Profile

Thomas Crook

PhD Student
Loughborough University
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Thomas (Tom) Crook is a proactive researcher who thrives on asking questions and challenging the status quo. He is a doctoral researcher in the ERBE CDT at Loughborough University with the Building Energy Research Group (BERG) and the 3D Concrete Printing (3DCP) Group. Tom's academic path, including BEng (Hons) Civil Engineering, MSc Low-Energy Building Services Engineering, and currently a PhD in Building Physics, reflects his broader interest in strategies for a higher-quality, affordable, decarbonised housing stock in the UK. Tom’s work focuses on how heat and moisture move through and are stored within novel wall systems. His current work characterises hygrothermal material properties (moisture storage, liquid transport, vapour permeability, thermal parameters) and validates predictive moisture-risk models for 3D printed concrete. This work aims to enable designers to specify healthier, more durable, and more energy efficient homes, thereby reducing risk and supporting the adoption of 3D printing in the construction industry.
Characterising and Validating the Hygrothermal Performance of 3D-Printed Concrete Walls

This project establishes and validates a reliable hygrothermal (HAM) modelling framework for 3D-printed concrete (3DPC) by: (i) characterising orientation-specific material properties (moisture storage, liquid conductivity/diffusivity, vapour permeability, thermal parameters); (ii) linking pore structure to transport using XCT/MIP/BET/SEM; and (iii) benchmarking isotropic, layered and tensor formulations under realistic boundary conditions. Predictive moisture-risk models (WUFI/Delphin) are validated against instrumented printed wall panels exposed to controlled indoor–outdoor climates (e.g., wind-driven rain, rising damp, drying). These transient simulations, driven by intrinsic material functions and specified boundary conditions, predict moisture contents and the approach to saturation years into the future. Outputs include a complete 3DPC dataset (X/Y/Z), orientation-specific input functions for industry tools, castable surrogate mixes for core/skin/interlayer zones, and model-accuracy benchmarks (RMSE/MBE and normalised metrics). The framework intends to provide the foundations for reliable prediction of hygrothermal behaviour in novel anisotropic concrete wall systems.

Supervisors: Prof David Allinson – Dr Matthew Li – Prof Richard Buswell