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Barrier formation and increasing the melt viscosity are addressed as the two main general fire retardancy mechanisms of polymer nanocomposites. They result in specific impacts on fire properties that consequentially cause varying flame retardancy efficiency in different fire tests. The barrier formation retards mainly flame spread (peak of heat release rate) in developing fires, but does not reduce fire load (total heat evolved), ignitability or flammability (limiting oxygen index, UL 94). Furthermore, this flame retardancy effect increases with increasing irradiation and vanishes with decreasing irradiation. The increased melt viscosity prevents dripping, which is beneficial or disadvantageous depending on the fire test used. In some test, it become the dominant influence, transforming self-extinguishing samples into flammable materials or causing wicking. Advantages and the limits are sketched comprehensively for exploiting the main general fire retardancy mechanisms of polymer nanocomposites. It is concluded that barrier formation and changing the melt viscosity in nanocomposites are not sufficient for most applications, but must be accompanied by additional mechanisms in special systems or in combination with other flame retardants.
A method was developed to assess the heat insulation performance of intumescent coatings. The method consists of temperature measurements using the bench-scaled experimental set-up of a cone calorimeter and finite difference simulation to calculate the effective thermal conductivity dependent on time/temperature. This simulation procedure was also adapted to the small scale test furnace, in which the standard time-temperature curve is applied to a larger sample and thus which provides results relevant for approval. Investigations on temperature and calculated effective thermal conduction were performed on intumescent coatings in both experimental set-ups using various coating thicknesses. The results correspond to each other as well as showing the limits of transferability between both fire tests. It is shown that bench-scaled cone calorimeter tests are a valuable tool for assessing and predicting the performance of intumescent coatings in larger tests relevant for approval. The correlation fails for processes at surface temperatures above 750°C, which are not reached in the cone calorimeter, but are attained in the small scale furnace set-up.
Implementation and validation of robot-enabled embedded sensors for structural health monitoring
(2024)
In the past decades, structural health monitoring (SHM) has matured into a viable supplement to regular inspections, facilitating the execution of repair and maintenance work in the early stages of structural damage. With the advent of wireless technologies and advancements in information and communication technologies, civil infrastructure has been increasingly instrumented with wireless sensor nodes to record, analyze, and communicate data relevant to SHM. A promising method for SHM is to embed sensors directly into concrete for recording SHM data from inside structural elements. In this paper, a sensor system for embedment into concrete is proposed, able to assess SHM data recorded from concrete. Power is supplied to the sensors on-demand by quadruped robots, which also collect the SHM data via radio-frequency identification (RFID), providing an automated and efficient SHM process. In laboratory experiments, the capability of the sensor system of automatically collecting the SHM data using quadruped robots is validated. In summary, the integration of RFID technology and robot-based inspection presented in this study demonstrates a vital approach to evolve current SHM practices towards more digitalized and automated SHM.
Remote gas sensors mounted on mobile robots enable the mapping of gas distributions in large or hardly accessible areas. A challenging task, however, is the generation of threedimensional distribution maps from these gas measurements.
Suitable reconstruction algorithms can be adapted, for instance, from the field of computed tomography (CT), but both their performance and strategies for selecting optimal measuring poses must be evaluated. For this purpose simulations are used, since, in contrast to field tests, they allow repeatable conditions. Although several simulation tools exist, they lack realistic models of remote gas sensors. Recently, we introduced a model for a Tunable Diode Laser Absorption Spectroscopy (TDLAS) gas sensor taking into account the conical shape of its laser beam. However, the novel model has not yet been validated with experiments. In this paper, we compare our model with a real sensor device and show that the assumptions made hold.
Remote gas sensors mounted on mobile robots enable the mapping of gas distributions in large or hardly accessible areas. A challenging task, however, is the generation of threedimensional distribution maps from these gas measurements.
Suitable reconstruction algorithms can be adapted, for instance, from the field of computed tomography (CT), but both their performance and strategies for selecting optimal measuring poses must be evaluated. For this purpose simulations are used, since, in contrast to field tests, they allow repeatable conditions. Although several simulation tools exist, they lack realistic models of remote gas sensors. Recently, we introduced a model for a Tunable Diode Laser Absorption Spectroscopy (TDLAS) gas sensor taking into account the conical shape of its laser beam. However, the novel model has not yet been validated with experiments. In this paper, we compare our model with a real sensor device and show that the assumptions made hold.