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D. Wiegand, F. Breitenecker, N. Popper, G. Hodecek, S. Tauböck:
"Utilization of Buildings: Understand, Model, Simulate! The MoseSpace Project at TU Vienna";
Vortrag: MATHMOD 2012 - 7th Vienna Conference on Mathematical Modelling, Wien; 14.02.2012 - 17.02.2012; in: "Preprints Mathmod 2012 Vienna - Full Paper Volume", F. Breitenecker, I. Troch (Hrg.); Argesim / Asim, 38 (2012), S. 4 - 5.

Developers of real estate and infrastructure and builders in general are faced with the task of designing, steering
and improving socio-technical systems. They deal with project organisation and with buildings and their use, all
along its life-cycle - from the first idea up to the building´s demolition. Due to the dynamic and complexity inherent
to such real world systems, almost all of the decisions faced by the aforementioned groups of people are based
upon incomplete or insufficient information. To them models and simulations are worthless if they do not answer
particular questions or provide valuable, additional information to support decision making processes.
In order for a model to provide vital information or support for decision
making in urban and real estate development, especially concerning
sustainability aspects, it is essential to assess the impacts of
potential changes of built environment respecting its interrelationship
with the systemic context. E.g. ecological builds constructed at
the periphery of cities might increase the overall carbon emission in
a certain region, due to fact that those who move into these buildings
will now drive to their workplaces by car. To identify the potential
scope for action a systemic perspective is necessary. According to
Schalcher such a holistic view is only possible "if the interdependence
of all human activity and natural events is consciously accepted
and not neglected" [1]. Consequentially one of the main obstacles
for a successful deployment of a simulation tool within (although not
limited to) this area of application, is the identification not only of
the system´s parameters but also of all external ones.
Drawing the border between these two sets of influencing factors is a very delicate task, as it is dependent of the
objective target, the methodological approach and the subjective point of view or definition of the system. Following
these steps one does obtain a dynamic model of the system at hand which becomes subject to in-depth analysis.
Based on this dynamic model closed loops, main influencing factors and thus reasonable action can be identified.
Only after such an analysis - and subsequent choice of rewarding search directions - does it become sensible
to engage mathematical modelling and simulation to improve ecological and economical sustainability and replace
experiences and assumptions by explicit knowledge. With the prior steps taken, simulation tools can now greatly
aid the decision finding process, as they produce results that address the questions formulated.
At the Vienna University of Technology the shortage of lecture rooms was the incentive to develop a model to
analyse and improve the utilisation of these rooms by means of a simulation and planning environment - called
MoreSpace [3]. An extensive analysis of the given situation based on current booking data as well as a thorough
inquiry about the room required showed the utilisation of rooms to be surprisingly low. The simulation model
developed according to these insights, following the aforementioned principal guidelines for building utilization,
allowed a further investigation of this situation; using the possibility of experimenting quickly showed that even
small well directed changes to the booking procedure did show great impact by increasing the room capacity utilisation
on one hand and merging free time slots to increase the disposability of lecture room space on the other
hand. Thus it could be proven that not the quantity of lecture room is the main problem but the strategy used to
utilise it. But only a very detailed and in depth analysis showed the source of the problem to be not based on the
room structure itself but the behaviour of the surrounding system.
MoreSpace , a simulation and planning tool based on DEVS and planning heuristics ([3], [4]), has been developed
within grants of Vienna University of Technology and by ZIT, the technology promotion agency of the City of
Vienna; MoreSpace is intended for general use at universities, schools, and similar institutions which want to
improve the utilization of their buildings