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Regulatory decisions require reliable data and knowledge derived from this. Among stakeholders in nanotechnology, however, there is often uncertainty about the quality of data for regulatory purposes. In addition, the general public often finds itself excluded from nanoregulation and policy decisions. This creates uncertainty in the nanotechnology field and also in other branches of technology and leads to concerns among the society.
To address these issues, NANORIGO elaborates a framework to support decision making as well as data, information and knowledge sharing and use. We refer to “reliability” of data and knowledge as a degree of readiness or maturity. According to these criteria we worked out a 9-level scale in analogy to TRL (technology readiness level), the KaRL system (Knowledge, Data and Information Readiness Level). KaRL allows assessment of knowledge readiness for decision making by applying defined quality criteria for each level. It also provides guidance on how to enhance the readiness level by the help of available tools and procedures. KaRL addresses SEIN[1] principles, circular economy and thus involves the public concerns in regulation. A specialized nanorisk governance council (being under development in NANORIGO) is suggested to perform quality check of an actionable document, thus, aiding in consensus on the reliability (maturity) of knowledge for decision making. Moreover, KaRL facilitates traceability of knowledge before its use in decision making. This enables the transparency demanded by all stakeholders.
Monitoring of reinforced concrete structures to ensure their stability and increase their service-life is a crucial element of a modern infrastructural concept. With classical methods of non-destructive testing and inspection, repeated measurements under comparable conditions are difficult to conduct. Therefore, DFG research unit FOR 2825 CoDA researches the assessment of concrete damage using ultrasound coda wave interferometry and embedded sensors. Embedding the sensors into the monitoring target reduces human and non-human factors influencing repeatability. Using Coda Wave Interferometry (CWI), small velocity changes in the material can be detected by comparison of repeated measurements. The technique is sensitive to damaging changes like cracking as well as to reversible influences like material temperature. The understanding of these different influences on the signal is crucial for the analysis of long-term monitoring data to make an educated assessment of the structure and its integrity. With several laboratory experiments in a climate chamber and a long-term experiment recording an annual cycle in a large model on an outdoor test site in Horstwalde close to Berlin, we try to understand the influence of temperature on the CWI results. The results show that the velocity change calculated by CWI does closely follow the trend of concrete temperature. After one year of data recording with the large model being exposed to environmental variations only, the calculated velocity change resembles the annual temperature curve. The data shows a linear dependency between velocity and temperature change in a range of -0.03 percent per °K to -0.06 percent per °K - regardless of specimen size. An approach to remove temperature influence from the yearly cycle recorded in the large-scale experiment using this linear relation is unable to remove high-frequency variations - especially daily influences. Low-pass filtering the data can eliminate these variations while preserving permanent shifts caused by damages. Although we have shown that the influence of temperature on long term monitoring can be removed to a significant extent, there is still an influence of environmental changes remaining in the data. Possible nonlinear effects and influences not related to temperature need to be investigated in the future.