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Abstract Gasoline particulate filters (GPFs) are important aftertreatment components that enable gasoline direct injection (GDI) engines to meet European Union (EU) 6 and China 6 particulate number emissions regulations for nonvolatile particles greater than 23 nm in diameter. GPFs are rapidly becoming an integral part of the modern GDI aftertreatment system. The Active Exhaust Tuning (EXTUN) Valve is a butterfly valve placed in the tailpipe of an exhaust system that can be electronically positioned to control exhaust noise levels (decibels) under various vehicle operating conditions. This device is positioned downstream of the GPF, and variations in the tuning valve position can impact exhaust backpressures, making it difficult to monitor soot/ash accumulation or detect damage/removal of the GPF substrate. The purpose of this work is to present a unique example of subsystem control and diagnostic architecture for an exhaust system combining GPF and EXTUN.

Abstract More than a decade ago, we proposed combined use of direct injection (DI) and jet ignition (JI) to produce high efficiency, high power-density, positive-ignition (PI), lean burn stratified, internal combustion engines (ICEs). Adopting this concept, the latest FIA F1 engines, which are electrically assisted, turbocharged, directly injected, jet ignited, gasoline engines and work lean stratified in a highly boosted environment, have delivered peak power fuel conversion efficiencies well above 46%, with specific power densities more than 340 kW/liter. The concept, further evolved, is here presented for unmanned aerial vehicle (UAV) applications. Results of simulations for a new DI JI ICE with rotary valve, being super-turbocharged and having gasoline or methanol as working fuel, show the opportunity to achieve even larger power densities, up to 430 kW/liter, while delivering a near-constant torque and, consequently, a nearly linear power curve over a wide range of speeds.

Abstract Sleep quality and maintenance of the optimal cognitive functioning is of crucial importance for aviation safety. Fatigue Risk Management (FRM) enables the operator to achieve the objectives set in their safety and FRM policies. As in any other risk management cycle, the FRM value can be realized by deploying suitable tools that aid robust decision-making. For the purposes of our article, we focus on fatigue hazard identification to explore the possible developments forward through the enhancement of objective tools in air transport operators. To this end we compare subjective and objective tools that could be employed by an FRM system. Specifically, we focus on an exploratory survey on 120 pilots and the analysis of 250 fatigue reports that are compared with objective fatigue assessment based on the polysomnographic (PSG) and neurocognitive assessment of three experimental cases.

Abstract The main focus of this article is the online estimation of the terminal airspace sector capacity from the Air Traffic Controller 0ATC) dynamical neural model using Neural Partial Differentiation (NPD) with permissible safe separation and affordable workload. For this purpose, a primarily neural model of a multi-input-single-output (MISO) ATC dynamical system is established, and the NPD method is used to estimate the model parameters from the experimental data. These estimated parameters have a less relative standard deviation, and hence the model validation results show that the predicted neural model response is well matched with the intervention of the ATC workload. Moreover, the proposed neural network-based approach works well with the experimental data online as it does not require the initial values of model parameters, which are unknown in practice.

Abstract This article serves as a proof-of-concept and feasibility analysis regarding a variable compression ratio (VCR) engine design utilizing an exhaust valve opening during the compression stroke to vary the compression ratio instead of the traditional method of changing the cylinder or piston geometry patented by Ford, Mercedes-Benz, Nissan, Peugeot, Gomecsys, et al. [1]. In this concept, an additional exhaust valve opening was used to reduce the virtual compression ratio of the engine, without geometric changes. A computational fluid dynamic model in ANSYS Forte was used to simulate a single-cylinder, cold flow, four-stroke, direct injection engine cycle. In this model, the engine was simulated at a compression ratio of 10:1. Then, the model was modified to a compression ratio of 17:1. Then, an additional valve opening at the end of the compression stroke was added to the 17:1 high compression model.

Abstract Effects of process parameters such as rotational speed, feed rate, and drill diameters on the drilling behavior of basalt-epoxy-based composites including 2.5 wt.% Al2O3 particles manufactured by mixing and compression method were investigated by Taguchi’s technique. The experimental results showed that the burr height (BH) increased considerably almost linearly with an increase in the drill diameter, while it remained stable with speed and decreased the feed rate slightly. There was an excellent correlation between the control factors and responses, BH of basalt fiber-reinforced plastics (BFRPs) through the Taguchi approach. The model had an adjusted R2 value of 96.3%. Generally, the inclusion of Al2O3 particles in BFRP increased its cutting force properties. Optimized drilling conditions for the input variables to produce the lowest response of the BH for composites were rotational speed of 560 rpm and feed rate of 0.28 mm/rev and a drill diameter of 4.5 mm.

Abstract The preliminary gas turbine combustor design process uses a huge amount of empirical correlations to achieve more optimized designs. Combustion efficiency, in relation to the basic dimensions of the combustor, is one of the most critical performance parameters. In this study, semi-empirical correlations for combustion efficiencies are examined and correlation coefficients have been revised using an experimental air-blasted tubular combustor that uses JP8 kerosene aviation fuel. Besides, droplet diameter and effective evaporation constant parameters have been investigated for different operating conditions. In the study, it is observed that increased air velocity significantly improves the atomization process and decreases droplet diameters, while increasing the mass flow rate has a positive effect on the atomization—the relative air velocity in the air-blast atomizer increases and the fuel droplets become finer.

Abstract Automated guided vehicle systems (AGVS) are the prominent one in modern material handling systems used in small manufacturing enterprises (SMEs) due to their exciting features and benefits. This article pinpoints the need of AGVS in SMEs by describing the material handling selection in SMEs and enlightening recent technological developments and approaches of the AGVS. Additionally, it summarizes the analytical and simulation-based tools utilized in design problems of AGVS along with the influence of material handling management and key hurdles of AGVS. The current study provides a limelight towards making smart automated guided vehicles (AGVs) with the simplified and proper routing system and favorable materials and more importantly reducing the cost and increasing the flexibility.

Abstract In this study, active-passive filling friction stir repairing (A-PFFSR) process was employed to repair the volume defects in friction stir welding (FSW) joints of Al-Cu alloy. The volume defects with varied geometries were first machined into taper holes, which are similar to keyhole defect by a rotational tool with a threaded pin. Then, the keyhole defect was effectively filled with the materials around the keyhole and an additional filler using a number of nonconsumable pinless tools with the shoulders having six spiral flutes. The macro/microstructures, microhardness, and tensile properties of the repaired joints were investigated. The influences of plunge speed on macro/microstructures and mechanical properties of the repaired joints have been analyzed too. It was noticed that decreasing plunge speed was effective to improve the frictional heat and material flow, which increased joint surface integrity avoiding interfacial drawbacks.

Abstract In an automated machining process, monitoring the conditions of the tool is essential for deciding to replace or repair the tool without any manual intervention. Intelligent models built with sensor information and machine learning techniques are predicting the condition of the tool with good accuracy. In this study, statistical models are developed to identify the conditions of the abrasive grinding wheel using the Acoustic Emission (AE) signature acquired during the surface grinding operation. Abrasive grinding wheel conditions are identified using the abrasive wheel wear plot established by conducting experiments. The piezoelectric sensor is used to capture the AE from the grinding process, and statistical features of the abrasive wheel conditions are extracted in time and wavelet domains of the signature. Machine learning algorithms, namely, Classification and Regression Trees (CART) and Support Vector Classifiers (SVC), are used to build statistical models.

Abstract The proposed approach present the development of a computer tool that allows, in the first phase, the modeling of the electric vehicle power chain. This phase is based on a library developed under the Matlab-Simulink simulation environment. This library contains all the components of the power chain; it offers the selection of the desired configuration of each component. In the second phase, the tool solves the autonomy optimization problem. This problem is resolved by a program based on genetic algorithms. This program permits to optimize the configuration parameters maximizing the vehicle autonomy of the chosen chain. This tool is based on a graphical interface developed under the Matlab simulation environment.

Abstract Due to the increasing requirements for efficiency, the wide range of characteristics and the improved possibilities of modern development and production processes, compressors in turbochargers have become more individualized in order to adapt to the requirements of internal combustion engines. An understanding of the working mechanisms as well as an understanding of the way that losses occur in the flow allows a reduced development effort during the optimization process. This article presents three-dimensional (3D) Computational Fluid Dynamics (CFD) investigations of the loss mechanisms and quantitative calculations of individual losses. The 3D-CFD method used in this article will reduce the drawbacks of one-dimensional calculation as far as possible. For example, the twist of the blades is taken into account and the “discrete” method is used for loss calculation instead of the “average” method.

Abstract Automotive vehicle includes various systems like engine, transmission, exhaust, air intake, cooling and many more systems. No doubt the performance of individual system depends upon their core design. But for performance, the system needs to be fastened properly. In automotive, most of the joints used fasteners which helps in serviceability of the components. There are more than thousands of fasteners used in the vehicle. At various locations, we found issue of bolt loosening and because of this design intent performance has not met by the system. During product development of ECS (Engine cooling system), various issues reported to loosening the bolt. The pre-mature failure of bolt loosening, increases the interest in young engineers for understanding the behavior of fastener in vehicle running conditions. This paper focuses on the design of wedge shape of washer to avoid bolt loosening.

Abstract The free piston linear generator (FPLG) is a novel machine that functions as an Auxiliary Power Unit (APU) for hybrid electric vehicles, which contains two opposed free piston engines and one linear generator between them. FPLG has attracted extensive interest for its potential advantages in terms of high power density and multi-fuel flexibility. The guarantee of FPLG generating electricity steadily and efficiently is the high controllability of compression ratio. In this article, a control-oriented discrete-time model was established based on Otto cycle. Since the fluctuation of in-cylinder pressure caused by instable fuel injection mass and combustion process is the main disturbance, a composite controller is designed to precisely control the compression ratio of FPLG. The composite controller is made up of a feedforward controller and a feedback tracking controller.

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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 As emissions regulations continue to tighten, both from lower imposed limits of pollutants, such as nitrous oxides (NOx), and in-use and real-world testing, the importance of quickly heating the aftertreatment to operating temperature during a cold start, as well as maintaining this temperature during periods of low engine load, is of increasing importance. Perhaps the best method of providing the necessary heating of the aftertreatment is to direct hot exhaust gasses to it directly from the engine. For heavy-duty diesel engines that utilize turbochargers, this is achieved by fully bypassing the exhaust flow around the turbine directly to the aftertreatment. However, this disables a conventional turbocharger, limiting engine operation to near-idle conditions during the bypass period.

Abstract In this study low temperature plasma technology was applied to expand auto-ignition operation region and control auto-ignition phasing of the homogeneous charge compression ignition (HCCI) combustion. The low temperature plasma igniter of a barrier discharge model (barrier discharge igniter (BDI)) with high-frequency voltage (15 kHz) was provided at the top center of the combustion chamber, and the auto-ignition characteristics of the HCCI combustion by the low temperature plasma assistance was investigated by using a single-cylinder gasoline engine. HCCI combustion with compression ratio of 15:1 was achieved by increasing the intake air temperature. The lean air-fuel (A/F) ratio limit and visualized auto-ignition combustion process on baseline HCCI without discharge assistance, spark-assisted HCCI, and BDI-assisted HCCI were compared.

Abstract The article describes the results achieved in developing a new diesel combustion system for passenger car application that, while capable of high power density, delivers excellent fuel economy through a combination of mechanical and thermodynamic efficiencies improvement. The project stemmed from the idea that, by leveraging the high fuel injection pressure of last generation common rail systems, it is possible to reduce the engine peak firing pressure (pfp) with great benefits on reciprocating and rotating components’ light-weighting and friction for high-speed light-duty engines, while keeping the power density at competitive levels. To this aim, an advanced injection system concept capable of injection pressure greater than 2500 bar was coupled to a prototype engine featuring newly developed combustion system. Then, the matching among these features has been thoroughly experimentally examined.