Deterioration/degradation modelling of infrastructure assets

This webinar will provide an overview of new CIRIA 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.


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

Delegates on this webinar will:

  • Receive an overview of C784
  • Listen to case study presentations
  • Ask questions of the author team and other presenters


12:30 Chair’s introduction

12:35 Author presentation - Leo McKibbins, Mott MacDonald

12:55 Presentation 3 - Simon Gee, AECOM

13:05 Presentation 2 - Joe Roebuck, SEAMS

13:15 Q&A

Thursday 16th May
12:30 - 13:30

Free for CIRIA members
Non-members: £35 + VAT

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The link to access the webinar is sent 2 days before the event. If you have registered after 14th May, the link will be sent to late bookings on 16th May at 10am.

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Further information
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Tel: 020 7549 3300
Fax: 020 7549 3349

16/05/2019 - 16/05/2019

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