The purpose of this study is to use machine learning to build a model capable of predicting the flash boiling spray characteristics. In this study, the flash boiling spray was visualized using Shadowgraph visualization technology, and then the spray image was processed with MATLAB to obtain quantitative data of spray characteristics. The experimental conditions were used as input, and the spray characteristics were used as output to train the machine learning model. For the machine learning model, the XGB (extreme gradient boosting) algorithm was used. Finally, the performance of machine learning model was evaluated using R2 and RMSE (root mean square error). In order to have enough data to train the machine learning model, this study used 12 injectors with different design parameters, and set various fuel temperatures and ambient pressures, resulting in about 12,000 data. By comparing the performance of the model with different amounts of training data, it was found that the number of training data must reach at least 7,000 before the model can show optimal performance. The model showed different prediction performances for different spray characteristics. Compared with the upstream spray angle and the downstream spray angle, the model had the best prediction performance for the spray tip penetration. In addition, the prediction performance of the model showed a relatively poor trend in the initial stage of injection and the final stage of injection. The model performance is expired to be further enhanced by optimizing the hyper-parameters input into the model.
BANG, Junsik;KIM, Jungkyu;KIM, YunJin;OH, Jung-Kwon;YEO, wanmyeong;KWAK, Hyo Won
Journal of the Korean Wood Science and Technology
/
제50권3호
/
pp.149-158
/
2022
To realize the infinite possibilities of materials derived from wood, it is necessary to overcome the weak moisture stability of wood. Thus, the development of an eco-friendly hydrophobic coating agent is essential, and of these, woody biomass-based materials are strongly attractive as coatings. In this study, eco-friendly hydrophobic wood coatings were prepared using carnauba wax purified from palm leaves and sprouts, and kraft lignin. The physicochemical properties of the carnauba wax/lignin blends according to the ratio of carnauba wax and lignin were observed by morphology and functional group change. In addition, the coating performance of carnauba wax/lignin blend coatings was confirmed by measuring the contact angle change. It was found that the addition of lignin could accelerate the atomization of wax particles, and that micro-roughness can be realized when applied to the actual wood surface, to ensure that the coating effect over time lasts longer. In addition, it was confirmed that the addition of lignin increases the hydrogen-bond-based interaction with the wood of the coating, thereby providing better coating stability and increasing the durability of the coating solvent under friction. The carnauba wax/lignin paint developed in this way is eco-friendly because all components are made of wood-based raw materials and have an excellent affinity with wood surfaces. Therefore, it is expected to be applicable to the coating process of wood-plastic composites and timber composites.
To implement carbon-neutrality in transportation sectors until 2050, hydrogen is considered a promising fuel for internal combustion engines because hydrogen does not contain carbon itself. Although hydrogen does not emit CO2 emission from its combustion process, the low energy density in a volume unit hinders the adoption of hydrogen. Therefore, the understanding of hydrogen jet behavior and measurement of equivalence ratio must be conducted to completely implement the high-pressure hydrogen direct injection. The main objective of this research is feasibility test of hydrogen local equivalence ratio measurement by laser-induced breakdown spectroscopy (LIBs). To visualize the macroscopic structure of hydrogen jet, high-speed schlieren imaging was conducted. Moreover, LIBs has been adopted to validate the feasibility of hydrogen local equivalence ratio measurement. The hydrogen injection pressure was varied from 4 MPa to 8 MPa and injected in a constant volume chamber where the ambient pressure was 0.5 MPa. The increased injection pressure extends the vertical penetration of hydrogen jet. Due to the higher momentum supply when the injection pressure is high, the hydrogen has easily diffused in all directions. As the laser trigger timing has delayed, the low hydrogen atomic emission was detected due to the longer mixture formation time. Based on equivalence ratio measurement results, LIBs could be applied as a methodology for hydrogen local equivalence ratio measurement.
This study examines whether engine fuel efficiency is improved by optimization of the exhaust valve timing in a state where the intake valve timing has been optimized in a small turbo gasoline engine that has intake cams and exhaust cams with fixed valve opening periods. When the exhaust valve is opened late, the expansion stroke is longer, and the efficiency can be improved. A 2-cylinder turbo gasoline engine with 0.8 liters of displacement and an MPI (Multi Point Injection) fuel system was used. The engine was operated at 1,500 and 3,000 rpm, and the load conditions included a partial load of 50 N·m and a high load of 70 N·m. Data was recorded as the exhaust valve timing was controlled, and this was used to calculate the efficiency of combustion using a heat release, the fuel conversion efficiency, and the pumping loss. Results and the hydrocarbon concentrations in the exhaust gas were compared for each condition. Experiment results confirmed that additional fuel efficiency improvements are possible through exhaust valve timing control at 1,500 rpm and 50 N·m. However, in other operating conditions, fuel efficiency improvements could not be obtained through exhaust valve timing control because cases where the pumping loss and fuel/air mixture slip increased when the exhaust valve timing changed and the fuel efficiency declined.
The objective of this numerical study is to investigate the effect of the shape and material of the blower blade for the electrified speed sprayer on the blowing performance. The shape of the blade was changed to the bonding angle, the number of blades, the width of the blade, and the blade length based on the existing model. In order to obtain the reliability of the numerical model, the analysis of the grid dependence was performed in the numerical analysis. The numerical analysis results were compared and analyzed in terms of the agricultural chemical penetration length characteristics, flow uniformity characteristics, and velocity distribution characteristics. Furthermore, the effect of material change on weight reduction and structural characteristics was also compared and analyzed. As a result of the analysis, it was found that the optimal condition was that the blade angle was 45°, the number of blades was 12, and the width was 115 mm, which was confirmed through a comparison of the inlet mass flow rate. As a result of the equivalent stress lower than the yield strength due to the material change from aluminum to steel compared to the existing steel, structural defects do not appear, and it is judged that the operation time compared to the battery capacity will be improved through the weight reduction of the blade.
The waste-heat-recovery boiler with water spray (HR-B/WS) applies the heat exchange between the inlet air and exhaust gas with the water spray into the inlet air. The evaporation of water in the inlet air promotes heat recovery from the exhaust gas so that thermal efficiency can be improved by the enhanced condensing effect. The NOx emission can also be reduced by lowering the flame temperature due to the dilution effect of the water. In this study, the validity of this concept is examined by the practical boiler test performed with a 24 kW condensing boiler under the full load condition according to the water injection amount. The theoretical amount of water injection is calculated under the assumption of full evaporation of the sprayed water, which is calculated as 50 g/min. Since the injected water cannot evaporate fully in the actual system, the maximum water spray amount is set as 100 g/min. The results showed that the water injection can increase the thermal efficiency up to 95.59% and reduce NOx and CO emissions simultaneously to 8.9 ppm and 35 ppm at 0% of O2. Although the heat energy loss increased due to the unevaporated water, the increase in water injection amount caused higher thermal efficiency due to the increased amount of the evaporated water.
In the cylinder of gasoline direct injection engines, the spray targeting from injectors is of great significance for fuel consumption and pollutant emissions. The automotive industry is putting a lot of effort into improving injector targeting accuracy. To improve the targeting accuracy of injectors, it is necessary to develop models that can predict the spray targeting positions. When developing spray targeting models, the most used technique is computational fluid dynamics (CFD). Recently, due to the superiority of machine learning in prediction accuracy, the application of machine learning in this field is also receiving constant attention. The purpose of this study is to build a machine learning model that can accurately predict spray targeting based on the design parameters of injectors. To achieve this goal, this study firstly used laser sheet beam visualization equipment to obtain many spray cross-sectional images of injectors with different parameters at different injection pressures and measurement planes. The spray images were processed by MATLAB code to get the targeting coordinates of sprays. A total of four models were used for the prediction of spray targeting coordinates, namely ANN, LSTM, Conv1D and Conv1D & LSTM. Features fed into the machine learning model include injector design parameters, injection conditions, and measurement planes. Labels to be output from the model are spray targeting coordinates. In addition, the spray data of 7 injectors were used for model training, and the spray data of the remaining one injector were used for model performance verification. Finally, the prediction performance of the model was evaluated by R2 and RMSE. It is found that the Conv1D&LSTM model has the highest accuracy in predicting the spray targeting coordinates, which can reach 98%. In addition, the prediction bias of the model becomes larger as the distance from the injector tip increases.
Cars are one of the main causes of air pollution in large cities, and 34.6% of domestic air pollution emissions come from mobile sources, of which cars account for 69.6%. In particular, the importance of nitrogen oxides (NOx) and particulate matter (PM), which are major pollutants in diesel vehicles, is increasing due to their high contribution to emissions. Therefore, in this study, the problem of natural regeneration caused by low exhaust gas temperature during low speed and low load operation was solved by applying a complex regeneration DPF that is not affected by temperature conditions to large diesel vehicles with higher driving time and engine displacement than small and medium-sized vehicles. And the feasibility of application to large diesel vehicles was reviewed by measuring the emission reduction efficiency. As a result of the reduction efficiency test on the actual vehicle durability product, PM showed a reduction efficiency of 84% to 86%, and the reduction efficiency of gaseous substances showed a high reduction efficiency of over 90%. The actual vehicle applicability test was completed with three driving patterns: village bus vehicle, police car, and road-going construction equipment vehicle, and no device problems occurred until the end of the test. Both load and no-load smoke measurement results showed a smoke reduction efficiency of over 96%.
As awareness of environmental pollution problems increases worldwide, interest in air pollutants is increasing. In particular, NOx and PM, which are major pollutants in diesel vehicles, are contributing significantly to emissions. As a result, its importance is increasing. In this study, based on research results applied to large diesel vehicles, the problem of natural regeneration caused by low exhaust gas temperature during low speed and low load operation is solved by applying a complex regeneration DPF that is not affected by temperature conditions to small diesel vehicles. The feasibility of application to small diesel vehicles was reviewed by measuring the emission reduction efficiency. As a result of the engine test, the power reduction rate and fuel consumption rate before and after device installation under full load conditions were 2.9% decrease and 3.5% increase, respectively, satisfying the standard for a 5% reduction, and as a result of the regeneration equilibrium temperature (BPT) test, the regeneration temperature was 310℃. appeared at the level. The reduction efficiency test results for the actual vehicle durability test equipment showed 97.3% PM, 51.0% CO, and 31.1% HC, while the city commuter vehicle had PM 97.5%, CO 61.7%, HC 40.0%, and the school bus vehicle had PM 96.8%, CO 44.4%, HC 34.3%, and low-speed logistics vehicles showed a reduction efficiency of 98.2% for PM, 36.0% for CO, and 45.7% for HC. Based on the results of this study, in the future, it is necessary to secure DPF technology suitable for all vehicle types through actual vehicle application research on temperature condition-insensitive composite regenerative DPF for medium-sized vehicles.
Understanding the fundamental characteristics of supersonic hydrogen jets is important for the optimization of combustion in hydrogen engines. Previous studies have used helium as a surrogate gas to characterize the hydrogen jet characteristics due to potential explosion risks of hydrogen. It was based on the similarity of hydrogen and helium jet structures in supersonic conditions that has been confirmed using hole-type injectors and large-cone-angle pintle-type injectors. However, the validity of using helium as a surrogate gas has not been examined for recent small-cone-angle pintle-type injectors applied to direct-injection hydrogen engines, which form a supersonic hollow cone near the nozzle and experience the jet collapse downstream. Differences in the physical properties of hydrogen and helium could alter the jet development characteristics that need to be investigated and understood. This study compares supersonic jet structures of hydrogen and helium injected by a small-cone-angle (50°) pintle-type hydrogen injector and discusses their differences and related mechanisms. Jet penetration length and dispersion angle are measured using the Schlieren imaging method under engine-like injection conditions. As a result, the penetration length of hydrogen and helium jets showed a slight difference of less than 5%, and the dispersion angle showed a maximum of 10% difference according to the injection condition.
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