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Aiming at the problem of torque fluctuations and intake pressure fluctuations caused by cycle cylinder deactivation, we introduced a refined control strategy encompassing fixed cycle frequency with fixed deactivation frequency, variable cycle frequency with fixed deactivation frequency, and variable cycle frequency with variable deactivation frequency. The cycle cylinder deactivation rate is determined by controlling the cycle frequency and the cylinder deactivation frequency, which provides a new method for exploring the torque fluctuation of the cycle cylinder deactivation. Furthermore, we introduced an intake compensation method based on the cylinder deactivation compensation coordinate system is proposed. The non-uniformity of the intake air volume of each cylinder of the cycle cylinder deactivation is improved by changing the valve lift. After compensation, the non-uniformity of the intake air volume and the mean indicated pressure of each cylinder are within 2%, and the maximum torque fluctuation is reduced by 52%. It provides a useful reference for enhancing the dynamic smoothness of cylinder deactivation in engines. [ABSTRACT FROM AUTHOR]

Designing a new API for a large-scale project requires developers to make strategic design choices that will allow the codebase to evolve sustainably. To create well-structured API components, developers can learn from existing APIs. However, the lack of standardized methods for comparing API designs often makes this learning process inefficient and challenging. To bridge this gap, we introduce API-Miner, which, to our knowledge, is one of the first engines to recommend API-to-API specifications. API-Miner retrieves relevant components from OpenAPI specifications-a widely recognized standard for describing web APIs. The engine introduces several key innovations: (1) novel techniques for processing and extracting critical information from OpenAPI specifications, (2) specialized feature extraction methods tailored to the technical domain of API specifications, and (3) a log-linear probabilistic model that integrates multiple signals to retrieve relevant and high-quality OpenAPI components based on a query specification. Through both quantitative and qualitative evaluations, API-Miner achieves a recall@1 of 91.7% and an F1 score of 56.2%, outperforming baseline models by 15.4 percentage points (pp) in recall@1 and 3.2 pp in F1. API-Miner enables developers to access relevant OpenAPI components from public or internal databases early in the API development cycle, facilitating the learning of best practices and the identification of potential redundancies. This tool helps streamline the development process and supports the creation of maintainable, high-quality APIs. The code for API-Miner is available at https://github.com/jpmorganchase/api-miner. [ABSTRACT FROM AUTHOR]

The InfiniBand (IB) interconnection technology is widely used in the networks of modern supercomputers and data centers. Among other advantages, the IB-based network devices allow for building multiple network topologies, and the IB control software (subnet manager) supports several routing engines suitable for the most common topologies. However, the implementation of some novel topologies in IB-based networks may be difficult if suitable routing algorithms are not supported, or if the IB switch or NIC architectures are not directly applicable for that topology. This work describes the implementation of the network topology known as KNS in a real HPC cluster using an IB network. As far as we know, this is the first implementation of this topology in an IB-based system. In more detail, we have implemented the KNS routing algorithm in the OpenSM software distribution of the subnet manager, and we have adapted the available IB-based switches to the particular structure of this topology. We have evaluated the correctness of our implementation through experiments in the real cluster, using well-known benchmarks. The obtained results, which match the expected performance for the KNS topology, show that this topology can be implemented in IB-based clusters as an alternative to other interconnection patterns. [ABSTRACT FROM AUTHOR]

Water injection (WI) is a well-known technique to mitigate knocking phenomena, reducing the in-cylinder gas temperature with a high heat of vaporization and specific heat of water. In this study, the effect of WI directly into the cylinder on fuel efficiency was investigated using a 2.0 L naturally aspirated (NA), four-cylinder, port fuel injection (PFI)-spark-ignited (SI) engine. Spray visualization of water injection by a commercial gasoline direct-injection (GDI) injector was performed to elucidate the water evaporation characteristics. In engine experiments, combustion characteristics were analyzed by adjusting the WI timing and amount. Synergistic effects with other gas dilution techniques, such as EGR and Lean burn, were also investigated. The spray image of WI showed poor evaporation of water compared to gasoline, even at high fuel temperatures. The optimal timing of WI was advanced up to the early intake stroke due to the harsh conditions of NA engines for water evaporation compared to turbocharged engines. With the combination of EGR, the optimal WI timing was advanced by the compression stroke, and further fuel efficiency improvement was achieved. In lean combustion, WI can improve both combustion stability and fuel efficiency. [ABSTRACT FROM AUTHOR]

Estimates of doses inside the spacecraft were carried out for flights to the Moon using low-thrust engines. The characteristics of the trajectory, which is significantly different from the Hohmann trajectory, are taken into account. Such a trajectory causes a long stay inside the radiation belts, which can cause disruptions in the operation of onboard equipment. It turned out that, during long-term transportation of food products, they may be damaged under the influence of radiation. This is extremely important in the case of the creation of habitable stations on the Moon surface or near-Moon orbit. The presented results can be used in the preparation of future space experiments. [ABSTRACT FROM AUTHOR]

This study presents an analysis of a two-state quantum mechanical Carnot-like engine using diatomic molecules i.e., the Morse oscillator MO, as the working substance. The engine's cycle consists of two adiabatic and two isoenergetic processes. The performance parameters such as the power output, dimensionless power (with its efficiency) and the optimal region of the engine were determined by considering the potential width L moving with finite speed. The results obtained in this work are found to be an analog of the classical Carnot heat engine. Notably, when comparing our results with those obtained using different working substances, such as the Harmonic oscillator HO within a similar engine setup, our analysis demonstrates that the MO stands out as a more potent working substance with enhanced efficiency for our engine. [ABSTRACT FROM AUTHOR]

Durability and reliability have been studied for decades through intensive trial-error experimentation. However, there are numerous fields of application where the costs associated with this approach are not acceptable. In lubricated machines with severe dynamic loads, such as high-power-density engines, simulation tools offer clear advantages over intensive testing. Prototypes and multiple scenarios can be cost-effectively simulated to assess different lubricants and engine configurations. The work presented here details the study of wear based on a validated elastohydrodynamic (EHD) simulation model of the connecting rod journal bearing. This model accounts for elastic deformation through a connecting rod finite element model (FEM). In addition, multiple lubricant rheological and tribological dependences, determined by specific experimental tests, are applied in the model through their interaction with the simulation software. Correspondingly, a novel wear algorithm is proposed to predict wear depth over time evolution along a proposed wear cycle based on the typical working ranges of high-performance engines. A final assessment is presented to compare 4 different ultralow-viscosity lubricants in their protective performance under severe conditions. The results show the evolution of the wear load and wear depth over the wear cycle. This evaluation is key to describing a lubricant selection procedure for high-power-density engines. [ABSTRACT FROM AUTHOR]

In the realm of prognosticating the remaining useful life (RUL) of pivotal components, such as aircraft engines, a prevalent challenge persists where the available historical life data often proves insufficient. This insufficiency engenders obstacles such as impediments in performance degradation feature extraction, inadequacies in capturing temporal relationships comprehensively, and diminished predictive accuracy. To address this issue, a 1D CNN-GRU prediction model for few-shot conditions is proposed in this paper. In pursuit of more comprehensive data feature extraction and enhanced RUL prognostication precision, the Convolutional Neural Network (CNN) is selected for its capacity to discern high-dimensional features amid the intricate dynamics of the data. Concurrently, the Gated Recurrent Unit (GRU) network is leveraged for its robust capability in extracting temporal features inherent within the data. We combine the two to construct a CNN-GRU hybrid network. Moreover, the integration of data distribution alongside correlation and monotonicity indices is employed to winnow the input of multi-sensor monitoring parameters into the CNN-GRU network. Finally, the engine RULs are predicted by the trained model. In this paper, experiments are conducted on a sub-dataset of the National Aeronautics and Space Administration (NASA) C-MAPSS multi-constraint dataset to validate the effectiveness of the method. Experimental results have demonstrated that this method has high accuracy in RUL prediction tasks, which can powerfully demonstrate its effectiveness. [ABSTRACT FROM AUTHOR]

Many consumers suffer from inadequate information and behavioral biases, which can produce internalities, understood as costs that people impose on their future selves. In these circumstances, "Choice Engines," powered by Artificial Intelligence (AI), might produce significant savings in terms of money, health, safety, or time. Different consumers care about different things, of course, which is a reason to insist on a high degree of freedom of choice, and a high degree of personalization. Nonetheless, it is important to emphasize that Choice Engines and AI might be enlisted by self-interested actors, who might exploit inadequate information or behavioral biases, and thus reduce consumer welfare. It is also important to emphasize that Choice Engines and AI might show behavioral biases, perhaps the same ones that human beings are known to show, perhaps others that have not been named yet, or perhaps new ones, not shown by human beings, that cannot be anticipated. [ABSTRACT FROM AUTHOR]

Regenerator in the Stirling engine is the most important element; the equation of momentum conservation has been proposed for the mass of gas in it. This makes it possible to take into account relaxation hydrodynamic processes in the regenerator and, as a consequence, the model is simplified greatly. The simulation was carried out in the isothermal approximation. In the engine, at the initial stage, high-frequency (~102 Hz or more) and low-frequency oscillations (~10 Hz or less) originate. The movement of the working piston and displacer corresponds to low frequency vibrations. Without relaxation processes in the regenerator, the Stirling engine does not work. There is a minimum temperature difference between the heater and cooler, below which a free-piston engine also does not operate, but can operate like another type of Stirling engine. [ABSTRACT FROM AUTHOR]

This study addresses the vital role of engine dampers in reducing vibrations and enhancing ride comfort in quad bikes. Utilizing ANSYS modal analysis and CATIA V5 design, the research aims to optimize damper design by assessing natural frequencies and potential resonance in the cage structure and engine. Through extensive analysis, the study evaluates vibrations transmitted from the engine to the chassis, crucial for understanding and improving overall vehicle performance. Neoprene rubber emerges as the optimal material for vibration dampers, offering superior density, elasticity, stiffness, and damping coefficient. Comparative analysis reveals that Design 3 of the dampers significantly outperforms Design 2 and Design 1, showcasing a remarkable 62% reduction in vibration. However, the study underscores the influence of various factors, such as application specificity and vibration characteristics, on damper effectiveness. Thus, while Design 3 may excel under certain conditions, careful consideration of diverse a variable is essential for optimal damper selection and performance across different engine types and operational contexts. [ABSTRACT FROM AUTHOR]

This study proposes the slope of the engine speed trend line (SlopeESTL) as a new misfire detection index for a four-cylinder engine, not limited to four-cylinder engines. SlopeESTL is defined as angular acceleration between the first and the last teeth of each cylinder in the cycle. SlopeESTL is flat and near 0 when the cylinder is normally combusted. A misfire leads to an abrupt decrease under the threshold. While it is affected by post oscillation just after misfires, there is enough margin between SlopeESTL of the misfired cylinder and post-oscillated SlopeESTL. The mean misfire detection and detection fault rates of the SlopeESTL were over 97% and under 1% in this study, making it a good misfire detection index. However, most of the first misfired cylinder on dual cylinder misfire can seldom be detected as a misfire at the high engine speed over 5000 rpm in the single cylinder misfire pattern. This is caused by the inertia force of the crankshaft system and is a demerit for the misfire detection index. It is one of the two RPM slopes used to calculate the Gap and ΔGap slopes proposed by the author. SlopeESTL can be used with Gap and ΔGap slopes, because they have their specific characteristics as misfire detection indices and their combination logic should be studied more. Furthermore, SlopeESTL can be affected by the machining tolerance of the teeth in the sensor wheel, torsional vibration, and non-uniformity in the stroke operation of the piston. However, it uses the tooth time measured using the existing crankshaft position sensor; an additional sensor is not required, which makes it economical. [ABSTRACT FROM AUTHOR]

Biodiesel and alternative fuels have been key research areas for the last two decades, but low energy density and emission of NOx are the barriers for their commercialization. However, existing reviews do not have a holistic approach for the commercialization of nanofuel in CI engines. So, in this regard, nanoparticles can address the aforementioned issues. Currently, research is going on to explore different nanoparticles in the area of biofuel and biodiesel. Hence, the current work's focus is structured in two parts: the first part reviews the application of nanoparticles in biodiesel fuels holistically, emphasizing fuel properties and engine characteristics. The second part examines research hotspots, financial implications, drawbacks, and alternatives to nano-biofuel. This study also summarises the holistic view of biodiesel and nanoparticles of various kinds and their effects on fuel properties and engine characteristics such as performance, combustion and emissions. Moreover, the nanoparticle characteristics, cost analysis of diesel engines, and impacts of nanoparticles in the environment with their prospects and future research opportunities have also been discussed in the current manuscript. Finally, the study concludes that incorporating hybrid Al2O3 and GO nanoparticles of size 20–30 nm in 20% waste oil biodiesel blended in 80% petro-diesel can be the potential fuel to be commercialized in CI engines without any engine modification. [ABSTRACT FROM AUTHOR]

In this work, a novel analytical time-sensitive model for Ericsson engines was developed taking into account the heat transfer phenomena between the working gas and the cylinder walls in the compressor and the expander. For the calculation of the mass flow entering/exiting each cylinder, another dedicated flow model was developed to account for the pressure drop at the valves. From the energy equilibrium taking into consideration the time-dependent thermal response of the cylinder walls and the enthalpy entering/exiting each cylinder through the valves, an analytical solution of the working gas pressure and temperature can be obtained for every time step and consequently, the thermal efficiency of the engine can be calculated. A case study was performed where the thermal efficiency of an Ericsson engine was calculated for different rotational speeds and heat exchanger gas temperatures. It was observed that with higher temperatures thermal efficiency maintained a more stable behaviour with a weak dependence on rotational speed. The thermal efficiency of the engine in the performed case studies was found in the range of 10% to 14%. The valve timing of the Ericsson engine was optimized in order to achieve the highest thermal efficiency possible. The thermal efficiency of the engine could be increased up to 26% as a percentage after a thorough optimization of the valve timing. Finally, backflow phenomena accounting for thermal efficiency drop were studied. The developed model can also be applied to other types of external combustion engines such as Stirling engines. [ABSTRACT FROM AUTHOR]

This paper provides a framework based on machine learning approach in I4.0 environment to predict the remaining useful life of an aviation engine. For illustration purpose, an industrial case study is presented which applies machine learning algorithms to analyze the data collected using the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) simulation which includes run-to-degradation data for a turbofan engine. The results obtained from the study validate the proposed framework to identify prominent features and perform sequential analysis on unstructured data for predicting the remaining useful life of an aviation engine. Six machine learning models are applied to the dataset containing four subsets: FD001, FD002, FD003 and FD004 in C-MAPSS dataset each working on different degradation conditions for turbofan engine. For FD001, random forest had the lowest RMSE (11.59), and for FD002, FD003 and FD004, the lowest RMSE was given by LGBM classifier (12.78, 7.95 and 11.04), respectively. From the findings, it is observed that LGBM performs better with higher AUC 89% and lowest RMSE. The proposed framework can be applied to a wide range of failure prediction applications. Regardless of the underlying physics, ML-based data-driven methodologies can be used to analyze a wide range of systems. [ABSTRACT FROM AUTHOR]

In the present study, based on kinetic energy theorem and Newton's second law, the velocity equation of the hard foreign object was derived by taking the engine inlet as reference frame. Taking a certain type of aircraft as an example, the factors that influence the impact velocity of foreign objects were discussed at 100% design rotating speed of the engine. It is observed that the velocity of the foreign object is not only related to the dimension, shape, material, and impact location of the foreign object, but also related to the length of the engine inlet as well as the working state of the engine. The proposed method can be used for estimating the impact velocity in FOD tests by taking into account working state of the engine. [ABSTRACT FROM AUTHOR]

Turboshaft engines are different from each other due to manufacturing and installation tolerances. Hence, it is difficult to draw out the physical model from the average component maps and design points to represent the performance of the individual engine. The available test-bed data is usually less than the number of correction coefficients to update the maps, and it is the underdetermined state optimization issue. In this paper, we propose a novel reduced-order optimization, namely PSO-EKF algorithm, combined with prior state estimation for non-linear model correction of the turboshaft engine. This method combines the advantages of PSO and extended Kalman filter (EKF). PSO-EKF method converts partial parameters optimized by PSO into parameters directly solved by EKF. The order of optimization space is reduced. Using the correction coefficient function, a stability improvement strategy is designed to ensure the stability of the optimization process. Compared with the GA and PSO algorithms, experimental verification shows that the method has a faster convergence speed and smaller model error than the general PSO. After the performance map is updated by this method, the error of outputs of the individual model is within 1.4 %. [ABSTRACT FROM AUTHOR]

The article addresses the material science solutions on the sources and mechanisms of operational and technological destruction in the main units of high-power liquid rocket engines and structural and technological solutions developed to prevent them. [ABSTRACT FROM AUTHOR]

Flow biocatalysis has emerged as an empowering tool to boost the potential of enzymatic reactions towards more automatized, sustainable, and generally efficient synthetic processes. In the last fifteen years, the increasing number of biocatalytic transformations carried out in continuous flow exemplified the benefits that this technology can bring to incorporate biocatalysis into industrial operations. This perspective aims to capture in a nutshell the available methodologies for flow biocatalysis as well as to discuss the current limitations and the future directions in this field. Article highlights: Integration of enzymatic reactions into flow reactors is an exponentially growing technology. Flow biocatalysis can produce valuable molecules for food, cosmetics, and pharmaceuticals in a more eco-friendly manner. An interdisciplinary effort is needed to overcome the current challenges for industrial flow biocatalysis. [ABSTRACT FROM AUTHOR]

Large-scale experiments were carried out in an engine room platform to investigate the mass burning rate and smoke temperature under mechanical ventilation. Four air inlet heights ranged from 0.1 m to 1.0 m and six ventilation rates ranged from 38 h−1 to 126 h−1 were explored. The mass burning rates of pool fire and temperature distributions in the engine room were obtained. The average and maximum temperature values of the entire engine room were calculated to analyze the temperature characteristics of the engine room under various mechanical ventilation conditions. Results showed that the mass burning rates were slightly affected by ventilation rates. The vertical temperature distribution of ship engine room fires under mechanical ventilation presented to be a single-zone distribution. The average temperature of the entire engine room decreased with the increase of ventilation rate. On the basis of thermal balance analysis, a prediction model was proposed to calculate the average temperature of the entire engine room, which was consistent with the temperature trend measured in the experiments within 20% error. [ABSTRACT FROM AUTHOR]

The digital twin concept proves to be highly advantageous for smart ships as it allows the digital model to adapt in real time with changes in the physical ship. The mean value engine model (MVEM) is investigated with three different compressor mass flow rate models: a 2D interpolation model (2D), an experience-based M-JENSEN (MJ) model, and a physics-based Kang Song (KS) model. Each model is studied on a MAN 7S80ME engine with ABB A270 turbochargers. The root-mean-square errors (RMSE) for the test data are approximately 2.5 m 3 / s for the 2D model, 2.8 m 3 / s for the KS model, and 0.56 m 3 / s for the MJ model. For the training data, the RMSEs are around 0.0, 3.0, and 0.69 m 3 / s , respectively. When coupling each model to the MVEM, it is observed that the calculated values differ only in the turbocharger speed. The RMREs under steady-state processes are 0.54% for MVEM with the 2D model, 1.63% for MVEM with the KS model, and 0.48% for MVEM with the MJ model. Under dynamic processes where the engine load is changed from 100% to 80%, the RMREs are 1.59%, 2.40%, and 1.58%, respectively. Among the studied models, the 2D model exhibits instability, the MJ model shows the highest accuracy, while the KS model performs the worst. However, all models demonstrate comparable results when used in the MVEM. Moreover, the physics-based KS model is a favorable choice for digital twin applications due to its excellent extrapolation ability and low dependence on measured data. [ABSTRACT FROM AUTHOR]

This review summarizes the current advances in the synthesis of polyoxyalkylene ethers and alkyl oxalates. It discusses the prospects for the application of these oxygenates as engine fuels and the methods for their structural modification to ensure effective control of their performance characteristics. [ABSTRACT FROM AUTHOR]

Architecture-Driven Modernization (ADM) is a special kind of reengineering that employs models along the process. The main ADM metamodel is the Knowledge Discovery Metamodel (KDM), which is a platform-independent metamodel able to represent several views of a system. Although a lot of research is currently focused on the reverse engineering phase of ADM, little has been devoted to the forward engineering one, mainly on the generation of Platform-Specific Models (PSMs) from KDM. The forward engineering phase is essential because it belongs to the end of the horseshoe model, completing the reengineering process. Besides, the lack of research and the absence of tooling support in this phase hinder the industrial adoption of ADM. Therefore, in this paper, we present a process for creating Transformation Engines (TEs) capable of transforming KDM instances in a chosen PSM. We highlight two main contributions in this work. The first is a process that software engineers can follow for building TEs capable of generating PSM instances (e.g., Java model, Python model, etc.) from KDM instances. Having that on their hands, modernization engineers can then use generators for generating language-specific source code from the PSM. The second is delivering a specific TE called RUTE-K2J, which is able to generate Java models from KDM models. The transformation rules of RUTE-K2J have been tested considering sets of common code structures that normally appear when modernizing systems. The test cases have shown that in this version of RUTE the transformation rules are able to correctly generate 92% of the source code submitted to the transformation. [ABSTRACT FROM AUTHOR]

The current study seeks to predict and optimize the performance and emission characteristics of a dual-fuel diesel engine powered by biogas and biodiesel. A Box–Behnken design (BBD) was employed to generate an L29 orthogonal array consisting of four factors and three levels. The experiments were conducted at a fixed engine load of 75% and a B20 (20% biodiesel and 80% diesel) pilot fuel blend, with varying compression ratios, fuel injection pressures, fuel injection timings, and biogas flow rates. An artificial neural network (ANN) model was developed using the collected data to estimate key performance and emission parameters. The ANN model exhibited high accuracy, with an overall correlation coefficient (R) of 0.9987 and a mean square error of 0.04. Multi-output RSM was employed to optimize the engine parameters, showing that a compression ratio of 16:1, an injection pressure of 246.08 bar, an injection timing of 26.05° bTDC, and a biogas flow rate of 0.36 kg/h were the optimal operating conditions for the engine. The corresponding optimal engine responses for brake thermal efficiency, brake specific fuel consumption, carbon monoxide, hydrocarbon, nitrogen oxides, and smoke emissions were calculated to be 28.25%, 0.30 kg/kWh, 3.00 g/kWh, 0.026 g/kWh, 4.42 g/kWh, and 42.85%, respectively. The experimental validation demonstrated a close agreement between the predicted results of the model and the actual experimental outcomes, with a maximum error of 7.7%. The ANN-coupled BBD approach represents a viable hybrid method for effectively modeling, predicting, and optimizing the performance of a dual-fuel engine. [ABSTRACT FROM AUTHOR]

Most distributed stream processing engines (DSPEs) do not support online task management and cannot adapt to time-varying data flows. Recently, some studies have proposed online task deployment algorithms to solve this problem. However, these approaches do not guarantee the Quality of Service (QoS) when the task deployment changes at runtime, because the task migrations caused by the change of task deployments will impose an exorbitant cost. We study one of the most popular DSPEs, Apache Storm, and find out that when a task needs to be migrated, Storm has to stop the resource (implemented as a process of Worker in Storm) where the task is deployed. This will lead to the stop and restart of all tasks in the resource, resulting in the poor performance of task migrations. Aiming to solve this problem, in this paper, we propose N-Storm (Nonstop Storm), which is a task-resource decoupling DSPE. N-Storm allows tasks allocated to resources to be changed at runtime, which is implemented by a thread-level scheme for task migrations. Particularly, we add a local shared key/value store on each node to make resources aware of the changes in the allocation plan. Thus, each resource can manage its tasks at runtime. Based on N-Storm, we further propose Online Task Deployment (OTD). Differing from traditional task deployment algorithms that deploy all tasks at once without considering the cost of task migrations caused by a task re-deployment, OTD can gradually adjust the current task deployment to an optimized one based on the communication cost and the runtime states of resources. We demonstrate that OTD can adapt to different kinds of applications including computation- and communication-intensive applications. The experimental results on a real DSPE cluster show that N-Storm can avoid the system stop and save up to 87% of the performance degradation time, compared with Apache Storm and other state-of-the-art approaches. In addition, OTD can increase the average CPU usage by 51% for computation-intensive applications and reduce network communication costs by 88% for communication-intensive applications. [ABSTRACT FROM AUTHOR]

This study investigates the impact of ventilation, specifically modeled by a radiator fan, on heptane pool fires within a military ground vehicle engine compartment. Experiments were conducted in a 2.44 m3 scale-1 compartment with varying fan-generated inflow velocities, initial fuel thicknesses, and pan diameters. The primary objective is to comprehensively assess how ventilation conditions affect pool fire behavior, focusing on properties such as mass loss rate, heat release, temperature, and heat flux in both the boiling and steady stages. The results reveal that the boiling stage occurs at initial fuel thicknesses of 10 and 15 mm, allowing us to analyze the boiling-to-steady ratio. This ratio exhibits variation across parameters. For burning duration, the ratios range from 0.45 to 0.93, while for mass loss rate, the ratios range from 2.3 to 3.5. Regarding total heat flux, the ratios span from 2.5 to 4. The boiling-to-steady ratio for temperature varies by position: in the vertical tree, it ranges from 1.1 to 1.7; in the ceiling tree, it ranges from 2.2 to 2.9; and in the ceiling side tree, it ranges from 1.2 to 2.25. Ventilation influences the boiling-to-steady ratio. Increasing inflow velocity generally increases the ratio for burning duration and ceiling tree temperature while decreasing the ratio for mass loss rate. The impact of ventilation on other properties depends on pan diameter and initial fuel thickness. [ABSTRACT FROM AUTHOR]

In this study, a new envelope winglet vortex generator is numerically analyzed and installed on the hot side of the thermoelectric generator (TEG) exhaust heat exchanger. Experiments for the TEG-based waste heat recovery (WHR) system integrated with engine exhaust have identified the best design configuration for the envelope winglet vortex generator in terms of pitch/channel height ratio (P/H) and tilt angles (θ ). The system's feasibility has been proven by contrasting the current thermoelectric-based WHR with conventional alternator technology. Numerical research showed that the more significant flow rates in longitudinal envelope winglet VGs resulted in a larger radius. The envelope winglet profile has a sizable impact on the performance of the innovative TEG system with a vortex generator in the exhaust heat exchanger. The current analysis indicates that the exhaust heat exchanger arrangement with a pitch/channel height ratio (P/H) of 3 and a tilt angle (θ ) of 60° produces the system's best power output. Maximum power output and maximum net power output at engine load L3 are shown at θ = 60° and 105 and 56.86% higher than those of the smooth channel, respectively. However, the largest power out and net power output increases are determined to be 68.08 and 42.28%, respectively, for P/H = 3. The recommended envelope winglet Vortex Generators (VGs) in engine operating mode L3 can raise brake-specific fuel consumption (BSFC) by up to 0.82%. The engine would operate at this mode's lowest fuel consumption and emissions. [ABSTRACT FROM AUTHOR]

This article compares engine performance, combustion, and emissions at part-load in cylinder deactivation (CD) mode versus the traditional spark ignition mode. This comparison demonstrates the applicability of cylinder deactivation for a compact 3-cylinder engine. Experiments have been performed on a multi-point fuel injection engine having a 1000 cc displacement and equipped with an open engine control unit. A response surface approach has been applied to design experiments and parametric engine optimization. The analysis of variance test indicates that the load is the input factor that impacts the deactivation mode most. At 3500 RPM and 45 N·m load, the engine performs best in CD mode, with BSFC, BTE, CP, HRR and UHC values of 332.805 g/kW-hr, 25.26 %, 52.51 bar, 43.24 J, and 10.38 ppm, respectively. The validation test results for CD mode show that the percentage error for the BSFC, BTE, CP, HRR, and UHC responses was found to be 2.86, 2.91, 3.01, 3.47, and 3.97, respectively, within the acceptable range. As compared to SI mode, the current analysis has discovered a considerable decrease in BSFC (11.47 %), an improvement in BTE (12.25 %), a higher CP (80.65 %), a greater HRR (91.74 %), and a decrease in UHC (95.48 %). [ABSTRACT FROM AUTHOR]

In-cylinder heat release features and nanoparticle emissions have been investigated in this study for CNG–diesel reactivity-controlled compression ignition (RCCI) engine. Study aims to determine the effect of low-temperature heat release (LTHR) and high-temperature heat release (HTHR) on the particles emissions from the RCCI engine. LTHR is obtained as a small peak (curve) before the main HTHR in the heat release rate curve. The LTHR and HTHR are not separated in heat release rate curve. The low-temperature heat release rate (LTHRR) is determined by extracting the heat release between start of combustion (SOC) to the intersection point of slope between LTHR and HTHR. The high-temperature heat release rate (HTHRR) is determined by fitting the trace between the intersection point of slope between LTHR and HTHR to the end of HTHR (the crank angle where the main HTHR turns negative after attaining the peak). This study calculates the amount of LTHR and HTHR by determining the absolute area under the LTHRR and HTHRR trajectories. Experiments are performed for different port-injected CNG masses (mc) and engine loads at a fixed engine speed of 1500 rpm. Single- and double-fuel injection strategy is used for injecting diesel. In the double-injection strategy, two cases are investigated. In the first case, diesel mass is split in the ratio of 50:50% between the first and second injection, whereas in the second case, diesel mass is divided into the proportion of 70:30%. CNG fuel mass, diesel start of injection (SOI), and the number of injections are controlled by engine electronic control unit (ECU). Results indicates that at a lower load with single-injection strategy, the lower amount of LTHR promotes the formation of small particles for 30° bTDC diesel SOI. It is found that increase in mc per cycle results in reduced and delayed LTHR and HTHR. With an increase in mc, the amount of LTHR decreases, and the total PN increases. The reduction in LTHR with an increase in mc leads to an increase in the formation of nucleation mode particles (NMPs) and a decrease in the accumulation mode particles (AMPs). [ABSTRACT FROM AUTHOR]

This paper presents a novel method to estimate the design parameters of a diaphragm thermoacoustic Stirling engine and investigate the stable limit cycle (sufficient condition) of the engine dynamic using the genetic algorithm and system energy changes. In this regard, first, the parametric equations are extracted by employing both the governing equations of the engine and energy standpoint. Next, V c 0 (initial volume of compression space), R q (pneumatic resistance), V h 0 (initial volume of expansion space), and hot gas temperature ( T h ) are taken as the design parameters in this study. Genetic algorithm and parametric equations were then utilized to estimate the chosen design parameters. Next, the sufficient condition of the engine is evaluated based on the estimated design parameters. The simulated outcomes are shown that the sufficient condition is satisfied by the estimated design parameters. Afterward, the simulated results are validated using experimental data gathered from the constructed SUTech-SR-3 engine. Comparing the extracted data eventuates a proper method of estimating design parameters and satisfying the sufficient condition related to the SUTech-SR-3 engine. It is worth noting that in this research, the dynamic of the thermoacoustic Stirling engine has investigated using a mechanical point of view. Also, in this paper, only the dynamic behavior of the engine has been investigated, and the production power and work have not been studied. [ABSTRACT FROM AUTHOR]

As multi/many-core processors are widely deployed in high-performance computing systems, efficient intra-node communication becomes more important. Intra-node communication involves data copy operations to move messages from source to destination buffer. Researchers have tried to reduce the overhead of this copy operation, but the copy operation performed by CPU still wastes the CPU resources and even hinders overlapping between computation and communication. The copy engine is a hardware component that can move data between intra-node buffers without intervention of CPU. Thus, we can offload the copy operation performed by CPU onto the copy engine. In this paper, we aim at exploiting copy engines for MPI blocking collective communication, such as broadcast and gather operations. MPI is a messaging-based parallel programming model and provides point-to-point, collective, and one-sided communications. Research has been conducted to utilize the copy engine for MPI, but the support for collective communication has not yet been studied. We propose the asynchronism in blocking collective communication and the CE-CPU hybrid approach to utilize both copy engine and CPU for intra-node collective communication. The measurement results show that the proposed approach can reduce the overall execution time of a microbenchmark and a synthetic application that perform collective communication and computation up to 72% and 57%, respectively. [ABSTRACT FROM AUTHOR]

The characteristics of fatigue failure of the working blades of the first stage of the high-pressure turbine of the power gas-turbine engine were determined. Experimental studies were carried out on blades obtained according to the improved technology from the CM88Y alloy, which is used in the serial production of gas-turbine units. The blades withstood the test base of 1×107 cycles at a stress of 200–240 MPa. The established endurance limit corresponded to the given service life of blades of this type. [ABSTRACT FROM AUTHOR]

This paper presents the architecture and features of RiskScape software. RiskScape is an open-source software with a flexible modelling engine for multi-hazard risk analysis. The RiskScape engine implements modeller-defined risk quantification workflows as 'model pipelines'. Model pipeline steps and functions analyse hazard, exposure, and vulnerability data across different spatio-temporal domains using geoprocessing and spatial sampling operations. The RiskScape engine supports deterministic and probabilistic risk quantification, with several probabilistic-based modes described in this paper. RiskScape advances modelling software for multi-hazard risk analysis through several implementation features. The RiskScape engine operates model pipelines independent of system prescribed model input data classifications or standards. Multiple hazard types, metric intensities, and temporal occurrence information is geometry processed and sampled to create coverage data of simultaneous or sequenced multi-hazard events at object-exposure locations. Escalating multi-hazard event impacts are then determined for object-exposures using scripted conditional or nested statements that apply vulnerability functions in a logical sequence of temporal hazard and impact occurrence. These model features, supported by open geospatial consortium standard geospatial data files and operations, expedite RiskScape for modelling multi-hazard risk at any geographical location or scale. [ABSTRACT FROM AUTHOR]

Fuzzy inference engine, as one of the most important components of fuzzy systems, can obtain some meaningful outputs from fuzzy sets on input space and fuzzy rule base using fuzzy logic inference methods. In multi-input–single-output (MISO) fuzzy systems, in order to enhance the computational efficiency of fuzzy inference engine, this paper aims mainly to investigate three MISO fuzzy hierarchical inference engines employed fuzzy implications satisfying the law of importation with aggregation functions (LIA). We firstly find some aggregation functions for well-known fuzzy implications such that they satisfy LIA. The fuzzy implication satisfying LIA with respect to a given aggregation function is then characterized. Finally, three fuzzy hierarchical inference engines in MISO fuzzy systems are constructed according to aforementioned theoretical developments. Three examples are also provided to illustrate our theoretical arguments. [ABSTRACT FROM AUTHOR]

The current study deals with a reactivity-controlled compression ignition (RCCI) engine working with 1-pentanol as the LRF and JOBD as the HRF. The composition of the pilot fuel includes 20% Jatropha oil and 80% diesel, which nearly matches the heating value and cetane index of petroleum diesel. The research focuses on studying the impact of the pilot fuel injection angle on the engine characteristics at full load conditions, and the pilot fuel injection angle varies from 19, 21, 23, 25, to 27° bTDC at a constant injection pressure of 600 bar. The results revealed that increasing the pilot fuel injection angle increased the engine performance with a 13.36% rise in BTE, a reduction in CO emissions by 11.03%, and a decrease in HC emissions by 9.28% at a pilot fuel injection angle of 25° bTDC at 30% pentanol energy share (BD70P30). On the other hand, NOx emissions rise by 11.07%. The results indicate that the performance of the ternary fuelled RCCI engine can be improved by increasing the fuel injection angle of the pilot fuel. [ABSTRACT FROM AUTHOR]

Currently, the globe is experiencing a difficult energy-related situation. Although nanotechnology has the potential to significantly advance a wide range of disciplines, there are concerns about the potential risks of its products and applications. Thus, the present research proposed a newly developed bio-nano diesel emulsion fuel for energy conservation, pollution reduction and improved diesel engine efficiency. The biodegradable carbon quantum dots (CQDs) were produced via a hydrothermal technique using waste sweet lime peel and were subsequently well characterized in terms of morphology. Water and carbon quantum dots were added to the biodiesel blends at increasing 25, 50, and 75 ppm concentrations. Using the Taguchi Technique, DOE-recommended tests have been carried out systematically. The engine load, compression ratio, engine speed, water, and CQD were considered input parameters for optimizing BP, BSFC, BTE, NOx, CO, HC, and smoke emissions of a biodiesel blend engine. The model recommended an optimal solution that fulfilled the indicated optimum input parameters of 42% engine load, 18 compression ratio, 1800 rpm engine speed, 10% water, and 75 ppm CQD using the desirability method. The optimum performance and emission characteristics (BP, BSFC, BTE, NOx, HC, CO, and smoke) are found to be 2.48 kW, 294 g/kWh, 30.36%, 317 ppm, 0.81 ppm, 0.0011%, and 5.27 HSU, respectively. The tested inaccuracy of optimum blend interactions for BP, BSFC, BTE, NOx, HC, CO, and smoke was determined to be 9.25%, 1.38%, 2.08%, 6.30%, 5.63%, 7.69%, and 0.75%, respectively, within acceptable limits. [ABSTRACT FROM AUTHOR]

The aim of this research is to study the double-nosing process in a tube. First, the single-nosing process was simulated and then experimentally tested. After validation of the simulation results, the double-nosing process was simulated. The main purpose of simulation is to shape the integrated production of the shell of a special engine through a double-nosing process. The process was simulated in cold conditions. The effects of friction coefficient, creating an obstacle at the end of the lower die, and creating a profile at the end of the tube on the final formed product and the die stresses were investigated. The results show that there is good agreement between experimental and simulation results. Reducing the friction coefficient reduces the middle buckling, and increasing the length of the profile from 50 to 100 mm increases the middle buckling and, as a result, reduces the length of the workpiece. Meanwhile, the effect of thermal profiles on the process has also been studied. A desirable product will be obtained after the noshing process by applying thermal profiles and mechanical properties at different temperatures. It takes about 110 tons of power to create this product. The maximum amount of plastic strain occurs at the top edge of the workpiece that undergoes the most deformation. The stresses created in the upper and lower dies are negligible, and the dies never enter the plastic phase. [ABSTRACT FROM AUTHOR]

IN order to improve the phenomenon of wall wetting caused by GDI engine injecting fuel directly into the cylinder. Based on the characteristics of small particle size, strong diffusivity and short penetration distance of the conical spray, a self-built laser ultra-high imaging system is used to validate the conical spray model in this study. The numerical and experimental results are found to be in good agreement by comparison. And numerical analysis of a four-stroke GDI engine with a conical injector under low engine speed was carried out to examine the effect of intake temperature on the mixture formation process and combustion events under different injection strategies. The results indicated that the mass of evaporation fuel was increased with the intake temperature increased from 273 to 300 and 330 K, and the peak pressure in the cylinder increased by about 19.6 and 45.7%. As the intake air temperature increases, the in-cylinder equivalence ratio distribution shows better uniformity. In addition, the maximum peak of the pressure in the cylinder is about 2 MPa larger than the minimum peak under different injection strategies. The different injection strategy from single to double and triple resulted in the earlier and higher in-cylinder pressure, resulting in more complete combustion and improved combustion. [ABSTRACT FROM AUTHOR]

Anime is quite well-received today, especially among the younger generations. As anime has recently garnered mainstream attention, we have insufficient information regarding users' penchant and watching habits. Therefore, it is an uphill task to build a recommendation engine for this relatively obscure entertainment medium. In this attempt, we have built a novel hybrid recommendation system that could act both as a recommendation system and as a means of exploring new anime genres and titles. We have analyzed the general trends in this field and the users' watching habits for coming up with our efficacious solution. Our solution employs deep autoencoders for the tasks of predicting ratings and generating embeddings. Following this, we formed clusters using the embeddings of the anime titles. These clusters form the search space for anime with similarities and are used to find anime similar to the ones liked and disliked by the user. This method, combined with the predicted ratings, forms the novel hybrid filter. In this article, we have demonstrated this idea and compared the performance of our implemented model with the existing state-of-the-art techniques. [ABSTRACT FROM AUTHOR]

The CPU-Accelerator heterogeneous systems have demonstrated performance and efficiency benefits on DBMSs. However, the CPU-Cache-DRAM architecture can not fully utilize the bandwidth of DRAMs such that in-memory approach get limited improvement. To overcome this drawback, it is non-trivial to customize efficient domain-specific accelerators and efficiently shuttle data between the host memory space and accelerator. But even if high-performance accelerators are available for DBMS, it is challenging to integrate the software with accelerator non-intrusively. To address these problems, we propose a hardware-software co-designed system, database offloading engine (DOE), which contains hardware accelerator architecture—Conflux for effective SQL operation offloading, and a software DOE programming platform—DP2 for application integration and seamless harness of the computing power. We subtly partition each well-known relational operator, such as filter, join, group by, aggregate, and sort, and dynamically map these operators on multiple kernels in parallel. The DOE kernels work in streaming processing mode, over which the microarchitecture aggressively exploits data parallelism and memory bandwidth. The experiment results show that DOE achieves more than 100x and 10x performance improvement compared with PostgreSQL and MonetDB respectively. [ABSTRACT FROM AUTHOR]

The periodic assessment of the revised capacity is essential and conventional techniques through bathymetric surveys and inflow-outflow techniques are time and resource intensive. The application of optical remote sensing data is practiced for a long time to compute the revised capacity of the reservoir but has the limitation of selecting threshold values and inefficacy of the method during the cloudy season. This research proposed the application of the Otsu segmentation technique in Google Earth Engine (GEE) to determine revised water spread using microwave remote sensing data. The Otsu technique is efficient in classifying the image into two distinct classes using within and between-class variances. An application has been developed using Sentinel data in GEE, which has the capacity of cloud-based computing and applied to the four reservoirs of Mahanadi Reservoir Project (MRP) namely Ravishankar Sagar, Murumsilli, Dudhawa, and Sondur reservoir in the Chhattisgarh state of India. The original capacities of these reservoirs vary from 910.51 MCM of Ravishankar (RS) Sagar to 165.89 MCM of Murumsilli reservoir. The revised water spreads computed in the GEE were further used to compute revised volume and in turn the revised cumulative capacities at different levels. The analysis suggested that 17.65% of dead storage (118.26 MCM from 143.00 MCM) and 9.25% of gross storage (85.26 MCM from 910.52 MCM) of RS Sagar has been lost in 42 years (1978 to 2020). Similarly, 10.33% gross capacity of Murumsilli, 13.12% of Sondur, and 12.37% of Dudhawa reservoirs have been lost due to the deposit of sediments from the catchments, and results were found comparable with bathymetric survey results of three reservoirs. The proposed application has been developed in GEE so it can be used in any part of the world in cloudy weather with no human interference. [ABSTRACT FROM AUTHOR]

Researchers are examining the possibilities for alternative fuel research as a fossil fuel replacement in light of global energy insecurity and other urgent challenges like global warming, severe emissions, and growing industrialization. This research uses 1-pentanol as a low reactivity fuel and Jatropha biodiesel as a high reactivity fuel to explore the reactivity-controlled compression ignition engine characteristics. A water-cooled single-cylinder engine is used in an experiment with varied loads of 25%, 50%, and 75% at a constant speed of 2000 rpm to examine the effects of operational parameters (i.e., (23 bTDC, 25 bTDC, and 27 bTDC) and (400 bar, 500 bar, and 600 bar)). The fuzzy-based Taguchi approach predicts operational parameters, including fuel injection time, fuel injection pressure, and engine load. Utilizing this ideal model, one may increase brake thermal efficiency and braking power while minimizing unburned hydrocarbon and nitrogen oxide emissions. An L20 orthogonal array is used to analyze the effects of various variables on an engine running on B20/1-pentanol fuel, including engine load, fuel injection timing, and fuel injection pressure. Multiple models are generated and verified with the use of experimental findings. Compared to other operating parameters, for reducing oxides of nitrogen, hydrocarbons, and brake-specific energy consumption maximally, engine load of 75%, FIP of 400 bar, and FIT of 23 bTDC are optimal based on the greatest MPCI value of 0.802. [ABSTRACT FROM AUTHOR]

The work shows the dependence of the moment of the discharge-activated zone ignition and the moment of self-ignition of the fuel mixture in the region ahead of the combustion wave front on two parameters: the crankshaft rotation angle at which the discharge was initiated and the specific energy input into the streamer channel. It is shown the necessity to take into account the change in pressure in the cylinder due to the movement of the piston in order to more accurately determine the optimal ignition limits of the activated zone and the occurrence of self-ignition. When modeling, the inhomogeneous formation of chemically active particles associated with the streamer and multi-pulse nature of the discharge was taken into account. [ABSTRACT FROM AUTHOR]

Recently, microbial oil has become one of the promising next-generation feedstocks for producing biodiesel. While microbial oil can be extracted from different sources, there is only limited work on microbial production from fruits and vegetables. In this work, biodiesel was extracted through a two-step process: microbial conversion of vegetable waste into microbial oil using Lipomyces starkeyi, followed by transesterification of microbial oil into biodiesel. The lipid accumulation, composition of microbial oil, and the fuel properties of biodiesel were evaluated. The microbial oil consisted mainly of C16:0, C18:0 and C18:1, which were close to the properties of palm oil. The fuel properties of biodiesel comply with the EN14214:2012 standard. Thus, the vegetable waste can be a good biodiesel feedstock. Three blends (MOB10, MOB20 and MOB30 with 10, 20, and 30% of biodiesel) were tested for engine performance and emission characteristics in a 3.5 kW VCR research engine. At full load, MOB20 reduced the pollutant emissions of CO and HC by 47.8% and 33.2% with the penalty of increased NOx by 3.9%, while BTE reduced by 0.8% with the increased BSFC by 5.2%. Thus, the addition of vegetable waste biodiesel blends reduced the emissions of CO and HC significantly with slight reduction of brake thermal efficiency. [ABSTRACT FROM AUTHOR]

This paper concerns fault detection filter design for switched Takagi–Sugeno (T–S) fuzzy systems against deception attacks. A fuzzy fault detection filter with attacked input signal is presented to detect system faults. Switched event-triggering schemes are adopted to efficiently utilize limited network communication bandwidth resources. Moreover, the filter adopts nonsynchronous premise variables with the system to handle communication delays caused by event-triggering schemes and network transmission. Then, the switched fuzzy residual systems are developed by utilizing a model transformation technique. Furthermore, by using piecewise Lyapunov functional method and persistent dwell time (PDT) technique, the resulting criterion provides sufficient conditions to ensure that switched fuzzy residual systems under deception attacks are mean-square exponentially (MSE) stable with an H ∞ performance. Accordingly, the conditions for the co-design of fuzzy filter and event-triggering schemes are given. Finally, the effectiveness of the design of the fault detection filter is verified by a numerical simulation and an air path of the TCSI engine simulation. [ABSTRACT FROM AUTHOR]

Heat reflow in the fan rotation center of a forced convection cooling system has a great influence on heat dissipation. In this research, a calculation model of the external flow field of an engine compartment's cooling module was established. Computational fluid dynamics method was used to calculate and analyze the heat flow characteristics of the existing radiator. By comparing the calculations with the experimental results, the regions and the reasons for the heat reflow were found. The existing heat dissipation scheme was recalculated by using the secondary heat dissipation model, and an optimized and improved scheme was proposed to introduce a deflector cone structure to eliminate heat reflow. This structure was connected to the fan hood by four blades. The front end of the structure acted as a diversion for the conical structure, and the back end was a hollow cylinder structure, making it easier for the fluid to transition to the conical structure. Both ends and the distance between the vertebrae were set to range from 2–5 mm. The research results showed that the secondary heat dissipation model could more accurately describe the heat reflow problem of the engine compartment, the heat flow organization of the improved structure was more reasonable, and the temperature distribution was more uniform. Moreover, the theoretical heat dissipation effect of the improved structure was more than 10 % higher than that of the existing structure. [ABSTRACT FROM AUTHOR]

The magnetic Otto thermal machine based on a two-spin-1/2 XYZ working fluid in the presence of an inhomogeneous magnetic field and antisymmetric Dzyaloshinskii–Moriya and symmetric Kaplan–Shekhtman–Entin-Wohlman–Aharony interactions is considered. Its possible modes of operation are found and classified. The efficiencies of engines at maximum power are estimated for various choices of model parameters. There are cases when these efficiencies exceed the Novikov value. New additional points of local minima of the total work are revealed, and the mechanism of their occurrence is analyzed. [ABSTRACT FROM AUTHOR]

In this study, the floating liner method is utilized to measure the friction generated in the piston assembly of a single-cylinder gasoline engine. The piston assembly is subjected to combustion pressure, lubricating friction, and asperity friction during engine operation and reciprocates within the cylinder. Therefore, the main goal of this study is to investigate the effect of engine combustion and lubricant conditions on piston friction. First, we analyze how the combustion pressure, obtained by changing the combustion load and the ignition timing, affects piston friction. Second, by adjusting engine speed and coolant/oil temperature, we analyze how each condition affects piston friction. Through the experiments for each case, it was confirmed that the friction increased as the combustion pressure increased under the same lubrication conditions. It was also confirmed that the piston friction was significantly measured due to the increase in lubrication friction as the engine speed increased. Finally, it was confirmed that as the temperature decreased, the oil viscosity increased, resulting in a large friction loss. [ABSTRACT FROM AUTHOR]

The current research work examines the usability of surfactant-free microemulsion fuels as a substitute in CI engines, with alcohol being used as an amphi-solvent. Studies were carried out on different compositions of microemulsions with 35% volume and 40% volume butanol, named ME35 and ME40, having 57.8–64.4% volume diesel and 0.6–2.2% volume water. Most of the microemulsions had properties such as viscosity, specific gravity, cloud point, and sulfur content comparable to those of diesel. The heating values and cetane indices of the microemulsions were 0.09–8.7% and 19.4–28.7% lower than diesel due to the addition of water and alcohol. The water and sediments percentages were found to be low, even after the addition of water, indicating the microemulsions were stable. ME40 showed an average of 0.6–3.5% improvement in BTE, but the BSFC was also increased by 5.3–8.9%. The emissions of HC, NOx, and PM showed an average decrease of 19.0–48.9%, 14.8–41.9%, and 10.06–50.24%, respectively, for all the microemulsions at all the loads. The CO emissions were lower at higher loads and vice versa, but the average CO emissions showed 5.16–31.9% decrease due to significant reductions at higher loads. It could, therefore, be concluded that microemulsions are a promising sustainable and cleaner substitute for diesel. Synopsis Microemulsion fuels successfully replaced up to 42% of diesel, with significant reduction in emissions of CO, HC, NOx, and PM. [ABSTRACT FROM AUTHOR]

This work focuses on the numerical and experimental analysis of turbocharger selection and boost pressure effects on a CNG-fueled spark-ignition engine. Because of this, investigations are carried out on the influence of downsized compression ratio of 10.5:1 at different boost pressures and compared with a naturally aspirated compression ratio of 12.5:1. In order to perform the experimentation, a twin-cylinder, port fuel-injected, CNG engine with 15.5 kW at 3400 rpm is modified to utilize compressed bio-methane as fuel under 100% throttle condition. A simulation is performed to study the compressor impeller for T1 and T2 turbochargers using the ANSYS turbomachinery tool. Results indicate that the circumferential velocity of T1 is higher than of T2 at all boost pressures. Subsequently, experimentation is performed using T1 and T2 at three different boost pressure levels in a compression ratio of 10.5:1 at 1.1, 1.3, and 1.5 bar. T2 developed a maximum boost pressure of 1.1 bar compared to T1. T1 is chosen for further experimentations. At 1.3 bar of boost pressure, a rise in brake power was recorded by 19.3% compared to 12.5:1 under the naturally aspirated mode. Consequently, there is a reduction in fuel consumption by 10.1%, and hydrocarbon, carbon monoxide, and carbon dioxide emission levels reduce by 25%, 8.2%, and 4.9%, respectively. Therefore, turbocharging at a lower compression ratio exhibits better performance and reduces emissions compared to a higher compression ratio under naturally aspirated mode. [ABSTRACT FROM AUTHOR]