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BAM is the German Federal Institute for Materials Research and Testing and the competent authority for mechanical and thermal safety assessment of transport packages for spent fuel and high level waste. In context with safety assessment of RAM packages BAM performed numerous drop tests in the last decades. The tests were mostly accompanied by extensive and various measurement techniques especially by instrumented measurements with strain gages and accelerometers.
The procedure of drop testing and the resulting measurement analysis are the main methods to evaluate the safety against mechanical test conditions. Measurement techniques are dedicated to answer questions in regard to the structural integrity of a RAM package, the mechanical behavior of the prototype as well as of its content under impact conditions.
Test results like deceleration-time functions constitute a main basis for the validation of assumptions in the safety analysis and for the evaluation of numerical calculations. In this context the adequate selection of accelerometers and measurement systems for the performance of drop tests is important. Therefore it is not only necessary to find suitable positions for the accelerometers at the test specimens, but also to consider technical boundary conditions as e.g. temperature.
This paper describes a wireless mobile prototype able to perform optical measurements by means of a miniatur-ized spectrometer for low light analysis, e.g. fluorescent sensors. Evaluations, calculations, calibration management and result display are performed by a computer or a standard tablet. The device was designed primarily to detect traces of oil in drinking or ground water and for the analyses of crude oils. However, it can also address a wide range of fluorescent sensors. The fast and user-friendly inspection of water quality or oil properties, as well as the adaptability and mobility, make the device attractive for a variety of users. Further application areas could be easily imple-mented by adapting the optics and the software (database, data processing and calibration plots, etc.)
Structural Health Monitoring (SHM) has become very important in today's rapidly developing time. High buildings, large bridges and complex technical structures need to be monitored continuously and this over long periods.
Visual monitoring cannot evaluate the internal condition of building structures. Thus, material embedded sensors are needed. Cable connection of these sensors pose the disadvantage of weak spots and water intrusion. For concrete embedded sensors the use of batteries is not convenient, because of limited lifetime, difficult charging, and generation of electrical waste.. Hence, monitoring should be implemented preferentially with firmly embedded passive RFID sensor modules. However, since the concrete structure forms an electromagnetically reflective and absorbing barrier, only limited energy can be transmitted to the module. This project requires a highly energy-saving system, which can record different sensor parameters at critical points.
In industrial environments, airborne by-products such as dust and (toxic) gases, constitute a major risk for the worker’s health. Major changes in automated processes in the industry lead to an increasing demand for solutions in air quality management. Thus, occupational health experts are highly interested in precise dust and gas distribution models for working environments. For practical and economic reasons, high-quality, costly measurements are often available for short time-intervals only. Therefore, current monitoring procedures are carried out sparsely, both in time and space, i.e., measurement data are collected in single day campaigns at selected locations only. Real-time knowledge of contaminant distributions inside the working environment would also provide means for better and more economic control of air impurities. For example, the possibility to regulate the workspace’s ventilation exhaust locations can reduce the concentration of airborne contaminants by 50%.
To improve the occupational health and safety of (industrial) workplaces, this work aims for developing a swarm of gas-sensitive aerial nano robots for monitoring indoor air quality and for localizing potential emission sources.