How Do the Validations of Simulations and Experiments Compare?
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Whereas experiments and computer simulations seem very different at first view because the former, but not the latter, involve interactions with material properties, we argue that this difference is not so important with respect to validation, as far as epistemology is concerned. Major differences remain nevertheless from the methodological point of view. We present and defend this distinction between epistemology (the domain of scientific operations that are justified by rational principles aiming at improving current knowledge) and methodology (the domain of scientific operations that are governed by rules, not all of which are grounded on rational, explicit principles). We illustrate this distinction and related claims by comparing how experiments and simulations are validated in evolutionary studies, a domain in which both experiments in the lab and computer simulations are relatively new but mutually reinforcing.
KeywordsTheory-ladeness Holism of confirmation Opacity Duhem–Quine problem Verification and Validation Calibration Benchmarking Parameter tuning Sensitivity analysis Measurement errors Numerical errors Evolutionary studies Richard Lenski’s Long-Term Experimental Evolution
- Franklin, A. (1997). Calibration. Perspectives on Science, 5, 31–80.Google Scholar
- Hourdin, F., Mauritsen, T., Gettelman, A., Golaz, J., Balaji, V., Duan, Q., et al. (2017). The art and science of climate model tuning. Bulletin of the American Meteorological Society.Google Scholar
- Humphreys, P. (2004). Extending ourselves. Computational science, empiricism, and scientific method. OUP.Google Scholar
- Lenhard, J. (2018). Holism, or the erosion of modularity–a methodological challenge for validation, to appear in Philosophy of Science (PSA 2016).Google Scholar
- Lenski, R. (2004). The future of evolutionary biology. Ludus Vitalis, 12(21), 67–89.Google Scholar
- Morrison, M. (2015). Reconstructing reality: Models, mathematics, and simulations. USA: OUP.Google Scholar
- Oberkampf, W. L., Trucano, T. G. (2002). Verification and validation in computational fluid dynamics. Rapport Sandia. SAND2002-0529.Google Scholar
- Roy, C. (2010). Review of discretization error estimators in scientific computing. In 48th AIAA Aerospace Sciences Meeting, Orlando, FL, January 4–7, 2010.Google Scholar
- Trucano, T. G., Swiler, L. P., Igusa, T., Oberkampf, W. L., & Pilch, M. (2006) Calibration, validation, and sensitivity analysis: What’s what. Reliability Engineering & System Safety, 91(10–11), 1331–1357.Google Scholar
- Winsberg, E. (2010). Science in the age of computer simulation. The University of Chicago Press.Google Scholar