• Journal of the Korean Geotechnical Society
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• v.35 no.12
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• pp.69-89
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• 2019

Design chart solution and table solution were proposed by Choi et al. (2019a), which conducted a parametric numerical study for the bored PHC piles socketed into weathered rocks through sandy soil layers. Based on the Choi et al. (2019a), the new prediction formulae for mobilized capacity components such as total capacity, total skin friction and skin friction of sand at the settlement of 5% pile diameter were proposed in this study. The proposed prediction formulae (EQ-G1) considers pile diameter, relative embedment length and ${\bar{N}}$ (i.e, corrected N) value and their verification results are as follows. The SRF calculated from the new proposed design method was 71~94%, which are greatly improved compared with results by the existing design method. The design efficiency of bearing capacity was in the range of reasonable design except 4 cases, and the design efficiency of the PHC pile was evaluated as 85%. Therefore, it is possible that allowable compressive load (P_all) of PHC pile can be utilized in the resonable design by means of the new proposed method using EQ-G1 equations. And the other new proposed equations of EQ-G2-3 can be utilized approximately in calculation of axial compressive bearing capacity components for prebored PHC pile.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.7 no.2
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• pp.63-68
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• 1989

This study was to develope the methmatic prediction model of accuracy for the convergent photographs using nonmetric camera in close range photogrammetry. By analyzing positioning error on object distance and convergent angles, the validity of the new formulae for prediction of accuracy were proved. Rational design of camera systems and convergent angles according to accuracy demands in plane and height were developed using these formulae.

• Steel and Composite Structures
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• v.33 no.2
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• pp.181-194
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• 2019

This paper presents an efficient approach to generate a new empirical formula to predict the axial compression capacity (ACC) of circular concrete-filled tube (CCFT) columns using the artificial neural network (ANN). A total of 258 test results extracted from the literature were used to develop the ANN models. The ANN model having the highest correlation coefficient (R) and the lowest mean square error (MSE) was determined as the best model. Stability analysis, sensitivity analysis, and a parametric study were carried out to estimate the stability of the ANN model and to investigate the main contributing factors on the ACC of CCFT columns. Stability analysis revealed that the ANN model was more stable than several existing formulae. Whereas, the sensitivity analysis and parametric study showed that the outer diameter of the steel tube was the most sensitive parameter. Additionally, using the validated ANN model, a new empirical formula was derived for predicting the ACC of CCFT columns. Obviously, a higher accuracy of the proposed empirical formula was achieved compared to the existing formulae.

• Computers and Concrete
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• v.28 no.6
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• pp.533-547
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• 2021

Calculating the shear capacity of slender reinforced concrete beams without shear reinforcement was the subject of numerous studies, where the eternal problem of developing a single relationship that will be able to predict the expected shear capacity is still present. Using experimental results to extrapolate formulae was so far the main approach for solving this problem, whereas in the last two decades different research studies attempted to use artificial intelligence algorithms and available data sets of experimentally tested beams to develop new models that would demonstrate improved prediction capabilities. Given the limited number of available experimental databases, these studies were numerically restrained, unable to holistically address this problem. In this manuscript, a new approach is proposed where a numerically generated database is used to train machine-learning algorithms and develop an improved model for predicting the shear capacity of slender concrete beams reinforced only with longitudinal rebars. Finally, the proposed predictive model was validated through the use of an available ACI database that was developed by using experimental results on physical reinforced concrete beam specimens without shear and compressive reinforcement. For the first time, a numerically generated database was used to train a model for computing the shear capacity of slender concrete beams without stirrups and was found to have improved predictive abilities compared to the corresponding ACI equations. According to the analysis performed in this research work, it is deemed necessary to further enrich the current numerically generated database with additional data to further improve the dataset used for training and extrapolation. Finally, future research work foresees the study of beams with stirrups and deep beams for the development of improved predictive models.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1990.10a
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• pp.53-58
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• 1990

The use of spreadsheet packages for solving noise control problems has been cited by several authors, eg Saha[1] and Thornton[2]. The effectiveness of using spreadsheet packages compared with the traditional computer programs written in high level languages was demonstrated when applied to relatively simple problems, such as the selection of hearing protectors or the prediction of noise equation which includes logarithmic additions at most represents the physics of the problem. The simplicity of the governing equation together with the requirement to handle a vast amount of data are considered to be the major reasons for noise control engineers to use spreadsheet packages. Although shipboard noise prediction seems to be very complicated, the calculation procedure itself is, in essence, identical especially true for prediction methods based on empirical formulae[3,4], ie the procedure that consists of the three basic elements, ie source, path and receiver. This paper discusses the application of spreadsheet package LOTUS 1-2-3 to shipboard noise prediction problems. A utility program of the package is written using macro functions and is shown to be especially useful for noise control engineers who are unfamiliar with spreadsheet packages. In addition, a new type of empirical formula, to estimate structureborne noise transmission loss, is proposed.

• Journal of Mechanical Science and Technology
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• v.14 no.7
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• pp.796-806
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• 2000

To understand the transient behavior of droplets after impingement in a diesel engine, a numerical model for diesel sprays impinging on a flat wall is newly developed by the proposition of several mathematical formulae to determine the post-impingement characteristics of droplets. The new model consists of three representative regimes such as rebound, deposition and splash. The gas phase is modeled in terms of the Eulerian conservation equations, and the dispersed phase is calculated using a discrete droplet model. To validate the new model, the calculated results are compared with several experimental data. The results show that the new model is generally in good agreement with the experimental data. Therefore, it is thought that the new model is acceptable for the prediction of transient behavior of wall sprays.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.24 no.7
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• pp.1010-1019
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• 2000

The main purpose of this article is to propose and assess a new spray impingement model considering film formation, which is capable of describing the droplet distribution and film flows in direct injection diesel engines. The spray-wall interaction model includes several mathematical formulae, newly made by the energy conservation law and some experimental results. The model consists of three representative regimes, rebound, deposition and splash. In addition, the film flow is described in the present model by solving the continuity and momentum equations for film flows using the integral method. To assess the new spray impingement model, the calculated results using the new model are compared with several experimental data for the normally impinging diesel sprays. The film model is also validated through comparing film radius and thickness against experimental data. The results show that the new model is generally in better agreement with experimental data and acceptable for prediction of the film radius and thickness.

• Geomechanics and Engineering
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• v.21 no.6
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• pp.583-598
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• 2020

This study is attempted to propose a new hybrid artificial intelligence model called integrative genetic algorithm with multivariate adaptive regression splines (GA-MARS) for settlement prediction of shallow foundations on sandy soils. In this hybrid model, the evolution algorithm - Genetic Algorithm (GA) was used to search and optimize the hyperparameters of multivariate adaptive regression splines (MARS). For this purpose, a total of 180 experimental data were collected and analyzed from available researches with five-input variables including the bread of foundation (B), length to width (L/B), embedment ratio (D_f/B), foundation net applied pressure (q_net), and average SPT blow count (N_SPT). In further analysis, a new explicit formulation was derived from MARS and its accuracy was compared with four available formulae. The attained results indicated that the proposed GA-MARS model exhibited a more robust and better performance than the available methods.

• Steel and Composite Structures
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• v.44 no.1
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• pp.119-139
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• 2022

This paper aims to use the artificial intelligence approach to develop a new model for predicting the ultimate axial strength of the circular concrete-filled steel tubular (CFST) stub columns. For this, the results of 314 experimentally tested circular CFST stub columns were employed in the generation of the design model. Since the influence of the column diameter, steel tube thickness, concrete compressive strength, steel tube yield strength, and column length on the ultimate axial strengths of columns were investigated in these experimental studies, here, in the development of the design model, these variables were taken into account as input parameters. The model was developed using the backpropagation algorithm named Bayesian Regularization. The accuracy, reliability, and consistency of the developed model were evaluated statistically, and also the design formulae given in the codes (EC4, ACI, AS, AIJ, and AISC) and the previous empirical formulations proposed by other researchers were used for the validation and comparison purposes. Based on this evaluation, it can be expressed that the developed design model has a strong and reliable prediction performance with a considerably high coefficient of determination (R-squared) value of 0.9994 and a low average percent error of 4.61. Besides, the sensitivity of the developed model was also monitored in terms of dimensional properties of columns and mechanical characteristics of materials. As a consequence, it can be stated that for the design of the ultimate axial capacity of the circular CFST stub columns, a novel artificial intelligence-based design model with a good and robust prediction performance was proposed herein.

• Korean Journal of Ophthalmology
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• v.32 no.6
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• pp.497-505
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• 2018

Purpose: To evaluate and compare published methods of calculating intraocular lens (IOL) power following myopic laser refractive surgery. Methods: We performed a retrospective review of the medical records of 69 patients (69 eyes) who had undergone myopic laser refractive surgery previously and subsequently underwent cataract surgery at Samsung Medical Center in Seoul, South Korea from January 2010 to June 2016. None of the patients had pre-refractive surgery biometric data available. The Haigis-L, Shammas, Barrett True-K (no history), Wang-Koch-Maloney, Scheimpflug total corneal refractive power (TCRP) 3 and 4 mm (SRK-T and Haigis), Scheimpflug true net power, and Scheimpflug true refractive power (TRP) 3 mm, 4 mm, and 5 mm (SRK-T and Haigis) methods were employed. IOL power required for target refraction was back-calculated using stable post-cataract surgery manifest refraction, and implanted IOL power and formula accuracy were subsequently compared among calculation methods. Results: Haigis-L, Shammas, Barrett True-K (no history), Wang-Koch-Maloney, Scheimpflug TCRP 4 mm (Haigis), Scheimpflug true net power 4 mm (Haigis), and Scheimpflug TRP 4 mm (Haigis) formulae showed high predictability, with mean arithmetic prediction errors and standard deviations of $-0.25{\pm}0.59$, $-0.05{\pm}1.19$, $0.00{\pm}0.88$, $-0.26{\pm}1.17$, $0.00{\pm}1.09$, $-0.71{\pm}1.20$, and $0.03{\pm}1.25$ diopters, respectively. Conclusions: Visual outcomes within 1.0 diopter of target refraction were achieved in 85% of eyes using the calculation methods listed above. Haigis-L, Barrett True-K (no history), and Scheimpflug TCRP 4 mm (Haigis) and TRP 4 mm (Haigis) methods showed comparably low prediction errors, despite the absence of historical patient information.