• Title/Summary/Keyword: Statistical-Mechanical Model

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Experimental studies on possible vortex shedding in a suspension bridge - Part I - Structural dynamic characteristics and analysis model

  • Law, S.S.;Yang, Q.S.;Fang, Y.L.
    • Wind and Structures
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    • 제10권6호
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    • pp.543-554
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    • 2007
  • The suspension bridge is situated in an area of complex topography with both open sea and overland turbulence characteristics, and it is subject to frequent typhoon occurrences. This paper investigates experimentally the possible vortex shedding events of the structure under high wind and typhoon conditions. A single-degree-of-freedom model for the vibration of a unit bridge deck section is adopted to determine the amplitude of vibration and to estimate the parameters related to the lifting force in a vortex shedding event. The results of the studies are presented in a companion paper (Law, et al. 2007). In this paper, statistical analysis on the measured responses of the bridge deck shows that the vibration response at the first torsional mode of the structure has a significant increase at and beyond the critical wind speed for vortex shedding as noted in the wind tunnel tests on a section model of the structure.

Crack growth life model for fatigue susceptible structural components in aging aircraft

  • Chou, Karen C.;Cox, Glenn C.;Lockwood, Allison M.
    • Structural Engineering and Mechanics
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    • 제17권1호
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    • pp.29-50
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    • 2004
  • A total life model was developed to assess the service life of aging aircraft. The primary focus of this paper is the development of crack growth life projection using the response surface method. Crack growth life projection is a necessary component of the total life model. The study showed that the number of load cycles N needed for a crack to propagate to a specified size can be linearly related to the geometric parameter, material, and stress level of the component considered when all the variables are transformed to logarithmic values. By the Central Limit theorem, the ln N was approximated by Gaussian distribution. This Gaussian model compared well with the histograms of the number of load cycles generated from simulated crack growth curves. The outcome of this study will aid engineers in designing their crack growth experiments to develop the stochastic crack growth models for service life assessments.

Approximate Nonrandom Two-Fluid Lattice-Hole Theory. General Derivation and Description of Pure Fluids

  • 유기풍;신훈용;이철수
    • Bulletin of the Korean Chemical Society
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    • 제18권9호
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    • pp.965-972
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    • 1997
  • An approximate molecular theory of classical fluids based on the nonrandom lattice statistical-mechanical theory is presented. To obtain configurational Helmholtz free energy and equation of state (EOS), the lattice-hole theory of the Guggenheim combinatorics is approximated by introducing the nonrandom two-fluid theory. The approximate nature in the derivation makes the model possible to unify the classical lattice-hole theory and to describe correctly the configurational properties of real fluids including macromolecules. The theory requires only two molecular parameters for a pure fluid. Results obtained to date have demonstrated that the model correlates quantitatively the first- and second-order thermodynamic properties of real fluids. The basic simplicity of the model can readily be generalized to multicomponent systems. The model is especially relevant to (multi) phase equilibria of systems containing molecularly complex species.

Prediction of the compressive strength of fly ash geopolymer concrete using gene expression programming

  • Alkroosh, Iyad S.;Sarker, Prabir K.
    • Computers and Concrete
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    • 제24권4호
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    • pp.295-302
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    • 2019
  • Evolutionary algorithms based on conventional statistical methods such as regression and classification have been widely used in data mining applications. This work involves application of gene expression programming (GEP) for predicting compressive strength of fly ash geopolymer concrete, which is gaining increasing interest as an environmentally friendly alternative of Portland cement concrete. Based on 56 test results from the existing literature, a model was obtained relating the compressive strength of fly ash geopolymer concrete with the significantly influencing mix design parameters. The predictions of the model in training and validation were evaluated. The coefficient of determination ($R^2$), mean (${\mu}$) and standard deviation (${\sigma}$) were 0.89, 1.0 and 0.12 respectively, for the training set, and 0.89, 0.99 and 0.13 respectively, for the validation set. The error of prediction by the model was also evaluated and found to be very low. This indicates that the predictions of GEP model are in close agreement with the experimental results suggesting this as a promising method for compressive strength prediction of fly ash geopolymer concrete.

Adaptive Neuro-fuzzy-based modeling of exhaust emissions from dual-fuel engine using biodiesel and producer gas

  • Prabhakar Sharma;Avdhesh Kr Sharma
    • Advances in Energy Research
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    • 제8권3호
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    • pp.175-184
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    • 2022
  • The dual-fuel technology, which uses gaseous fuel as the main fuel and liquid as the pilot fuel, is an appealing technology for reducing the exhaust emissions. The current study proposes emission models based on ANFIS for a dual-fuel using producer gas (PG)-diesel engine. Emissions measurements were taken at different engine load levels and fuel injection timings. The proposed model predictions were examined using statistical methods. With R2 values in the range of 0.9903 to 0.9951, the established ANFIS model was found to be consistently robust in predicting emission characteristics. The mean absolute percentage deviate in range 1.9 to 4.6%, and mean squared error varies in range 0.0018 to 13.9%. The evaluation of the ANFIS model developed shows a reliable claim of intrinsic sensitivity, strength, and outstanding generalization. The presented meta-model can be used to simulate the engine's operation in order to create an efficient control tool.

시변환 스트레스 조건에서의 와이블 분포의 모수 및 가속 모수에 대한 베이시안 추정을 사용하는 이산 시간 접근 방법 (A Discrete Time Approximation Method using Bayesian Inference of Parameters of Weibull Distribution and Acceleration Parameters with Time-Varying Stresses)

  • 정인승
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2008년도 추계학술대회A
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    • pp.1331-1336
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    • 2008
  • This paper suggests a method using Bayesian inference to estimate the parameters of Weibull distribution and acceleration parameters under the condition that the stresses are time-dependent functions. A Bayesian model based on the discrete time approximation is formulated to infer the parameters of interest from the failure data of the virtual tests and a statistical analysis is considered to decide the most probable mean values of the parameters for reasoning of the failure data.

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좁은밴드모델을 이용한 실린더 내의 비회색 가스 복사열전달 연구 (Study on Nongray Gas Radiation within a Cylindrical Enclosure by Using the Narrow Band Model)

  • 박원희;정현성;김태국
    • 대한기계학회논문집B
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    • 제26권6호
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    • pp.859-867
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    • 2002
  • Radiative transfer in energy systems such as furnaces, combustors, boilers and high temperature machineries is a significant mode of heat transfer. Although there are many solution schemes suggested for analysis of radiative transfer in multi-dimensional systems, the applicabilities and accuracies of these schemes have not fully tested for nongray gases. Especially reference data for enclosures of non-orthogonal shapes are not yet enough. In this paper we present some precise radiative transfer solutions for a black walled 3-dimensional cylindrical system filled with nongray gases. The SNB(statistical narrow band) model and the ray-tracing method with the T$_{N}$ quadrature set are used for finding nongray solutions. Although the solution method used in this study is not suitable for engineering purposes, the resulting solutions are proved to be quite accurate and can be regarded as the exact solutions and the results presented in this paper can be used in developing various solution schemes fur radiative transfer by real gas mixtures.s.

PCVN 시편 파괴인성의 균열 깊이 영향에 대한 Scaling 모델 해석 (Analysis of Cleavage Fracture Toughness of PCVN Specimens Based on a Scaling Model)

  • 박상윤;이호진;이봉상
    • 대한기계학회논문집A
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    • 제33권4호
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    • pp.409-416
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    • 2009
  • Standard procedures for a fracture toughness testing require very severe restrictions for the specimen geometry to eliminate a size effect on the measured properties. Therefore, the used standard fracture toughness data results in the integrity assessment being irrationally conservative. However, a realistic fracture in general structures, such as in nuclear power plants, may develop under the low constraint condition of a large scale yielding with a shallow surface crack. In this paper, cleavage fracture toughness tests have been made on side-grooved PCVN (precracked charpy V-notch) type specimens (10 by 10 by 55 mm) with various crack depths. The constraint effects on the crack depth ratios were evaluated quantitatively by the developed scaling method using the 3-D finite element method. After the fracture toughness correction from scaling model, the statistical size effects were also corrected according to the standard ASTM E 1921 procedure. The results were evaluated through a comparison with the $T_0$ of the standard CT specimen. The corrected $T_0$ for all of the PCVN specimens showed a good agreement to within $5.4^{\circ}C$ regardless of the crack depth, while the averaged PCVN $T_0$ was $13.4^{\circ}C$ higher than the real CT test results.

변동하중하에서 고강도 알루미늄 합금의 피로수명 예측 (Fatigue Life Prediction for High Strength AI-alloy under Variable Amplitude Loading)

  • 심동석;김강범;김정규
    • 대한기계학회논문집A
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    • 제24권8호
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    • pp.2074-2082
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    • 2000
  • In this study, to investigate and to predict the crack growth behavior under variable amplitude loading, crack growth tests are conducted on 7075-T6 aluminum alloy. The loading wave forms are generated by normal random number generator. All wave forms have same average and RMS(root mean square) value, but different standard deviation, which is to vary the maximum load in each wave. The modified Forman's equation is used as crack growth equation. Using the retardation coefficient D defined in previous study, the load interaction effect is considered. The variability in crack growth process is described by the random variable Z which was obtained from crack growth tests under constant amplitude loading in previous work. From these, a statistical model is developed. The curves predicted by the proposed model well describe the crack growth behavior under variable amplitude loading and agree with experimental data. In addition, this model well predicts the variability in crack growth process under variable amplitude loading.

Bayesian approach for prediction of primary water stress corrosion cracking in Alloy 690 steam generator tubing

  • Falaakh, Dayu Fajrul;Bahn, Chi Bum
    • Nuclear Engineering and Technology
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    • 제54권9호
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    • pp.3225-3234
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    • 2022
  • Alloy 690 tubing has been shown to be highly resistant to primary water stress corrosion cracking (PWSCC). Nevertheless, predicting the failure by PWSCC in Alloy 690 SG tubes is indispensable. In this work, a Bayesian-based statistical approach is proposed to predict the occurrence of failure by PWSCC in Alloy 690 SG tubing. The prior distributions of the model parameters are developed based on the prior knowledge or information regarding the parameters. Since Alloy 690 is a replacement for Alloy 600, the parameter distributions of Alloy 600 tubing are used to gain prior information about the parameters of Alloy 690 tubing. In addition to estimating the model parameters, analysis of tubing reliability is also performed. Since no PWSCC has been observed in Alloy 690 tubing, only right-censored free-failure life of the tubing are available. Apparently the inference is sensitive to the choice of prior distribution when only right-censored data exist. Thus, one must be careful in choosing the prior distributions for the model parameters. It is found that the use of non-informative prior distribution yields unsatisfactory results, and strongly informative prior distribution will greatly influence the inference, especially when it is considerably optimistic relative to the observed data.