• 터널과지하공간
• /
• 제29권5호
• /
• pp.356-366
• /
• 2019

다양한 TBM 성능 예측 모델이 개발되었기만 대부분 관입율 예측에 한정되어 있다. 일부 모델들이 수식과 그래프를 이용하여 TBM 가동율을 추정하는 방법을 제시하기도 하지만, TBM 가동율에 대한 연구는 매우 드문 편이다. TBM 가동율은 TBM 장비의 종류, 운영, 유지보수, 지질 조건, 시공자의 경험 등에 영향을 받는다. 본 연구에서는 100여개 이상의 사례 분석을 통해서 TBM 가동율과 RMR, 암종 등의 지반 조건, TBM의 종류, 터널의 연장 및 직경 등과의 관계를 조사하였다. 단순 및 다중 회귀분석을 수행하여 TBM 가동율 예측모델을 개발하였다. 암종 등의 지반조건, TBM의 종류, 터널의 연장 및 직경 등을 설명 변수로 갖는 회귀모델은 낮은 상관계수를 나타내었다. RMR을 설명변수로 갖는 회귀모델이 더 높은 상관계수를 나타내었다.

• 대한영양사협회학술지
• /
• 제25권1호
• /
• pp.30-43
• /
• 2019

This study compared the predictive models for the growth kinetics of Staphylococcus aureus in ham rice balls. In addition, a semi-quantitative risk assessment of S. aureus on ham rice balls was conducted using FDA-iRISK 4.0. The rice was rounded with chopped ham, which was mixed with mayonnaise (SHM), soy sauce (SHS), or gochujang (SHG), and was contaminated artificially with approximately $2.5{\log}\;CFU{\cdot}g^{-1}$ of S. aureus. The inoculated rice balls were then stored at $7^{\circ}C$, $15^{\circ}C$, and $25^{\circ}C$, and the number of viable S. aureus was counted. The lag phases duration (LPD) and maximum specific growth rate (SGR) were calculated using a Baranyi model as a primary model. The growth parameters were analyzed using the polynomial equation as a function of temperature. The LPD values of S. aureus decreased with increasing temperature in SHS and SHG. On the other hand, those in SHM did not show any trend with increasing temperature. The SGR positively correlated with temperature. Equations for LPD and SGR were developed and validated using $R^2$ values, which ranged from 0.9929 to 0.9999. In addition, the total DALYs (disability adjusted life years) per year in the ham rice balls with soy sauce and gochujang was greater than mayonnaise. These results could be used to calculate the expected number of illnesses, and set the hazard management method taking the DALY value for public health into account.

• Computers and Concrete
• /
• 제28권6호
• /
• pp.533-547
• /
• 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.

• 경제분석
• /
• 제26권3호
• /
• pp.1-47
• /
• 2020

본 연구는 이자율 스프레드 혹은 이자율 스프레드의 각 구성요소인 기대 스프레드와 기간 프리미엄의 경기 예측력에 관한 1990년대 이후 선행연구를 서베이하고, 한국의 국고채 현물이자율 데이터를 이용하여 이자율 스프레드 및 각 구성요소의 산업생산 증가율, 소비자물가 상승률, 생산갭 등에 대한 예측력에 관한 실증분석을 수행하였다. 먼저 주로 미국 경제를 대상으로 한 선행 연구들을 서베이한 결과 이자율 스프레드는 주요 경제변수들에 대하여 유의한 예측력을 갖고 있으나 1980년대 중반 이후 인플레이션 타깃팅 강화 경향 등에 따라 이자율 스프레드의 경기 예측력이 저하되고 있는 것으로 나타났다. 다음으로 한국 데이터를 대상으로 산업생산 증가율, 소비자물가 상승률, 생산갭 등에 대한 이자율 스프레드 및 각 구성요소의 예측력을 분석한 결과, 특히 이자율 스프레드의 구성요소 중 기간 프리미엄이 유의한 예측력을 갖는 것으로 나타났다. 이자율 스프레드를 이용하여 표본외 분석을 수행한 결과, 예측방정식이 구조적으로 불안정한 것으로 나타났으며, 특히 산업생산지수 예측에 있어서 이자율 스프레드의 분해가 유의한 기여를 하는 것으로 나타났다.

• Asian-Australasian Journal of Animal Sciences
• /
• 제30권11호
• /
• pp.1590-1597
• /
• 2017

Objective: This study aims to identify the relationship between odd- and branched-chain fatty acids (OBCFAs) and microbial nucleic acid bases in the rumen, and to establish a model to accurately predict microbial protein flow by using OBCFA. Methods: To develop the regression equations, data on the rumen contents of individual cows were obtained from 2 feeding experiments. In the first experiment, 3 rumen-fistulated dry dairy cows arranged in a $3{\times}3$ Latin square were fed diets of differing forage to concentration ratios (F:C). The second experiment consisted of 9 lactating Holstein dairy cows of similar body weights at the same stage of pregnancy. For each lactation stage, 3 cows with similar milk production were selected. The rumen contents were sampled at 4 time points of every two hours after morning feeding 6 h, and then to analyse the concentrations of OBCFA and microbial nucleic acid bases in the rumen samples. Results: The ruminal bacteria nucleic acid bases were significantly influenced by feeding diets of differing forge to concentration ratios and lactation stages of dairy cows (p<0.05). The concentrations of OBCFAs, especially odd-chain fatty acids and C15:0 isomers, strongly correlated with the microbial nucleic acid bases in the rumen (p<0.05). The equations of ruminal microbial nucleic acid bases established by ruminal OBCFAs contents showed a good predictive capacity, as indicated by reasonably low standard errors and high R-squared values. Conclusion: This finding suggests that the rumen OBCFA composition could be used as an internal marker of rumen microbial matter.

• 전자통신동향분석
• /
• 제39권4호
• /
• pp.42-53
• /
• 2024

Mathematical modeling is the process of representing physical phenomena using equations, and it often describes various scientific phenomena through differential equations. Numerical analysis, which is capable of approximating solutions to partial differential equations representing physical phenomena, is widely utilized. However, in high-dimensional or nonlinear systems, computational costs can substantially increase, leading to potential numerical instability or convergence issues. Recently, Physics-Informed Neural Networks (PINNs) have emerged as an alternative approach. A PINN leverages physical laws even with limited data to provide highly reliable predictive performance and can address the convergence issues and high computational costs associated with numerical analysis. This paper analyzes the weak signals, research trends, patent trends, and case studies of PINNs. On the basis of this analysis, it proposes directions for the development of PINN techniques in the agricultural field. In particular, the application of PINNs in agriculture is expected to be more effective than in other industries because of their ability to reflect real-time changes in biological processes. While the technology readiness level of PINNs remains low, the potential for model training with minimal data and real-time prediction capabilities suggests that PINNs could replace traditional numerical analysis models. It is anticipated that the research and industrial applications of PINN will develop at an increasing pace while focusing on addressing the complexity of mathematical models in agriculture, mathematical modeling and the application of various biological processes; securing key patents related to PINNs; and standardizing PINN technology in the field of agriculture.

• 한국수자원학회논문집
• /
• 제36권3호
• /
• pp.507-520
• /
• 2003

V형 여울은 하천 양안에 설치하여 여울의 가운데로 물의 흐름을 집중시켜 하도 중앙 직하류에 세굴로 인한 소(pool)를 형성하는 역할을 하는 인공 여울이다. V형 여울의 설치 목적은 평탄화된 하도에 소를 형성시켜 갈수시 어류의 서식처 노는 피난처를 제공하고, 홍수시에는 유속이 약한 구간을 발생시켜 어류의 피난처를 제공하는 것이다. 본 연구에서는 V형 여울의 수리 모형 실험을 실시하여 각 조건에 따른 세굴심을 측정하여 세굴 특성을 분석하였고, 나아가 수리량 조건 및 V형 여울 형태와 세굴 간의 정량적인 관계를 실험 결과로부터 도출하였다. 또한 V형 여울과 형태가 유사한 수제에서의 세굴심에 대한 기존의 연구 결과와 V형 여울의 경우를 비교하였다. 그 결과 Breusers와 Raudkivi(1991)가 제안한 수제에서의 세굴심 예측식은 V형 여울에서의 세굴심을 과소평가하지만 V형 여울께서의 세굴 특성을 일부 반영하는 것으로 나타났다. V형 여울의 세굴에 영향을 주는 인자들의 무차원화를 통해 V형 여울에서의 세굴심 예측식을 제안하였고 제안된 예측식은 V형 여울의 적용에 있어서 세굴심을 추정하는데 사용될 수 있고 판단된다. V형 여울의 세굴에 지배적인 영향을 주는 인자는 여울 중앙에서의 프루드 수이고, 그밖에 여울과 흐름의 각도와 여울 개구부의 폭도 부분적으로 영향을 준다.

• 한국도로학회논문집
• /
• 제16권6호
• /
• pp.105-113
• /
• 2014

PURPOSES: The objective of this paper is to select the confidential intervals by utilizing the second moment reliability index(Hasofer and Lind; 1974) related to the number of load applications to failure which explains the fatigue failure and rut depth that it indicates the permanent deformation. By using Finite Element Method (FEM) Program, we can easily confirm the rut depth and number of load repetitions without Pavement Design Procedures for generally designing pavement depths. METHODS : In this study, the predictive models for the rut depth and the number of load repetitions to fatigue failure were used for determining the second moment reliability index (${\beta}$). From the case study results using KICTPAVE, the results of the rut depth and the number of load repetitions to fatigue failure were deducted by calculating the empirical predictive equations. Also, the confidential intervals for rut depth and number of load repetitions were selected from the results of the predictive models. To determine the second moment reliability index, the spreadsheet method using Excel's Solver was used. RESULTS : From the case studies about pavement conditions, the results of stress, displacement and strain were different with depth conditions of layers and layer properties. In the clay soil conditions, the values of strain and stresses in the directly loaded sections are relatively greater than other conditions. It indicates that the second moment reliability index is small and confidential intervals for rut depth and the number of load applications are narrow when we apply the clay soil conditions comparing to the applications of other soil conditions. CONCLUSIONS : According to the results of the second moment reliability index and the confidential intervals, the minimum and maximum values of reliability index indicate approximately 1.79 at Case 9 and 2.19 at Case 22. The broadest widths of confidential intervals for rut depth and the number of load repetitions are respectively occurred in Case 9 and Case 7.

• 한국안전학회지
• /
• 제22권4호
• /
• pp.37-42
• /
• 2007

Flash points for the flammable binary systems, n-propanol+acetic acid and n-propanol+n-propionic acid, were measured by Cleveland open cup tester. The Raoult's law, the van Laar equation and the UNIQUAC equation were used for predicting flash points and were compared with experimentally-derived data. The calculated values based on the van Laar and UNIQUAC equations were found to be better than those based on the Raoult's law. And the predictive curve of the flash point prediction model based on the UNIQUAC equation described the experimentally-derived data more effectively than was the case when the prediction model was based upon the the van Laar equation.

• 한국연소학회지
• /
• 제4권2호
• /
• pp.51-62
• /
• 1999

NOx formation in turbulent flames is strongly coupled with temperature, superequilibrium concentration of O radical, and residence time. This implies that in order to accurately predict NO level, it is necessary to develop sophisticated models able to account for the complex turbulent combustion processes including turbulence/chemistry interaction and radiative heat transfer. The present study numerically investigates the turbulent nonpremixed hydrogen jet flames using the laminar flamelet model. Flamelet library is constructed by solving the modified Peters equations and the turbulent combustion model is extended to nonadiabatic flame by introducing the enthalpy defect. The effects of turbulent fluctuation are taken into account by the presumed joint PDFs for mixture fraction, scalar dissipation rate, and enthalpy defect. The predictive capability of the present model has been validated against the detailed experimental data. Effects of nonequilibrium chemistry and radiative heat loss on the thermal NO formation are discussed in detail.