• Journal of Korean Society for Quality Management
• /
• v.35 no.4
• /
• pp.61-66
• /
• 2007

The performance of a building material degrades as time goes by and the failure of the material is often defined as the point at which the performance of the material reaches a pre-specified degraded level. Based on a stochastic deterioration model, a performance based service life prediction method for building materials and components is developed. As a stochastic degradation model, a gamma process is considered and lifetime distribution and service life of a material are predicted using the degradation model. A numerical example is provided to illustrate the use of the proposed service life prediction method.

• Nuclear Engineering and Technology
• /
• v.19 no.4
• /
• pp.233-241
• /
• 1987

Difficulties are encountered when the behavior of complex systems (i.e., fuel failure probability) that have unreliable deterministic models is predicted. For more realistic prediction of the behavior of complex systems with limited observational data, the present study was undertaken to devise an approach of combining predictions from the deterministic model and actual observational data. Predictions by this method of combining are inferred to be of higher reliability than separate predictions made by either model taken independently. A systematic method of hierarchical pattern discovery based on the method developed in the SPEAR was used for systematic search of weighting factors and pattern boundaries for the present method. A sample calculation was performed for prediction of CANDU fuel failures that had occurred due to power ramp during refuelling process. It was demonstrated by this sample calculation that there exists a region of feature space in which fuel failure probability from the PROFIT model nearly agree with that from observational data.

• Computers and Concrete
• /
• v.12 no.6
• /
• pp.775-783
• /
• 2013

A novel reliability-based work model of k/n (G) system has been developed. Unit failure probability is given based on the load and strength distributions and according to the stress-strength interference theory. Then a dynamic reliability prediction model of repairable k/n (G) system is established using probabilistic differential equations. The resulting differential equations are solved and the value of k can be determined precisely. The number of work unit k in repairable k/n (G) system is obtained precisely. The reliability of whole life cycle of repairable k/n (G) system can be predicted and guaranteed in the design period. Finally, it is illustrated that the proposed model is feasible and gives reasonable prediction.

• Steel and Composite Structures
• /
• v.48 no.6
• /
• pp.667-679
• /
• 2023

Concrete filled rectangular steel tubular (CFRST) composite truss girder is composed of the CFRST truss and concrete slab. The failure mechanism of the girder was different under bending and shear failure modes. The bending and shear strength of the girder were investigated experimentally. The influences of composite effect and shear to span ratio on failure modes of the girder was studied. Results indicated that the top chord and the joint of the truss were strengthened by the composited effect. The failure modes of the specimens were changed from the joint on top chord to the bottom chord. However, the composite effect had limited effect on the failure modes of the girder with small shear to span ratio. The concrete slab and top chord can be regarded as the composite top chord. In this case, the axial force distribution of the girder was close to the pin-jointed truss model. An approach of strength prediction was proposed which can take the composite effect and shear to span ratio into account. The approach gave accurate predictions on the strength of CFRST composite truss girder under different bending and shear failure modes.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.23 no.4
• /
• pp.111-130
• /
• 1998

We propose an imperfect repair model which depends on external effects quantified by covariates. The model is based on the Brown-Proschan imperfect repair model wherefrom the probability of perfect repair is represented by a function of covariates. We are motivated by deficiency of the BP model whose stationarity prevents us from predicting dynamically the time to next failure according to external condition. Five types of function for the probability of perfect repair are proposed. This article also presents a procedure for estimating the parameter of the function for the probability of perfect repair, as well as the inherent lifetime distribution of the system, based on consecutive inter-failure times and the covariates. The estimation procedure is based on the expectation-maximization principle which is suitable to incomplete data problems. focusing on the maximization step, we derive some theorems which guarantee the existence of the solution. A Monte Carlo study is also performed to illustrate the prediction power of the model as well as to show reasonable properties of the estimates. The model reduces significantly the mean square error of the in-sample prediction. so it can be utilized in real fields for evaluating and maintaining repairable systems.

• Proceedings of the Korea Concrete Institute Conference
• /
• 2001.05a
• /
• pp.207-212
• /
• 2001

The aim of this study is to present a practical and simple method for decision of ultimate failure mode of high-strength concrete beam members, based on interaction between shear strength and displacement ductility. Four tests were conducted on full-scale beam specimens having concrete compressive strength of 410kgf/$cm^{2}$. Prediction of failure mode from presented method and comparison with test results are also presented

• Journal of Electrical Engineering and Technology
• /
• v.6 no.6
• /
• pp.760-768
• /
• 2011

The performance of transmission lines and its shielding design during a lightning phenomenon are quite essential in the maintenance of a reliable power supply to consumers. The leader progression model, as an advanced approach, has been recently developed to calculate the shielding failure rate (SFR) of transmission lines using geometrical data and physical behavior of upward and downward lightning leaders. However, such method is quite time consuming. In the present paper, an effective method that utilizes artificial neural networks (ANNs) to create a metamodel for calculating the SFR of a transmission line based on shielding angle and height is introduced. The results of investigations on a real case study reveal that, through proper selection of an ANN structure and good training, the ANN prediction is very close to the result of the detailed simulation, whereas the Processing time is by far lower than that of the detailed model.

• Journal of Intelligence and Information Systems
• /
• v.7 no.2
• /
• pp.83-93
• /
• 2001

Prediction of corporate failure using past financial data is well-documented topic. Early studies of bankruptcy prediction used statistical techniques such as multiple discriminant analysis, logit and probit. Recently, however, numerous studies have demonstrated that artificial intelligence such as neural networks (NNs) can be an alternative methodology for classification problems to which traditional statistical methods have long been applied. Although numerous theoretical and experimental studies reported the usefulness or neural networks in classification studies, there exists a major drawback in building and using the model. That is, the user can not readily comprehend the final rules that the neural network models acquire. We propose a genetic algorithms (GAs) approach in this study and illustrate how GAs can be applied to corporate failure prediction modeling. An advantage of GAs approach offers is that it is capable of extracting rules that are easy to understand for users like expert systems. The preliminary results show that rule extraction approach using GAs for bankruptcy prediction modeling is promising.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.38 no.12
• /
• pp.1379-1385
• /
• 2014

Even the rough prediction of the product test time before the lifetime test of mechanical component begins would be of use in estimating cost and deciding how to keep up with the test. The reliability predictions of mechanical components are difficult because failure or degradation mechanisms are complicated, and few plausible databases are available for lifetime prediction. Therefore, this study conducted lifetime predictions of elastomeric U seals that were respectively installed in a hydraulic actuator and a pneumatic actuator using lifetime models and a field database based on failure physics and an actual test database obtained from the NSWC handbook. To validate the results, the predicted failure rates were compared with the actual lifetime test results acquired in the lab durability tests. Finally, this study discussed an engineering procedure to determine the coefficients in the failure rate models and analyzed the sensitivity of each influential parameter on the seal lifetime.

• Steel and Composite Structures
• /
• v.28 no.2
• /
• pp.251-266
• /
• 2018

Compared to conventional flat web I-beams, the prediction of shear buckling stress of corrugated web steel beams (CWSBs) is not straightforward. But the CWSBs combined advantages of lightweight large spans with low-depth high load-bearing capacities justify dealing with such difficulties. This work investigates experimentally and analytically the shear strength of trapezoidal CWSBs. A set of large scale CWSBs are manufactured and tested to failure in shear. The results are compared with widely accepted CWSBs shear strength prediction models. Confirmed by the experimental results, the linear buckling analyses of trapezoidal corrugated webs demonstrated that the local shear buckling occurs only in the flat plane folds of the web, while the global shear buckling occurs over multiple folds of the web. New analytical prediction model accounting for the interaction between the local and global shear buckling of CWSBs is proposed. Experimental results from the current work and previous studies are compared with the proposed analytical prediction model. The predictions of the proposed model are significantly better than all other studied models. In light of the dispersion of test data, accuracy, consistency, and economical aspects of the prediction models, the authors recommend their proposed model for the design of CWSBs over the rest of the models.