This paper is concerned with nonlinear modeling and efficient numerical simulation of electrostrictive materials and structures. Two types of such materials are considered: relaxor ferroelectric ceramics and electrostrictive polymers. For ceramics, a geometrically linear formulation is developed, whereas polymers are studied in a geometrically nonlinear regime. In the paper, we focus on constitutive modeling first. For the reversible constitutive response under consideration, we introduce the augmented Helmholtz free energy, which is composed of a purely elastic part, a dielectric part and an augmentation term. For the elastic part, we involve an additive decomposition of the strain tensor into an elastic strain and an electrostrictive eigenstrain, which depends on the polarization of the material. In the geometrically nonlinear case, a corresponding multiplicative decomposition of the deformation gradient tensor replaces the additive strain decomposition used in the geometrically linear formulation. For the dielectric part, we first introduce the internal energy, to which a Legendre transformation is applied to compute the free energy. The augmentation term accounts for the contribution from vacuum to the energy. In our formulation, the augmented free energy depends not only on the strain and the electric field, but also on the polarization and an internal polarization; the latter two are internal variables. With the constitutive framework established, a Finite Element implementation is briefly discussed. We use high-order elements for the discretization of the independent variables, which include also the internal variables and, in case the material is assumed incompressible, the hydrostatic pressure, which is introduced as a Lagrange multiplier. The elements are implemented in the open source code Netgen/NGSolve. Finally, example problems are solved for both, relaxor ferroelectric ceramics and electrostrictive polymers. We focus on thin plate-type structures to show the efficiency of the numerical scheme and its applicability to thin electrostrictive structures.

We investigate the influence of nonlinear viscoelastic damping on the response of a cantilever sensor covered by piezoelectric layers in a symmetric or asymmetric configuration. We formulate an initial-boundary-value problem which consistently incorporates both geometric and material nonlinearities including the effect of viscoelastic damping which cannot be ignored for micro- and nano-mechanical sensor operation in a vacuum environment. We employ an asymptotic multiple-scales methodology to yield the system nonlinear frequency response near its primary resonance and employ a model-based estimation procedure to deduce the system damping backone curve from controlled experiments in vacuum. We discuss the effect of nonlinear damping on sensor applications for scanning probe microscopy.

A two-layer beam consisting of an elastoplastic layer and a functional layer made of shape memory alloy (SMA) TiNi is considered. Constitutive relations for SMA are set by a microstructural model capable to calculate strain increment produced by arbitrary increments of stress and temperature. This model exploits the approximation of small strains. The equations to calculate the variations of the strain and the internal variables are based on the experimentally registered temperature kinetics of the martensitic transformations with an account of the crystallographic features of the transformation and the laws of equilibrium thermodynamics. Stress and phase distributions over the beam height are calculated by steps, by solving on each step the boundary-value problem for given increments of the bending moment (or curvature) and the tensile force (or relative elongation). Simplifying Bernoulli's hypotheses are applied. The temperature is considered homogeneous. The first stage of the numerical experiment is modeling of preliminary deformation of the beam by bending or stretching at a temperature corresponding to the martensitic state of the SMA layer. The second stage simulates heating and subsequent cooling across the temperature interval of the martensitic transformation. The curvature variation depends both on the total thickness of the beam and on the ratio of the layer's thicknesses.

When no extensometer is available in a generic tensile-compression test carried out by a universal testing machine (for instance the model BIONIX from Material Testing Systems (MTS)), the test results only provide the relative displacement between the machine grips. The test does not provide any information on the local behaviour of the material. This contribution presents the potential of an application of Digital Image Correlation (DIC) toward the reconstruction of the behaviour along the specimen. In particular, the authors test a Ni-Ti shape memory alloys (SMA) specimen with emphasis on the coupling of the two measurement techniques.

In this paper we present an overview of damage diagnosis algorithms that have been developed over the past two decades using vibration signals obtained from structures. Then, the paper focuses primarily on algorithms that can be used following an extreme event such as a large earthquake to identify structural damage for responding in a timely manner. The algorithms presented in the paper use measurements obtained from accelerometers and gyroscope to identify the occurrence of damage and classify the damage. Example algorithms are presented include those based on autoregressive moving average (ARMA), wavelet energies from wavelet transform and rotation models. The algorithms are illustrated through application of data from test structures such as the ASCE Benchmark structure and laboratory tests of scaled bridge columns and steel frames. The paper concludes by identifying needs for research and development in order for such algorithms to become viable in practice.

In recent years, vision-based monitoring has received great attention. However, structural identification using vision-based displacement measurements is far less established. Especially, simultaneous identification of structural systems and unknown excitation using vision-based displacement measurements is still a challenging task since the unknown excitations do not appear directly in the observation equations. Moreover, measurement accuracy deteriorates over a wider field of view by vision-based monitoring, so, only a portion of the structure is measured instead of targeting a whole structure when using monocular vision. In this paper, the identification of structural system and excitations using vision-based displacement measurements is investigated. It is based on substructure identification approach to treat of problem of limited field of view of vision-based monitoring. For the identification of a target substructure, substructure interaction forces are treated as unknown inputs. A smoothing extended Kalman filter with unknown inputs without direct feedthrough is proposed for the simultaneous identification of substructure and unknown inputs using vision-based displacement measurements. The smoothing makes the identification robust to measurement noises. The proposed algorithm is first validated by the identification of a three-span continuous beam bridge under an impact load. Then, it is investigated by the more difficult identification of a frame and unknown wind excitation. Both examples validate the good performances of the proposed method.

The machine-vision based structural displacement measurement methods are widely used due to its flexible deployment and non-contact measurement characteristics. The accuracy of vision measurement is directly related to the image resolution. In the field of computer vision, super-resolution reconstruction is an emerging method to improve image resolution. Particularly, the deep-learning based image super-resolution methods have shown great potential for improving image resolution and thus the machine-vision based measurement. In this article, we firstly review the latest progress of several deep learning based super-resolution models, together with the public benchmark datasets and the performance evaluation index. Secondly, we construct a binocular visual measurement platform to measure the distances of the adjacent corners on a chessboard that is universally used as a target when measuring the structure displacement via machine-vision based approaches. And then, several typical deep learning based super resolution algorithms are employed to improve the visual measurement performance. Experimental results show that super-resolution reconstruction technology can improve the accuracy of distance measurement of adjacent corners. According to the experimental results, one can find that the measurement accuracy improvement of the super resolution algorithms is not consistent with the existing quantitative performance evaluation index. Lastly, the current challenges and future trends of super resolution algorithms for visual measurement applications are pointed out.

The degradation of wheel tread may result in serious hazards in the railway operation system. Therefore, timely wheel defect diagnosis of in-service trains to avoid tragic events is of particular importance. The focus of this study is to develop a novel wheel defect detection approach based on the relevance vector machine (RVM) which enables online detection of potentially defective wheels with trackside monitoring data acquired under different running-speed conditions. With the dynamic strain responses collected by a trackside monitoring system, the cumulative Fourier amplitudes (CFA) characterizing the effect of individual wheels are extracted to formulate multiple probabilistic regression models (MPRMs) in terms of multi-kernel RVM, which accommodate both variables of vibration frequency and running speed. Compared with the general single-kernel RVM-based model, the proposed multi-kernel MPRM approach bears better local and global representation ability and generalization performance, which are prerequisite for reliable wheel defect detection by means of data acquired under different running-speed conditions. After formulating the MPRMs, we adopt a Bayesian null hypothesis indicator for wheel defect identification and quantification, and the proposed method is demonstrated by utilizing real-world monitoring data acquired by an FBG-based trackside monitoring system deployed on a high-speed trial railway. The results testify the validity of the proposed method for wheel defect detection under different running-speed conditions.

Among the approaches to the production of "green" energy, geothermal power systems are becoming quite popular in Europe. Their installation in existing buildings requires an extended, external pipes appendix and its laying operation needs a drilling activities nearby structural skeletons often designed to support static loads only, especially when ancient buildings are targeted. This contribution reports and discusses the experimental results achieved within a specific case study within the European project GEOFIT. In particular, standard accelerometric measurements in and nearby a single-story reinforced concrete building are collected and analysed in the absence of drilling (pre-drilling) and during drilling activities (drilling phase) to monitor the structure response to the external source of vibrations related to the excavations phase. The target is to outline automatic guidelines toward installations preventing from any sort of structural damage.

In building envelope, transparent components play an important role. The structural glazing systems are the weak element of the casing in terms of mechanical resistance, thermal and acoustic insulation. In the present work, new structural glass panels with granular aerogel in interspace were investigated from different points of view. In particular, the mechanical characterization was carried out in order to assess the resistance to bending of the single glazing pane. To this end, a special instrument system was built to define an alternative configuration of the coaxial double ring test, able to predict the fracture strength of glass large samples (400 × 400 mm) without overpressure. The thermal and lighting performance of an innovative double-glazing façade with granular aerogel was evaluated. An experimental campaign at pilot scale was developed: it is composed of two boxes of about 1.60 × 2 m² and 2 m high together with an external weather station. The rooms, identical in terms of size, construction materials, and orientation, are equipped with a two-wing window in the south wall surface: the first one has a standard glazing solution (double glazing with air in interspace), the second room is equipped with the innovative double-glazing system with aerogel. The indoor mean air temperature and the surface temperature of the glass panes were monitored together with the illuminance data for the lighting characterization. Finally, a brief energy characterization of the performance of the material was carried out by means of dynamic simulation models when the proposed solution is applied to real case studies.

Planning activity is complex process assuming the term "complexity" as a group of elements interconnected each other. The common knowledge about city planning underlines its main aim as: figuring the present, imaging the future, governing every day the territory and the way people use and live it at different scales. When considering the strength of technological opportunities and the spreading of ICT and IoT devices within everyday life, that mean within the life of cities, the complex nature of the urban system increases with the intensification of information and their connections. Recent orientations about urban and regional planning try to carry the discipline to a more flexible approach in respect to the hyperdeterminant role of direct technical applications. This passage is a fundamental aspect considering the faster and faster modifications of social and economic assets at the global and local scale. At the same time, the "environment question" became more and more relevant at the worldwide scale within the 2015 UN 2030 Agenda for Sustainable Development. Another relevant aspect about the recent urban planning orientations regards the role of the different subjects that are part of the planning process. Approaching the government of smart cities means to define how every subject, with different roles (public or private), could enrich the knowledge of the functioning of the "urban machine" and the awareness of participation of people and city users in the quality of urban life. In the paper author starts defining recent approaches in urban planning, then the nature of the city as a complex system is analyzed from the point of view of planners and of the different subjects that act in the city. Then the smart city is introduced as a further level of complexity and finally author propose the basic element of a Planning Support System.