline direct injection (GDI) concept lies in effectively stratifying the charge at different engine operating conditions. This is generally obtained by properly directing the air and fuel through carefully oriented intake port(s) and fuel spray and appropriately changing injection parameters. However, robust methods of charge stratification are essential to extend the lean operating range, particularly in small GDI engines. In this work, a novel piston shape was developed for a 200 cm3, single-cylinder, four-stroke gasoline engine to attain charge stratification. Stratification of charge is achieved even when the fuel was injected early in the intake stroke by a specially shaped wedge on the piston crown that produced twin vortices during compression and physically separated the charge into two sides in the combustion chamber.

Abstract Emission Control has always been a major concern in each and every field. An increase in emissions leads to climate change, global warming, and even various diseases. The transportation system is responsible for around 30% of emission production, of which 70% of the total atmospheric burden comes from automobiles. Recently developed emission-free electric vehicles have positively affected the levels of impurity in the environment, yet the remaining Internal Combustion Engine (ICE) vehicles on the road have been left with unchecked emissions. Traditional Catalytic Converters are widely used to reduce the emissions of vehicles. It works on the principle of converting hazardous gases emitted from the engine to less harmful carbon dioxide (CO2), nitrogen (N2), and water (H2O). It is integrated with the exhaust of the engine. High efficiency and better emission control catalytic converters are still major milestones to achieve for automotive industries.

Abstract Considering the biodiesel composition, blend percentage, and temperature as input variables in the models to predict biodiesel-diesel blends’ properties is imperative. However, there are no models available in the literature to predict the properties of biodiesel-diesel blends that consider all these variables. The accuracy of spray and combustion models for diesel engines depends on the accuracy at which the fuel properties are estimated. Thus, straightforward approaches to accurately predict the properties of biodiesel-diesel blends are required. A novel reference property-based approach is proposed in the present work to predict the biodiesel-diesel blends’ properties to address this research gap. Models available in the literature correlating the properties of interest to fuel temperature were modified by including a reference property measured at 293 K.

Abstract Mankind’s quest for clean alternative energy sources pushes the boundaries of science and technology every passing day. Increasing environmental and human health concerns caused by conventional fuels underscores the importance of identifying an energy source which is sustainable in terms of production, emissions, and wide application. Hythane (hydrogen-methane gas) is a contender for applications ranging from transportation and combined heating-power generation to cooking. In land transportation, the use of gaseous hythane for internal combustion engines shows better performance, enhanced combustion, and lower emission than conventional liquid hydrocarbon fuels. The use of liquefied Natural Gas (NG) and hydrogen in aircraft and ships is a steppingstone to more the wide-scale use of hythane in air, sea, and rail transportation sectors which could lower emissions and operating costs.

Abstract Many consider hydrogen to be the automobile fuel of the future. Indeed, it has numerous characteristics that makes it very attractive. Hydrogen has a much higher energy density than gasoline, can be produced from water, and its only emission is water. However, there are numerous challenges associated with hydrogen. In particular, the production of hydrogen is a key issue. Currently, most hydrogen is developed from methane, resulting in hydrogen having a carbon footprint. New investments into electrolysis from renewable energy sources is showing promise as an alternative for generating hydrogen. Further, the distribution of hydrogen poses many problems, requiring substantial infrastructure to support a hydrogen economy. Additionally, hydrogen storage is a key issue since most conventional storage mechanisms are overly bulky. If these three issues can be addressed, hydrogen is posed for being a key fuel as the world tries to move away from fossil fuels.

Abstract This article reports a reduced-order modeling framework of bladed disks on a rotating shaft to simulate the vibration signature of faults in different components, aiming toward simulated data-driven machine learning. We have employed lumped and one-dimensional analytical models of the subcomponents for better insight into the complex dynamic response. The framework addresses some of the challenges encountered in analyzing and optimizing fault detection and identification schemes for health monitoring of aeroengines and other rotating machinery. We model the bladed disks and shafts by combining lumped elements and one-dimensional finite elements, leading to a coupled system. The simulation results are in good agreement with previously published data. We model and analyze the cracks in a blade with their effective reduced stiffness approximation.

Abstract Particulate matter (PM) indices—those linking PM emissions from gasoline engines to the composition and properties of the fuel—have been a topic of significant study over the last decade. It has long been known that fuel composition has a significant impact on particulate emissions from gasoline engines. Since gasoline direct injection (GDI) engines have become the market-leading technology, this has become more significant because the evaporative behavior of fuel increases in importance. Several PM indices have been developed to provide metrics describing this behavior and correlating PM emissions. In this article, 16 different PM indices are identified and collected—to the authors’ knowledge, all of the indices are available at the time of writing. The indices are reviewed and discussed in the context of the information required to calculate them, as well as their utility.