Validity Analysis of Spray Model by Comparing Simulated with Measured Spray Liquid and Vapor Phase

( Zhe Sun ),( Xue Dong ),( Peng Yin ),( Tianyun Li ),( David L. S. Hung ),( Min Xu ) 한국액체미립화학회 2017 한국액체미립화학회 학술강연회 논문집 Vol.2017 No.-

Gasoline direct injection (GDI) Engine is proved to be a key technology to save energy and reduce emissions, which improves the overall engine performance. Spray injection affect the fuel-air mixing directly and computational fluid dynamics(CFD)software is utilized to model the macroscopic shape of the spray and the vapor mass. In this paper, the liquid and vapor phase of the spray of a one-hole injector was studied both experimentally and numerically. The structure and concentration distribution of the vapor phase of the spray, vapor mass and spray penetration were measured using laser induced exciplex fluorescence (LIEF) technique in a constant volume chamber. The simulations were performed by the CONVERGE software. Both the spray penetration and Sauter Mean Diameter (SMD) employed in the simulation were calibrated with the in-chamber measurements. The comparison of vapor concentration between the simulated results and the measured results acquired from the chamber suggest that the evaporation model of the single component fuel has significant influence on the simulated results. In addition, an analysis based on the present evaporation model has been made in this study. The results show that the 2-D plane and local line distributions of vapor concentration in simulation do not best match those from the experiments. It is found to get higher vapor concentration in the simulation model, suggesting that the relationship between vapor concentration and evaporation rate should be considered and further verified.

Nonlinear Finite Element Analysis of Prestressed Concrete Containment Vessel under Severe Accident Loads

Song Jin,Zhongcheng Li,Tianyun Lan,Zhanfa Dong,Jinxin Gong 대한토목학회 2020 KSCE JOURNAL OF CIVIL ENGINEERING Vol.24 No.3

Prestressed concrete containment vessel act as a reliable leak tight barrier during the accident conditions. There is a growing demand to study nonlinear behavior of containment structure under severe accident loads in depth. This paper presents nonlinear finite element analysis of prsestressed concrete containment vessel under severe accident loads with consideration of material nonlinearity, penetrations, local reinforcement and temperature-dependent degradationcharacteristic of materials. To reflect the prestressing effects realistically, non-uniform distribution of effective prestressing along the tendon profile is explicitly considered and python scripts are developed to add the corresponding temperature drop value for each node of the prestressed tendons to ABAQUS input files automatically. Nonlinear finite element analysis for pressure only case and combined thermal and pressure case has been investigated in detail. Nonlinear finite element analysis results of the containment structure indicate that, thermal effects have negligible effect on pressure capacity of containment, considering the thermal effects, pressure capacity of containment decrease not more than 5% and margin of the containment still meets the requirements of not less than 2.5. The effect of temperature exhibit significantly influence on displacement response of containment structure, and the effect of temperature on the strain of liner and reinforcing steel is much greater than that on prestressed tendon. Thermal effects exhibit the greatest influence on nonlinear displacement response of the dome apex location and the least influence on the 33 m elevation.

On the Pacific Decadal Oscillation Simulations in CMIP6 Models: A New Test‑Bed from Climate Network Analysis

Yiling Ma,Naiming Yuan,Tianyun Dong,Wenjie Dong 한국기상학회 2023 Asia-Pacific Journal of Atmospheric Sciences Vol.59 No.1

As a dominant pattern of the North Pacific sea surface temperature decadal variability, the Pacific Decadal Oscillation (PDO) has remarkable influences on the marine and terrestrial ecosystems. However, the PDO is highly unpredictable. Here, we assess the performance of the Coupled Model Intercomparison Project Phase 6 (CMIP6) models in simulating the PDO, with an emphasis on the evaluation of CMIP6 models in reproducing a recently detected early warning signal based on climate network analysis for the PDO regime shift. Results show that the skill of CMIP6 historical simulations remains at a low level, with a skill limited in reproducing PDO’s spatial pattern and nearly no skill in reproducing the PDO index. However, if the warning signal for the PDO regime shift by climate network analysis is considered as a test-bed, we find that even in historical simulations, a few models can represent the corresponding relationship between the warning signal and the PDO regime shift, regardless of the chronological accuracy. By further conducting initialization, the performance of the model simulations is improved according to the evaluation of the hindcasts from two ensemble members of the Decadal Climate Prediction Project (NorCPM1 and BCC-CSM2-MR). Particularly, we find that the NorCPM1 model can capture the early warning signals for the late-1970s and late-1990s regime shifts 5–7 years in advance, indicating that the early warning signal somewhat can be captured by some CMIP6 models. A further investigation on the underlying mechanisms of the early warning signal would be crucial for the improvement of model simulations in the North Pacific.

SUPPRESSED PROMPT ATOMIZATION OF FLASHBOILING SPRAY BY ELEVATING INJECTION PRESSURE

( Qinglin Xu ),( Min Xu ),( David L. S. Hung ),( Tianyun Li ),( Xue Dong ) 한국액체미립화학회 2017 한국액체미립화학회 학술강연회 논문집 Vol.2017 No.-

In a direct injection spark ignition (DISI) engine, the mixing time of the fuel with intake air in the cylinder is limited, thus quicker atomization and evaporation are desired. In general, there are two viable ways to promote these processes. One of them is by increasing the injection pressure, which has always been the key technology adopted by automobile manufacturers to improve the engine performance and meet the emission regulations. While high-pressure injection is already applied in most of the DISI engines, it has been reported that further increase of injection pressure is still beneficial on fuel efficiency and emissions reduction. In addition to this, flash-boiling is also regarded as an effective way to improve fuel atomization and evaporation with the potential to reduce fuel consumption and emissions. Existing research on flash-boiling spray mainly focuses on the multi-hole injector. Its plume-to-plume interaction phenomenon, as called “collapse”, has been thoroughly studied. Its benefits on atomization and evaporation have been proved. However, limited work has been done on the flash-boiling spray of a single-hole injector. Its breakup mechanism and movement behavior need to be further studied. Moreover, the study of high pressure gasoline spray beyond 35 MPa is also limited, especially at flash-boiling conditions. The effects of injection pressure on flash-boiling spray is still unrevealed. Therefore, the objective of this work is to study the influence of the superheat degree and injection pressure on the spray penetration and dispersion of a single-hole injector. Results show that in promoting dispersion and reducing penetration of the fuel, the effect of superheat degree was better than that of high injection pressure. In addition, increasing injection pressure of superheated fuel led to the increase in the tip penetration and decrease in the spray width while the injection pressure had opposite effects on subcooled fuel spray.

Using GA - BP Coupling Algorithm to Predict the High-performance Concrete Mechanical Property

Libing Jin,Jie Duan,Tai Fan,Pengfei Jiao,Tianyun Dong,Qiang Wu 대한토목학회 2023 KSCE Journal of Civil Engineering Vol.27 No.2

As a cementitious composite, concrete’s property depends on the matrix generated from cement hydration and the dispersed phases such as aggregates. Compression strength is an important mechanics performance index of concrete quality, especially the High-performance Concrete (HPC). However, owing to the expensive cost of test and the existence of high-dimensional nonlinear mapping between compression strength and basic materials, it is uneasiness to precisely forecast the compression strength value of HPC by general formula method. In this research, a novel machine learning system, Genetic Algorithm and BP Neural Network (GA-BPNN) coupling algorithm, is offered to predict the compression strength of HPC. GA-BPNN coupling algorithm model used 181 groups of HPC mixture data to determine 8 factors affecting its compression strength (i.e., Water, Portland Cement, Water-binder Ratio, Fine Aggregate Ratio, Air-entraining Agent, Fly Ash, Silica Fume, and Superplasticizer) as the input variables of the model, while compression strength was set as the output variable. In addition, 166 sets of training set data were segmented into training, validation and test set again, and BP neural network (BPNN) was compared with GA-BPNN to verify the generalizationcapacity of the model in this research. By forecasting the compression strength of 15 test sets, the average relative error is only 0.902%. Finally, the sensitivity of input variables of GA-BPNN model was analyzed by using Gray Relational analysis (GRA) method. Six models were established to research the impact of sensitivity and quantity of input variables on model performance by ignoring individual input variable. The research is shown that GA-BPNN model not only has the powerful nonlinear mapping ability of BPNN, but also has the global search optimization ability of GA, and showed stronger robustness and prediction potential in the assessment of compression strength value of HPC. The sensitivity analysis shows that, to compression strength of HPC, Cement, Water and Water-binder ratio has a sensitivity score of 0.8166, 0.70122, 0.66772, respectively while Fly Ash has the lowest sensitivity.