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An energy-based method to determine material constants in nonlinear rheology with applications
(2016)
Many polymer-type materials show a rate-dependent and nonlinear rheological behavior. Such a response may be modeled by using a series of spring-dashpot systems. However, in order to cover different time scales the number of systems may become unreasonably large. A more appropriate treatment based on continuum mechanics will be presented herein. This approach uses representation theorems for deriving material equations and allows for a systematic increase in modeling complexity. Moreover, we propose an approach based on energy to determine thematerial parameters.This method results in a simple linear regression problemeven for highly nonlinearmaterial equations. Therefore, the inverse problem leads to a unique solution. The significance of the proposed method is that the stored and dissipated energies necessary for the procedure are measurable quantities. We apply the proposed method to a 'semi-solid' material and measure its material parameters by using a simple-shear rheometer.
Leaking methane (CH4) from infrastructures, such as pipelines and landfills, is critical for the environment but can also pose a safety risk. To enable a fast detection and localization of these kind of leaks, we developed a novel robotic platform for aerial remote gas sensing. Spectroscopic measurement methods for remote sensing of selected gases lend themselves for use on mini-copters, which offer a number of advantages for inspection and surveillance over traditional methods. No direct contact with the target gas is needed and thus the influence of the aerial platform on the measured gas plume can be kept to a minimum. This allows to overcome one of the major issues with gas-sensitive mini-copters. On the other hand, remote gas sensors, most prominently Tunable Diode Laser Absorption Spectroscopy (TDLAS) sensors have been too bulky given the payload and energy restrictions of mini-copters. Here, we present the Unmanned Aerial Vehicle for Remote Gas Sensing (UAV-REGAS), which combines a novel lightweight TDLAS sensor with a 3-axis aerial stabilization gimbal for aiming on a versatile hexacopter. The proposed system can be deployed in scenarios that cannot be addressed by currently available robots and thus constitutes a significant step forward for the field of Mobile Robot Olfaction (MRO). It enables tomographic reconstruction of gas plumes and a localization of gas sources. We also present first results showing its performance under realistic conditions.
Structural Health Monitoring (SHM) is an important part of buildings surveillance and maintenance to detect material failure as early as possible and to contribute in protection of structures and their users.
The implementation of Radio Frequency Identification (RFID) sensor systems without cable connection and battery into building components offers innovative possibilities to enable long-term in-situ SHM of addressed structures, bridges. The objectives of the presented study are complete embedding of RFID sensors systems in concrete, full passive communication with the systems, at best for the whole life span of structures. One challenge for this task is the highly alkaline environment in concrete, which requires non-degrading and robust encapsulation. Further Requirements are passive communication and energy supply, appropriate antenna design, placement and fixation in concrete, and the selection and implementation of sensors and connections. The concept is to develop and optimize a simple and robust system, which meets the requirements, as well as comprehensive validation in concrete specimen and real world applications. Two different systems were developed (HF and UHF RFID, respectively).
First tasks were the implementation of analog sensors using the superposition principle for the signal adaption. Investigation of suitable materials for robust encapsulation and sensor protection against basic environments.
Four materials were investigated in pH 13 solution for 14 days
- 3D-Printer-Polymer was completely resolved
- PVC has no noticeable decrease in weight
- (VitaPro) glass filter for the sensor protector, has weight loss 2.7 %
- The epoxy resin has increased by 1.8 % due to moisture expansion
Different concrete samples were prepared for the validation of the systems.
RFID sensors were embedded in different integration depths. Investigate the energy- and data transfer through concrete, also with varying moisture content. Additionally, signal strength data was used to optimize and validate the antenna characteristics in concrete. Next steps are to guarantee a sufficient energy supply for UHF RFID systems embedded in different concrete mixtures and further embedding the HF and UHF RFID systems in real bridges and buildings to validate the long term monitoring.
The use of open GIS standards offers a broad variety of potential, particularly in the field of data exchange, data storage, and interoperability. GML and CityGML are excellent examples for the ontological description of real world objects by means of an open standard whereas SensorML serves to describe measurements, sensors and measuring platforms. The use of such standards offers not only the possibility of using a common standardised language, but also the use of open service standards. The combination of spatial data and sensor standards in services and service-oriented architectures goes far beyond previous existing solutions on the market and provides a novel platform for monitoring structures. That in fact is far more than a simple data storage model. The methods and models presented in this contribution allow a direct integration of sensor data and its provision through an open standard language. In this case, all the intermediate steps at any time through an open service interface are addressed and may be made available and provided to different actors and stakeholders participating in a construction scenario. The great potential and the added value of such an information system is the permanent availability of measurement and object data and an associated integrated analysis of sensor data in combination with a finite element model (FEM). The automatic derivation of a finite element model from the 3D structure model, the visualisation of FEM, the provision of raw (measurement) data and sensor information for each time of measurement transform the platform into a universal tool in the field of structural monitoring. This contribution introduces the individual components, the standards used and the interaction between the components to an overall system.
Within the presented research project, experimental and numerical investigations were performed to develop a thin-shelled, modular, mobile element system made of a micro-reinforced ultra-high-performance ductile concrete (DUCON®). Material parameters were experimentally determined to adapt the material model within the numerical analysis applying the Drucker-Prager relationship. Afterwards, for validation of the numerical models, quasi-static and high-velocity impact tests were performed on plate-like structures. Finally, a suitable geometry of transportable barrier elements will be designed, which provides a maximum of resistance against impact by a minimum of weight and a maximum of mobility.
Within the presented research project, experimental and numerical investigations were performed to develop a thin-shelled, modular, mobile element system made of a micro-reinforced ultra-high-performance ductile concrete (DUCON®). Material parameters were experimentally determined to adapt the material model within the numerical analysis applying the Drucker-Prager relationship. Afterwards, for validation of the numerical models, quasi-static and high-velocity impact tests were performed on plate-like structures. Finally, a suitable geometry of transportable barrier elements will be designed, which provides a maximum of resistance against impact by a minimum of weight and a maximum of mobility.
One major ambition in Structural Health Monitoring (SHM) is to develop the ability to detect, identify and localize damage as well as to predict the lifespan of civil structures (Worden et al. 2007). This would allow well-informed decision on whether to repair or to demolish these structures. The word monitoring in SHM brings up several frequently ignored questions: What type of sensors and accuracies are needed to monitor a given structure? Where are the optimal sensor placements? How many sensors are necessary? How to analyse spatially distributed hybrid measurements? Or, in short: What is the sensor configuration best suited for structural health monitoring? If these questions are not explicitly addressed, the usefulness of the measurement data for an evaluation is left to coincidence.
The best-known discretization methods for solving engineering problems formulated as partial differential equations are finite difference method (FDM), finite element method (FEM) and finite volume method (FVM). While the finite volume method is used in fluid mechanics, the finite element method is predominant in solid state mechanics. At first glance, FVM and FEM are two highly specialized methods. However, both methods can solve problems of both solid mechanics and fluid mechanics well. Since experimental mechanics deals not only with solid state physics but also with fluid mechanics problems, we want to understand FVM in the sense of FEM in this work. In the long term, we want to use the variational calculus to unify many important numerical methods in engineering science into a common framework. In this way, we expect that experiences can be better exchanged between different engineering sciences and thus innovations in the field of experimental mechanics can be advanced. But in this work, we limit ourselves to the understanding of the FVM with the help of the variational calculus already known in FEM. We use a simple 1D Poisson equation to clarify the point. First, we briefly summarize the FVM and FEM. Then we will deal with the actual topic of this paper, as we establish the FEM and the FVM on a common basis by variation formulation. It is shown here that the FVM can be understood in terms of the finite element method with the so-called Galerkin-Petrov approach.
Many engineering structures are made of composite materials or metal foam. To simulate the deformational behaviour of these structures often requires a high number of discretisation elements. This in turn yields a very large system of linear equations that are extremely time and memory consuming or practically impossible to solve. It is therefore desirable to find an approach to overcome this obstacle.
Many engineering structures are made of composite materials or metal foam. To simulate the deformational behaviour of these structures often requires a high number of discretisation elements. This in turn yields a very large system of linear
equations that are extremely time and memory consuming or practically impossible to solve. It is therefore desirable to find an approach to overcome this obstacle.