• Title/Summary/Keyword: experimental prediction formulas

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Rotor High-Speed Noise Prediction with a Combined CFD-Kirchhoff Method (CFD와 Kirchhoff 방법의 결합을 이용한 로터의 고속 충격소음 해석)

  • 이수갑;윤태석
    • Journal of KSNVE
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    • v.6 no.5
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    • pp.607-616
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    • 1996
  • A combined computational fluid dynamics(CFD)-Kirchhoff method is presented for predicting high-speed impulsive noise generated by a hovering blade. Two types of Kirchhoff integral formula are used; one for the classical linear Kirchhoff formulation and the other for the nonlinear Kirchhoff formulation. An Euler finite difference solver is solved first to obtain the flow field close to the blade, and then this flow field is used as an input to a Kirchhoff formulation to predict the acoustic far-field. These formulas are used at Mach numbers of 0.90 and 0.95 to investigate the effectiveness of the linear and nonlinear Kirchhoff formulas for delocalized flow. During these calculiations, the retarded time equation is also carefully examined, in particular, for the cases of the control surface located outside of the sonic cylinder, where multiple roots are obtained. Predicted results of acoustic far-field pressure with the linear Kirchhoff formulation agree well with experimental data when the control surface is at the certain location(R=1.46), but the correlation is getting worse before or after this specific location of the control surface due to the delocalized nonlinear aerodynamic flow field. Calculations based on the nonlinear Kirchhoff equation using a linear sonic cylinder as a control surface show a reasonable agreement with experimental data in negative amplitudes for both tip Mach numbers of 0.90 and 0.95, except some computational integration problems over a shock. This concliudes that a nonlinear formulation is necessary if the control surface is close to the blade and the flow is delocalized.

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Experimental study of internal solitary wave loads on the semi-submersible platform

  • Zhang, Jingjing;Liu, Yi;Chen, Ke;You, Yunxiang;Duan, Jinlong
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.13 no.1
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    • pp.718-733
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    • 2021
  • A prediction method, based on the Morison equation as well as Froude-Krylov formula, is presented to simulate the loads acting on the columns and caissons of the semi-submersible platform induced by Internal Solitary Wave (ISW) respectively. Combined with the experimental results, empirical formulas of the drag and inertia coefficients in Morison equation can be determined as a function of the Keulegan-Carpenter (KC) number, Reynolds number (Re) and upper layer depth h1/h respectively. The experimental and calculated results are compared. And a good agreement is observed, which proves that the present prediction method can be used for analyzing the ISW-forces on the semi-submersible platform. Moreover, the results also demonstrate the layer thickness ratio has a significant effect upon the maximum horizontal forces on the columns and caissons, but both minimum horizontal and vertical forces are scarcely affected. In addition, the incoming wave directions may also contribute greatly to the values of horizontal forces exerted on the caissons, which can be ignored in the vertical force analysis.

Fatigue Life Assessment of Ship Structures based on Crack Propagation Analysis -Simplified Prediction Method of Stress Intensity Factors- (균열전파해석에 의한 선체의 피로수명 평가법 -응력강도계수의 간이추정법-)

  • C.W. Kim;I.S. Nho;D.S. Kim
    • Journal of the Society of Naval Architects of Korea
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    • v.39 no.1
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    • pp.90-99
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    • 2002
  • The prediction of stress intensity factor(SIF) is one of the most important factors to analyse the propagation behavior of cracks in hull structural members. Up to now, however, simplified prediction method of SIF has not yet been established for the cracks experienced in large complex structures. As a first step to predict crack propagation behavior in a ship structure with very large structural redundancies, simplified SIF prediction formulas for various crack shapes were derived based on the results of the stress analysis under a non-crack condition in this study. The adequacy of the proposed method was then verified in comparison with other experimental and analysis results.

A Study on Shear Strength Prediction for High-Strength Reinforced Concrete Deep Beams Using Strut-and-Tie Model (스트럿-타이 모델에 의한 고강도 철근콘크리트 깊은 보의 전단강도 예측에 관한 연구)

  • 이우진;서수연;윤승조;김성수
    • Proceedings of the Korea Concrete Institute Conference
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    • 2003.05a
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    • pp.918-923
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    • 2003
  • Reinforced concrete deep beams are commonly used in many structural applications, including transfer girders, pile caps, foundation walls, and offshore structures. The existing design methods were developed and calibrated using normal strength concrete test results, and their applicability th HSC deep beams must be assessed. For the shear strength prediction of high-strength concrete(HSC) deep beams, this paper proposed Softened Strut-and-Tie Model(SSTM) considered HSC and bending moment effect. The shear strength predictions of the refined model, the formulas the ACI 318-02 Appendix A STM, and Eq. of ACI 318-99 11.8 are compared with the collected experimental data of 74 HSC deep beams with compressive strength in the range of 49-78MPa . It is shown the shear strength of deep beam calculated by those equations are conservative on comparing test results. The comparison shows that the performance of the proposed SSTM is better than the ACI Code approach for all the parameters under comparison. The parameters reviewed include concrete strength, the shear span-depth ratio, and the ratio of horizontal and vertical reinforcement. The proposed SSTM gave a mean predicted to experimental ratio of 0.99, 32 percent higher than ACI 318-02 Code, however with the low coefficient variation.

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Prediction of bridge flutter under a crosswind flow

  • Vu, Tan-Van;Lee, Ho-Yeop;Choi, Byung-Ho;Lee, Hak-Eun
    • Wind and Structures
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    • v.17 no.3
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    • pp.275-298
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    • 2013
  • This paper presents a number of approximated analytical formulations for the flutter analysis of long-span bridges using the so-called uncoupled flutter derivatives. The formulae have been developed from the simplified framework of a bimodal coupled flutter problem. As a result, the proposed method represents an extension of Selberg's empirical formula to generic bridge sections, which may be prone to one of the aeroelastic instability such as coupled-mode or single-mode (either dominated by torsion or heaving mode) flutter. Two approximated expressions for the flutter derivatives are required so that only the experimental flutter derivatives of ($H_1^*$, $A_2^*$) are measured to calculate the onset flutter. Based on asymptotic expansions of the flutter derivatives, a further simplified formula was derived to predict the critical wind speed of the cross section, which is prone to the coupled-mode flutter at large reduced wind speeds. The numerical results produced by the proposed formulas have been compared with results obtained by complex eigenvalue analysis and available approximated methods show that they seem to give satisfactory results for a wide range of study cases. Thus, these formulas can be used in the assessment of bridge flutter performance at the preliminary design stage.

Prediction of compressive strength of concrete using multiple regression model

  • Chore, H.S.;Shelke, N.L.
    • Structural Engineering and Mechanics
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    • v.45 no.6
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    • pp.837-851
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    • 2013
  • In construction industry, strength is a primary criterion in selecting a concrete for a particular application. The concrete used for construction gains strength over a long period of time after pouring the concrete. The characteristic strength of concrete is defined as the compressive strength of a sample that has been aged for 28 days. Neither waiting for 28 days for such a test would serve the rapidity of construction, nor would neglecting it serve the quality control process on concrete in large construction sites. Therefore, rapid and reliable prediction of the strength of concrete would be of great significance. On this backdrop, the method is proposed to establish a predictive relationship between properties and proportions of ingredients of concrete, compaction factor, weight of concrete cubes and strength of concrete whereby the strength of concrete can be predicted at early age. Multiple regression analysis was carried out for predicting the compressive strength of concrete containing Portland Pozolana cement using statistical analysis for the concrete data obtained from the experimental work done in this study. The multiple linear regression models yielded fairly good correlation coefficient for the prediction of compressive strength for 7, 28 and 40 days curing. The results indicate that the proposed regression models are effectively capable of evaluating the compressive strength of the concrete containing Portaland Pozolana Cement. The derived formulas are very simple, straightforward and provide an effective analysis tool accessible to practicing engineers.

Prediction methods on tunnel-excavation induced surface settlement around adjacent building

  • Ding, Zhi;Wei, Xin-jiang;Wei, Gang
    • Geomechanics and Engineering
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    • v.12 no.2
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    • pp.185-195
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    • 2017
  • With the rapid development of urban underground traffic, the study of soil deformation induced by subway tunnel construction and its settlement prediction are gradually of general concern in engineering circles. The law of soil displacement caused by shield tunnel construction of adjacent buildings is analyzed in this paper. The author holds that ground surface settlement based on the Gauss curve or Peck formula induced by tunnel excavation of adjacent buildings is not reasonable. Integrating existing research accomplishments, the paper proposed that surface settlement presents cork distribution curve characters, skewed distribution curve characteristics and normal distribution curve characteristics when the tunnel is respectively under buildings, within the scope of the disturbance and outside the scope of the disturbance. Calculation formulas and parameters on cork distribution curve and skewed distribution curve were put forward. The numerical simulation, experimental comparison and model test analysis show that it is reasonable for surface settlement to present cork distribution curve characters, skewed distribution curve characteristics and normal distribution curve characteristics within a certain range. The research findings can be used to make effective prediction of ground surface settlement caused by tunnel construction of adjacent buildings, and to provide theoretical guidance for the design and shield tunnelling.

Prediction of Scour Potential Distributions in a Shallow Plunge Pool (얕은 감세지내의 세굴능 분포형태의 예측)

  • 손광익
    • Water for future
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    • v.27 no.3
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    • pp.35-43
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    • 1994
  • Because a failure to provide enough plunge pool depth can create a risk to the structural stability of the psillways or dams, many researchers have proposed experimental formulas for claculating ultimate scour depth under jet issued from spillways and pipe culverts. For the design purposes of a plunge pool, scour potential distribution is important as much as the ultimate scour depth is. In this study scour potential distributions near the jet impinging point on a porous plane which can simulate a real cohesionless movable flat bed has been measured. Experimental results showed that scour potential distributions are geometrically similar to each other provided the angle of jet impact was the same. Statistical analysis of experimental results showed that scour potential distributions for the design purposes of a plunge pool could be expressed by a single equation within a range of this experiment. The proposed formula for the prediction of scour potential distributions agrees well with experimental measurements.

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Prediction of Wave Breaking Using Machine Learning Open Source Platform (머신러닝 오픈소스 플랫폼을 활용한 쇄파 예측)

  • Lee, Kwang-Ho;Kim, Tag-Gyeom;Kim, Do-Sam
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.32 no.4
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    • pp.262-272
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    • 2020
  • A large number of studies on wave breaking have been carried out, and many experimental data have been documented. Moreover, on the basis of various experimental data set, many empirical or semi-empirical formulas based primarily on regression analysis have been proposed to quantitatively estimate wave breaking for engineering applications. However, wave breaking has an inherent variability, which imply that a linear statistical approach such as linear regression analysis might be inadequate. This study presents an alternative nonlinear method using an neural network, one of the machine learning methods, to estimate breaking wave height and breaking depth. The neural network is modeled using Tensorflow, a machine learning open source platform distributed by Google. The neural network is trained by randomly selecting the collected experimental data, and the trained neural network is evaluated using data not used for learning process. The results for wave breaking height and depth predicted by fully trained neural network are more accurate than those obtained by existing empirical formulas. These results show that neural network is an useful tool for the prediction of wave breaking.

Modeling of compressive strength of HPC mixes using a combined algorithm of genetic programming and orthogonal least squares

  • Mousavi, S.M.;Gandomi, A.H.;Alavi, A.H.;Vesalimahmood, M.
    • Structural Engineering and Mechanics
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    • v.36 no.2
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    • pp.225-241
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    • 2010
  • In this study, a hybrid search algorithm combining genetic programming with orthogonal least squares (GP/OLS) is utilized to generate prediction models for compressive strength of high performance concrete (HPC) mixes. The GP/OLS models are developed based on a comprehensive database containing 1133 experimental test results obtained from previously published papers. A multiple least squares regression (LSR) analysis is performed to benchmark the GP/OLS models. A subsequent parametric study is carried out to verify the validity of the models. The results indicate that the proposed models are effectively capable of evaluating the compressive strength of HPC mixes. The derived formulas are very simple, straightforward and provide an analysis tool accessible to practicing engineers.