• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.1
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• pp.32-40
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• 2018

In this research, a method of deriving statistical weight prediction formula which is used during the conceptual design phase was studied and it was programmed using Microsoft Excel and verified by applying to jet transport aircraft. The database was built while referencing the variables of conventional wing weight estimation formulas and it was used for modeling the jet transport wing weight regression equation. The model was evaluated using the K-fold cross validation method to solve the overfitting problem of the model.

• International Journal of Highway Engineering
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• v.6 no.3 s.21
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• pp.55-64
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• 2004

Maximum dry unit weight, ${\gamma}_{dmax}$, is the most important engineering properties for subgrade soil. Existing models to predict ${\gamma}_{dmax}$ containing many parameters, seem to be rather complex. This paper presents new simple models to predict ${\gamma}_{dmax}$. for sandy soils, A number of sieve analysis and compaction tests for 36 types of sands were conducted to develop the regression-based models. Parameters used to estimate ${\gamma}_{dmax}$ are both the geometric mean and geometric standard deviation of the soils, or the particle-size distribution curve parameters. Maximum dry unit weights predicted by the models are in good agreement with the laboratory measurements for the soil samples obtained at 16 locations within the Korea.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2023.11a
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• pp.251-252
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• 2023

본 연구에서는 오염물의 선택적 흡수가 가능한 반응재료의 분광정보 예측을 위하여 반응재료 배합 조건에 따른 분광정보와 최대건조단위중량의 상관관계를 평가하였다. 그 결과, 배합 조건에 따라 최대건조단위중량 증가하게 되면, 최대분광반사율은 감소하였고, 이를 바탕으로 분광정보 경향의 예측이 가능하였다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.9
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• pp.723-734
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• 2018

A structural weight estimation methodology for the multicopter design process is presented. In general, a multicopter is composed of an airframe, motors, propellers, battery and so on. Among these, the weight of motors, propellers and battery can be obtained from the weight trends with respect to design parameters. However, the structural weight is hard to be estimated due to the various configurations and design concepts of multicopters. Moreover, the airframe weights of most commercial multicopter products are not provided. Thus, an accurate airframe weight model is required for the reliable mutlcopter design process. Firstly, the standard configuration of multicopters is defined. Then, we proposed the structural weight estimation method using the number and diameter of propellers determined from the initial step of sizing process. Finally, we validated our suggested method using the commerical products.

• Applied Biological Chemistry
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• v.27 no.3
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• pp.146-150
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• 1984

Changes of weight loss and quality in 3 different apple cultivars and four storage conditions were investigated for 6 month storage. Weight loss changes in the pilot scale low temperature storage $(^{\circ}C)$ could be predicted with linear equations. Quality defects were remarkably increased at 5% of weight loss in all cultivars and storage conditions. It was possible to predict by linear equations the quality of apples by measuring acidity and texture highly correlated to the sensory scores.

• Journal of the Korean Society of Propulsion Engineers
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• v.17 no.3
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• pp.56-66
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• 2013

Weight reduction of the VTHL / TSTO type of the reusable launch vehicles using RBCC engines are investigated. To predict weight and thrust of the vehicles, equations of motion are analyzed. Analysis results are compared with specifications of existing launch vehicles for validations. For the mission of inserting 2.5 ton payload to 200 km circular orbit, the case A, which uses the RBCC engine in the 1st stage shows smaller weight than the case B, which uses the RBCC engine in the 2nd stage. The weight of the case A shows only 25.8% of a existing rocket launch vehicle's weight.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.4
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• pp.236-244
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• 2024

A representative problem in domestic chestnut industry is the high loss of flesh due to excessive knife peeling in order to increase the peeling rate, resulting in a decrease in production efficiency. In this study, a prediction model for weight loss rate of chestnut by stage of knife peeling process was developed as undergarment study to optimize conditions of the machine. 51 control conditions of the two-stage blade peeler used in the experiment were derived and repeated three times to obtain a total of 153 data. Machine learning(ML) models including artificial neural network (ANN) and random forest (RF) were implemented to predict the weight loss rate by chestnut peel stage (after 1st peeling, 2nd peeling, and after final discharge). The performance of the models were evaluated by calculating the values of coefficient of determination (R), normalized root mean square error (nRMSE), and mean absolute error (MAE). After all peeling stages, RF model have better prediction accuracy with higher R values and low prediction error with lower nRMSE and MAE values, compared to ANN model. The final selected RF prediction model showed excellent performance with insignificant error between the experimental and predicted values. As a result, the proposed model can be useful to set optimum condition of knife peeling for the purpose of minimizing the weight loss of domestic chestnut flesh with maximizing peeling rate.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.2
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• pp.529-536
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• 2014

Physical characteristics of cement-admixed clay such as water content, specific gravity, unit weight and void ratio are main factors for strength, compressibility and prediction of consolidation behavior. In the past, the physical characteristics of admixed soils could be understanded through complex laboratory tests and field survey after construction. In this study, the tests were performed with conditions such as clay water contents 0%-170%, cement contents 5%-25% and curing period 3-90days after that analyzed for changes which are water content, specific gravity unit weight and void ratio of admixed soils. A prediction of properties through mechanical relationships with clay in situ water content, cement content and curing period could be proposed using the test results. The prediction equation of void ratio of admixed soils was derived using void ratio equation in geotechnical engineering and compared with test results of bangkok clay and then this study could be verified.

• Journal of the Korea Society of Computer and Information
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• v.27 no.4
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• pp.27-36
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• 2022

In this paper, to improve the conditions of the fish processing site, we propose a method to predict the cutting point of fish according to the target weight using AI machine vision. The proposed method performs image-based preprocessing by first photographing the top and front views of the input fish. Then, RANSAC(RANdom SAmple Consensus) is used to extract the fish contour line, and then 3D external information of the fish is obtained using 3D modeling. Next, machine learning is performed on the extracted three-dimensional feature information and measured weight information to generate a neural network model. Subsequently, the fish is cut at the cutting point predicted by the proposed technique, and then the weight of the cut piece is measured. We compared the measured weight with the target weight and evaluated the performance using evaluation methods such as MAE(Mean Absolute Error) and MRE(Mean Relative Error). The obtained results indicate that an average error rate of less than 3% was achieved in comparison to the target weight. The proposed technique is expected to contribute greatly to the development of the fishery industry in the future by being linked to the automation system.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3A
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• pp.189-197
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• 2009

In this study, truck weight data and load effects of single truck on bridges are analyzed for development of new vehicular load model of the reliability-based bridge design code. Rational load model and statistical properties of loads are important for developing reliability-based design code. In this study, truck weight data collected at four locations are used as well as data from four locations in other studies. Truck weight data are collected from WIM or BWIM system, which are known to give reliable data. Typical truck types, dimensions and axle weight distribution are determined. Probability distributions of upper 20% total truck weight are assumed as Extreme Type I and 100 years maximum truck weights are estimated by linear regression on the probability paper. The load effects of trucks having estimated maximum weights are analyzed for span length from 10 m to 200 m.