• Mark Svare

Student thesis: Doctoral ThesisDoctor of Philosophy


Forensic Scientist, Engineers and Fire Investigators (Fire Investigation Practitioners), often working together as a team are commonly tasked with determining both the origin and the cause of fire. The internationally recognized, National Fire Protection Association (NFPA) 921: “Guide for Fire and Explosion Investigations” [1] currently outlines three methods of data collection to assist in fire origin determination. These are (1) witness information and / or electronic data, (2) fire patterns (including identification of electrical arc sites) and (3) fire dynamics. The correct application of any fire origin determination method is incumbent on the knowledge, skill, education, training and experience of the fire investigator.

Currently, the most commonly published method of utilizing the electrical system for origin determination is called arc mapping, although more correctly identified as arc surveying. According to NFPA 921, arc mapping is based on the fire investigator’s ability to identify and document a fire pattern derived from the identification of electrical arc sites on wiring that may be used to aid in determining the area of fire origin and / or spread.

The first objective of this work was to explore the ability of fire investigation practitioners to correctly identify different types of electrical artefacts (arc melt sites and fire melt sites) and the impact that a short custom training intervention had on this capability. The second objective was to determine the ability fire investigation practitioners to mobilise existing electrical knowledge to assist in origin and cause determinations and the impact of training on this skill development.

65 full-scale, live burn cell experiments and 121 scaled experiments using a designed experimental test apparatus were conducted utilizing both United Kingdom and North American electrical cabling. The ability of the scaled experiments to generate the same morphological artefacts as a real fire was validated and a subset of the generated artefacts from both the full-scale fires and scaled experiments were used as the test set for fire investigation practitioners.

Quantitative analysis of the physical artefacts generated during the electrical experiments (full-scale and scaled fire experiments) identified measurable differences between arc melt (AM) sites and fire melt (FM) sites that were located on post-fire damaged electrical wiring recovered from the fire scenes and test cables generated using the experimental apparatus.

The experiments were conducted under specific conditions and in particular the fault current was controlled for both the full-scale fires and scaled experiments using overcurrent protection devices (circuit breakers) to match domestic electrical supply. Additional experiments may be required for different or varying electrical circuits configuration and installations. The sample test set was generated in order to produce exemplars of specific damage (arc melts and fire melts) so that the ability of practitioners to identify such damage correctly could be tested before and after training. As such they provide a fit for purpose sample set to address this specific research question.

Qualitative and quantitative data was collected by surveying 912 respondents within the fire investigation community across four test conditions (i) no specific electrical training (n=221) (ii) the impact of a one-hour electrical fire investigation presentation (n=320), (iii) the use of electrical knowledge on origin and cause determination (n=371) and (iv) the impact of a custom 40hour training course on the use of use of electrical knowledge on origin and cause determinations (n=11).

The resultant data demonstrated that a short electrical fire training session improved fire investigators abilities to correctly distinguish between arc melt sites and fire melt sites by over 30%. Moreover, the abilities of fire investigators, once trained effectively, to correctly implement their electrical knowledge for origin and cause determination also increased by over 30% .
Date of Award2022
Original languageEnglish
SupervisorNiamh Nic Daeid (Supervisor) & Rod Jones (Supervisor)

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