• Journal of ILASS-Korea
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• v.28 no.1
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• pp.1-9
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• 2023

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.

• International Journal of Reliability and Applications
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• v.7 no.1
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• pp.27-39
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• 2006

Many real world cases in material failure analysis do not follow perfectly the normal distribution. Forcing of the normality assumption may lead to inaccurate predictions and poor product quality. We examine the failure process of the internal bond (IB or tensile strength) of medium density fiberboard (MDF). We propose a forced censoring technique that closer fits the lower tails of strength distributions and better estimates extremely smaller percentiles, which may be valuable to continuous quality improvement initiatives. Further analyses are performed to build an accelerated common-shaped Weibull model for different product types using the $JMP^{(R)}$ Survival and Reliability platform. In this paper, a forced censoring technique is implemented for the first time as a software module, using $JMP^{(R)}$ Scripting Language (JSL) to expedite data processing, which is crucial for real-time manufacturing settings. Also, we use JSL to automate the task of fitting an accelerated Weibull model and testing model homogeneity in the shape parameter. Finally, a package script is written to readily provide field engineers customized reporting for model visualization, parameter estimation, and percentile forecasting. Our approach may be more accurate for product conformance evaluation, plus help reduce the cost of destructive testing and data management due to reduced frequency of testing. It may also be valuable for preventing field failure and improved product safety even when destructive testing is not reduced by yielding higher precision intervals at the same confidence level.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2702-2719
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• 2013

A new optimal scheme based on curvelet transform is proposed for retinal image enhancement (RIE) using real-coded quantum genetic algorithm. Curvelet transform has better performance in representing edges than classical wavelet transform for its anisotropy and directional decomposition capabilities. For more precise reconstruction and better visualization, curvelet coefficients in corresponding subbands are modified by using a nonlinear enhancement mapping function. An automatic method is presented for selecting optimal parameter settings of the nonlinear mapping function via quantum genetic search strategy. The performance measures used in this paper provide some quantitative comparison among different RIE methods. The proposed method is tested on the DRIVE and STARE retinal databases and compared with some popular image enhancement methods. The experimental results demonstrate that proposed method can provide superior enhanced retinal image in terms of several image quantitative evaluation indexes.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.09a
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• pp.173-183
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• 2010

Numerical analysis using a three dimensional finite element program(ABAQUS) is a powerful method which can evaluate the soil-pile-structure interaction under the dynamic loading and reduce the computation time significantly, but has not be widely used because modeling a soil-pile system and setting the parameter for the entire model are difficult and a three dimensional finite element program is not user friendly. However, a three dimensional finite element program is expected to be widely used because of advance in research of modeling technique and development of the modeling and visualization. In this study, ABAQUS is used to simulate the 1g shaking table model pile test, and the numerical results are compared with the 1g shaking table test results. The application about the soil stiffness and boundary condition change is estimated and then parametric study for various input acceleration amplitudes, various input frequencies, and various surcharge is carried out.

• Journal of Biosystems Engineering
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• v.37 no.3
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• pp.131-139
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• 2012

In this study, we developed a simulation program for the prediction of tractive performance of a tractor, by applying a widely used empirical model for tractive performance prediction of single tire, Brixius. The tractive performance prediction program can readily predict and estimate tractive performance according to various soil conditions and different specifications of tractors. The program was developed with the considerations of tractor's specification-related parameters (e.g., weight, tire size, and wheelbase of the tractor), a soil parameter (i.e., cone index which represents the soil strength), and operating conditions of the tractor (e.g., theoretical speed and driving types such as 2WD and 4WD). Also, the program was designed to provide tractive performance prediction results of tractors such as gross traction, motion resistance, net traction, and tractive efficiency, in the form of not only numerical values but also graphical visualization. To evaluate the feasibility of the program, we input three different soil conditions (which have different cone indexes each other) and tractor operating conditions to the program and analyzed the tractive performance from each input condition. From the analysis, it can be concluded that the developed program can be effectively utilized to predict the tractive performance under various soil conditions and driving types of tractors with different specifications.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.2
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• pp.136-142
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• 2007

A small supersonic wind tunnel was designed and built to study the flow characteristics of a supersonic impulse turbine cascade. The supersonic cascade with a 2-dimensional supersonic nozzle was tested for the axial gap ratio (${\delta}$) of the supersonic turbine that is the one of the turbine design parameter. Firstly, the flow was visualized by a single pass Schlieren system. Next, total and static pressure of the cascade were measured by a pressure scanning system. Highly complicated flow patterns including shocks, nozzle-cascade interaction and shock boundary layer interactions, flow characteristics of the supersonic turbine were observed.

• Journal of the Korea Computer Industry Society
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• v.2 no.10
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• pp.1291-1300
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• 2001

This article come to study the visualization representation technique of eye brain of person, basing on the ground of the dynamic graphics which is able to change the real time, manipulating the image as graphic factors of the multi-data. And the important thought in such realization is as follows ; corresponding the character points of human face and the parameter control value which obtains basing on the existing image recognition algorithm to the multi-dimensional data, synthesizing the image, it is to create the virtual image from the emotional expression according to the changing contraction expression. The proposed DyFIG system is realized that it as the completing module and we suggest the module of human face graphics which is able to express the emotional expression by manipulating and experimenting, resulting in realizing the emotional data expression description and technology.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2006.05a
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• pp.361-366
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• 2006

A small supersonic wind tunnel was designed and built to study the flow characteristics of a supersonic impulse turbine cascade. The supersonic cascade with a 2-dimensional supersonic nozzle was tested for the leading edge chamfer angle $(\gamma)$ of the supersonic turbine that is the one of the turbine design parameter. Firstly, the flow was visualized by a single pass Schlieren system. Next, total and static pressure of the cascade were measured by a pressure scanning system. Finally, highly complicated flow patterns including shocks, nozzle-cascade interaction and shock boundary layer interactions, flow characteristics of the supersonic turbine were observed.

• Journal of Korea Multimedia Society
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• v.12 no.1
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• pp.50-57
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• 2009

This paper proposes a extraction of feature lines on a polygonal model using local implicit surface fitting technique. To extract feature lines on a polygonal model, the previous technique addressed to compute the curvature and their derivatives at mesh vertices via global implicit surface fitting. It needs a user-specified precision parameter for finding an accurate projection of the mesh vertices onto an approximating implicit surface and requires high-time consumption. But we use a local implicit surface fitting technique to estimate the local differential information near a vertex by means of an approximating surface. Feature vertices are easily detected as zero-crossings, and can then be connected along the direction of principal curvature. Our method, demonstrated on several large polygonal models, produces a good fit which leads to improved visualization.

• Journal of the Korea Computer Graphics Society
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• v.8 no.1
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• pp.1-11
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• 2002

In order to widely use volume rendering technology in practical fields, a user should be able to control the classification parameter interactively and extract a meaningful information easily from the 3D data as fast as it can be. Previous work on an accelerating volume rendering reconstructs an isotropic volume from an anisotropic one and classifies in pre-processing time and then renders the classified volume rapidly in run time. But, this traditional step may result in long pre-processing time and no real-time feedback. In this paper, we present an efficient classification and rendering method that allows a user to set the opacity transfer function interactively at rendering time on a personal computer without special-purpose hardware.