Silicone polymers have enormous applications, especially in the areas of biomedical engineering. Ecoflex, a commercially available room temperature cured silicone polymer, has attracted considerable attention due to its wide range of applications as medical-grade silicones and as matrix materials in producing nano-filled stretchable sensors and dielectric elastomers for soft robotics. In this contribution, we have conducted a wide range of experiments under thermo-mechanical loadings. These experiments consist of loading-unloading cyclic tests, single-step relaxation tests, Mullins effects tests at different strain rates and stretches, stress recovery tests at different rest time etc. In order to assess the temperature influences on Ecoflex, a number of viscoelastic tests are performed in a thermal chamber with temperature ranging from-40 • C to 140 • C. Extensive experimental findings illustrate that Ecoflex experiences a significant stress softening in the first cycles and such a softening recovers gradually with respect to time. It also shows a significant amount of cyclic dissipation at various stretch levels as well as a considerable stress relaxation only for virgin samples. Cyclic dissipations and stress relaxation almost disappear for the case of pre-stretched samples. Furthermore, the material is more or less sensitive under a wide range of temperature differences.

This article addresses the prediction-based distributed filtering problem for a class of time-varying nonlinear stochastic systems with communication delays and missing measurements through the sensor networks. The phenomenon of the missing measurements is depicted by a set of Bernoulli distributed random variables, where each sensor node possesses its own missing probability. The communication delays are taken into account, which commonly occur during the estimation exchanges among the sensor nodes with communication links. A new prediction-based suboptimal distributed filter is designed by taking the missing probabilities and the prediction estimation into account, which has the advantages on the active compensation of the impacts caused by the missing measurements and communication delays. That is, a new compensation filtering method within the time-varying framework is presented based on the predictive estimation and the innovation measurements. A locally minimum upper bound matrix for the estimation error covariance is obtained by properly designing the distributed filter gain Manuscript

Digital Light Synthesis (DLS) technology creates ample opportunities for making 3D printed soft polymers for a wide range of grades and properties. In DLS, a 3D printer uses a continuous building technique in which the curing process is activated by an ultraviolet (UV) light. In this contribution, EUP40, a recently invented commercially available elastomeric polyurethane (EPU) printed by the DLS technology, is experimentally characterised. For characterizing the mechanical properties, an extensive viscoelastic experimental study on the digitally printed EPU taking the strain rate-dependence are conducted. The study reveals a significant time-dependency on its mechanical responses. Moreover, the material demonstrates noticeable nonlinear viscosities that depend on strain and strain rates. Based on the experimental findings for the printed elastomer, a large strain viscoelastic model is devised where evolution laws are enhanced by strain and strain rate-dependent nonlinear viscosities. Following identifications of relevant material parameters, we validate the model with the experimental data that show its good predictability. Such an extensive experimental study along with a constitutive model will help in designing and simulating more complex cellular and structured metamaterials using 3D printed elastomeric polyurethanes.

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Reducing the impact on the environment and the associated commercial implications are two major challenges that the global commercial aviation industry is addressing with significant commitment today. In this respect, Clean Sky, which is a €1.6 billion Joint Technology Initiative part funded by the European Commission is the largest ever programme addressing the greening of air transportation in response to the Advisory Council for Aeronautics Research in Europe (ACARE) goals of reducing CO2 and perceived noise emissions by 50% and NOx by 80% by 2020 compared to 2000 condition. This paper presents research work carried out within the Systems for Green Operations Integrated Technology Demonstrator (ITD) of Clean Sky that is associated with GATAC, a trajectory and route planning tool to enable the multi-objective optimization of flight trajectories and missions. The design and operational methodology of the tool, the optimization algorithms and models are discussed and the results of a preliminary application for a long-range commercial flight are presented.