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<doi>0705-cd</doi>
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<article-title>Computational Complexity of Experiment Design in Civil Engineering</article-title>
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<author>Olga Kosheleva<sup>1</sup>, Yan Wang<sup>2</sup> and Vladik Kreinovich<sup>3</sup></author>

<aff><sup>1</sup>Department of Teacher Education, University of Texas at El Paso, USA</aff>

<email><a href="mailto:olgak@utep.edu">olgak@utep.edu</a></email>

<aff><sup>2</sup>School of Mechanical Engineering, Georgia Institute of Technology, USA</aff>

<email><a href="mailto:yan.wang@me.gatech.edu">yan.wang@me.gatech.edu</a></email>

<aff><sup>3</sup>Department of Computer Science, University of Texas at El Paso, USA</aff>

<email><a href="mailto:vladik@utep.edu">vladik@utep.edu</a></email>

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<title>ABSTRACT</title>
<p>To guarantee reliability and safety of engineering structures, we need to regularly measure their mechanical properties. Such measurements are often expensive and time-consuming. It is therefore necessary to carefully plan the corresponding measurement experiments, to minimize the corresponding expenses.<br/>
It is known that, in general, experiment design is NP-hard. However, the previous proofs dealt either with nonlinear systems, or with situations with low measurement accuracy. In civil engineering, however, most systems are welldescribed by linear systems, and measurements are reasonably accurate. In this paper, we show that experiment design is NP-hard even for civil engineering problems. We show that even checking whether the results of the previous measurements are sufficient to determine the value of the desired mechanical quantity &#8211; or additional measurement are needed &#8211; even this problem is, in general, NP-hard. So, crudely speaking, no feasible algorithm can always answer this question &#8211; and thus, overspending on measurements is inevitable.</p>
<p><italic>Keywords: </italic>Civil engineering, NP-hard, Experiment design, Linear elasticity.</p>
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