• Computational Structural Engineering : An International Journal
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• v.1 no.2
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• pp.137-137
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• 2001

The reliability/redundancy of structural system has become a serious concern among engineers and researchers after structural failures in Northridge and Kobe earthquakes. The reliability/redundancy factor, ρ, in current codes considers only member force and floor area and has received much criticism from dissatisfied engineers. Within a reliability framework. the redundancy is investigated for dual systems of primary shear walls and secondary moment frames and steel moment frame systems. Probabilistic performance analyses are carried out baled on nonlinear responses under SAC ground motion. The effects of structural configuration, ductilily capacity, 3-D motion, and uncertainty of demand verses capacity are investigated. Important redundancy-contributing factors are identified and a uniform-risk redundancy factor is developed for design. The result are compared with the p factor and its inconsistency is pointed out.

• Smart Structures and Systems
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• v.31 no.2
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• pp.113-130
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• 2023

Hybrid simulation (HS) has attracted community attention in recent years as an efficient and effective experimental technique for structural performance evaluation in size-limited laboratories. Traditional hybrid simulations usually take deterministic properties for their numerical substructures therefore could not account for inherent uncertainties within the engineering structures to provide probabilistic performance assessment. Reliable structural performance evaluation, therefore, calls for stochastic hybrid simulation (SHS) to explicitly account for substructure uncertainties. The experimental design of SHS is explored in this study to account for uncertainties within analytical substructures. Both computational simulation and laboratory experiments are conducted to evaluate the pseudo-random Sobol sequence for the experimental design of SHS. Meta-modeling through polynomial chaos expansion (PCE) is established from a computational simulation of a nonlinear single-degree-of-freedom (SDOF) structure to evaluate the influence of nonlinear behavior and ground motions uncertainties. A series of hybrid simulations are further conducted in the laboratory to validate the findings from computational analysis. It is shown that the Sobol sequence provides a good starting point for the experimental design of stochastic hybrid simulation. However, nonlinear structural behavior involving stiffness and strength degradation could significantly increase the number of hybrid simulations to acquire accurate statistical estimation for the structural response of interests. Compared with the statistical moments calculated directly from hybrid simulations in the laboratory, the meta-model through PCE gives more accurate estimation, therefore, providing a more effective way for uncertainty quantification.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.04a
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• pp.479-486
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• 2004

The purpose of this study is to practical use with increase safety, usablility and economical. In this study, the property of fatigue behavior was tested by comparing reinforced concrete and steel fiber reinforced concrete. The basic test, the static test and fatigue test were used as the research methods. Basic on the test, the material compressive strength test and split tensile strength test ware conducted 7 days and 28 days after the concrete was poured. In the static test, there ware four types of experimental variables of the steel fiber mixing ratio : 0.00%, 0.75%, 1.00%, and 1.25%. The ultimate load initial diagonal tension crack, and initial load of flexural cracking were all observed by static test. A methodology for the probabilistic assement of steel fiber reinforced concrete(SFRC) which takes into account material variability, confinement model uncertainty and the uncertainty in local and globa failure criteria is applied for the derivation of vulnerability curves for the serviceability and ultimate limit states, the reliability of SFRC using the proposed practical linear limit state model is evaluated by using the AFOSM(Advanced First Order Second Moment) method and MCS(monte-Calrosimulation) method.

• Analytical Science and Technology
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• v.32 no.6
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• pp.225-232
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• 2019

Traceability establishment in chemical measurements is a like a linkage established through an unbroken chain from the measured results to the international system (SI) of units. The primary process for traceability establishment is the purity assignment of a target material to be measured. In this study, we studied the purity assignment of 17α-hydroxyprogesterone (17-OHP). The presence of 17-OHP is indicative of congenital adrenal hyperplasia (CAH) and it builds up due to the deficiency of 21-hydroxylase and 11β-hydroxylase enzyme in the human blood. The purity assignment of 17-OHP was performed by the mass balance method, in which the impurities are categorized into four classes: total related structural impurities, water, residual organic solvents, and nonvolatiles/inorganics. The total related structural impurities were characterized by HPLC-UV; water content was determined by Karl-Fisher coulometer; and the total residual solvents and nonvolatiles/inorganics were determined by TGA. The purity of 17-OHP from a commercial manufacturer was calculated as 993.30 mg/g, and the expanded uncertainty was 0.58 mg/g. The proposed method was validated by uncertainty evaluation and comparing with the actual value of purity.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1682-1685
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• 2005

System algorithms estimated by deterministic input may occur the error between predicted and actual output. Especially, actual system can't predict the exact outputs due to uncertainty and tolerance of input parameters. A single output to a set of inputs has a limited value without the variation. Hence, we should consider various scatters caused by the load assessment, material characteristics, stress analysis and manufacturing methods in order to perform the robust design or estimate the reliability of structure. The system design with uncertainty should perform the probabilistic structural optimization with the statistical response and the reliability. This method calculated the probability distributions of the characteristics such as stress by combining stress analysis, response surface methodology and Monte-Carlo Method and got the probabilistic sensitivity. The sensitivity of structural response with respect to inconstant design variables was estimated by fracture probability. Therefore, this paper proposed the probabilistic reliability design method for fracture of uncorved freight end beam and the design criteria by fracture probability.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.5
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• pp.631-638
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• 2013

The probabilistic fatigue life analysis is one of the common methods to account the uncertainty of parameters on the structural failure. Frequently, the Bayesian approach has been demonstrated as a proper method to show the uncertainty of parameters. In this work, the application of probabilistic fatigue life prediction method for the aircraft structure was studied. This effort was conducted by using the PoF(Probability of Failure) based on Bayesian approach. Furthermore, numerical example was carried out to confirm the validation of the suggested approach. In conclusion, it was shown that the Bayesian approach can calculate the probabilistic fatigue lives and the quantitative value of PoF effectively for the aircraft structural component. Moreover the calculated probabilistic fatigue lives can be utilized to determine the optimized inspection period of aircraft structures.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.5
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• pp.589-595
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• 2010

This paper presents a reliability-based shape optimization (RBSO) using the evolutionary structural optimization (ESO). An actual design involves uncertain conditions such as material property, operational load, poisson's ratio and dimensional variation. The deterministic optimization (DO) is obtained without considering of uncertainties related to the uncertainty parameters. However, the RBSO can consider the uncertainty variables because it has the probabilistic constraints. In order to determine whether the probabilistic constraint is satisfied or not, simulation techniques and approximation methods are developed. In this paper, the reliability-based shape design optimization method is proposed by utilization the reliability index approach (RIA), performance measure approach (PMA), single-loop single-vector (SLSV), adaptive-loop (ADL) are adopted to evaluate the probabilistic constraint. In order to apply the ESO method to the RBSO, a sensitivity number is defined as the change of strain energy in the displacement constraint. Numerical examples are presented to compare the DO with the RBSO. The results of design example show that the RBSO model is more reliable than deterministic optimization.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.6
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• pp.77-82
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• 2008

This paper presents a Reliability-Based Topology Optimization(RBTO) using the Evolutionary Structural Optimization(ESO). An actual design involves some uncertain conditions such as material property, operational load and dimensional variation. The Deterministic Topology Optimization(DTO) is obtained without considering the uncertainties related to the uncertainty parameters. However, the RBTO can consider the uncertainty variables because it has the probabilistic constraints. In order to determine whether the probabilistic constraints are satisfied or not, simulation techniques and approximation methods are developed. In this paper, the reliability index approach(RIA) is adopted to evaluate the probabilistic constraints. In order to apply the ESO method to the RBTO, sensitivity number is defined as the change in the reliability index due to the removal of the ith element. Numerical examples are presented to compare the DTO with the RBTO.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.10
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• pp.1318-1326
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• 2014

The purpose of a tracking control system is to track a moving target and to find the exact information of the target. If the platform of the tracking control system is equipped on a moving vehicle such as a ship, the tracking control system will treat even the additional platform motion. In order to avoid the complexity comprising the tracking control system, a process to treat the platform motion, named stabilizing system, must be separated from the tracking control system. In this paper, a method to comprise an attitude control system for the platform stabilization is proposed using an adaptive fuzzy control which is applicable to the system with structural and parametric uncertainty. The suggested adaptive fuzzy control algorithm is the 2nd/1st-type indirect adaptive fuzzy control algorithm using the advantages of 1st-type and 2nd-type indirect adaptive fuzzy control algorithm. Several experiments using the implemented stabilizing system are executed for verifying the effectiveness of the suggested method.

• Journal of the Korean Society for Railway
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• v.12 no.3
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• pp.342-347
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• 2009

Failure Mode Effects and Criticality Analysis (FMECA) is one of most widely used methods in modern engineering system to investigate potential failure modes and its severity upon the system. While performing FMECA, the experts evaluates criticality and severity of each failure mode and visualize the risk level matrix putting those indices to column and row variable respectably. Which results uncertainty in the result. In order to handle the uncertainty and conclude risk level matrix, this paper proposes a new FMECA procedure using minimal cut set (MCS) and fuzzy theory. Severity is calculated by proposed structural importance while criticality is determined by typical equipment failure rate data from IEEE Std 493. Finally, the risk level is compounded of these indices.