Temperature based death time estimation – Optimizing methods for practical application

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Temperature based death time estimation (TTDE) in the early pm phase is usually done by forensic specialists. In many application cases there are special non-standard cooling conditions in the sense of the Marshall and Hoare and Henßge approach (MHH), where the MHH-model cannot be applied. Phenomenological methods like MHH use ad hoc formulae of the rectal temperature time curve with fitted parameters. In contrast, physics based approaches like the Finite-Element-Method (FEM) solve the heat equation for complex geometries and real initial- and boundary-conditions. Therefore, the latter type of TTDE-technique seems most promising for real case work application. The project shall focus on enhancing the applicability of FEM-based TTDE-methods in practical casework on the basis of the earlier DFG-project on FEM-TTDE’s outcome. Starting from the individualized FEM-TTDE of the last project, we would like to investigate simplified mathematical models of body cooling with a smaller number of model parameters. Since they can be parametrized with much smaller effort in time, IT-, and measurement-equipment, direct application in crime scene case work TTDE will be possible on a much larger scale. The new project shall investigate the following three approaches to generate simplified models for TTDE: - Surrogate models - Dynamically reduced models - Geometrically reduced models The approaches used for Surrogate models include analytical representations as well as neural networks. Model construction is done by machine learning with FEM-generated training data. Reduced models in turn are discretizations with problem-specific basis functions. Geometrically reduced models downsize the individualized FE-model by omitting or coarsening the FE-mesh of model regions far from the core temperature measurement point. All of the aforementioned simplified model generation types start from individualized FEM-models resulting from the predecessor project. In case of the surrogate models this is done by using the individualized FE-model to generate the training-data necessary. Further goals are: - Representation of complex thermodynamic interactions between corpse and environment. - Classification of ambient scenarios and of their relevant thermodynamic processes as well as of their thermodynamic parameters to be recorded - (Partial) reconstruction of ambient temperature time curves during body cooling and their implementation in simplified methods. A climatic chamber can be used to measure thermodynamic data and mimic real cooling scenarios for the investigations mentioned above for phantoms or real human bodies. Thermal interactions will be captured using an IR camera, and object surfaces are digitized by 3D camera.