It is fascinating to read about great events in the history of science. For example, the account of how the famous astronomer Johannes Kepler, in the early 17th century, synthesized many years of observational data into his famous three laws of planetary motion is a source of inspiration to anyone who has mountains of data with which to deal [1]. Kepler carried out painstaking numerical analysis, coupled with a theoretical idea – planetary orbits were not necessarily perfect circles. Holding fast to that theoretical idea, Kepler’s numerical analysis had a goal that was achieved – the formulation of the three laws of planetary motion.
About sixty years later, Sir Isaac Newton, using his newly-invented calculus and some ideas about gravitation, derived these laws mathematically [2]. This derivation had the eventual impact that new astronomical observations were inspired and quantified by Newton’s theory, and Kepler’s laws were more widely accepted because of this new theoretical basis in valid mathematics and physics. It can be argued that if Newton had not made this derivation, the usefulness of Kepler’s laws would have been limited. It can also be argued that if Kepler had not synthesized his data in terms of mathematical laws, but left it in neat but less useful tables, Newton would have had nothing with which to motivate or validate his mathematical derivations. This historical incident illustrates the truth that good experiments inspire theory, and in turn theory explains these experiments and suggests new experiments. The cycle continues and progress is made.
What is the corresponding situation for concrete, or, more generally, cement-based materials? The relevant science for cement-based materials is materials science, which is a combination of condensed matter physics, chemistry, and mechanics. Materials science theory for concrete, a random, complex, multiphase composite material, involves solving equations numerically and making what we call models, or what should really be called computational materials science. Experimental materials science involves characterizing raw and processed materials, imaging microstructure at various length scales, and measuring physical and chemical properties. There are also many, many experiments or rather tests carried out on concrete and its raw materials that basically measure empirical parameters, many of which are not directly connected to physical and chemical parameters. Many of these test results are of utility in the actual use of concrete, but many are not at all useful but are simply repetitious results that lead nowhere; e.g., many durability tests, unfortunately.
In this paper, I argue that concrete science will advance more rapidly and address the difficult problems faced in this difficult material, if we have computational and experimental materials science working together. This goes far beyond just a simple call for more validation of models. The rise of quantitative models drives experiments to be more fundamental, measuring materials science-based quantities. Measurements of materials science-based quantities inspire model building and validation. This synergistic interplay of theory and experiment is necessary for the materials science of concrete to progress, since models of many empirical tests are useless or even impossible to develop, and empirical tests by themselves result in slow or even non-existent progress. By “progress,” I don’t just mean scientific progress that is of interest only to a few specialists, but I mean progress in using concrete in better, more long-lasting, and more profitable ways: profitable economically and environmentally and socially. The late Dr. Geoffrey J.C. Frohnsdorff was an advocate of this position, and a short review of his career will not only pay tribute to this recently-deceased visionary scientist and research leader, but will help to elaborate the thesis of this paper.
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