30,948 research outputs found
Operational strategies for offshore wind turbines to mitigate failure rate uncertainty on operational costs and revenue
Several operational strategies for offshore wind farms have been established and explored in order to improve understanding of operational costs with a focus on heavy lift vessel strategies. Additionally, an investigation into the uncertainty surrounding failure behaviour has been performed identifying the robustness of different strategies. Four operational strategies were considered: fix on fail, batch repair, annual charter and purchase. A range of failure rates have been explored identifying the key cost drivers and under which circumstances an operator would choose to adopt them. When failures are low, the fix on fail and batch strategies perform best and allow flexibility of operating strategy. When failures are high, purchase becomes optimal and is least sensitive to increasing failure rate. Late life failure distributions based on mechanical and electrical components behaviour have been explored. Increased operating costs because of wear-out failures have been quantified. An increase in minor failures principally increase lost revenue costs and can be mitigated by deploying increased maintenance resources. An increase in larger failures primarily increases vessel and repair costs. Adopting a purchase strategy can negate the vessel cost increase; however, significant cost increases are still observed. Maintenance actions requiring the use of heavy lift vessels, currently drive train components and blades are identified as critical for proactive maintenance to minimise overall maintenance costs
SHM strategy optimization and structural maintenance planning based on Bayesian joint modelling
In this contribution, an example is used to illustrate the application of
Bayesian joint modelling in optimizing the SHM strategy and structural maintenance
planning. The model parameters were evaluated first, using the Markov
Chain Monte Carlo (MCMC) method. Then different parameters including expected
SHM accuracy and risk acceptance criteria were investigated in order to
give an insight on how the maintenance planning and life-cycle benefit are influenced.
The optimal SHM strategy was then identified as the one that maximizes
the benefit
Report : review of the literature : maintenance and rehabilitation costs for roads (Risk-based Analysis)
Realistic estimates of short- and long-term (strategic) budgets for maintenance and
rehabilitation of road assessment management should consider the stochastic
characteristics of asset conditions of the road networks so that the overall variability
of road asset data conditions is taken into account.
The probability theory has been used for assessing life-cycle costs for bridge
infrastructures by Kong and Frangopol (2003), Zayed et.al. (2002), Kong and
Frangopol (2003), Liu and Frangopol (2004), Noortwijk and Frangopol (2004), Novick
(1993). Salem 2003 cited the importance of the collection and analysis of existing
data on total costs for all life-cycle phases of existing infrastructure, including bridges,
road etc., and the use of realistic methods for calculating the probable useful life of
these infrastructures (Salem et. al. 2003). Zayed et. al. (2002) reported conflicting
results in life-cycle cost analysis using deterministic and stochastic methods.
Frangopol et. al. 2001 suggested that additional research was required to develop
better life-cycle models and tools to quantify risks, and benefits associated with
infrastructures.
It is evident from the review of the literature that there is very limited information on
the methodology that uses the stochastic characteristics of asset condition data for
assessing budgets/costs for road maintenance and rehabilitation (Abaza 2002,
Salem et. al. 2003, Zhao, et. al. 2004). Due to this limited information in the research
literature, this report will describe and summarise the methodologies presented by
each publication and also suggest a methodology for the current research project
funded under the Cooperative Research Centre for Construction Innovation CRC CI
project no 2003-029-C
Implementing Snow Load Monitoring to Control Reliability of a Stadium Roof
This contribution shows how monitoring can be
used to control reliability of a structure not complying
with the requirements of Eurocodes. A general
methodology to obtain cost-optimal decisions using limit
state design, probabilistic reliability analysis and cost
estimates is utilised in a full-scale case study dealing with
the roof of a stadium located in Northern Italy. The
results demonstrate the potential of monitoring systems
and probabilistic reliability analysis to support decisions
regarding safety measures such as snow removal, or
temporary closure of the stadium
Analysis of offshore wind turbine operation & maintenance using a novel time domain meteo-ocean modeling approach
This paper presents a novel approach to repair modeling using a time domain Auto-Regressive model to represent meteo-ocean site conditions. The short term hourly correlations, medium term access windows of periods up to days and the annual distibution of site data are captured. In addition, seasonality is included. Correlation observed between wind and wave site can be incorporated if simultaneous data exists. Using this approach a time series for both significant wave height and mean wind speed is described. This allows MTTR to be implemented within the reliability simulation as a variable process, dependent on significant wave height. This approach automatically captures site characteristics including seasonality and allows for complex analysis using time dependent constaints such as working patterns to be implemented. A simple cost model for lost revenues determined by the concurrent simulated wind speed is also presented. A preliminary investigation of the influence of component reliability and access thresholds at various existing sites on availability is presented demonstrating the abiltiy of the modeling approach to offer new insights into offshore wind turbine operation and maintenance
- âŠ