Deterioration/Degradation Modelling of Infrastructure Assets
This webinar provides an overview of CIRIA's industry guidance Deterioration modelling of civil engineering infrastructure assets C784. C784 provides industry with current practices, needs, and future intentions with respect to the evaluation, and prediction of asset condition, and performance.
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Background
Predicting the future is difficult but, for those responsible for the management of assets, it is necessary. Deterioration modelling essentially provides a systematic means of predicting the future, improving asset knowledge in support of the wider process of effective asset management. In particular, results from deterioration models can make an important contribution to the understanding of asset performance and risk and how these might change over time, which is fundamental to the core asset management principles of informed planning and decision making.
Deterioration modelling approaches have developed significantly in the past 20 years or so, and over this period a great quantity of academic literature has been published giving details of specific methodologies and approaches. Many of these approaches are relatively complex and require significant specialist knowledge that is not typically held by those involved in the management and maintenance of civil engineering assets.
The skills and technologies that are required to make deterioration modelling a more viable and rewarding prospect than has previously been the case – including environmental and structural sensors, non-contact scanning equipment, data transmission, storage and processing capabilities and advanced modelling and machine learning techniques - are rapidly developing and becoming more familiar and widely available to asset owners and their suppliers. Against a backdrop of ongoing constraints on resources for maintaining and renewing existing civil infrastructure and of current UK and international initiatives to make better use of data for asset management, to standardise data formats and encourage and facilitate the sharing of data and to develop associated data acquisition and analysis technologies, this would appear to be a very opportune time to advance the field of deterioration modelling to support the achievement of these aims.
Why attend
• Receive an overview of C784
• Listen to case study presentations
When
Wednesday 29th April 2020
4:00 - 5:00
Programme
Leo McKibbins, Mott MacDonald
Simon Gee, AECOM
Joe Roebuck, Arcadis Gen
Fees
Free for CIRIA members
Non-members: £35 + VAT
Booking
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