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The working temperature of any 3D printer has a critical effect on process feasibility as well as the final quality of the product. In this respect, thermal analysis can provide a comprehensive understanding of operation parameters and optimization potential. This most certainly also is the case for the new layer-wise additive manufacturing system, selective thermoplastic electrophotographic process (STEP). In the present paper, we propose a 3D part-scale finite element thermal model for multi-materials which is developed in the commercial software Abaqus/CAE 2021. The reduced-order method, flash heating (FH), is adopted in the model to obtain good accuracy with acceptable simulation time. A specific analysis of the trade-offs between accuracy and CPU-time is carried out by varying the amount of lumping in the meta-layers in the FH method. Furthermore, we conduct an in-house experiment in which we use IR cameras for measuring temperatures during manufacturing, and the results are applied for model validation and calibration. We specifically compare measured and numerically predicted average surface temperatures when steady state is obtained after printing of each layer. Here we obtain a mean error up to 6% depending on the thickness of the meta-layers. Moreover, parametric studies show that pulse duration and heater intensity significantly influence both the surface and bulk temperature profiles, and this provides us with an increased understanding of the thermal behavior of the recently developed STEP process which in turn could make way for further process optimization. [ABSTRACT FROM AUTHOR]