Multifunctional cement composites strain and damage sensors applied on reinforced concrete (RC) structural elements

In this research, strain-sensing and damage-sensing functional properties of cement composites have been studied on a conventional reinforced concrete (RC) beam. Carbon nanofiber (CNFCC) and fiber (CFCC) cement composites were used as sensors on a 4 m long RC beam. Different casting conditions (in situ or attached), service location (under tension or compression) and electrical contacts (embedded or superficial) were compared. Both CNFCC and CFCC were suitable as strain sensors in reversible (elastic) sensing condition testing. CNFCC showed higher sensitivities (gage factor up to 191.8), while CFCC only reached gage factors values of 178.9 (tension) or 49.5 (compression). Furthermore, damage-sensing tests were run, increasing the applied load progressively up to the RC beam failure. In these conditions, CNFCC sensors were also strain sensitive, but no damage sensing mechanism was detected for the strain levels achieved during the tests. Hence, these cement composites could act as strain sensors, even for severe damaged structures near to their collapse.

Strain and damage sensing properties on multifunctional cement composites with CNF admixture

Both strain and damage sensing properties on carbon nanofiber cement composites (CNFCC) are reported in the present paper. Strain sensing tests were first made on the material’s elastic range. The applied loading levels have been previously calculated from mechanical strength tests. The effect of several variables on the strain-sensing function was studied, e.g. cement pastes curing age, current density, loading rate or maximum stress applied. All these parameters were discussed using the gage factor as reference. After this first set of elastic experiments, the same specimens were gradually loaded until material’s failure. At the same time both strain and resistivity were measured. The former was controlled using strain gages, and the latter using a multimeter on a four probe setup. The aim of these tests was to prove the sensitivity of these CNF composites to sense their own damage, i.e. check the possibility of fabricating structural damage sensors with CNFCC’s. All samples with different CNF dosages showed good strain-sensing capacities for curing periods of 28 days. Furthermore, a 2%CNF reinforced cement paste has been sensitive to its own structural damage.

Control framework for dexterous manipulation using dynamic visual servoing and tactile sensors’ feedback

Tactile sensors play an important role in robotics manipulation to perform dexterous and complex tasks. This paper presents a novel control framework to perform dexterous manipulation with multi-fingered robotic hands using feedback data from tactile and visual sensors. This control framework permits the definition of new visual controllers which allow the path tracking of the object motion taking into account both the dynamics model of the robot hand and the grasping force of the fingertips under a hybrid control scheme. In addition, the proposed general method employs optimal control to obtain the desired behaviour in the joint space of the fingers based on an indicated cost function which determines how the control effort is distributed over the joints of the robotic hand. Finally, authors show experimental verifications on a real robotic manipulation system for some of the controllers derived from the control framework.

Contribution to Real-Time Estimation of Crop Phenological States in a Dynamical Framework Based on NDVI Time Series: Data Fusion With SAR and Temperature

In this study, a methodology based in a dynamical framework is proposed to incorporate additional sources of information to normalized difference vegetation index (NDVI) time series of agricultural observations for a phenological state estimation application. The proposed implementation is based on the particle filter (PF) scheme that is able to integrate multiple sources of data. Moreover, the dynamics-led design is able to conduct real-time (online) estimations, i.e., without requiring to wait until the end of the campaign. The evaluation of the algorithm is performed by estimating the phenological states over a set of rice fields in Seville (SW, Spain). A Landsat-5/7 NDVI series of images is complemented with two distinct sources of information: SAR images from the TerraSAR-X satellite and air temperature information from a ground-based station. An improvement in the overall estimation accuracy is obtained, especially when the time series of NDVI data is incomplete. Evaluations on the sensitivity to different development intervals and on the mitigation of discontinuities of the time series are also addressed in this work, demonstrating the benefits of this data fusion approach based on the dynamic systems.

Controlled rippling of graphene via irradiation and applied strain modify its mechanical properties: a nanoindentation simulation study

Ripples, present in free standing graphene, have an important influence in the mechanical behavior of this two-dimensional material. In this work we show through nanoindentation simulations, how out-of-plane displacements can be modified by strain resulting in softening of the membrane under compression and stiffening under tension. Irradiation also induces changes in the mechanical properties of graphene. Interestingly, compressed samples, irradiated at low doses are stiffened by the irradiation while samples under tensile strain do not show significant changes in their mechanical properties. These simulations indicate that vacancies, produced by the energetic ions, cannot be the ones directly responsible for this behavior. However, changes in roughness induced by the momentum transferred from the energetic ions to the membrane, can explain these differences. These results provide an alternative explanation to recent experimental observations of stiffening of graphene under low dose irradiation, as well as paths to tailor the mechanical properties of this material via applied strain and irradiation.