W. Jefferson Stroud¹, T. Krishnamurthy¹, Steven A. Smith²

CMES-Computer Modeling in Engineering & Sciences, Vol.3, No.6, pp. 755-772, 2002, DOI:10.3970/cmes.2002.003.755

Abstract The effects of uncertainties on the predicted strength of a single lap shear joint are examined. Probabilistic and possibilistic methods are used to account for uncertainties. A total of ten variables are assumed to be random, with normal distributions. Both Monte Carlo Simulation and the First Order Reliability Method are used to determine the probability of failure. Triangular membership functions with upper and lower bounds located at plus or minus three standard deviations are used to model uncertainty in the possibilistic analysis. The alpha cut (or vertex) method is used to evaluate the possibility of failure. Linear and geometrically nonlinear… More >

B.K. Raghu Prasad¹, T.V.R.L. Rao¹, A.R.Gopalakrishnan¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.6, No.2, pp. 99-112, 2008, DOI:10.3970/icces.2008.006.099

Abstract A modified lattice model using finite element method has been developed to study the mode-I fracture analysis of heterogeneous materials like concrete. In this model, the truss members always join at points where aggregates are located which are modeled as plane stress triangular elements. The truss members are given the properties of cement mortar matrix randomly, so as to represent the randomness of strength in concrete. It is widely accepted that the fracture of concrete structures should not be based on strength criterion alone, but should be coupled with energy criterion. Here, by incorporating the strain softening through a parameter… More >

Christos C. Chamis¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.4, No.2, pp. 59-66, 2007, DOI:10.3970/icces.2007.004.059

Abstract A formal procedure for the probabilistic design evaluation of a composite structure is described. The uncertainties in all aspects of a composite structure (constituent material properties, fabrication variables, structural geometry, and service environments, etc.), which result in the uncertain behavior in the composite structural responses, are included in the evaluation. The probabilistic evaluation consists of: (1) design criteria, (2) modeling of composite structures and uncertainties, (3) simulation methods, and (4) the decision-making process. A sample case is presented to illustrate the formal procedure and to demonstrate that composite structural designs can be probabilistically evaluated with accuracy and efficiency. More >

M R Moarefzadeh¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.10, No.1, pp. 5-6, 2009, DOI:10.3970/icces.2009.010.005

Abstract Among varieties of techniques to estimate structural reliability, directional simulation is well developed. This technique was first proposed to be used in standard Gaussian space where all random processes/variables are involved [1]. The main advantage of this procedure is that in each directional sample a closed form expression is available to estimate structural probability of failure conditioned on the sampled direction. The technique was then extended to a space in which all random variables/processes are involved, but they are not necessarily Gaussian [2,3]. Furthermore, Melchers [4] proposed this technique to be utilized in the load space rather than the space… More >

Heekun Ju, Hyung-Jo Jung^*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.21, No.1, pp. 7-7, 2019, DOI:10.32604/icces.2019.05846

Abstract Latin hypercube sampling (LHS) is widely applied to estimate a probabilistic floor response spectrum (FRS) of nonlinear nuclear power plant (NPP) structure. ASCE 4-16 Standards recommend that the minimum number of simulations should be larger than 30 when using LHS. Although this recommendation is commonly used for the minimum number of the simulation, there is no theoretical background. The variability of the estimations may exist according to the number of the simulation. Stated differently, the minimum number of the simulation may be varied depending on the characteristics of the problem (i.e., problem-dependent). In this context, the required sample size of… More >

Doo Kie Kim¹, Dong Hyawn Kim², Seong Kyu Chang¹, Sang Kil Chang¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.2, No.2, pp. 35-40, 2007, DOI:10.3970/icces.2007.002.035

Abstract The stability numbers determining the Armor units are very important to design breakwaters, because armor units are designed for defending breakwaters from repeated wave loads. This study presents a probabilistic neural network (PNN) for predicting the stability number of armor blocks of breakwaters. PNN used the experimental data of van der Meer as train and test data. The estimated results of PNN were compared with those of empirical formula and previous artificial neural network (ANN) model. The comparison results showed the efficiency of the proposed method in the prediction of the stability numbers in spite of data incompleteness and incoherence.… More >

Doo Kie Kim¹, Seong Kyu Chang¹, Sang Kil Chang¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.2, No.1, pp. 29-34, 2007, DOI:10.3970/icces.2007.002.029

Abstract Accurate and realistic strength estimation before the placement of concrete is highly desirable. In this study, the advanced probabilistic neural network (APNN) was proposed to reflect the global probability density function by summing the heterogeneous local probability density function automatically determined in the individual standard deviation of variables. Currently, the estimation of the compressive strength of concrete is performed by a probabilistic neural network (PNN) on the basis of concrete mix proportions, and the PNN is improved by the iteration method. However, an empirical method has been incorporated to specify the smoothing parameter in the PNN technique, causing significant uncertainty… More >

G. Renaud¹, M. Liao¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.1, No.2, pp. 87-92, 2007, DOI:10.3970/icces.2007.001.087

Abstract This paper presents a probabilistic crack growth model developed for the Holistic Structural Integrity Process (HOLSIP) framework. Statistical data, obtained from testing and fractographic analyses of 2024-T3 test coupons, were used to derive the fatigue crack growth material variability. Results showed the relative impact of material variability in the short and long crack regimes. Monte Carlo simulations showed good agreement between analytical life distributions and test results. More >

Yong Li^1,*, Joel P. Conte², Philip E. Gill³

CMES-Computer Modeling in Engineering & Sciences, Vol.120, No.3, pp. 517-543, 2019, DOI:10.32604/cmes.2019.06269

Abstract In the field of earthquake engineering, the advent of the performance-based design philosophy, together with the highly uncertain nature of earthquake ground excitations to structures, has brought probabilistic performance-based design to the forefront of seismic design. In order to design structures that explicitly satisfy probabilistic performance criteria, a probabilistic performance-based optimum seismic design (PPBOSD) framework is proposed in this paper by extending the state-of-the-art performance-based earthquake engineering (PBEE) methodology. PBEE is traditionally used for risk evaluation of existing or newly designed structural systems, thus referred to herein as forward PBEE analysis. In contrast, its use for design purposes is limited… More >

R. Rongo^1,2, D. D’Ambrosio^1,2, G. Iovine^2,3, F. Lucà⁴, V. Lupiano⁵, V.P.Boñgolan⁶, W. Spataro^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.109-110, No.2, pp. 105-130, 2015, DOI:10.3970/cmes.2015.109.105

Abstract Determining sectors that could be affected by lava flows in volcanic areas is essential for risk mitigation purposes. Traditionally, when adopting methods based on probabilistic numerical simulations, the hazard is assessed by analysing a huge set of simulations of hypothetical events, each characterized by a distinct probability of occurrence based on statistics of historical events. If lateral or eccentric eruptions are also taken into account, simulated lava flows usually start from the nodes of regular grids of potential vents, uniformly covering the study area. In this study, an alternative approach to evaluate flow-type hazard, based on a nonuniform grid of… More >