High-speed Diesel Research Articles

Analysis and countermeasures of early delamination of the nitrided tappet insterts in the valve train of a high speed and heavy load diesel engine

Early delamination of the nitrided tappet inserts in the valve train of a high speed and heavy duty diesel engine occurred and thus the failure mechanism of early delamination was investigated with the method of numerical simulation and experiment at first. Additionally, the countermeasure was put forward and identified using a valve train bench test rig. Flying off of the tappet in valve train took place, causing repeated impact forces between the interfaces of the tappet and cam. Early delamination of the compound layer (CL) was formed once the surface crack connected with the subsurface crack. Removal of the CL of the nitrided tappet inserts was verified as an effective countermeasure for avoiding the early delamination as well as protecting the matching part, which suggests the hard and brittle CL of the nitrided part should be removed under a heavy load condition especially accompanying with repeated impact forces.

An experimental study on the air pollutant emission characteristics of high-speed diesel engine for small coastal ships according to the application of the LP EGR and DOC-DPF systems

An experimental study on the air pollutant emission characteristics of high-speed diesel engine for small coastal ships according to the application of the LP EGR and DOC-DPF systems

Marine diesel exhaust manifold failure and life prediction under high-temperature vibration

The working environment of the diesel exhaust manifold is harsh. On one hand, exhaust gas with high temperature continues to flush on the inner wall of the manifold, and on the other hand, the manifold is also affected by some complex factors, such as diesel engine vibration. If the design is unreasonable, air leakage, cracking, and other failure phenomena are easy to appear. In this article, aiming at the aforementioned problems in the exhaust manifold design process, a high-speed diesel exhaust manifold is taken as an example and analyzed by computational fluid dynamics and finite element method technology. The temperature field distribution of the exhaust manifold is simulated by the fluid–structure interaction method, and then the thermal stress distribution is simulated based on the temperature field of the exhaust manifold. According to the thermal stress of the exhaust manifold and the vibration stress in three directions (axial, transverse, and vertical), combined with the time domain acceleration signals, the high-cycle fatigue life of the exhaust manifold is obtained. The exhaust manifold structure is optimized based on the minimum high-cycle fatigue life position. Then, the high-cycle fatigue life analysis of the optimized structure shows that the optimized structure can significantly improve the life of the exhaust manifold. Then, the optimized structure is further analyzed for low-cycle fatigue life to check whether it meets the requirements of low-cycle fatigue life. After simulation, it can be known that the low-cycle fatigue life meets the design requirements. Finally, sensitivity analysis of the fatigue life under different loading conditions (thermal load and vibration intensity) shows that the thermal load has a significant influence on the fatigue life, so the thermal load should be paid attention to in the design process.

Prediction of In-Cylinder Pressure of Diesel Engine Based on Extreme Gradient Boosting and Sparrow Search Algorithm

In-cylinder pressure is one of the most important references in the process of diesel engine performance optimization. In order to acquire effective in-cylinder pressure value, many physical tests are required. The cost of physical testing is high; various uncertain factors will bring errors to test results, and the time of an engine test is so long that the test results cannot meet the real-time requirement. Therefore, it is necessary to develop technology with high accuracy and a fast response to predict the in-cylinder pressure of diesel engines. In this paper, the in-cylinder pressure values of a high-speed diesel engine under different conditions are used to train the extreme gradient boosting model, and the sparrow search algorithm—which belongs to the swarm intelligence optimization algorithm—is introduced to optimize the hyper parameters of the model. The research results show that the extreme gradient boosting model combined with the sparrow search algorithm can predict the in-cylinder pressure under each verification condition with high accuracy, and the proportion of the samples which prediction error is less than 10% in the validation set is 94%. In the process of model optimization, it is found that compared with the grid search method, the sparrow search algorithm has stronger hyper parameter optimization ability, which reduces the mean square error of the prediction model by 27.99%.

Evaluation of an Additional Generator on the Economic Effect Based on a Load Sharing Optimization of Medium-Speed/High-Speed Diesel Generators in a Microgrid

This study investigates the additional installation of a high-speed diesel generator to independent microgrids (MG) such as remote islands where relatively efficient medium-speed diesel generators (DGs) are mainly used. While small-sized and lightweight, high-speed DGs are not widely spread for continuous usage because their efficiency is lower than that of the medium-speed DGs. The objective of this study is to evaluate the performance of the new method of load sharing optimization to improve the economy by interconnecting a high-speed DG to an independent MG where the medium-speed DGs are operated. The study investigates the effect of operation cost reduction by installing the new load sharing method of operation following the load sharing pattern derived by the mixed-integer programming. As a result of this study, there was some effect to installing a high-speed DG operated by the conventional method. In addition, by adding the new method of load sharing with optimization, the economic effect became even higher.

Prediction of Network Traffic in Wireless Mesh Networks Using Hybrid Deep Learning Model

Wireless mesh networks are getting adopted in the domain of network communication. Their main benefits include adaptability, configuration, and flexibility, with added efficiency in cost and transmission time. Traffic prediction refers to forecasting the traffic volumes in a network. The traffic volume includes incoming requests and outgoing data transmitted by the network nodes. The previous logs of traffic in the network are used for extracting patterns that help for accurate predictions. In this paper, an analysis of various existing traffic prediction methods is done. Specifically, the analysis of a case study where the performance of the High-Speed Diesel (HSD) pump is predicted by observing its output. A network of sensors form a less mesh network; sensors act as nodes while reading the parameters, namely, three-phase Current, Voltage, Temperature, and Vibration. In this case study, a High-Speed Diesel pumps’ performance is predicted by predicting the vibration parameter as the output parameter. Other parameters affecting the performance of the High-Speed Diesel pump which are causing the change in vibration value are identified. Various algorithms, including Statistical Auto-Regressive Integration and Moving Average, Poisson’s regression, and a few Machine Learning and Deep Learning algorithms like Decision Tree Regressor, Multi-Layer Perceptron, Linear Regression, and Long Short-Term Memory are implemented and evaluated for this purpose. Along with the comparison, a novel architecture using Convolution Neural Network and Long Short-Term Memory is described in this paper. The result and comparison between these give the clear understanding that the suggested novel Convo-LSTM model gives better performance and helps to predict the performance of the High-Speed Diesel pump. The proposed system makes a strong case for the network traffic prediction, where the use of historical data is collected over the wireless mesh network. A similar analogy can be used where this model could be implemented further for network monitoring tasks.

Effect of Piston Bowl Geometry on Performances of a High Speed Diesel Engine

As one of the primary performances of the diesel engine, the special power can be promoted by increasing the speed or the indicated mean effective pressure. However, the diesel engine will not have enough time for fuel-air mixing and combustion under higher speed, so the excellent matching of injection-bowl is the main way to improve mixing and accelerate combustion. In order to achieve the rapid combustion of a high-speed diesel engine, the effects of piston bowl geometry, diameter-depth ratio, and nozzle arrangement on combustion and performance are calculated by using CFD numerical simulation. The results show that the mixing quality can be improved, the combustion duration can be shortened, and higher combustion efficiency and higher power can be obtained by using a double-layer diverging combustion chamber with a shallow basin structure in the upper and lower layers. With the increase of the diameter-depth ratio of the two-layer diverging combustion chamber, the maximum explosion pressure, the peak heat release rate and the turbulent kinetic energy increase, and the power rise is continuously improved. A new double-layer diverging combustion system matched with a double-layer stagger nozzle based on double-layer diverging combustion chamber the is proposed, the mixing in the cylinder is uniform, the combustion is accelerated and close to complete combustion, and the special power is 61.39kW/L.

Bubble Identification in the Emerging Economy Fuel Price Series: Evidence from Generalized Sup Augmented Dickey–Fuller Test

In the recent past, the world in general and Pakistan in particular faced a drastic fuel price change, affecting the economic productivity of the country. This has drawn the attention of empirical researchers to analyze the abrupt change in fuel prices. This study takes a lead and investigates for the first time, in the literature related to Pakistan, the presence of multiple fuel price bubbles, with the purpose of knowing if the price driver is due to demand or it is exuberant consumer behavior that prevails and contributes to a sudden boom in fuel price series. The empirical analysis is performed through a recently proposed state-of-the-art generalized sup ADF (GSADF) approach on six commonly used fuel price series, namely, LDO (light diesel oil), HSD (high-speed diesel), petrol, natural gas, kerosene, and MS (motor spirit). The bubble analysis for each of the six fuel price series is based on monthly data from July 2005 to August 2020. The findings provide evidence of the existence of multiple bubbles in all series considered. Specifically, four bubbles are detected in each of the kerosene and natural gas price series, whereas three bubbles are noted in each of the HSD, LDO, petrol and MS price series. The maximum duration of occurrence of bubbles is of 12 months for kerosene. The date-stamping of the bubbles shows that the financial crisis of 2008 contributed to the emergence of bubbles that pushed oil prices upward and caused a depreciation in the national currency.

Influence of iron oxide nanoparticles with different injection pressures using lotus seed methyl ester biodiesel: an experimental investigation

ABSTRACT The present research work explores the utilization of lotus seed methyl ester in a Common rail direct injection diesel engine. It evaluates the performance, combustion aspects, emission features at different injection pressures 210 bar to 240 bar intervals of 10 bar, along with 120 ppm of iron oxide nanoparticle. For this investigation, the B20 blend used as fuel contains 80% diesel and 20% biodiesel (Lotus seed Methyl Ester). The iron oxide nanoparticles were mixed with the fuel using a mechanical homogenizer and ultrasonication. The present work results revealed a reduction in FC by 12.5%, decreased CO by 50%, a decrease in HC by 16.88%, and the reduction of smoke density by 16.51% compared to that of baseline fuel maximum load (5.2 kW). The combined effect of 240 bar injection pressure and 120 ppm of iron oxide nanoparticle gives the best result. Abbreviation: MS; Motor Sprit (Petrol): HSD; High Speed Diesel: AFT; Transportation fuels: ICRA; Investment Information and Credit Rating Agency of India Limited: IONP; Iron Oxide Nano Particles: SFC; Specific Fuel Consumption: LSME; Lotus Seed Methyl Ester: MT; Metric Ton: BTE; Brake Thermal Efficiency: HC; Hydrocarbon: CO; Carbon monoxide: NOx; Nitrogen Oxides: HRR; Rate of Heat Release: BP; Brake Power

Improving the performance of cast iron bushings of small-sized marine diesel engines

An increase in the performance and wear resistance, a decrease in the running-in time of piston internal combustion engines of high-speed marine small-sized diesel engines by applying boron-containing coating and copper coating to the cylinder surface are considered. An processing unit was designed for applying pastes when boriding the working surface of the sleeve with laser heating. Keywords: friction pair, internal combustion engine cylinder, piston sleeve, wear resistance, performance, surface roughness, running-in. nurik909@mail.ru

Impact of high-speed diesel drop trains: Pursuing cleaner diesel engines

This paper is associated with a video winner of a 2020 American Physical Society's Division of Fluid Dynamics (DFD) Milton van Dyke Award for work presented at the DFD Gallery of Fluid Motion. The original video is available online at the Gallery of Fluid Motion, https://doi.org/10.1103/APS.DFD.2020.GFM.V0052.

Emission performance of major ship classes: An estimation based on a new set of emission factors and realistic activity profile data

The maritime sector significantly contributes on the major environmental problems that humanity is being confronted with their consequences. The Greenhouse Gases (GHGs) emitted from the sector, which are responsible for the global phenomenon of climate change, are estimated in 2,89% of total anthropogenic GHGs. Ships are also an important source of local air-quality degradation in coastal areas by emitting major quantities of pollutants such as Nitrogen Oxides (NOx), Sulphur Oxides (SOx) and Particulate Matter (PM). The overall emitted quantities of the sector seem not to be equally allocated to the major ship classes (containers, dry and liquid bulk carriers, cruise ships, ro-ro ships etc.), even though the engine technologies that are being used in these classes are approximately the same (slow speed, medium speed, high speed diesel engines). A factor of differentiation among the ship types is the activity profile. Depending on the ship type, engines (main, auxiliary, boilers) present different power needs and therefore are being operated at different load points which among others are related with the sailing profile (cruising, maneuvering, hoteling), the cargo type and weight conditions (laden, ballast). In this context the target of the present paper is to evaluate the emission performance of the major ship classes. This evaluation is performed by using a new set of engine load-dependent Emission Factors for ships, which have been derived by a statistical analysis of emission rates found in literature, in combination with average activity profiles per ship type as these are found in dedicated shipping inventory databases and in literature. These activity data concern a global scale of consideration. Results aim to highlight the differences and similarities in the emission performance of ship types, enhancing the understanding of policy makers and ship operators, on the principle of tackling pollutants especially at ports, close to cities.

Comparison between PEE10 and PEE10-Bioethanol Blends on Performance and Emission Characteristics of a HSDI Diesel Engine

Biofuels are an alternative fuel currently being developed to reduce the diesel-engine environmental impact. The release of carbon dioxide (CO2), nitric oxide (NO) and black smoke (BS) becomes an issue derived from diesel engines even in lean-mixture combustion causing an adverse effect to human health. The main aim of the research study is to present the use of biofuels, a mixture of diesel and 10 % palm oil ethyl ester (PEE10) and PEE10 blended with bioethanol from 5 to 20 %, compared with conventional diesel fuel. The biofuels were run on a high-speed direct injection diesel engine at a constant speed of 3,000 rpm under various loads. The use of PEE10 resulted in brake thermal efficiency (BTE) reduction by 2 % and brake specific fuel consumption (BSFC) incrementation by 8 %, but the exhaust emissions were lower than diesel, except for CO2 and NO. However, PEE10 engine performance was better and exhaust gas emissions were lower for both pollutants than diesel mixed with 10 % bioethanol. The investigation of PEE10 with increasing bioethanol revealed that the use of PEE10 blended with 5 % bioethanol (PEE10E5) can improve engine performance, while the BTE and BSFC were close to that of diesel, and exhaust emissions, especially CO2, NO and BS reduced. Moreover, BTE from PEE10E5 fueling increased by 2 % but BSFC was subtle increased, compared to PEE10. On the other hand, the increasing bioethanol from 10 to 20 % in PEE10 led to the more reduction in engine performance, but the engine pollutants were also continuously decreased. Specifically, the blend of PEE10 and 20 % bioethanol indicates that CO2, NO and BS were reduced by 10, 15 and 33 %, respectively, compared to diesel fuel.
 HIGHLIGHTS
 
 A mixture of diesel and 10 % palm oil ethyl ester (PEE10) has less exhaust emissions than diesel blended with 10 % palm oil methyl ester (PME10)
 PEE10 blended with 5 % bioethanol can improve engine performance, while the brake thermal efficiency and brake specific fuel consumption are close to that of diesel and PME10
 The increasing bioethanol from 10 to 20 % in PEE10 leads to the more reduction in engine performance, but the engine pollutants, especially carbon dioxide, nitric oxide and black smoke, are also continuously decreased
 
 GRAPHICAL ABSTRACT

SIMULATION OF THE MIXING PROCESS OF DIESEL AND BIOFUELS

The viscosity of a fuel depends on its hydrocarbon composition. Vegetable oil is considered an alternative to diesel fuel. Its high viscosity makes it difficult to consider as a commercial diesel fuel. Vegetable oil is lipids, fatty acid esters. They have a high calorific value and contain straight hydrocarbon chains, resulting in their relatively high cetane number. Viscosity and density determine the evaporation and mixing process in an engine, as they affect the shape and type of the fuel flame, the size of the droplets formed, and how they enter the combustion chamber. Low density and viscosity provide better fuel injection; with an increase in the diameter of the droplet, its complete combustion decreases, therefore, the specific fuel consumption increases and the smoke of the exhaust gases increases. The viscosity of the fuel affects the pump flow and fuel leakage through the piston pair clearance. As the viscosity decreases, the amount of diesel fuel leaks between the plunger and bushing increases, resulting in a decrease in pump flow. Converting the engine to a fuel with a lower density and viscosity will result in burnout of the piston head, so the fuel equipment needs to be adjusted. Plunger wear is viscosity dependent. It fuel is in the range of 1.8-7.0 mm2/s, which practically does not affect the durability of modern high-speed diesel equipment. Consider using vegetable rapeseed oil as an alternative to diesel fuel. Its viscosity can be reduced by chemically converting esterification to ethyl esters. When the cheese rapeseed oil is heated to 80 °C, it will give a viscosity value similar to that of commercial diesel. The mixing system will have an operating power equivalent to that of a diesel engine when heated to 40-50 °C.

The synthesis of a high-quality biodiesel product derived from Krabok (Irvingia Malayana) seed oil as a new raw material of Thailand

The production of high-quality biodiesel product from Krabok (Irvingia Malayana) seed oil, new high efficiency, and high potential raw material, was studied using liquid biofuel energy in Thailand. The seed flesh of Krabok was extracted with hexane as a solvent by several techniques to compare the efficiency of each extraction method. The optimal technique for extracting the oil from the Krabok seed flesh was the Soxhlet extraction method which could extract oil content up to 63.58 wt%. The major fatty acid compositions of the obtained Krabok seed flesh oil were lauric acid (C12:0) and myristic acid (C14:0) as around 52 and 35 wt%, respectively. Additionally, the results also found that the extracted Krabok seed flesh oil was obtained greater than 95 wt% of the saturated fatty acid compound. The synthesis of a high-quality biodiesel product from Krabok seed flesh oil was performed via a one-step transesterification process catalyzed by a CaO catalyst. The obtained Krabok seed flesh oil biodiesel product was within both the ASTM-D6751 and EN-14214 standards for liquid bio-auto fuels, and it has properties that were very close to high-speed petroleum diesel oil. Consequently, the Krabok seed flesh oil was one of the exciting sources of raw materials in terms of high efficiency, quality, and potentiality in the production of biodiesel products.

Exergy based evaluation of power plants for sustainability and economic performance identification

Enhanced sustainability and efficiency are among the prime indicators to achieve in the power generation sector of any country. The decline in efficiency might be caused by improper utilization of fuels and increasing entropy in outdated generation units. Reduced efficiency in power generation is particularly detrimental for the sustainability in developing countries, as resources are limited and need to be carefully allocated and maintained. Exergy analysis based on the laws of thermodynamics are currently gaining traction among researchers to study the overall performances of power generation units. Taking Bangladesh as a case study, this work investigates the power generation data for the country since 2009 till 2019 to study the internal energy losses of natural gas, oil, high-speed diesel, coal, and hydro based plants and provides a baseline for investment policy formulation. Our study found that, due to lack of maintenance and proper planning during the initial phases, the overall energy efficiencies among these sectors are relatively low, staying in the range of 34.55%–36.1% while the exergy efficiencies are 35.07%–36.59%. Corresponding exergetic parameters as depletion number, exergy sustainability index, relative irreversibility, lack of production, cumulative exergy loss, waste exergy ratio, and environmental effect factor pointed to similar findings in terms of sustainability as well. Comparing these parameters, it is observed that hydroelectric plants are more sustainable and efficient compared to fossil fuel-based generation units. Cost estimation of fuels and financial losses in the power generation sector are also explored for a better understanding of the return on investment.

Research on coordination design method of main bearing assembly structure based on the maximum radial deformation of bearing bush

Aiming at the difficulty of control and evaluation of main bearing deformation in the coordination design of the main bearing assembly structure for a high-speed diesel engine, taking MRD (the MRD means the maximum radial deformation of the bearing bush) of the bearing bush as an index to evaluate the out-of-round deformation of the bearing bush was proposed in this paper. The numerical calculation method of the MRD was given and the correctness of the method was experimentally verified. And the influence rules of different design parameters on the MRD were analyzed. On this basis, the coordination multi-objective optimization research of the main bearing assembly structure was carried out, and the optimization results were analyzed based on the influence rules of different design parameters on the reliability indexes. The results show that, when the pre-tightening force of the vertical bolt and the bearing bush interference are 240 kN and 0.17 mm respectively, the MRD reaches the minimum value. If the two values continue to increase, redundant loads can be generated, leading to the increase of the MRD. After optimization, the engine block strength coordination and bearing cap strength coordination had increased by 2.47% and 10.48%, respectively, and the deformation coordination and contact coordination had increased by 46.15% and 14.84%, respectively.

A study of smart thermal insulation coating on improving thermal efficiency in a marine two-stroke low-speed diesel engine

An advanced heat insulation coat, named Smart Thermal Coating (Smart TIC), was investigated in a marine low-speed two-stroke engine. Different with the conventional adiabatic engines that feature constant high temperature on combustion walls and low volumetric efficiency, the Smart TIC using low-heat-conductivity and low-heat-capacity materials can produce ''Temperature Swing'' (Temperature fluctuation) on the combustion chamber walls, reducing the heat transfer loss while increasing the volumetric efficiency and fuel efficiency. The performance of the Smart TIC with various thicknesses and thermophysical properties were evaluated through numerical simulations based on the ANSYS Software and CFD-code CONVERGE. The results show that the thinner Smart TIC can significantly increase the volumetric efficiency and thermal efficiency of the engine. The Smart TIC with the thermal conductivity of 0.1 W/((m*K)), the heat capacity of 20 J/(kg*K) and the thicknesses of 0.1 mm can increase the indicated thermal efficiency by up to 3.55% of the engine with little increases of NOx emissions. Furthermore, according to exergy analysis of exhaust gas, the engine with Smart TIC can improve exhaust energy available, which could improve fuel efficiency by waste heat recovery of engine. In addition, the potential of applying Smart TIC in a high-speed diesel engine was investigated in the last part, the results show the Smart TIC also can effectively improve the thermal efficiency of high-speed four-stroke engine. These results are believed to valuable reference for engine researchers and developers to further improve thermal efficiency of engine

Experimental Analysis of Engine Performance and Exhaust Pollutant on a Single-Cylinder Diesel Engine Operated Using Moringa Oleifera Biodiesel

In this investigation, biodiesel was produced from Moringa oleifera oil through a transesterification process at operating conditions including a reaction temperature of 60 °C, catalyst concentration of 1% wt., reaction time of 2 h, stirring speed of 1000 rpm and methanol to oil ratio of 8.50:1. Biodiesel blends, B10 and B20, were tested in a compression ignition engine, and the performance and emission characteristics were analyzed and compared with high-speed diesel. The engine was operated at full load conditions with engine speeds varying from 1000 rpm to 2400 rpm. All the performance and exhaust pollutants results were collected and analyzed. It was found that MOB10 produced lower BP (7.44%), BSFC (7.51%), and CO2 (7.7%). The MOB10 also reduced smoke opacity (24%) and HC (10.27%). Compared to diesel, MOB10 also increased CO (2.5%) and NOx (9%) emissions.

Development of empirical correlations for density and viscosity estimation of ternary biodiesel blends

This study aims to investigate the density and viscosity of ternary biodiesel blends. Fuel density and viscosity play an important role in the fuel injection system, flame propagation, and combustion process in compression ignition engine. The density and viscosity of biodiesel are higher than high-speed diesel which is an implication in the commercialization of biodiesel. In the present study, palm oil has been used for the production of biodiesel through the ultrasound-assisted transesterification process. Three different types of fuel additives including butanol, dimethyl carbonate, and plastic oil have been used for the preparation of nine ternary biodiesel blends. The density and viscosity of individual fuels and ternary biodiesel were measured experimentally in a temperature range of 281.51 K–348.15 K. For the prediction of density and viscosity of ternary biodiesel blends, four density and viscosity models were developed. The prediction accuracy of these developed models was assessed by a statistical tool absolute percentage error (APE). Newly proposed exponential regression models predicted well compared to experimental data for density and viscosity values with high regression coefficient 0.9995 and 0.9841 and lower mean absolute percentage of error 0.012 % and – 0.516 % at (348.15 K) temperature respectively. These correlations are significant for the automobile industry in developing fuel pipeline and transport equipment where additives would be present in diesel-biodiesel fuel blends.