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The  RSS North Eastern Local Group is jointly hosting a half-day event at
Newcastle University on "Statistical Challenges in Data-Centric Engineering"
with the RSS Emerging Applications Section. This event is sponsored by the
Alan Turing Institute - Lloyd's Register Foundation programme on data-
centric engineering (https://www.turing.ac.uk/research/research-programmes/
data-centric-engineering). The event will take place 1-4pm on Wednesday
21st November in TR4, Herschel Building, Newcastle University, and will
involve three speakers giving talks on their work in this area. Titles and
abstracts for the talks are given below.

Tea, coffee and biscuits will be available between the talks.

Attendance is free but for catering and room booking purposes we ask you to
register here: https://www.eventbrite.co.uk/e/statistical-challenges-in-data
-centric-engineering-tickets-51645393763?ref=estw

You can find details of all of our events on the local group website
http://www.mas.ncl.ac.uk/rss/ and you can follow us on Twitter
@NorthEasternRSS ‏.

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Speakers:

Dr Victoria Stephenson (University of Bath).

Seeking Resilience for Historic Engineered Structures; Working with Vague
and Uncertain Information.


As data-driven tools and techniques become more commonplace in the
management of the built environment, so resilient built systems are
promoted through the improved performance evaluation offered by digital
technologies and automated, real-time assessment. Application of these
data-driven
techniques to heritage structures is often not a viable solution, and as
such other statisticaland analytical methods need to be employed to better
understand and manage these ageing systems. Limited and vague information
is often available about the design, construction and current condition of
historic engineered structures. As such a high degree of uncertainty
underpins assessment of these physical systems. Added to this, current and
future uncertainty about the environmental conditions in which these
structures are needed to perform, compounds the issue of predicting and
managing them, and through this hinders resilience strategies. This
presentation explores this problem via a number of case studies involving
historic masonry structures in the UK, through work carried out with Dr.
Chris Oates (Newcastle University).

Dr Amy Wilson (University of Edinburgh).

Statistical modelling for assessing the risk of electricity shortfalls in
Great Britain.

A reliable electricity supply is a key consideration for energy system
planners. In Great Britain, a long-term planning study known as the
electricity capacity assessment is performed annually to assess the
long-term risk of insufficient electricity generation to meet demand. The
need to meet climate targets has resulted in a rise in wind and solar
generation in Great Britain. As wind and solar generation are weather
dependent, the effect of this rise has been an increase in variability in
the availability of electricity generation. An additional difficulty is
that wind, solar and demand are correlated. New statistical methods that
account for this correlation and increased variability are therefore needed
to assess the long-term risk of electricity shortfall. This presentation
will discuss statistical modelling for the electricity capacity assessment
study. Focus will be on models for demand and wind. A new model which makes
use of extreme value theory to capture the behaviour of demand-net-of-wind
at the extremes will be presented and compared to existing approaches.

Dr Matthew Revie (University of Strathclyde).

Reflections on Data-Driven Decision Making within Engineering Organisations.

Based on recent work with Scottish Water, Ministry of Defence, BAE SYSTEMS,
Scottish Power, SSE and Bruce Power, Matthew will reflect on some of the
existing challenges facing many Engineering organisations that are moving
towards a data-centric approach to decision-making. A high level overview
of these projects and the modelling involved will be provided, providing
the basis for drawing out similar challenges across different sectors.
These challenges will focus across a broad spectrum of organisational, data and
modelling challenges.


--
Catalina Vallejos M.

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