Hazard and early warning analysis based on domain specific modeling technologies

Imran, Syed

Hazard and early warning analysis based on domain specific modeling technologies

dc.check.embargoformat	Not applicable	en
dc.check.info	No embargo required	en
dc.check.opt-out	Not applicable	en
dc.check.reason	No embargo required	en
dc.check.type	No Embargo Required
dc.contributor.advisor	Dokas, Ioannis	en
dc.contributor.advisor	Pitt, Ian	en
dc.contributor.author	Imran, Syed
dc.contributor.funder	Environmental Protection Agency	en
dc.date.accessioned	2013-04-09T13:08:32Z
dc.date.available	2013-04-09T13:08:32Z
dc.date.issued	2013
dc.date.submitted	2013
dc.description.abstract	An aim of proactive risk management strategies is the timely identification of safety related risks. One way to achieve this is by deploying early warning systems. Early warning systems aim to provide useful information on the presence of potential threats to the system, the level of vulnerability of a system, or both of these, in a timely manner. This information can then be used to take proactive safety measures. The United Nation’s has recommended that any early warning system need to have four essential elements, which are the risk knowledge element, a monitoring and warning service, dissemination and communication and a response capability. This research deals with the risk knowledge element of an early warning system. The risk knowledge element of an early warning system contains models of possible accident scenarios. These accident scenarios are created by using hazard analysis techniques, which are categorised as traditional and contemporary. The assumption in traditional hazard analysis techniques is that accidents are occurred due to a sequence of events, whereas, the assumption of contemporary hazard analysis techniques is that safety is an emergent property of complex systems. The problem is that there is no availability of a software editor which can be used by analysts to create models of accident scenarios based on contemporary hazard analysis techniques and generate computer code that represent the models at the same time. This research aims to enhance the process of generating computer code based on graphical models that associate early warning signs and causal factors to a hazard, based on contemporary hazard analyses techniques. For this purpose, the thesis investigates the use of Domain Specific Modeling (DSM) technologies. The contributions of this thesis is the design and development of a set of three graphical Domain Specific Modeling languages (DSML)s, that when combined together, provide all of the necessary constructs that will enable safety experts and practitioners to conduct hazard and early warning analysis based on a contemporary hazard analysis approach. The languages represent those elements and relations necessary to define accident scenarios and their associated early warning signs. The three DSMLs were incorporated in to a prototype software editor that enables safety scientists and practitioners to create and edit hazard and early warning analysis models in a usable manner and as a result to generate executable code automatically. This research proves that the DSM technologies can be used to develop a set of three DSMLs which can allow user to conduct hazard and early warning analysis in more usable manner. Furthermore, the three DSMLs and their dedicated editor, which are presented in this thesis, may provide a significant enhancement to the process of creating the risk knowledge element of computer based early warning systems.	en
dc.description.status	Not peer reviewed	en
dc.description.version	Accepted Version
dc.format.mimetype	application/pdf	en
dc.identifier.citation	Imran, S., 2013. Hazard and early warning analysis based on domain specific modeling technologies . PhD Thesis, University College Cork.	en
dc.identifier.endpage	179
dc.identifier.uri	https://hdl.handle.net/10468/1038
dc.language.iso	en	en
dc.publisher	University College Cork	en
dc.rights	© 2013, Syed Imran	en
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/	en
dc.subject	Early warning signs	en
dc.subject	Domain specific modelling	en
dc.subject	Modelling languages	en
dc.subject.lcsh	Software engineering	en
dc.subject.lcsh	Risk management	en
dc.subject.lcsh	Domain-specific programming languages	en
dc.thesis.opt-out	false	*
dc.title	Hazard and early warning analysis based on domain specific modeling technologies	en
dc.type	Doctoral thesis	en
dc.type.qualificationlevel	Doctoral	en
dc.type.qualificationname	PhD (Science)	en
ucc.workflow.supervisor	cora@ucc.ie	*