Engine Compressor Research Articles

Compressed Air Vehicle

ct - This paper presents an experimental study of an engine driven by compressed air. The compressed air engine is a modified 100 cc internal combustion engine. The engine is modified from a 4-working stroke to a 2- working stroke engine (power and exhaust) by modification of cam-gear system. A temperature decrease from room temperature to 15 °C was observed at exhaust. The project was successfully manufactured and tested. Experimental analysis were carried out on this modified engine to find out its performance characteristics like brake power, indicated power, torque etc. It should be noted that pressure higher than that currently employed can result in increased engine performance in terms of output power, torque and speed. Nevertheless, the main advantage of this engine is that no hydrocarbon fuel is required that means no combustion process is taking place, thus the compressed air vehicle will play important role in reducing air pollution. Another benefit is that it uses air as fuel which is available abundantly in atmosphere. This study presents the atmospheric air which can be used in vehicles as the main or auxiliary source of power system. Key Words: Compressed air, Alternative Sources of Energy, clean & highly efficient, light weight, Non-polluting.

Metamodeling of turbofan engine compressor characteristics using SVM-based improved Kriging method

Purpose The purpose of this paper is to overcome the inherent lack of precision in commonly used interpolation procedures when solving the mathematical model of turbofan engines, as well as to address the issue that the theoretical variogram model in traditional Kriging models is prone to subjective selection bias, which makes it impossible to accurately capture the inherent fluctuation patterns in compressor data. Design/methodology/approach To mitigate this challenge, based on the spatial distribution characteristics of the compressor characteristic data of a certain type of turbofan engine, the input and output dimensions of the model are defined. By determining the stable operating region from the original component data, the authors use the proposed Kriging method improved with a support vector machine model to reconstruct the characteristics at unknown speeds within this region. The effectiveness of the proposed method is evaluated using the established assessment metrics. Findings Experimental results demonstrate that the proposed method exhibits significant advantages over the conventional Kriging approach. Specifically, it leads to a substantial reduction in root mean square error and mean absolute error by 0.0153/0.0118 (low speed), 0.1306/0.0362 (medium speed) and −0.0066/0.2366 (high speed). Originality/value This refined approach not only offers notable engineering applicability but also contributes significantly to the enhancement of aerospace engine model solutions’ precision.

A multi-layer Kriging surrogate model for the reliability analysis of variable stator vanes in aero engines

Abstract The variable stator vanes (VSV) are a set of typical spatial linkage mechanisms widely used in the variable cycle engine compressor. Various factors influence the angle adjustment precision of the VSV, leading to the failure of the mechanism. The reliability analysis of VSV is a complex task due to the involvement of multiple components, high dimensionality input and computational inefficiency. Considering the hierarchical characteristics of VSV structure, we propose a novel multi-layer Kriging surrogate (MLKG) for the reliability analysis of VSV. The MLKG combines multiple Kriging surrogate models arranged in a hierarchical structure. By breaking the problem down into more minor problems, MLKG works by presenting each small problem as a Kriging model and reducing the input dimension of the sub-layer Kriging model. In this way, the MLKG can capture the complex interactions between the inputs and outputs of the problem while maintaining a high degree of accuracy and efficiency. This study proves the error propagation process of MLKG. To evaluate MLKG’s accuracy, we test it on two typical high-dimensional non-linearity functions (Rosenbrock and Michalewicz function). We compared MLKG with some contemporary KG surrogate modeling techniques using mean squared error (MSE) and R square ( ${R^2}$ ). Results show that MLKG achieves an excellent level of accuracy for reliability analysis in high-dimensional problems with a small number of sample points.

Methane emission reduction through hydrogen blending in a large bore 2-stroke lean-burn natural gas compressor engine

Impending and increasingly stringent emissions regulations regarding natural gas compressor engines drive the research behind blending hydrogen with natural gas to make these internal combustion engines and their combustion process more efficient. This investigation seeks to answer two fundamental questions: will blending hydrogen with natural gas reduce overall engine fuel consumption, and can greenhouse gas emissions be reduced by blending hydrogen with natural gas? A 4-cylinder Cooper–Bessemer GMV engine, housed at Colorado State University’s Powerhouse facility, was investigated for hydrogen–natural gas blending using multiple engine configurations. A lean-burn engine uses an active pre-combustion chamber as its ignition source, along with electronically activated high pressure fuel injection in the main combustion chamber. One configuration tested utilized high-pressure fuel injection and blending in hydrogen, up to 40% by volume, in both the main chamber and pre-combustion chamber fuel supplies. A second configuration, where the main combustion chamber fuel was solely natural gas and only the pre-combustion chamber received hydrogen-blended natural gas, was also tested. The final configuration to be tested used low pressure fuel injection with mechanically actuated valves in the main chamber with a traditional spark plug ignition source. All engine configurations saw reductions in methane emissions of up to 30% using blended natural gas and hydrogen. Carbon dioxide emissions were also shown to be reduced for the two configurations. A reduction in brake-specific fuel consumption of up to 2% was also seen for two configurations. These results support the hypothesis that blending hydrogen into natural gas can reduce engine total fuel consumption and reduce greenhouse gas emissions.

Applications of machine learning techniques to broaden operating envelope of biodiesel-fueled HCCI engines

A significant shortcoming of Homogeneous charge compression ignition (HCCI) engines is their narrow operating envelope, particularly with high-reactivity fuels like biodiesel. Additionally, the compositional variability of biodiesels, reflected in cetane number variations based on different source feedstocks, poses another challenge. While various strategies have successfully extended the maximum load limit in diesel-HCCI engines, they have not been adequately explored in biodiesel-fueled HCCI engines. This study is the first to comprehensively investigate the interplay of biodiesel composition, cetane number, engine compression ratio, and charge dilution strategy for extending the operating envelope of a light-duty HCCI engine. Given the impracticality of controlling multiple variables experimentally, this work focuses on the potential of machine learning (ML) algorithms to predict the operational limits of an HCCI engine using neat biodiesels derived from diverse sources. Among the ML models explored, artificial neural networks were the most accurate in predicting the minimum stable load, with prediction errors of 3.5% (calibration) and 3.9% (validation). Support vector machine models predicted the maximum load (with and without dilution) with errors below 5%. Notably, biodiesel produced from a blend of linseed, karanja, coconut, and mustard oils in specific proportions (42%, 3%, 25%, and 30% mass, respectively) yielded a wide HCCI operating range from 0.4 to 3.25 bar (without dilution) and up to 3.67 bar BMEP with charge dilution. This study highlights the novelty and practicality of using ML to predict and extend the operating envelope for biodiesel-fueled HCCI engines, demonstrating their suitability for future applications.

Comparison and mathematical modeling of surge avoidance methods in turbojet engine compressor

Comparison and mathematical modeling of surge avoidance methods in turbojet engine compressor

Performance and emissions of a CI engine using a diesel, jatropha biodiesel and biodiesel adopting Al2O3 nanomaterial as fuel blend.

A nanocomposites of aluminum dioxide was employed as a fuel additive in a compression engine test. Nanoparticle stability in diesel was measured by their impact on the fuel's flash point, density, and viscosity. When compared to other forms of fuel, conventional biodiesel has superior qualities. Al2O3 was also put through its paces in terms performance of engine and pollution testing. The thermal efficiency of the engine's brakes may be improved by adding nanoparticles in to the jatropha biodiesel. Using Al2O3 nanoparticles has been shown to reduce brake-specific fuel consumption by 23%. In addition, this solution can cut hydrocarbon emissions by 19%.

Research on Dimension Reduction Method for Combustion Chamber Structure Parameters of Wankel Engine Based on Active Subspace

The combustion chamber structure of a rotary engine involves a combination of interacting parameters that are simultaneously constrained by engine size, compression ratio, machining, and strength. It is more difficult to study the weight of the effect of the combustion chamber structure on the engine performance using traditional linear methods, and it is not possible to find the combination of structural parameters that has the greatest effect on the engine performance under the constraints. This makes it impossible to optimize the combustion chamber structure of a rotary engine by focusing on important structural parameters; it can only be optimized based on all structural parameters. In order to solve the above problems, this paper proposes a method of dimensionality reduction for the structural parameters of a combustion chamber based on active subspace and combining a probability box and the EDF (Empirical Distribution Function). This method uses engine performance indexes such as explosion pressure, maximum cylinder temperature, and indicated average effective pressure as the influence proportion analysis targets and quantitatively analyzes the influence proportion of combustion chamber structure parameters on engine performance. Eight main structural parameters with an influence of more than 85% on the engine performance indexes were obtained, on the basis of which three important structural parameters with an influence of more than 45% on the engine performance indexes and three adjustable structural parameters with an influence of less than 15% on the engine performance indexes were determined. This quantitative analysis work provides an optimization direction for the further optimization of the combustion chamber structure in the future.

Combustion Analysis on Compression Engine by using Blends of Methyl Ester, Diesel and Turmeric Oil as an Additive

Combustion Analysis on Compression Engine by using Blends of Methyl Ester, Diesel and Turmeric Oil as an Additive

Experimental and numerical analysis of mechanics and fracture characteristics of engine compressor

Abstract Investigating the fatigue failure behavior of compressor fan blades and their materials in aero-engines is a crucial research area. This paper focuses on the compressor fan blades and their constituent materials of aero-engines. Firstly, fluid-structure interaction (FSI) numerical simulations under various rotational speeds are conducted to determine the stress distribution and identify the maximum stress. Secondly, based on the FSI results, fatigue tests on fan blade materials under different stress amplitudes are performed to explore the relationship between load and life, so as to analyze the fracture characteristics under various stress amplitudes. This research has significant implications for ensuring the stable operation of aero-engine fan blades.

Effect of particle impact on spatial and temporal erosion characteristics of turboshaft engine compressor

When turboshaft engines operate in dusty environments, particulate matter erodes the compressor blades, which may leads to structural damage and presents a severe threat to the operational reliability and safety of helicopters. The aim of this study is to determine the erosion characteristics of compressor blades and how it changes with time. Particle velocimetry and erosive experiments were conducted to obtain the SiO2 particle velocity and the erosion rate of the Ti-6Al-4V titanium alloy. Based on the measured data, the parameters of the Tabakoff erosion model have been refined, which is critical for establishing a transient erosion model for the 1.5-stage compressor of a turboshaft engine that accounts for the effect of particle erosion time. Simulation results show that the motion behavior of particles exhibits changing patterns at different time intervals, which leads to variations in the erosion area and erosion rate of the compressor. The erosion area and rate on blades increase nonlinearly with time. In some locations, when erosion time increases, the erosion area and erosion rate also increase. While, in other locations, the erosion area and erosion rate hardly change with time. The maximum erosion rates increased by 27.3 %, 28.6 %, and 87.2 % for the guide blades, 42.9 %, 69.6 %, and 84.0 % for the rotor blades, and 69.0 %, 103.6 %, and 142.8 % for the stator blades at 0.50s, 0.75s, and 1.00s, respectively, in comparison to 0.25s.

Studies on fuels and engine attributes powered by bio-diesel and bio-oil derived from stone apple seed (Aegle marmelos) for bioenergy

Biofuel is an alternative fuel for diesel engines which is necessary to reduce exhaust emissions and helps to balance the depletion of fossil fuels. This study details the synthesis of bio-diesel and bio-oil from stone apple seeds ( Aegle marmelos) through transesterification, direct oxygenate additive, and pyrolysis processes. The diesel engine is powered by the resulting stone apple methyl ester bio-diesel/diesel and bio-oil/diesel mixtures. In a test engine rig, the effectiveness and emission uniqueness of test fuel mixes were examined at various engine loads (EL = 3 kg–12 kg) and compression ratios (CR = 16–17.5) while maintaining a steady speed of 1500 r/min. Furthermore, engine performance and emissions for bio-diesel and bio-oil are measured and compared. The oxides of nitrogen (NOx) emission by bio-diesel and bio-oil opus were higher than neat diesel (FD). Also, carbon monoxide (CO) and hydrocarbon (HC) emissions were measured to be lower. The improvements of BTE by 4.87% and decrement of CO by 18.8%, HC by 13.26% were observed with the trans-esterified bio-diesel/diesel opus compared to diesel at a higher CR and rated load conditions. The engine analysis responses revealed that the FBD blend showed enhanced performance and lower emissions except NOx compared to diesel fuel. Hence, trans-esterified bio-diesel is a greater diesel alternative than FBDE and FBO.

Optimization strategies for enhancing diesel engine performance and emissions control with biofuel blends: A multi-objective approach

This study examines the effects of engine compression ratio, load, and biofuel composition on performance, combustion, and emissions. The experimental setup includes testing different compression ratios (16, 17, 18) and loads (25 %, 50 %, 75 % torque) at a fixed speed of 1500 rpm, using Thai standard diesel as the control fuel. Biofuel variations tested include neat biodiesel, neat biokerosene, and blends of 30 % biokerosene with 70 % biodiesel and 50 % biokerosene with 50 % biodiesel. The results show that an increased compression ratio enhances combustion efficiency, reduces brake specific fuel consumption, and improves brake thermal efficiency, although it also leads to higher nitrogen oxide emissions. Biofuels improve brake thermal efficiency due to their higher oxygen content. However, the increased viscosity of biodiesel can hinder fuel atomization, resulting in higher emissions. In contrast, biokerosene improves brake thermal efficiency by facilitating earlier combustion and reducing emissions. Performance is primarily affected by load, while emissions are influenced by both biokerosene content and load. Gradient boosting models and optimization techniques, such as the non-dominated sorting genetic algorithm III (NSGA-III) and adaptive geometry estimation-based multi-objective evolutionary algorithms (AGE-MOEA), produce consistent results, with AGE-MOEA identifying denser optimal points. The findings suggest that optimal biokerosene blends ranging from 20 % to 40 %, across all compression ratios and loads of 50 %–75 %, provide valuable insights for advancing sustainable fuel utilization practices in automotive vehicles.

Diesel Engine Turbocharger Monitoring by Processing Accelerometric Signals through Empirical Mode Decomposition and Independent Component Analysis

In this study, a method for the monitoring of internal combustion engine operation by vibration signals is proposed. The work falls within the context of the increasingly stringent standards relating to the environmental impact of engines and the development of monitoring and control techniques to ensure increased engine performance as well as fuel saving and reduction of pollutant emissions. Experimentation was performed on a turbocharged light-duty compression ignition direct-injection engine. Two monoaxial accelerometers were installed on the engine compressor case, the speed of which has been demonstrated to be closely related to the engine operation. Vibration measurements of the engine compressor case have been processed by combining the Empirical Mode Decomposition technique with Independent Component Analysis and Short Time Fourier Transform to indirectly estimate the turbocharger speed. The obtained traces have been compared to the direct turbocharger velocity measures during the stationary running of the engine (speed and load conditions varied in the complete engine’s range of operation). The results point out the potentiality of the methodology in algorithms devoted to identifying modifications of the combustion development regarding regular operation via indirect turbocharger speed monitoring.

A model to assess the importance of runway and taxiway particles to aircraft engine compressor deterioration

A model to assess the importance of runway and taxiway particles to aircraft engine compressor deterioration

Investigation of the operating characteristics of diesel engines with chromium oxide (Cr2O3) nanoparticles dispersed in Mesua ferrea biodiesel: an experimental and predictive approach using ANNs and RSM

Abstract This study investigates the effects of using biodiesel from Mesua ferrea (BD20) and chromium oxide (Cr2O3) nanoparticles in diesel engines. The Response Surface Methodology (RSM) model and artificial neural networks (ANNs) were developed to make precise predictions of the operating parameters. The amount of Cr2O3 nanoparticles was set at 80 mg/L, and surfactant and dispersant were applied to the nanoparticles in the same amounts. The study was carried out with different compression ratios and load conditions. The parameters evaluated were engine load, fuel samples and compression ratio as inputs and BTE, BSFC, CP, NHRR, CO, UHC, NO x and smoke opacity as outputs. The addition of the QPAN80 additive at the same dosage of 80 mg/L together with the BD20 fuel blend containing Cr2O3 at a concentration of 80 mg/L resulted in a significant increase in BTE by 16.58 % and a reduction in BSFC by 0.58 %. While the NHRR increased by 85.40 %, the CP increased sharply by 24.47 %. The CO concentration decreased by 31.85 %, the UHC concentration by 22.22 %, the NO x concentration by 6.16 % and the smoke emission by 62.61 %. For each output parameter, the correlation coefficient (R 2), calculated using ANNs and RSM was between 0.96 and 0.98. The observed range of values demonstrates a robust correlation between the experimental data and the predicted outcomes.

On the Influence of Engine Compression Ratio on Diesel Engine Performance and Emission Fueled with Biodiesel Extracted from Waste Cooking Oil

Despite the extensive research on biodiesels, further investigation is warranted on the impact of compression ratios on emissions and engine performance. This study addresses this gap by evaluating the effects of increasing the engine’s compression ratio on engine performance metrics—brake-specific fuel consumption (BSFC), power, torque, and exhaust gas temperature—and emissions—unburnt hydrocarbons (HCs), carbon dioxide (CO2), carbon monoxide (CO), nitrogen oxides (NOx), and oxygen (O2)—when fueled with a 20% blend of waste cooking oil biodiesel (WCB20) and petroleum diesel (PD) under various operating conditions. The viscosity of the prepared fuels was measured at 25 °C and 40 °C. Experiments were conducted on a single-cylinder diesel engine under wide-open throttle conditions at three different speeds (1400 rpm, 2000 rpm, and 2600 rpm) and two compression ratios (16:1 and 18:1). The results revealed that at a lower compression ratio, both WCB20 and petroleum diesel exhibited reduced BSFC compared to higher compression ratios. However, increasing the compression ratio from 16:1 to 18:1 significantly decreased HC emissions but increased CO2 and NOx emissions. Engine power increased with engine speed for both fuels and compression ratios, with WCB20 initially producing less power than diesel but surpassing it at higher compression ratios. WCB20 demonstrated improved combustion quality with lower unburnt hydrocarbons and carbon monoxide emissions due to its higher oxygen content, promoting complete combustion. This study provides critical insights into optimizing engine performance and emission characteristics by manipulating compression ratios and utilizing biodiesel blends, paving the way for more efficient and environmentally friendly diesel engine operations.

Evaluation Strength of Materials of the Compressor Wheel and Engine Power in the Turbocharger

Evaluation Strength of Materials of the Compressor Wheel and Engine Power in the Turbocharger

A comprehensive analysis of energy, exergy, performance, and emissions of a spark-ignition engine running on blends of gasoline, ethanol, and isoamyl alcohol

This present study showed a comprehensive analysis of energy, exergy, performance, and emission characteristics of a spark-ignition engine powered by blends of gasoline-isoamyl alcohol-ethanol at volume proportions (100_0_0)% (P0E0), (90_5_5)% (P5E5), (80_5_15)% (P5E15), and (70_5_25)% (P5E25) at various engine speeds and compression ratios (CR). The outcomes of thermodynamic analyses revealed that the highest exergy and energy efficiency were 28.92 % (P0E0, 2600 rpm, CR of 9:1) and 31.01 % (P0E0, 2600 rpm, CR of 9:1), respectively. In addition, the average brake power and brake thermal efficiency for P0E0, P5E5, P5E15, and P5E25 increased by (30.36 %, 27 %, 26.74 %, 27.84 %) and (0.34 %, 0.07 %, 0.35 %, 0.33 %) respectively, while brake specific fuel consumption decreased by (2.5 %, 0.64 %, 3.62 %, 6.33 %) in the engine speed range of 2600–3200 rpm. Compared to gasoline, the maximum reduction of carbon monoxide emissions was 6.13 %, 8.81 %, and 9.96 %, while unburnt hydrocarbon emissions exhibited the maximum decrement by 5.8 %, 10.75 %, 12.58 % for P5E5, P5E15, and P5E25, respectively. However, nitrogen oxide (NOx) emissions for P5E25 tended to increase significantly compared to P0E0, while the difference in NOx emissions for P5E15 and P0E0 was marginal. Overall, P5E15 could be considered as the potential alternative fuel for spark-ignition engines towards the goal of sustainable energy conversion.

Exploring the Combustion Performance of a Non-Road Air-Cooled Two-Cylinder Turbocharged Diesel Engine

In order to explore the combustion performance of a non-road air-cooled two-cylinder turbocharged diesel engine, an experiment on the effects of engine compression ratio, combustion chamber shape and injection timing were systematically conducted in this study. Moreover, the effects of intake air conditions on combustion performance were numerically investigated using the one-dimensional simulation platform. The findings of this study could help provide new insights for promoting the sustainable development of diesel engines used in generator sets. The results show that the increase in intake air temperature can delay the combustion center of gravity and improve the combustion performance and the sustainability of diesel engines. The decrease in intake air pressure leads to a reduction in oxygen amount during the combustion process, thus causing the deterioration of cylinder pressure and combustion performance. By modifying the combustion chamber, the ignition delay and combustion duration are each extended by 1.6 degrees and 4.2 degrees under 100% engine load. The ignition delay and combustion duration are not obviously affected by modifying the combustion chamber shape under 25% and 50% loads. By increasing the compression ratio from 19.5 to 20.5, the ignition delay and combustion duration are shortened, which could enhance the cylinder pressure and heat release rate. However, reducing the compression ratio from 19.5 to 18.5 could significantly decrease the heat release rate. Under middle and low loads, combustion duration is less affected by injection timing. Under 100% load, the peak cylinder pressure increases to 11.4 MPa, and the ignition delay is shortened by advancing injection timing from −17 °CA to −20 °CA.