Lee J.H.,ST Asset Management
Journal of Performance of Constructed Facilities | Year: 2015
A bridge-deterioration approach is to predict the condition ratings and the deterioration pattern of bridge elements for determining optimal maintenance strategies and estimating future funding requirements. To effectively predict long-term bridge performance, an advanced integrated deterioration approach has been developed that incorporates a time-based model, a state-based model with the Elman neural network (ENN) and a backward prediction model (BPM). The proposed approach involves the categorization of the selected inspection records by bridge components, material types, traffic volume, and the construction era. The primary advantage of such categorization is to group similar components together, thereby identifying the common deterioration patterns. A selection process embedded in the proposed approach offers the ability to automatically select the most appropriate model for predicting future bridge condition ratings. To demonstrate the advantage of the proposed approach in predicting long-term bridge performances, case studies are performed using available inspection records. To compare the performance of the proposed approach against the standard Markovian-based deterioration procedure in predicting future bridge condition ratings, a total of 40 bridges with 464 bridge substructure inspection records are selected and used as input. The predicted outcomes are validated by a cross-validation process, which demonstrates that the proposed approach is more accurate than the standard Markovian-based procedure. © 2014 American Society of Civil Engineers.
Zaghloul S.,ST Asset Management |
Al-Hazmi A.,Ministry of Municipal and Rural Affairs MOMRA |
Al-Harthi S.,Ministry of Municipal and Rural Affairs MOMRA
International Journal of Pavement Research and Technology | Year: 2013
Despite the fact that long-term pavement performance is highly dependent on the quality of construction, construction quality has rarely been addressed or considered in Pavement Management Systems (PMS). In this paper the impact of construction quality on pavement performance predictions, and hence the accuracy of PMS analysis, such as priority analysis and capital investment programs, is presented. This impact is demonstrated in this paper and found to be significant. A practical approach to integrate construction quality into PMS analysis is also presented in the paper. © Chinese Society of Pavement Engineering.
Bradshaw R.A.,ST Asset Management |
Bradshaw R.A.,Associated Engineering Ont. Ltd |
Illaszewicz G.L.,Associated Engineering Ont. Ltd |
Avrahamson Y.G.,ST Asset Management
Water Quality Research Journal of Canada | Year: 2013
In pursuing their mandate of providing good and safe drinking water, water system operators and asset owners work continuously towards developing and maintaining the trust and confidence of their customers. The goal of developing and maintaining customer trust has led to an increased emphasis in the water sector to explicitly assess and manage risks. In this paper, we introduce Layers of Protection Analysis (LOPA) as an approach to assessing technical and organizational risk in the water industry. LOPA offers a robust, rational and defensible approach for assessing the adequacy of independent protection layers (IPLs), such as treatment units, standard operating procedures and incident response procedures, used to mitigate environmental and process risks in water supply systems. The strength of LOPA is not only its ability to facilitate a review of technical systems' reliability, but also its versatility to be used for the review of organizational resilience under trying conditions and the opportunity to learn from failure. This is demonstrated in this paper with a review of more than 400 incidents affecting a large water utility serving some six million customers between 1997 and 2006. © IWA Publishing 2013.
Horng T.-L.,Feng Chia University |
Tien C.-Y.,ST Asset Management
Lecture Notes in Engineering and Computer Science | Year: 2013
The early exercise property of American option changes the original Black-Scholes equation to an inequality that cannot be solved via traditional finite difference method. Therefore, finding the early exercise boundary prior to spatial discretization is a must in each time step. This overhead slows down the computation and the accuracy of solution relies on if the early exercise boundary can be accurately located. A simple numerical method based on finite difference and method of lines is proposed here to overcome this difficulty in American option valuation. Our method averts the otherwise necessary procedure of locating the optimal exercise boundary before applying finite difference discretization. The method is efficient and flexible to all kinds of pay-off. Computations of American put, American call with dividend, American strangle options are demonstrated to show the efficiency of the current method.
Khan M.U.,ST Asset Management |
Mesbah M.,ST Asset Management |
Ferreira L.,ST Asset Management |
Williams D.J.,ST Asset Management
Road and Transport Research | Year: 2014
Natural disasters can cause severe damage to infrastructure such as roads. Currently, there are no road deterioration (RD) models that can address flooding or other natural disasters. It is suggested that a probabilistic RD model incorporating uncertainty of events such as flooding should be used for asset management purposes. Moreover, the derivation of post-flood and optimum maintenance and rehabilitation (M&R) strategies should also be incorporated into pavement life-cycle analysis. As a case study, the paper has considered flooding in Queensland, Australia, and has used 34 000 km of the Queensland's main road authority's road database. A critical literature review has been undertaken to assess existing RD models, work effect models and optimisation in obtaining an M&R strategy. The paper highlights existing pavement management systems (PMS) in Australia; the importance of RD models (deterministic and probabilistic) in a PMS and the use of probabilistic models for road deterioration prediction. Details of Markov chain, homogenous and non-homogeneous transition probability matrices (TPMs) have been discussed. The paper identifies six methods for deriving RD models using non-homogeneous TPMs. Approaches deriving (i) RD models with flooding, using nonhomogenous TPMs and Monte Carlo simulations and (ii) an optimum M&R strategy with HDM-4 model have been highlighted. As an example, the paper has given a new roughness-based RD model for a road group, to show its pavement performance incorporating flooding. Some expected results are also included, to show a pavement performance with post-flood and optimum M&R strategies. It is believed that this new RD model will help in selecting the appropriate treatment with necessary budget for post-flood rehabilitation. Certainly, it will help road engineers to manage flood-damaged roads more efficiently.
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