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Copyright of Chemical Engineering (China) / Huaxue Gongcheng is the property of Hualu Engineering Science & Technology Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

At present, there’s a lack of combustion visualization in the combustion control of heating boilers. To understand the combustion of coal in the furnace, only experienced workers can observe it through visual inspection. Using infrared thermal imaging technology to monitor the combustion can realize combustion visualization. This paper analyzed and solved two problems: the installation position and number of infrared cameras, and the infeasible of using infrared cameras observing the combustion condition in the furnace through heat-resistant glass. Monitored parameters such as oxygen content, furnace temperature and smoke exhaust temperature, and monitored the concentration of PM, NOx, and SO2 in the main atmospheric pollutants in the flue gas. After calculation, the air leakage coefficient when the inspection doors are opened for observation is 0.04. This value still includes the sum of air leakage from coal hopper, furnace door, grate side seal, peep holes and other parts. The monitored average emission concentration of PM decreased by 16.28%, from which we can concluded that the use of thermal imaging technology to monitor the combustion in the furnace is conducive to emission reduction. The application of thermal imaging technology implementation of coalfired boiler combustion visualization is feasible. [ABSTRACT FROM AUTHOR]

Due to the rapidly increasing energy demand, the world needs to focus more on identifying alternative energy sources like biofuels and energy conservation techniques that enhance the efficiency of various systems. A cogeneration (CHP) system is one of the most emerging techniques for achieving the goal of energy conservation by providing useful power (electricity) and heating simultaneously. So the current study proposes a diesel engine-driven CHP system that is fueled with different blends of biodiesel. The objective of the current study is to investigate the impact of Eureka Sativa oil biodiesel on waste heat recovery, performance, and emission characteristics of diesel engine driven combined heating and power generation system. The cogeneration unit is developed by connecting the exhaust pipe of a single-cylinder, four-stroke diesel engine with a heat exchanger. The pure diesel, along with 10%, 15%, 20%, and 25% by volume of biodiesel, was used as fuel for the cogeneration unit. The AVL Di-Gas 444N multi-gas analyzer was utilized to evaluate the engine exhaust gas emissions. Diesel fuel has the highest brake thermal efficiency and the lowest brake specific fuel consumption (BSFC). B20 has the highest brake thermal efficiency and the lowest BSFC among all blends of biodiesel. Also, B20 has better emission characteristics than all other blends of biodiesel. The exhaust gas temperature and waste heat recovery increase with the percentage of biodiesel in the blends. The B25 has the highest overall efficiency (38.49%) among all blends, which is 1.93 % lower than pure diesel. However, result analysis revealed that B20 is the best fuel among all biodiesel blends in terms of engine performance and emission formation. Whereas B25 is a better fuel in terms of WHR and overall cogeneration unit efficiency. [ABSTRACT FROM AUTHOR]

This article introduces the upgrading and renovation of the waste heat recovery system of the No. 1 jet fuel hydrogenation unit of SINOPEC Hainan Refining & Chemical Co., Ltd. The renovation plan is as follows: By recalculating the thermal efficiency and load of the heating furnace, the original heat pipe preheater is planned to be optimized into a new ceramic regenerative air preheater. The specific renovation content is as follows: Remove the heat pipe preheater originally installed on the top of the heating furnace, and add four sets of ceramic regenerative air preheater modules on the side ground of the reaction feed heating furnace ; Reuse the original induced draft fan as a cold flue gas induced draft fan; Add a blower and smoke and air duct. The results show that after the implementation of the modification, the exhaust gas temperature of the heating furnace can be reduced to below 70 °C, the thermal efficiency of the heating furnace can be increased to over 95%, the exhaust gas temperature can be flexibly adjusted, and the fuel gas consumption of the heating furnace can be reduced by about 10%. The system has good anti-corrosion performance and is stable and reliable during long-term operation of the unit. [ABSTRACT FROM AUTHOR]

This article analyzes the effect of modifications of injector opening pressure on the operating values of a compression ignition engine, including the temperature of the exhaust gas. A program of experimental investigation is described, considering the available test stand and measurement capabilities. The structure of the test stand on which the experimental measurements were conducted is presented. The method of introducing real modifications of injector opening pressure to the existing test engine was characterized. It was proposed to use F statistic of Fisher-Snedecor (F-S) distribution to evaluate the importance of the impact of modifications of injector opening pressure on the specific enthalpy of the flue gas flow. Qualitative and statistical studies of the results achieved from the measurements were carried out. The specific enthalpy of the exhaust gas for a single cycle of the compression ignition engine, determined from the course of rapidly variable flue gas temperature, was analyzed. The results of these studies are presented and the usable adoption of this type of assessment in parametric diagnosing of compression ignition engines is discussed. [ABSTRACT FROM AUTHOR]

The problems related to assessment of the technical state of diesel engines by remote collecting data on the state of several diagnostic parameters are discussed. During the operation the system allows one to reliably assess the technical state of an engine, using remote monitoring of several diagnostic parameters. At the same time, for each type and brand of the engine, a decision-making algorithm is used, based on the experimental studies carried out. [ABSTRACT FROM AUTHOR]

Copyright of Petroleum Refinery Engineering is the property of Petroleum Refinery Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article presents a continuation of research carried out to determine the effect of input parameters (changes in engine structure parameters) on selected output parameters (diagnostic measures), based on quickly changing exhaust gas temperature. A method of determining the simultaneous influence of two input factors (the structure parameter and the engine load) on one output factor was presented, as well as an evaluation of which of the analysed input factors has a stronger influence on the output parameter. The article presents the stages of the experimental research conducted and statistical inference based on the results. Three changing parameters for the structure were reviewed: the active cross-sectional area of the inlet air channel, the injector opening pressure and the compression ratio. Based on the quickly changing temperatures of the exhaust gases, three diagnostic measures were defined and subjected to statistical tests. The following data were averaged over one cycle for a 4-stroke engine operation: the intensity of changes, the specific enthalpy and the peak-to-peak value of the exhaust gas temperature. The results of the two-factor analysis are presented. Conclusions on the analysis are given and a criterion for the selection of a diagnostic measure, depending on the analysed parameter of the structural design of the diesel engine, is proposed.

The monitoring of sintering bed temperature is crucial for controlling physical and chemical reactions during the sintering process and achieving low carbonization trends. However, accurately monitoring this temperature is challenging due to the ''black box'' nature of the sintering bed, which includes the sintering trolley and cup. As a result, a theoretical model needs to be developed urgently to predict the sintering bed's temperature profile. In this investigation, we propose a mathematical model that utilizes the characteristic value of the lognormal distribution to estimate indirectly the temperature of the sintering bed based on the measured temperature of the sintering exhaust gas. The sintering exhaust gas temperature and sintering bed temperature conform to the function: T=T0+A2πw⋅te−(ln(t−tc))2w22. To further enhance the accuracy of the sintering bed temperature prediction, the longitudinal positions of the sintering bed were expanded from three points to multiple points, enabling the construction of a temperature prediction function for the entire sinter bed and obtaining a cloud map of the sintering bed temperature. By determining the sintering terminal point and controlling the sintering machine's speed according to the location of the high-temperature region on the cloud map, the performance of the temperature prediction model was optimized. Through an analysis of the mathematical model and construction of the sintering temperature profile, a predictive route of exhaust gas temperature → three-point sintering bed → total sintering bed was established. This predictive method can significantly enhance the understanding of the sintering process and can be employed in industrial plants.

In this paper the performance and emission characteristics of thermal energy storage integrated micro-cogeneration system was investigated. This system was developed by connecting the vapor absorption refrigeration (VAR) system and thermal energy storage (TES) system with the exhaust gas pipe of a single-cylinder diesel engine. The vapor absorption refrigeration system has the cooling capacity of 500 W. A cabin of 1500 mm length, 1200 mm width and 1500 mm height was fabricated with proper insulation as space for cooling. The cabin temperature drop of 8.6 ℃ was achieved in 45 min. The cooling capacity of the VAR system was 302 W, and the COP of the VAR system was 0.398. The cabin temperature drop decrease with decrease in engine RPM but it was maintain stable (8.6℃) for 25 min by using TES. The overall efficiency of the cogeneration system was 1.79 % higher than the single generation. Hence, the result showed that the small capacity (5 kW) stationary diesel can be successfully converted into a cogeneration system to produce power and space cooling simultaneously.

The paper considers issues related to the assessment of technical condition of diesel engines by creating a remote diagnostic system capable of assessing the technical condition of the engine under check. Based on the analysis of the read and stored diagnostic data, the system can calculate and correct their critical values. These system capabilities make it possible to solve problems related to service life forecasting. Special subsystems with the possibility of self-learning are used, based on algorithms that establish a connection between the system states and data obtained in real time for each diagnostic parameter. [ABSTRACT FROM AUTHOR]

An investigation was conducted to evaluate the impact of ethanol/diesel fuel blends on the diesel engine's performance and emissions. The objective of this study is to determine the optimum ethanol/diesel fuel blend percentage, in comparison to using diesel fuel alone, that achieves both improved performance and reduced emissions concurrently. A test is being carried out on five different ethanol/diesel fuel blends. One of them is pure diesel fuel and the others are blended with diesel fuel using 5% to 20% absolute ethanol in increments of 5%. Ethanol-diesel blends have garnered significant attention as an alternative fuel. Making it an environmentally sustainable choice. This fuel option is cleaner-burning, undergoing more complete combustion and resulting in reduced emissions of greenhouse gases linked to climate change. Additionally, ethanol possesses a higher octane rating than diesel, which enhances the performance of compression-ignition engines. By blending ethanol with diesel, engine efficiency, and power output can be improved while reducing issues like engine knock and noise levels. Moreover, it has positive economic implications, generating job opportunities in agriculture. The test measurements were carried out with engine torque ranging from 0 to 21 N.m. with an addition of 6 N.m, at a constant engine speed of 1,500 rpm, and with various compression ratios of 16, 17, and 18. In this study, the performance parameters of an engine were evaluated. These parameters included imep, bsfc, ηbth, ηm, and Tex. Also analyzed the engine's exhaust emissions, which included CO, NOx, HC, O2, and CO2. To measure these emissions, an exhaust gas analyzer was used, and the smoke opacity was measured using a smoke meter. The results indicated that the highest bsfc was recorded for E20 fuel and the lowest for E0. E0 diesel fuel exhibits the highest ηbth, followed by E5, E10, E15, and E20 diesel fuel blends. The value of Tex for E5, E10, E15, and E20 is lower than that of E0, with values of 419°C, 421°C, 423°C, and 424°C respectively, under full load conditions. In comparison, the Tex of E0 is 426°C. Using ethanol/diesel fuel blends results in reduced CO emissions and increased CO2 emissions under specific load conditions and decreasing the percentage of NOx emissions and increasing the emission of O2. Finally, according to the test results, the engine running on blends produced lower smoke opacity compared to the engine running on diesel. [ABSTRACT FROM AUTHOR]

Aiming at engine health management, a novel hybrid prediction method is proposed for exhaust gas temperature (EGT) prediction of gas turbine engines. This hybrid model combines a nonlinear autoregressive with exogenous input (NARX) model and a moving average (MA) model. A feature attention mechanism-enhanced long short-term memory network (FAE-LSTM) is first developed to construct the NARX model, which is used for identifying the aircraft engine using condition parameters and gas path measurement parameters that correlate to the EGT. A vanilla LSTM is then used for constructing the MA model, which is used for improving the difference between the actual EGT and the predicted EGT given by the NARX model. The proposed method is evaluated using real flight process data and compared to several dynamic prediction techniques. The results show that our hybrid model reduces the predicted RMSE and MAE by at least 13.23% and 18.47%, respectively. The developed FAE-LSTM network can effectively deal with dynamic data. Overall, the present work demonstrates a promising performance and provides a positive guide for predicting engine parameters. [ABSTRACT FROM AUTHOR]

A significant obstacle to creating efficient machine health monitoring systems is estimating performance degradation in dynamic systems, like aero plane engines. In exceedingly complex systems with many components, states, and parameters, conventional model-based and data-driven methods fall short of producing satisfactory results. While traditional methods had several drawbacks, deep learning has emerged as a viable computational tool for dynamic system prediction. In order to track system deterioration and estimate the EGT, a novel technique based on the Long Short-Term Memory (LSTM) network, (an architecture created to find the hidden patterns hidden in time series data) is provided in this research. The health monitoring information of aircraft turbofan engines is used to assess the effectiveness of the proposed strategy. As a result of this network’s ability to recognize the input data as a real-time series, the output in the following step can be predicted. Results of the suggested study show a significant ability to anticipate the output in the following time step. Additionally, the proposed model has a shorter learning curve and is more accurate.

Low load is one of the most challenging combustion stages for a fixed-speed diesel electric generator. Due to incomplete combustion during this phase, a significant proportion of contaminants form inside the cylinder. This can lead to numerous chemical and mechanical harms to the diesel engine, resulting in friction, efficiency reduction, increased fuel consumption, and prematurely ending the generator's life. These phenomena are qualified as underperformance, possibly due to a misfire and/or a low-efficiency value (air fuel–fuel ratio). Therefore, detecting and preventing underperformance and reducing its extended operation is crucial. This paper deals with the performance and emission analysis of a multicylinder fixed-speed diesel engine driving an electric generator (300 kW) fueled with ultra-low sulfur diesel (≤15 mg/kg) to provide energy in an isolated Canadian community. The tests were carried out according to ISO 3046-1:2002 standard in a remote site to identify clues that can prevent prolonged operation in underperformance. Among the tests conducted, emissions such as sulfur (S), carbon dioxide (CO2), nitrogen oxide (NOx), and exhaust gas temperature are considered the best indices for detecting the underperformance of a fixed-speed diesel–electric generator under very-low and low load (0–30%) with the following registered values: 18 ppm for S, 4% for CO2, 150 ppm for NOx, and 210 °C for the temperature. [ABSTRACT FROM AUTHOR]

The exhaust gas temperature (EGT) baseline of an aeroengine is key to accurately analyzing engine health, formulating maintenance decisions and ensuring flight safety. However, due to the complex performance characteristics of aeroengine and the constraints of many external factors, it is difficult to obtain accurate non-linear features between various operating factors and EGT. In order to diagnose and forecast aeroengine performance quickly and accurately, four data-driven baseline prediction frameworks for EGT are proposed. These baseline frameworks took engine operating conditions and operating state control parameters as input variables and EGT as predicted output variables. The original data were collected from CFM56-5B engine ACARS flight data. Four typical machine learning methods, including Generalized Regression Neural Network (GRNN), Radial Basis Neural Network (RBF), Support Vector Regression (SVR) and Random Forest (RF) are trained to develop the models. Four aeroengine EGT baseline models were validated by comparing the after-flight data of another engine. The results show that the developed GRNN models have the best accuracy and computational efficiency compared with other models, and their RE and CPU calculation time on the verification set are 1.132 × 10−3 and 3.512 × 10−3 s, respectively. The developed baseline prediction frameworks can meet the needs of practical engineering applications for airlines. The methodologies developed can be employed by airlines to predict the EGT baseline for the purpose of engine performance monitoring and health management. [ABSTRACT FROM AUTHOR]

The operational well-being of aircraft-engine turbine components is paramount for engine safety. Monitoring exhaust gas temperature (EGT) serves as a key indicator of their condition. Real-time and precise EGT prediction in aircraft engines plays a pivotal role in ensuring flight safety and effective engine health management. A deep learning model based on the long short-term memory (LSTM), integrated with the physical topology of the aircraft engine, served as the basic prediction model for EGT. Based on Taylor expansion, error compensation was performed on model errors arising from sensor error and performance degradation, three compensation models were developed: a Base model consistent with the basic prediction model, an LSTM model, and a multilayer perceptron model. Their influence on prediction accuracy was examined. Each compensation model was trained using two distinct fusion methods: a global compensation method (GCM) and a real-time compensation method (RtCM). The research also explored how different fusion methods contributed to enhancing prediction accuracy. The results showed that the basic model used in this study achieved high prediction precision. The addition of the compensation model further improved the prediction precision. The GCM effectively reduced the mean absolute relative error (MARE), while the RtCM effectively reduced the maximum absolute relative error (Emax) without increasing the prediction time. The best model evaluated on the four engine test datasets had a MARE value of 0.166%, Emax value of 2.745% and mean absolute error of 1. 13 ° C , indicating high prediction precision. [ABSTRACT FROM AUTHOR]

In this paper, attention was paid to the problem of low controllability of marine medium- and high-speed engines during operation, which significantly limits the parametric diagnosis. The measurement of quickly changing temperature of engine exhaust gas was proposed, the courses of which can be a source of diagnostic information. The F statistic of the Fisher-Snedecor distribution was chosen as a statistical tool. Laboratory tests were carried out on the bench of a Farymann Diesel engine. The tests consisted of introducing the real changes in the constructional structure of the considered functional systems of the engine. Three changed parameters for the structure were reviewed: the active cross-sectional area of the inlet air channel, injector opening pressure and compression ratio. Based on the recorded plots of the quick-changing temperatures of the exhaust gases, three diagnostic measures were defined and subjected to statistical tests. The following data were averaged over one cycle for a 4-stroke piston engine operation, (1) the peak-to-peak value of the exhaust gas temperature, (2) the specific enthalpy of the exhaust gas, and (3) the rate of increase and decrease in the values for the quick-changing exhaust gas temperature.

The paper discusses the impact of changes in the compression ratio on the operating parameters of a diesel engine, e.g. on the temperature of exhaust gases. It presents the construction of the laboratory test stand, on which experimental measurements were realized. It is characterized how the actual changes of the compression ratio were introduced to the existing engine. The program of experimental investigations taking into account the available test stand and measurement possibilities was described. A statistical and qualitative analysis of the obtained measurement results was made. The use of F statistics of the Fisher-Snedecor distribution was proposed to assess the significance of the effect of compression ratio changes on the specific enthalpy of the exhaust gas stream. The specific enthalpy of exhaust gases was analysed for one cycle of diesel engine work, determined on the basis of the course of quickly varying temperature of exhaust gases. The results of these analyses are discussed and the utilitarian purpose of this type of evaluation in parametric diagnostics of piston engines is presented.

Aiming at engine health management, a novel hybrid prediction method is proposed for exhaust gas temperature (EGT) prediction of gas turbine engines. This hybrid model combines a nonlinear autoregressive with exogenous input (NARX) model and a moving average (MA) model. A feature attention mechanism-enhanced long short-term memory network (FAE-LSTM) is first developed to construct the NARX model, which is used for identifying the aircraft engine using condition parameters and gas path measurement parameters that correlate to the EGT. A vanilla LSTM is then used for constructing the MA model, which is used for improving the difference between the actual EGT and the predicted EGT given by the NARX model. The proposed method is evaluated using real flight process data and compared to several dynamic prediction techniques. The results show that our hybrid model reduces the predicted RMSE and MAE by at least 13.23% and 18.47%, respectively. The developed FAE-LSTM network can effectively deal with dynamic data. Overall, the present work demonstrates a promising performance and provides a positive guide for predicting engine parameters.

Low load is one of the most challenging combustion stages for a fixed-speed diesel electric generator. Due to incomplete combustion during this phase, a significant proportion of contaminants form inside the cylinder. This can lead to numerous chemical and mechanical harms to the diesel engine, resulting in friction, efficiency reduction, increased fuel consumption, and prematurely ending the generator’s life. These phenomena are qualified as underperformance, possibly due to a misfire and/or a low-efficiency value (air fuel–fuel ratio). Therefore, detecting and preventing underperformance and reducing its extended operation is crucial. This paper deals with the performance and emission analysis of a multicylinder fixed-speed diesel engine driving an electric generator (300 kW) fueled with ultra-low sulfur diesel (≤15 mg/kg) to provide energy in an isolated Canadian community. The tests were carried out according to ISO 3046-1:2002 standard in a remote site to identify clues that can prevent prolonged operation in underperformance. Among the tests conducted, emissions such as sulfur (S), carbon dioxide (CO2), nitrogen oxide (NOx), and exhaust gas temperature are considered the best indices for detecting the underperformance of a fixed-speed diesel–electric generator under very-low and low load (0–30%) with the following registered values: 18 ppm for S, 4% for CO2, 150 ppm for NOx, and 210 °C for the temperature.

Copyright of Computer Measurement & Control is the property of Magazine Agency of Computer Measurement & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Modern automotive gasoline engines have highly efficient after-treatment systems that reduce exhaust gas emissions. However, this efficiency greatly depends on the conditions of the exhaust gas, mainly the temperature and air–fuel ratio. The temperature instability during transient conditions may cause a reduction in the efficiency of the three-way catalyst (TWC). By using a thermal energy storage system before TWC, this negative effect can be suppressed. In this paper, the effects of the temperature stabilization on the efficiency of the three-way catalyst were investigated on a 1-D turbocharged gasoline engine model, with a focus on fuel consumption and emissions. The thermal energy storage system (TESS) was based on PCM materials and was built in the exhaust between the turbine and TWC to use the energy of the exhaust gas. Three different materials were picked up as possible mediums in the storage system. Based on the results, the usage of a TESS in a gasoline after-treatment system has shown great potential in improving TWC efficiency. This approach can assist the catalyst to operate under optimal conditions during the drive. In this study, it was found that facilitating the heat transfer between the PCM and the catalyst can significantly improve the emissions' reduction performance by avoiding the catalyst to light out after the cold start. The TESS with PCM H430 proved to reduce the cumulative CO and HC emissions by 8.2% and 10.6%, respectively, during the drive. Although a TES system increases the after-treatment cost, it can result in emission reductions and fuel consumption over the vehicle's operating life. [ABSTRACT FROM AUTHOR]

The 21st century aviation and aerospace technologies have evolved and become more complex and technical. Turbofan jet engines as well as their cousins, the rocket engines (liquid/solid) have gone through several design upgrades and enhancements during the course of their design and exploitation. These technological upgrades have made engines very complex and expensive machines which need constant monitoring during their working phase. As the demand and use of such engines is growing steadily, both in the civilian and military sectors, it becomes necessary to monitor and predict the behavior of parametric data generated by these complex engines during their working phases. In this paper flight parameters such as Exhaust Gas Temperature (EGT), Engine Fan Speeds (N1 and N2), Fuel Flow (FF), Oil Temperature (OT), Oil Pressure (OP), Vibration and others where used to determine engine fault. All turbo fan engines go through several distinctly different working phases: Take-off phase, Cruise phase and Landing phase. Recording generated parametric data during these different phases leads to a massive amount of in-flight data and maintenance reports, which makes the task of designing and developing a fault diagnostic system highly challenging. It becomes imperative to use modern techniques in data analysis that can handle large volumes of generated data and provide clear visual results for determining the technical status of the engine under investigation/monitoring. These modern techniques should be able to give clear and objective assessment of the object under investigation. Cluster analysis methods based on Neural Networks such as c-means, k-means, self-organizing maps and DBSCAN algorithm have been used to build clusters. Differences in cluster groupings/patterns between healthy engine and engine with degraded performance are compared and used as the bases for defining faults. Fault diagnosis plays a crucial role in aircraft engine management. Timely and accurate detection of faults is the foundation on which maintenance turnaround times, operational costs and flight safety are based. The data used in this paper for analysis was obtained from flight data recorder during one flight cycle. The final decision on a fault is taken by an engineer.

In this paper, attention was paid to the problem of low controllability of marine medium- and high-speed engines during operation, which significantly limits the parametric diagnosis. The measurement of quickly changing temperature of engine exhaust gas was proposed, the courses of which can be a source of diagnostic information. The F statistic of the Fisher-Snedecor distribution was chosen as a statistical tool. Laboratory tests were carried out on the bench of a Farymann Diesel engine. The tests consisted of introducing the real changes in the constructional structure of the considered functional systems of the engine. Three changed parameters for the structure were reviewed: the active cross-sectional area of the inlet air channel, injector opening pressure and compression ratio. Based on the recorded plots of the quick-changing temperatures of the exhaust gases, three diagnostic measures were defined and subjected to statistical tests. The following data were averaged over one cycle for a 4-stroke piston engine operation, (1) the peak-to-peak value of the exhaust gas temperature, (2) the specific enthalpy of the exhaust gas, and (3) the rate of increase and decrease in the values for the quick-changing exhaust gas temperature. In this paper will present results of the first stage of the elimination study: the one-factor statistical analysis (randomised complete plan). The next part will present the results of the second stage of studies: two-factor analysis (block randomised plan), where the significance of the effect of changing the values of the structure parameters on the diagnostic measures was analysed in the background of a variable engine load. [ABSTRACT FROM AUTHOR]

This paper presents the application of Fisher-Snedecor distribution F statistics to assess the significance of the influence of changes in the active cross-sectional area of the inlet air channel (Adol) flow in a diesel engine on the observed diagnostic parameter determined on the basis of measurements of the quick changing exhaust gas temperature in the outlet channel, which is the specific enthalpy of the exhaust gas stream within one engine operating cycle (hspal). A plan of experimental tests carried out on the laboratory stand of a single-cylinder Farymann Diesel type D10 laboratory engine was presented and the method of determination of F statistics values for the obtained measurement results was characterized. Representative results of calculations were presented and the strength of Adol input parameter influence on the determined diagnostic parameter hspal simplified physical model of the working process of a compression ignition engine as the object of diagnosis was evaluated. It is planned to further develop the experimental research program to determine the significance of the influence of changes in the values of selected parameters of the engine structure on other diagnostic measures determined from the exhaust gas temperature signal, i.e. the mean peak-to-peak value as well as the rate (intensity) of increase and decrease in its value for individual engine cycles.

Current on-road vehicles are generally outfitted with exhaust after-treatment (EAT) systems to meet the stringent emission regulations. At cold start and low-loaded operations, those systems need to be warmed up above a threshold temperature (generally 250oC) for effective performance. High exhaust temperatures and high exhaust flow rates are required to accelerate the EAT warm up which are mostly not available at low-loaded diesel vehicle operations. Therefore, the objective of this work is to improve EAT warm up at low loads through utilizing exhaust valve opening (EVO) modulation which allows both elevated exhaust temperatures and exhaust flow rates. A 1-D engine simulation program is used to model the system which is set to operate at 1200 RPM engine speed and at 2.5 bar brake mean effective pressure (BMEP) engine load. Exhaust temperature can be increased above 250oC via either early or late EVO timings. Reduced expansion work in advanced EVO timings and increased pumping loss in retarded EVO timings require higher fuel consumption (up to 15 % and 20 %, respectively) to keep engine load constant. Those high fuel penalties reduce engine air-to-fuel ratio and rise exhaust temperature more than 55oC. Exhaust mass flow rate is improved up to 9 % in the system as well. The method increases exhaust gas energy up to 40 % and rises heat transfer rate to the EAT system up to 140 % compared to nominal condition. The technique is highly effective at heating up EAT systems, however, it also causes high fuel inefficiency which needs to be considered.

The exhaust gas temperature (EGT) baseline of an aeroengine is key to accurately analyzing engine health, formulating maintenance decisions and ensuring flight safety. However, due to the complex performance characteristics of aeroengine and the constraints of many external factors, it is difficult to obtain accurate non-linear features between various operating factors and EGT. In order to diagnose and forecast aeroengine performance quickly and accurately, four data-driven baseline prediction frameworks for EGT are proposed. These baseline frameworks took engine operating conditions and operating state control parameters as input variables and EGT as predicted output variables. The original data were collected from CFM56-5B engine ACARS flight data. Four typical machine learning methods, including Generalized Regression Neural Network (GRNN), Radial Basis Neural Network (RBF), Support Vector Regression (SVR) and Random Forest (RF) are trained to develop the models. Four aeroengine EGT baseline models were validated by comparing the after-flight data of another engine. The results show that the developed GRNN models have the best accuracy and computational efficiency compared with other models, and their RE and CPU calculation time on the verification set are 1.132 × 10−3 and 3.512 × 10−3 s, respectively. The developed baseline prediction frameworks can meet the needs of practical engineering applications for airlines. The methodologies developed can be employed by airlines to predict the EGT baseline for the purpose of engine performance monitoring and health management.

In order to know the characteristics of reducing the exhaust gas infrared signal of the lobed mixer according to the external air mixing ratio, an infrared signal and temperature distribution measurement using a micro-turbojet engine is performed. A certain amount of compressed air is supplied through an external duct mounted on the micro-turbojet engine exhaust to simulate bypass flow, which is mixed with high-temperature core air and ejected to the atmosphere. The exhaust nozzle used in the experiment is a lobed mixer with a lobe of sinusoidal shape and is designed to have a penetration of 0.2. Exhaust gas temperature and infrared signal are measured according to distance from nozzle outlet under conditions of bypass ratio of 0.5, 1.0 and 1.4. Infrared reduction rates are compared to data without compressed air supply. As a result of the experiment, as the bypass ratio increased, the infrared signal of the exhaust gas and the temperature decrease with bypass ratio increase, and in the case of a bypass ratio of 1.4, the effect of reducing the temperature is observed even at a long distance. In addition, we compared the results of previous studies of a simple cone shape without mixer with infrared reduction effect. The results show that the lobed mixer has a greater effect on reducing the temperature of the exhaust gas and reducing the infrared signal than the cone nozzle. The structure of the mixed jet flow is also studied through Schlieren visualisation and 3D temperature distribution. [ABSTRACT FROM AUTHOR]

Data-driven condition-based maintenance (CBM) and predictive maintenance (PdM) strategies have emerged over recent years and aim at minimizing the aviation maintenance costs and environmental impact by the diagnosis and prognosis of aircraft systems. As the use of data and relevant algorithms is essential to AI-based gas turbine diagnostics, there are different technical, operational, and regulatory challenges that need to be tackled in order for the aeronautical industry to be able to exploit their full potential. In this work, the machine learning (ML) method of the generalised additive model (GAM) is used in order to predict the evolution of an aero engine’s exhaust gas temperature (EGT). Three different continuous synthetic data sets developed by NASA are employed, known as New Commercial Modular Aero-Propulsion System Simulation (N-CMAPSS), with increasing complexity in engine deterioration. The results show that the GAM can be predict the evolution of the EGT with high accuracy when using several input features that resemble the types of physical sensors installed in aero gas turbines currently in operation. As the GAM offers good interpretability, this case study is used to discuss the different data attributes a data set needs to have in order to build trust and move towards certifiable models in the future.

The paper discusses the impact of changes in the compression ratio on the operating parameters of a diesel engine, e.g. on the temperature of exhaust gases. It presents the construction of the laboratory test stand, on which experimental measurements were realized. It is characterized how the actual changes of the compression ratio were introduced to the existing engine. The program of experimental investigations taking into account the available test stand and measurement possibilities was described. A statistical and qualitative analysis of the obtained measurement results was made. The use of F statistics of the Fisher-Snedecor distribution was proposed to assess the significance of the effect of compression ratio changes on the specific enthalpy of the exhaust gas stream. The specific enthalpy of exhaust gases was analysed for one cycle of diesel engine work, determined on the basis of the course of quickly varying temperature of exhaust gases. The results of these analyses are discussed and the utilitarian purpose of this type of evaluation in parametric diagnostics of piston engines is presented. [ABSTRACT FROM AUTHOR]

The present investigation reports the production of pyrolytic plastic oils and their performance in compression ignition (CI) diesel engines with different oil and additive blends. Experimental investigation has been conducted on a four-stroke single-cylinder variable compression diesel engine at a steady engine speed of 1,500 rpm with a different blend of pyrolytic plastic oil (PPO) and ethanol with diesel for various load conditions. Parametric studies are conducted for blend proportion of 10%–20% and compression ratio of 16–18. The engine thermal efficiency is found to be augmented significantly by 2.67% and specific fuel consumption reduced by 0.59% at maximum engine load for 60D20PPO20E to that of diesel. The brake specific fuel consumption is also diminished for fuel mixtures by increase of concentration of additives in the fuel blend than diesel. The overall improvement in engine performance is found at 20% blend of PPO and ethanol in diesel with the highest compression ratio of 18. The novel correlation for brake thermal efficiency with respect to influencing parameters has been developed. [ABSTRACT FROM AUTHOR]

In this study, we explore the utilization of low calorific value waste gas for in-situ conversion mining of oil shale. Through simulation, we analyze the effects of variations in the parameters of the catalytic combustion heater's independent variables on the exhaust gas temperature, methane conversion rate, and system energy efficiency (dependent variables). The results demonstrate that larger values of the pore radius, gas injection flow rate, and pulsation flow rate parameters lead to reductions in the corresponding dependent variables. The system's energy efficiency remains stable between 21.94% and 22.46% with increasing gas injection temperature. Furthermore, an increase in the oxygen molar fraction results in elevated methane conversion rates from 0.64% to 58.2% and system energy efficiency from 0.4% to 21.51%. Conversely, an increase in the methane molar fraction causes a decrease in methane conversion from 76.17% to 7.18% and a decline in system energy efficiency from 32.83% to 7.18%. Notably, gas flowback occurs at downhole pressure conditions of 2 MPa. The variation in pressure stabilizes the system's energy efficiency between 21% and 22.10%. The simulation and analysis findings of this study provide significant reference value for subsequent practical testing efforts. This diagram depicts the process by which low calorific value waste gas is injected into a heater through a heat injection well and heated by catalytic combustion releasing high temperature exhaust gas to produce oil and gas from oil shale formations. [Display omitted] • Using low calorific value waste gas for oil shale conversion. • Catalytic combustion improves downhole heaters. • Simulation result guides experiments on catalytic combustion heater. [ABSTRACT FROM AUTHOR]

Catalytic converter (CATCO) and its effect on engine performance and exhaust gas temperature became an exciting field in automotive research. In this study purposed to compare existing CATCO which is ceramic and metallic with FeCrAl CATCO that treated with a combination of ultrasonic bath and electroplating technique in 30 minutes holding time (UB+EL 30 min). This study proposed to select an appropriate CATCO that used in a gasoline engine to increase the performance and to reduce the exhaust gas temperature as well as its potential to reduce the exhaust gas emission. Mitsubishi 4G93 conducted this analysis with 1.8 L and 10.5 compression ratio with a variable speed of 100, 2000 and 3000 rpm and different engine load of 10, 20 and 30%. The result shows that the FeCrAl CATCO was more useful to reduce fuel consumption up to 66.42% and increase torque up to 15.79% as well as reduce exhaust gas temperature up to 30.11% as compared to ceramic and metallic CATCO. It can be concluded that FeCrAl CATCO coated by UB+EL 30 min was recommended to increase engine performance and to reduce exhaust gas emission.

The creation of modern high-powered gas and gas-diesel engines is associated with the solution of two main tasks – the elimination of abnormal combustion and reduction of engine thermal factor. The paper discusses ways to reduce exhaust gas temperatures, methods to eliminate hot-tube ignition and detonation in single fuel gas engines. The ways of reducing exhaust gas temperatures, reducing the thermal factor of diesel injectors (pressure, duration of injection) and detonation issues in two-fuel gas-diesel engines are considered. The results of computational and experimental studies are presented. It is shown that due to the optimization of intake systems, fuel supply and control algorithms it is possible to significantly reduce the thermal stress of gas and gas-diesel engines, while ensuring the achievement of high values of the average effective cycle pressure up to 28 bar and the achievement of high volume power up to 43 kW/l.

Featured Application: A CFD-FVM model of the exhaust pipe of a compression-ignition engine has been used to raise the prediction capabilities of an indirect torque-evaluation model for that engine based on the exhaust gas temperature. The article illustrates in detail also the CFD-FVM model tuning procedure, making use of the Response Surface Methodology and specific procedures based on the exhaust gas temperature at three different locations along the exhaust pipe, detected in some preliminary experimental tests. A truly universal system to optimize consumptions, monitor operation and predict maintenance interventions for internal combustion engines must be independent of onboard systems, if present. One of the least invasive methods of detecting engine performance involves the measurement of the exhaust gas temperature (EGT), which can be related to the instant torque through thermodynamic relations. The practical implementation of such a system requires great care since its torque-predictive capabilities are strongly influenced by the position chosen for the temperature-detection point(s) along the exhaust line, specific for each engine, the type of installation for the thermocouples, and the thermal characteristics of the interposed materials. After performing some preliminary tests at the dynamometric brake on a compression-ignition engine for agricultural purposes equipped with three thermocouples at different points in the exhaust duct, a novel procedure was developed to: (1) tune a CFD-FVM-model of the exhaust pipe and determine many unknown thermodynamic parameters concerning the engine (including the real EGT at the exhaust valve outlet in some engine operative conditions), (2) use the CFD-FVM results to considerably increase the predictive capability of an indirect torque-detection strategy based on the EGT. The joint use of the CFD-FVM software, Response Surface Method, and specific optimization algorithms was fundamental to these aims and granted the experimenters a full mastery of systems' non-linearity and a maximum relative error on the torque estimations of 2.9%. [ABSTRACT FROM AUTHOR]

Backfire is one of the major technical issues in a port injection type hydrogen fuelled spark ignition engine. It is an abnormal combustion phenomenon (pre-ignition) that takes place in combustion chamber and intake manifold during suction stroke. The flame propagates toward the upstream of the intake manifold from combustion chamber during backfire and thus can damage the intake and fuel supply systems of the engine, and stall the engine operation. The main cause of backfire could be the presence of any hot spot, lubricating oil particle's traces (HC and CO due to evaporation of the oil) and hot residual exhaust gas present in the combustion chamber during suction stroke which could act as an ignition source for fresh incoming charge. Monitoring the temperatures of the lubricating oil and exhaust gas during engine operation can reduce the probability of backfire. This was achieved by developing an electronic device which delays the injection timing of hydrogen fuel with the inputs of engine oil temperature (T lube oil) and exhaust gas temperature (T exh). It was observed from the experimental results that the threshold values of T lube oil and T exh were 85 °C and 540 °C respectively beyond which backfire occurred at equivalence ratio (φ) of 0.82. The developed device works based on the algorithm that retards the hydrogen injection to 40 0aTDC whenever the temperatures (T lube oil and T exh) reached to the above mentioned values and thus the backfire was controlled. Delaying injection of hydrogen increased the time period at which only air is inducted during the early part of the suction stroke, this allows cooling of the available hot spots in the combustion chamber, hence the probability of backfire would be reduced. • Online monitoring of lube oil and exhast gas temperatures can reduce the backfire. • The threshold values of T lube oil and T exh were 85 °C and 540 °C at φ of 0.82. • The developed electronic device retards the H 2 injection to eliminate the backfire.. [ABSTRACT FROM AUTHOR]

Modern automotive gasoline engines have highly efficient after-treatment systems that reduce exhaust gas emissions. However, this efficiency greatly depends on the conditions of the exhaust gas, mainly the temperature and air–fuel ratio. The temperature instability during transient conditions may cause a reduction in the efficiency of the three-way catalyst (TWC). By using a thermal energy storage system before TWC, this negative effect can be suppressed. In this paper, the effects of the temperature stabilization on the efficiency of the three-way catalyst were investigated on a 1-D turbocharged gasoline engine model, with a focus on fuel consumption and emissions. The thermal energy storage system (TESS) was based on PCM materials and was built in the exhaust between the turbine and TWC to use the energy of the exhaust gas. Three different materials were picked up as possible mediums in the storage system. Based on the results, the usage of a TESS in a gasoline after-treatment system has shown great potential in improving TWC efficiency. This approach can assist the catalyst to operate under optimal conditions during the drive. In this study, it was found that facilitating the heat transfer between the PCM and the catalyst can significantly improve the emissions’ reduction performance by avoiding the catalyst to light out after the cold start. The TESS with PCM H430 proved to reduce the cumulative CO and HC emissions by 8.2% and 10.6%, respectively, during the drive. Although a TES system increases the after-treatment cost, it can result in emission reductions and fuel consumption over the vehicle’s operating life.

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In this study, balanites Aegyptiaca (L.) Del biodiesel was blended in proportions of 10% and 20% on the volume basis with diesel fuel and tested in a single cylinder, VCR diesel engine under measured load conditions with varied EGR rates (0, 10 and 20%). The results showed that B10 and B20 blends shown a significant reduction rate in terms of NOx emissions that were familiar with biodiesel blends. At peak load conditions, BTE increased slightly for test fuel blends compared with pure diesel fuel while the BSFC rate and EGT suffered from increasing and decreasing nature with respect to blending percentage. From the emissions point of view, with the increase in blends percentage, a significant reduction rate is observed in terms of CO and HC concentrations (up to 12.34 and 17.5%, respectively) while NOx emissions decreased at peak load conditions (up to 24.34%). HC and CO emissions decreased with increase in blends percentage. However, lower levels of NOx and EGT (up to 21.37 and 8.47%, respectively) and the average increase in terms of BTE and BSFC (up to 2.83 and 2.9%, respectively) can be realised with B20 test fuel blend under 20% EGR rate.

The present work investigates the engine emissions characteristics for direct injection diesel engine using coconut biodiesel, soya bean methyl ester and fish oil blends without any engine modifications. The coconut oil has three fuel samples, such as DF (100% diesel fuel), CB5 (5% coconut biodiesel and 95% DF), and CB15 (15% CB and 85% DF) respectively are used. Lower HC and CO, and higher CO2 and NOx emissions have been found for biodiesel blended fuels in comparison with the different blends of a soybean methyl ester (SME) with diesel fuel. There are two samples of SME oils such as B20 SME and B100 SME are used. The measured CO emissions of B20% SME and B100% SME were found to be 11.36% and 41.7% lower than that of diesel fuel. The various blends of fish-oil biodiesel with diesel, B25, B50, B75, B100 were used in the experiment. At full load, B100 fuel produced higher smoke, NOx, CO and HC emissions of 34.95%, 1.65%, 14.6%, and 1.8% respectively with reference to diesel fuel. [ABSTRACT FROM AUTHOR]

This paper presents the application of Fisher-Snedecor distribution F statistics to assess the significance of the influence of changes in the active cross-sectional area of the inlet air channel (Adol) flow in a diesel engine on the observed diagnostic parameter determined on the basis of measurements of the quick changing exhaust gas temperature in the outlet channel, which is the specific enthalpy of the exhaust gas stream within one engine operating cycle (hspal). A plan of experimental tests carried out on the laboratory stand of a single-cylinder Farymann Diesel type D10 laboratory engine was presented and the method of determination of F statistics values for the obtained measurement results was characterized. Representative results of calculations were presented and the strength of Adol input parameter influence on the determined diagnostic parameter hspal simplified physical model of the working process of a compression ignition engine as the object of diagnosis was evaluated. It is planned to further develop the experimental research program to determine the significance of the influence of changes in the values of selected parameters of the engine structure on other diagnostic measures determined from the exhaust gas temperature signal, i.e. the mean peak-to-peak value as well as the rate (intensity) of increase and decrease in its value for individual engine cycles. [ABSTRACT FROM AUTHOR]

High nitrogen oxide levels of the conventional diesel engine combustion often requires the introduction of exhaust gas recirculation at high engine loads. This can adversely affect the smoke emissions and fuel conversion efficiency associated with a reduction of the in-cylinder air-fuel ratio (lambda). In addition, low exhaust gas temperatures at low engine loads reduce the effectiveness of aftertreatment systems necessary to meet stringent emissions regulations. These are some of the main issues encountered by current heady-duty diesel engines. In this work, variable valve actuation-based advanced combustion control strategies have been researched as means of improving upon the engine exhaust temperature, emissions, and efficiency. Experimental analysis was carried out on a single-cylinder heady-duty diesel engine equipped with a high-pressure common-rail fuel injection system, a high-pressure loop cooled exhaust gas recirculation, and a variable valve actuation system. The variable valve actuation system enables a late intake valve closing and a second intake valve opening during the exhaust stroke. The results showed that Miller cycle was an effective technology for exhaust temperature management of low engine load operations, increasing the exhaust gas temperature by 40°C and 75°C when running engine at 2.2 and 6 bar net indicated mean effective pressure, respectively. However, Miller cycle adversely effected carbon monoxide and unburned hydrocarbon emissions at a light load of 2.2 bar indicated mean effective pressure. This could be overcome when combining Miller cycle with a second intake valve opening strategy due to the formation of a relatively hotter in-cylinder charge induced by the presence of internal exhaust gas recirculation. This strategy also led to a significant reduction in soot emissions by 82% when compared with the baseline engine operation. Alternatively, the use of external exhaust gas recirculation and post injection on a Miller cycle operation decreased high nitrogen oxide emissions by 67% at a part load of 6 bar indicated mean effective pressure. This contributed to a reduction of 2.2% in the total fluid consumption, which takes into account the urea consumption in aftertreatment system. At a high engine load of 17 bar indicated mean effective pressure, a highly boosted Miller cycle strategy with exhaust gas recirculation increased the fuel conversion efficiency by 1.5% while reducing the total fluid consumption by 5.4%. The overall results demonstrated that advanced variable valve actuation-based combustion control strategies can control the exhaust gas temperature and engine-out emissions at low engine loads as well as improve upon the fuel conversion efficiency and total fluid consumption at high engine loads, potentially reducing the engine operational costs. [ABSTRACT FROM AUTHOR]