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The continuous improvement of spark-ignition direct-injection (SIDI) engines is largely attributed to the enhanced understanding of air-fuel mixing and combustion processes. The intricate interaction between transient spray behavior and the ambient flow field is important to unveil the airflow dynamics during the spray injection process. This study investigates the fuel-spray boundary interactions under different superheated conditions by analyzing the ambient flow field pattern with constraint-based modeling (CBM). In the experimental setup, superheated conditions are facilitated by adjusting different fuel temperatures and ambient pressures. By adding the tracer particles containing Rhodamine 6G to the ambient air, the combined diagnostic of fluorescent particle image velocimetry (FPIV) and Mie-scattering is implemented to measure the velocity distribution and flow trajectory of the air surrounding the spray formation and propagation.

The majority of transportation systems have continued to be powered by the internal combustion engine and fossil fuels. Heavy-duty applications especially are reliant on diesel engines for their high brake efficiency, power density, and robustness. Although engineering developments have advanced engines towards significantly fewer emissions and higher efficiency, the use of fossil-derived diesel as fuel sets a fundamental threshold in the achievable total net carbon reduction. Dimethyl ether can be produced from various renewable feedstocks and has a high chemical reactivity making it suitable for heavy-duty applications, namely compression ignition direct injection engines. Literature shows the successful use of DME fuels in diesel engines without significant hardware modifications.

Compression ignition engines used in heavy-duty applications are typically powered by diesel fuel. The high energy density and feedstock abundance provide a continuing source for the immense energy demand. However, the heavy-duty transportation sector is challenged with lowering greenhouse gas and combustion by-product emissions, including carbon dioxide, nitrogen oxides, and particulate matter. The continuing development of engine management and combustion strategies has proven the ability to meet current regulations, particularly with higher fuel injection pressure. Nonetheless, a transition from diesel to a renewable alternative fuel source will play a significant role in reducing greenhouse gases while maintaining the convenience and energy density inherent in liquid fuels. Dimethyl ether is a versatile fuel that possesses combustion properties suitable for compression ignition engines and physical properties helpful for clean combustion.

In order to meet increasingly stringent emission regulations, it is significance to establish a control- oriented transient NOx and PM emission prediction model and improve the accuracy and real-time performance. In this study, the prediction model of transient PM emissions based on Transformer is established. In terms of model accuracy and real-time performance, Transformer emission prediction model is compared with Multilayer perceptron (MLP) neural network and Long-Short Term Memory (LSTM) emission prediction model. The results show that the performance of Transformer transient emission prediction model is superior to other model structures, it can be used for real-time prediction.

Visual Place Recognition (VPR) excels at providing a good location prior for autonomous vehicles to initialize the map-based visual SLAM system, especially when the environment changes after a long term. Condition change and viewpoint change, which influences features extracted from images, are two of the major challenges in recognizing a visited place. Existing VPR methods focus on developing the robustness of global feature to address them but ignore the benefits that local feature can auxiliarily offer. Therefore, we introduce a novel hierarchical place recognition method with both global and local features deriving from homologous VLAD to improve the VPR performance. Our model is weak supervised by GPS label and we design a fine-tuning strategy with a coupled triplet loss to make the model more suitable for extracting local features.

Alumina (Al2O3) thin film coatings are applied on Al alloys using Plasma Electrolytic Oxidation (PEO) method to reduce the wear and corrosion problems. Plasma Electrolytic Aluminating (PEA) is a technique which could generate Alumina coatings on cast iron, mild steel and copper alloys. In this study, the aim is to explore the anti-wear and anti-corrosion behaviours of PEA Alumina coatings on gray cast iron. The dry sliding tribology test data was obtained from Pin-on-Disk (POD) tests against SAE 52100 steel and Tungsten Carbide (WC) counterfaces. Comparing with the PEO Alumina coatings, the PEA Alumina coating has much lower Coefficient of Friction (COF) and less wear. The microstructure, chemical composition and phase composition of this coating were investigated with Scanning Electron Microscope (SEM), Energy-Dispersive X-Ray Spectroscopy (EDX) and X-Ray Diffraction (XRD), respectively. There was FeO (or FeAl2O4) found on the PEA Alumina coating.

Oxygenated, low energy-density fuels have the potential to decouple the NOx-soot emissions trade-off in compression-ignition engines. Additionally, synthetic fuels can provide a pathway to reach carbon-neutral utilization of hydrocarbon-based fuels in IC engines. Oxymethylene Dimethyl Ether (OME) is one such synthetic, low energy-density fuel, derived from sustainable sources that in combination with conventional fossil fuels with higher energy content, has the potential to reduce CO2 emissions below the US and EU VI legislative limits, while maintaining ultra-low soot emissions. The objective of this work is to investigate and compare the performance, emissions and efficiency of a modern multi-cylinder diesel engine under conventional high temperature combustion (HTC) with two different fuels; 1) OME310 - a blend of 10% OME3 by volume, with conventional Ultra-Low Sulphur Diesel (ULSD), and 2) D100 - conventional ULSD in North America.

Performance of the ignition system becomes more important than ever, because of the extensively used EGR in modern spark-ignition engines. Future lean burn SI and SACI combustion modes demand even stronger ignition capability for robust ignition control. For spark-based ignition systems, extensive research has been carried out to investigate the discharge characteristics of the ignition process, including discharge current amplitude, discharge duration, spark energy, and plasma stretching. The correlation between the spark stretch and the discharge energy, as well as the impact of discharge current level on this correlation, are important with respect to both ignition performance, and ignition system design. In this paper, a constant volume combustion chamber is applied to study the impact of plasma stretch on the spark energy release process with cross-flow speed from 0 m/s up to 70 m/s.

Increasingly strict emission regulations and unfavorable economic climate bring severe challenges to the energy conservation of marine low-speed engine. Besides traditional methods, the energy and exergy analysis could acknowledge the losses of fuel from a global perspective to further improve the engine efficiency. Therefore, the energy and exergy analysis is conducted for a marine low-speed engine based on the experimental data. Energy analysis shows the exhaust gas occupies the largest proportion of all fuel energy waste, and it rises with the increment of engine load. The heat transfer consumes the second largest proportion, while it is negatively correlated to engine load. The energy analysis indicates that the most effective way to improve the engine efficiency is to reduce the energy wasted by exhaust gas and heat transfer. However, the latter exergy analysis demonstrates that there are other effective approaches to improve the engine efficiency.

The heterogeneous nature of direct injection (DI) combustion yields high combustion efficiencies but harmful emissions through the formation of high nitrogen oxide (NOx) and smoke emissions. In response, extensive empirical and computational research has focused on balancing the NOx-smoke trade-off to limit diesel DI combustion emissions. Dimethyl ether (DME) fuel is applicable in DI compression ignition engines and its high fuel oxygen produces near-smoke-free emissions. Moreover, the addition of a premixed fuel can improve mixture homogeneity and minimize the DI fuel energy demands lessening injection durations. For this technique, a low reactivity fuel such as ethanol is essential to avoid early autoignition in high compression ratio engines. In this work, empirical experiments of dual fuel operation have been conducted using premixed ethanol with high-pressure direct injection DME.

Gluing is an essential fastening step in the field of aircraft assembly except for riveting and bolting. Generally, the robotic programs of gluing are generated in CAM environment. Due to the positioning errors and deformation of the workpiece to be glued in the fixture, the nominal pose and the actual pose of the workpiece are no longer consistent with each other. The Robot trajectory of dispensing glue is adjusted manually according to the actual pose of the workpiece by robot teaching. In this paper, an on-line gluing path correction method is developed by 2D laser profile measurement. A pose calibration method for 2D laser profiler integrated into a gluing robot by measuring a fixed center point of a standard ball is proposed to identify the position and orientation of the laser sensor, which enables the accurate transforming coordinates between the robot frame and the sensor frame.

To alleviate the shortage of petroleum resources and the air pollution caused by the burning of fossil fuels, the development of renewable fuels has attracted widespread attention. Among the various renewable fuels, ethanol can be produced from biomass and does not require much modification when applied to practical engines, so it has been widely used. However, ethanol fuel has a higher heat of vaporization than gasoline, it is difficult to evaporate and atomize under cold start conditions. Besides, the catalyst has not reached the conversion temperature at this time, resulting in lower conversion efficiency. These factors all lead to higher pollutant emission levels in ethanol-gasoline blends. To solve the above problems, this research used visualization techniques to compare the effects of flash boiling and high-energy ignition technologies on the in-cylinder combustion process and pollutant emission of ethanol-gasoline blends fuel.

Low temperature combustion (LTC) has been proved to overcome the trade-off between NOx and soot emissions in direct injection compression ignition engines. However, the lowered NOx emissions are accompanied by high hydrocarbon and CO emissions. Moreover, the NOx emissions under LTC has much higher NO2 concentrations compared with traditional high temperature combustion conditions. Experimental investigations have been carried out to show the hydrocarbon impact on NOx emissions and NO-NO2 conversion under various engine operation conditions, but the mechanism is less understood. The article includes numerical studies of the impact of hydrocarbons in the in-cylinder conversion of NO to NO2 during low temperature conditions in a compression ignition engine. In the present work, a stochastic reactor model with detailed chemical kinetics is utilized to investigate the reaction pathways during the NOx reduction and NO2 conversion processes.

Computational fluid dynamics (CFD) modeling has many potentials for the design and calibration of modern and future engine concepts, including facilitating the exploration of operation conditions and casting light on the involved physical and chemical phenomena. As more attention is paid to the matching of different fuel types and combustion strategies, the use of detailed chemistry in characterizing auto-ignition, flame stabilization processes and the formation of pollutant emissions is becoming critical, yet computationally intensive. Therefore, there is much interest in using tabulated approaches to account for detailed chemistry with an affordable computational cost. In the present work, the tabulated flamelet progress variable approach (TFPV), based on flamelet assumptions, was investigated and validated by simulating constant-volume Diesel combustion with primary reference fuels - binary mixtures of n-heptane and iso-octane.

With the development of economic globalization, the speed of development of container terminals is also very rapid. Under the pressure brought by the surge in throughput, the unmanned and intelligent terminals will become the future development direction of terminals. As the cornerstone of the unmanned terminal, the positioning technology provides the most basic position information for system scheduling, path planning, real-time correction, and loading and unloading. Therefore, this paper is aimed to design a low-cost, high-precision, and easy-to-maintain unmanned dock positioning system in order to better solve the problem of unmanned dock positioning. The main research content of this paper is to design a positioning algorithm for unmanned terminal Automated Guided Vehicle (AGV) based on single-line lidar, including point cloud data acquisition, background filtering, point cloud clustering, vehicle position extraction, and result optimization.

Applications of methanol and biodiesel in internal combustion engines have raised widespread concerns, but there is still huge scope for improvement in efficiency and emissions. The brand-new combustion mode, named as Intelligent Charge Compression Ignition (ICCI) combustion, was proposed with methanol-biodiesel dual fuel direct injection. In this paper, effects of injection parameters such as two-stage split-injections, injection timings, injection pressure and intake pressure on engine combustion and emissions were investigated at IMEP = 8, 10, and 12 bar. Results show that the indicated thermal efficiency up to 53.5% and the NOx emissions approaching to EURO VI standard can be obtained in ICCI combustion mode.

Developing advanced combustion mode has been the active area for high efficiency and ultra-low emissions of the next-generation internal combustion engines. In this paper, a series of experiments were conducted in a modified single-cylinder compression ignition engine for operating a brand-new combustion mode denoted as intelligent charge compression ignition (ICCI) mode. By using two common-rail systems, commercial gasoline and diesel were alternately directly injected into the cylinder through multi-injection strategies in the injection timing range of 50~320 °CA BTDC. Thus, the in-cylinder stratified condition can be flexibly and accurately adjusted in this unique combustion mode. The key injection parameters, such as gasoline injection timing and diesel split ratio, were investigated to explore their effects on engine combustion, emissions, and fuel consumption.

Autonomous vehicles are currently a subject of great interest and there is heavy research on creating and improving algorithms for detecting objects in their vicinity. A ROS-based deep learning approach has been developed to detect objects using point cloud data. With encoded raw light detection and ranging (LiDAR) and camera data, several basic statistics such as elevation and density are generated. The system leverages a simple and fast convolutional neural network (CNN) solution for object identification and localization classification and generation of a bounding box to detect vehicles, pedestrians and cyclists was developed. The system is implemented on an Nvidia Jetson TX2 embedded computing platform, the classification and location of the objects are determined by the neural network. Coordinates and other properties of the object are published on to various ROS topics which are then serviced by visualization and data handling routines.

Flash boiling is considered a useful method in enhancing the liquid fuel jet break-up and spray atomization process for internal combustion engine applications. Spray atomization efficiency plays a vital role in the combustion process. Although some researches have demonstrated that flash boiling has the potential to improve the combustion efficiency and optimize emission-related issues, the effect of flash boiling spray characteristics on the combustion process has not been fully investigated. In this paper, spray characteristics and its related combustion process were studied via various non-intrusive diagnostics methods. The spray and combustion process under different test conditions were studied using an optical engine. It was found that by using flash boiling atomization, the combustion duration was reduced and IMEP enhanced significantly. Experimental results have built the relationship between flash boiling spray characteristics and the combustion performance in the engine.

Increasingly stringent emission standards have promoted the interest in alternate fuel sources. Because of the comparable energy density to the existing fossil fuels and renewable production, alcohol fuels may be a suitable replacement, or an additive to the gasoline/diesel fuels to meet the future emission standards with minimal modification to current engine geometry. In this research, the combustion characteristics of neat n-butanol are analyzed under spark ignition operation using a single cylinder SI engine. The fuel is injected into the intake manifold using a port-fuel injector. Two modes of charge dilution were used in this investigation to test the limits of stable engine operation, namely lean burn using excess fresh air and exhaust gas recirculation (EGR). The in-cylinder pressure measurement and subsequently, heat release analysis are used to investigate the combustion characteristics of the fuel under low load SI engine operation.