• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.1
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• pp.9-18
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• 2015

In this paper, we verify the optimal topology design for heat conduction problems in steady stated which is obtained numerically using the adjoint design sensitivity analysis(DSA) method. In adjoint variable method(AVM), the already factorized system matrix is utilized to obtain the adjoint solution so that its computation cost is trivial for the sensitivity. For the topology optimization, the design variables are parameterized into normalized bulk material densities. The objective function and constraint are the thermal compliance of the structure and the allowable volume, respectively. For the experimental validation of the optimal topology design, we compare the results with those that have identical volume but designed intuitively using a thermal imaging camera. To manufacture the optimal design, we apply a simple numerical method to convert it into point cloud data and perform CAD modeling using commercial reverse engineering software. Based on the CAD model, we manufacture the optimal topology design by CNC.

• 한국지구물리탐사학회:학술대회논문집
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• 2004.06a
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• pp.3-17
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• 2004

Space-borne Earth observation technique is one of the most cost effective and rapidly advancing Earth science research tools today and the potential field and micro-wave radar applications have been leading the discipline. The traditional optical imaging systems including the well known Landsat, NOAA - AVHRR, SPOT, and IKONOS have steadily improved spatial imaging resolution but increasing cloud covers have the major deterrent. The new Earth observation satellites ENVISAT (launched on March 1 2002, specifically for Earth environment observation), ALOS (planned for launching in 2004 - 2005 period and ALOS stands for Advanced Land Observation Satellite), and RADARSAT-II (planned for launching in 2005) all have synthetic aperture radar (SAR) onboard, which all have partial or fully polarimetric imaging capabilities. These new types of polarimetric imaging radars with repeat orbit interferometric capabilities are opening up completely new possibilities in Earth system science research, in addition to the radar altimeter and scatterometer. The main advantage of a SAR system is the all weather imaging capability without Sun light and the newly developed interferometric capabilities, utilizing the phase information in SAR data further extends the observation capabilities of directional surface covers and neotectonic surface displacements. In addition, if one can utilize the newly available multiple frequency polarimetric information, the new generation of space-borne SAR systems is the future research tool for Earth observation and global environmental change monitoring. The potential field strength decreases as a function of the inverse square of the distance between the source and the observation point and geophysicists have traditionally been reluctant to make the potential field observation from any space-borne platforms. However, there have recently been a number of potential field missions such as ASTRID-2, Orsted, CHAMP, GRACE, GOCE. Of course these satellite sensors are most effective for low spatial resolution applications. For similar objects, AMPERE and NPOESS are being planned by the United States and France. The Earth science disciplines which utilize space-borne platforms most are the astronomy and atmospheric science. However in this talk we will focus our discussion on the solid Earth and physical oceanographic applications. The geodynamic applications actively being investigated from various space-borne platforms geological mapping, earthquake and volcano .elated tectonic deformation, generation of p.ecise digital elevation model (DEM), development of multi-temporal differential cross-track SAR interferometry, sea surface wind measurement, tidal flat geomorphology, sea surface wave dynamics, internal waves and high latitude cryogenics including sea ice problems.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.2
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• pp.29-33
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• 2010

The purpose of LiDAR ground classification is to archive both goals which are acquiring confident ground points with high precision and describing ground shape in detail. In spite of many studies about developing optimized algorithms to kick out this, it is very difficult to classify ground points and describing ground shape by airborne LiDAR data. Especially it is more difficult in a dense forested area like Korea. Principle misclassification was mainly caused by complex forest canopy hierarchy in Korea and relatively coarse LiDAR points density for ground classification. Unfortunately, a lot of LiDAR surveying performed in summer in South Korea. And by that reason, schematic LiDAR points distribution is very different from those of Europe. So, this study propose enhanced ground classification method considering Korean land cover characteristics. Firstly, this study designate highly confident candidated LiDAR points as a first ground points which is acquired by using big roller classification algorithm. Secondly, this study applied weighted gradient kernel(WGK) algorithm to find and include highly expected ground points from the remained candidate points. This study methods is very useful for reconstruct deformed terrain due to misclassification results by detecting and include important terrain model key points for describing ground shape at site. Especially in the case of deformed bank side of river area, this study showed highly enhanced classification and reconstruction results by using WGK algorithm.

• Journal of Bio-Environment Control
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• v.28 no.4
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• pp.358-365
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• 2019

This study was conducted to estimate the dimensions of horticultural products and the mean plant height of plug seedlings using three-dimensional (3D) images. Two types of camera, a ToF camera and a stereo-vision camera, were used to acquire 3D images for horticultural products and plug seedlings. The errors calculated from the ToF images for dimensions of horticultural products and mean height of plug seedlings were lower than those predicted from stereo-vision images. A new indicator was defined for determining the mean plant height of plug seedlings. Except for watermelon with tap, the errors of circumference and height of horticultural products were 0.0-3.0% and 0.0-4.7%, respectively. Also, the error of mean plant height for plug seedlings was 0.0-5.5%. The results revealed that 3D images can be utilized to estimate accurately the dimensions of horticultural products and the plant height of plug seedlings. Moreover, our method is potentially applicable for segmenting objects and for removing outliers from the point cloud data based on the 3D images of horticultural crops.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.174-192
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• 2021

The LIDAR sensor, which provides higher cognitive performance than cameras and radar, is difficult to apply to ADAS or autonomous driving because of its high price. On the other hand, as the price is decreasing rapidly, expectations are rising to improve existing autonomous driving functions by taking advantage of the LIDAR sensor. In level 3 autonomous vehicles, when a dangerous situation in the cognitive module occurs due to a sensor defect or sensor limit, the driver must take control of the vehicle for manual driving. If the driver does not respond to the request, the system must automatically kick in and implement a minimum risk maneuver to maintain the risk within a tolerable level. In this study, based on this background, a LIDAR-based LKS MRM algorithm was developed for the case when the normal operation of LKS was not possible due to troubles in the cognitive system. From point cloud data collected by LIDAR, the algorithm generates the trajectory of the vehicle in front through object clustering and converts it to the target waypoints of its own. Hence, if the camera-based LKS is not operating normally, LIDAR-based path tracking control is performed as MRM. The HAZOP method was used to identify the risk sources in the LKS cognitive systems. B, and based on this, test scenarios were derived and used in the validation process by simulation. The simulation results indicated that the LIDAR-based LKS MRM algorithm of this study prevents lane departure in dangerous situations caused by various problems or difficulties in the LKS cognitive systems and could prevent possible traffic accidents.

• Journal of Cadastre & Land InformatiX
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• v.52 no.1
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• pp.69-80
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• 2022

Drone photogrammetry generally acquires images vertically or obliquely from above, so when photographing for the purpose of three-dimensional modeling, image matching for the ground of a building and spatial accuracy of point cloud data are poor, resulting in poor 3D mesh completeness. Therefore, to overcome this, this study analyzed the spatial accuracy of each drone image by acquiring smartphone images from the ground, and evaluated the accuracy improvement and completeness of 3D mesh when the smartphone image is not combined with the drone image. As a result of the study, the horizontal (x,y) accuracy of drone photogrammetry was about 1/200,000, similar to that of traditional photogrammetry. In addition, it was analyzed that the accuracy according to the photographing method was more affected by the photographing angle of the object than the increase in the number of photos. In the case of the smartphone image combination, the accuracy was not significantly affected, but the completeness of the 3D mesh was able to obtain a 3D mesh of about LoD3 that satisfies the digital twin city standard. Therefore, it is judged that it can be sufficiently used to build a 3D model for digital twin city by combining drone images and smartphones or DSLR images taken on the ground.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.245-256
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• 2021

This study was conducted to identify the applicability of a LiDAR sensor to forest resources inventories by comparing data on a tree's position, height, and DBH obtained by the sensor with those by existing forest inventory methods, for the tree species of Criptomeria japonica in Jeolmul forest in Jeju, South Korea. To this end, a backpack personal LiDAR (Greenvalley International, Model D50) was employed. To facilitate the process of the data collection, patterns of collecting the data by the sensor were divided into seven ones, considering the density of sample plots and the work efficiency. Then, the accuracy of estimating the variables of each tree was assessed. The amount of time spent on acquiring and processing the data by each method was compared to evaluate the efficiency. The findings showed that the rate of detecting standing trees by the LiDAR was 100%. Also, the high statistical accuracy was observed in both Pattern 5 (DBH: RMSE 1.07 cm, Bias -0.79 cm, Height: RMSE 0.95 m, Bias -3.2 m), and Pattern 7 (DBH: RMSE 1.18 cm, Bias -0.82 cm, Height: RMSE 1.13 m, Bias -2.62 m), compared to the results drawn in the typical inventory manner. Concerning the time issue, 115 to 135 minutes per 1ha were taken to process the data by utilizing the LiDAR, while 375 to 1,115 spent in the existing way, proving the higher efficiency of the device. It can thus be concluded that using a backpack personal LiDAR helps increase efficiency in conducting a forest resources inventory in an planted coniferous forest with understory vegetation, implying a need for further research in a variety of forests.

• Korean Chemical Engineering Research
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• v.40 no.6
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• pp.703-708
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• 2002

High pressure phase behavior data for poly(propyl acrylate) and poly(propyl methacrylate) with supercritical $CO_2$, ethylene, propane, butane, propylene, 1-butene, dimethyl ether, and $CHClF_2$ were measured in the temperature range from $23^{\circ}C$ to $186^{\circ}C$ and at pressures up to 2,400 bar. The cloud point were obtained at dissolved pressure below 2,070, 1,400, 1,880, 450, 2,200, 250, and 150 bar for poly(propyl acrylate) in supercritical $CO_2$, ethylene, propane, propylene, butane, 1-buthen, and dimethyl ether, respectively. The temperature range is $23-175^{\circ}C$. The poly(propyl methacrylate) does not dissolve in $CO_2$ at temperature of $240^{\circ}C$ and pressure 2,900 bar. The poly(propyl methacrylate)-propane, poly(propyl methacrylate)-butane, poly(propyl methacrylate)-propylene, poly(propyl methacrylate)-1-butene, and poly(propyl methacrylate)-$CHClF_2$ systems were dissolved at the pressures less than 2,390 bar, below 2,100 bar, below 570 bar, below 310 bar, below 300 bar, and below 170 bar, respectively. The temperature range shows from 40 to $186^{\circ}C$. The phase behavior of between binary poly(propyl acrylate)-$CO_2$ and poly(propyl acrylate)-dimethyl ether system were measured from upper critical solution temperature region to lower critical solution temperature region with added dimethyl ether concentrations of 5, 15 and 50 wt%.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.387-397
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• 2023

Plant height is a growth parameter that provides visible insights into the plant's growth status and has a high correlation with yield, so it is widely used in crop breeding and cultivation research. Investigation of the growth characteristics of crops such as plant height has generally been conducted directly by humans using a ruler, but with the recent development of sensing and image analysis technology, research is being attempted to digitally convert growth measurement technology to efficiently investigate crop growth. In this study, the canopy height of rice grown at various nitrogen fertilization levels was measured using a laser scanner capable of precise measurement over a wide range, and a comparative analysis was performed with the actual plant height. As a result of comparing the point cloud data collected with a laser scanner and the actual plant height, it was confirmed that the estimated plant height measured based on the average height of the top 1% points showed the highest correlation with the actual plant height (R² = 0.93, RMSE = 2.73). Based on this, a linear regression equation was derived and used to convert the canopy height measured with a laser scanner to the actual plant height. The rice growth curve drawn by combining the actual and estimated plant height collected by various nitrogen fertilization conditions and growth period shows that the laser scanner-based canopy height measurement technology can be effectively utilized for assessing the plant height and growth of rice. In the future, 3D images derived from laser scanners are expected to be applicable to crop biomass estimation, plant shape analysis, etc., and can be used as a technology for digital conversion of conventional crop growth assessment methods.