No abstract

Scheduling is a major concern in construction planning and management, and current construction simulation research typically targets the shortest total duration. However, uncertainties are inevitable in actual construction, which may lead to discrepancies between the actual and planned schedules and increase the risk of total duration delay. Therefore, developing a robust construction scheduling technique is of vital importance for mitigating disturbance and improving completion probability. In the present study, the authors propose a robustness analysis method that involves underground powerhouse construction simulation based on the Markov Chain Monte Carlo (MCMC) method. Specifically, the MCMC method samples construction disturbances by considering the interrelationship between the states of parameters through a Markov state transition probability matrix, which is more robust and efficient than traditional sampling methods such as the Monte Carlo (MC) method. Additionally, a hierarchical simulation model coupling critical path method (CPM) and a cycle operation network (CYCLONE) is built, using which construction duration and robustness criteria can be calculated. Furthermore, a detailed measurement method is presented to quantize the robustness of underground powerhouse construction, and the setting model of the time buffer is proposed based on the MCMC method. The application of this methodology not only considers duration but also robustness, providing scientific guidance for engineering decision making. We analyzed a case study project to demonstrate the effectiveness and superiority of the proposed methodology. underground powerhouse, construction schedule, simulation model, MCMC method, robustness Citation: Zhong D H, Bi L, Yu J, et al. Robustness analysis of underground powerhouse construction simulation based on Markov Chain Monte Carlo method.

Construction duration and schedule robustness are of great importance to ensure efficient construction. However, the current literature has neglected the importance of schedule robustness. Relatively little attention has been paid to schedule robustness via deviation of an activity’s starting time, which does not consider schedule robustness via structural deviation caused by the logical relationships among activities. This leads to a possibility of deviation between the planned schedule and the actual situation. Thus, an optimization model of construction duration and schedule robustness is proposed to solve this problem. Firstly, duration and two robustness criteria including starting time deviation and structural deviation were selected as the optimization objectives. Secondly, critical chain method and starting time criticality (STC) method were adopted to allocate buffers to the schedule in order to generate alternative schedules for optimization. Thirdly, hybrid grey wolf optimizer with sine cosine algorithm (HGWOSCA) was proposed to solve the optimization model. The movement directions and speed of grey wolf optimizer (GWO) was improved by sine cosine algorithm (SCA) so that the algorithm’s performance of convergence, diversity, accuracy, and distribution improved. Finally, an underground power station in China was used for a case study, by which the applicability and advantages of the proposed model were proved.

Traditional project evaluation and optimal selection based on multi-objective programming and Delphi is highly dependent on subjective cognition, difficult to define weighted coefficient and without considering the uncertainty of the indexes. To solve these problems, this paper builds a multi-level fuzzy comprehensive evaluation model for the evaluation and optimal selection of diversion tunnels construction simulation schemes, and unites entropy weight and analytic hierarchy process (AHP) to calculate composite index weights. Through the comprehensive evaluation in a real-life diversion tunnels, this method is proved advanced and intuitive for giving objective evaluations and providing optimization suggestions for program development.

The construction process of water conveyance tunnel is complex and stochastic under the karst geological condition. Aiming at analyzing the construction process under this special condition, a simulation modeling method of water conveyance tunnel construction is presented. Through demonstrating the simulation analysis and predicting the schedules in a real case study of a water conveyance tunnel, this method is proved advanced and intuitive for formulating and analyzing the construction schedules under the karst geological condition.

The design of a feedback equalizer (FE) in Multi-level Decisiofi Feedback Equalization (MDFE) for magnetic recording channels is presented. The fully digital feedback equalizer is implemented with a look-up-table based architecture. The FE has 11 taps where the past decisions are stored and subsequently used to determine the feedback coefficients. With the insertion of a single pipeline, two clock periods are allowed for the completion of the critical timing loop. The improvement in throughput is made possible with the application of look-ahead computation. Based on a 0.35-pm CMOS technology, the post-layout simulation results show that the FE is capable of operating at a clock rate of 132MHz under the typical conditions.

A 100 Mbls experimental multilevel DecisionFeedback Equalization read channel has been designed and prototyped in discrete-components. The analog forward equalizer consists of two Bi-quads, designed based on the maximization of inner eye versus noise power plus uncancelled IS1 at the input to the detector. The feedback equalizer consists of a 6 taps filter plus an RC exponential decay network which helps reduce hardware complexity. The digitally implemented timinglgainldc-offset loops are adjusted only when there are transitions. Bench testing shows that the error rate performance is about 1.5 dB away from the theoretically designed performance at user density 2.0.

A rapid and reliable acquisition procedure is proposed for DFE detection. This new approach eliminates the false-lock problem which arises in these detectors due to the decision feedback. The acquisition process comprises four distinct steps. It is illustrated with MDFE detection on the magnetic recording channel. Monte-Carlo simulations verify the robustness and accuracy of the acquisition process.