Abstract: The Markov decision process (MDP) based
methodology is implemented in order to establish the optimal
schedule which minimizes the cost. Formulation of MDP problem
is presented using the information about the current state of pipe,
improvement cost, failure cost and pipe deterioration model. The
objective function and detailed algorithm of dynamic programming
(DP) are modified due to the difficulty of implementing the
conventional DP approaches. The optimal schedule derived from
suggested model is compared to several policies via Monte
Carlo simulation. Validity of the solution and improvement in
computational time are proved.
Abstract: CO2 capture and storage/sequestration (CCS) is a key technology for addressing the global warming issue. This paper proposes an integrated model for the whole chain of CCS, from a power plant to a reservoir. The integrated model is further utilized to determine optimal operating conditions and study responses to various changes in input variables.
Abstract: Water pipe network is installed underground and once equipped, it is difficult to recognize the state of pipes when the leak or burst happens. Accordingly, post management is often delayed
after the fault occurs. Therefore, the systematic fault management system of water pipe network is required to prevent the accident and
minimize the loss. In this work, we develop online fault detection system of water pipe network using data of pipes such as flow rate
or pressure. The transient model describing water flow in pipelines
is presented and simulated using MATLAB. The fault situations such
as the leak or burst can be also simulated and flow rate or pressure data when the fault happens are collected. Faults are detected using
statistical methods of fast Fourier transform and discrete wavelet transform, and they are compared to find which method shows the
better fault detection performance.