An optimal sensor placement method for SHM based on Bayesian experimental design and polynomial chaos expansion

We present an optimal sensor placement methodology for structural health monitoring (SHM) purposes, relying on a Bayesian experimental design approach. The unknown structural properties, e.g. the residual strength and stiffness, are inferred from data collected through a network of sensors, whose architecture, i.e., type and position may largely affect the accuracy of the monitoring system. In tackling this issue, an optimal network configuration is herein sought by maximizing the expected information gain between prior and posterior probability distributions of the parameters to be estimated. Since the objective function linked to the network topology cannot be analytically computed, a numerical approximation is provided by means of a Monte Carlo analysis, wherein each realization is obtained via finite element modeling. Since the computational burden linked to this procedure often grows infeasible, a Polynomial Chaos Expansion (PCE) approach is adopted for accelerating the computation of the forward problem. The analysis expands over joint samples covering both structural state and design variables, i.e., sensor locations. Via increase of the number of deployed sensors in the network, the optimization procedure soon turns computationally costly due to the curse of dimensionality. To this end, a stochastic optimization method is adopted for accelerating the convergence of the optimization process and thereby the damage detection capability of the SHM system. The proposed method is applied to thin flexible structures, and the resulting optimal sensor configuration is shown. The effects of the number of training samples, the polynomial degree of the approximation expansion and the optimization settings are also discussed

Vibration-based structural performance assessment via output-only sub-Nyquist/compressive wireless sensor data

This paper assesses two different approaches for efficient output - only Vibration - based Structural Health Monitoring (V - SHM) in large - scale civil engineering structures, promoting the use of dense arrays of low - power wireless sensors. Firstly, a non - uniform deterministic sub - Nyquist multi - coset sampling scheme is considered to acquire ambient stationary structural response signals. This sampling scheme is coupled with a power spectrum blind sampling technique along with the frequency domain decomposition algorithm of operational modal analysis to obtain structural modal properties. This is accomplished without necessitating either signal reconstruction in the time - domain or signal sparsity assumption . Secondly, a spectro-temporal compressive sensing approach is considered applicable to cases where sign al reconstruction in time - domain is desired. The latter approach considers non-uniform in time random sampling at sub - Nyquist average rates informed by prior knowledge of signal sparsity gained through smart on-sensor operations and sensor/server communication. The usefulness and applicability of two approaches is numerically demonstrated by considering field recorded data pertaining to the monitoring of an overpass open to the traffic and of an operating on-shore wind turbine

The built environment as determinant of childhood obesity: a systematic literature review

We evaluated the epidemiological evidence on the built environment and its link to childhood obesity, focusing on environmental factors such as traffic noise and air pollution, as well as physical factors potentially driving obesity-related behaviours, such as neighbourhood walkability and availability and accessibility of parks and playgrounds. Eligible studies were i) conducted on human children below the age of 18 years, ii) focused on body size measurements in childhood, iii) examined at least one built environment characteristic, iv) reported effect sizes and associated confidence intervals, and v) were published in English language. A z-Test, as alternative to the meta-analysis, was used to quantify associations due to heterogeneity in exposure and outcome definition. We found strong evidence for an association of traffic-related air pollution (nitrogen dioxide and nitrogen oxides exposure; p<0.001) and built environment characteristics supportive of walking (street intersection density; p<0.01 and access to parks; p<0.001) with childhood obesity. We identified a lack of studies which account for interactions between different built environment exposures or verify the role and mechanism of important effect modifiers such as age

Low-frequency wide band-gap elastic/acoustic meta-materials using the K-damping concept

The terms "acoustic/elastic meta-materials" describe a class of periodic structures with unit cells exhibiting local resonance. This localized resonant structure has been shown to result in negative effective stiffness and/or mass at frequency ranges close to these local resonances. As a result, these structures present unusual wave propagation properties at wavelengths well below the regime corresponding to band-gap generation based on spatial periodicity, (i.e. "Bragg scattering"). Therefore, acoustic/elastic meta-materials can lead to applications, especially suitable in the low-frequency range. However, low frequency range applications of such meta-materials require very heavy internal moving masses, as well as additional constraints at the amplitudes of the internally oscillating locally resonating structures, which may prohibit their practical implementation. In order to resolve this disadvantage, the K-Damping concept will be analyzed. According to this concept, the acoustic/elastic meta-materials are designed to include negative stiffness elements instead or in addition to the internally resonating added masses. This concept removes the need for the heavy locally added heavy masses, while it simultaneously exploits the negative stiffness damping phenomenon. Application of both Bloch's theory and the classical modal analysis at the one-dimensional mass-in-mass lattice is analyzed and corresponding dispersion relations are derived. The results indicate significant advantages over the conventional mass-in-a mass lattice, such as broader band-gaps and increased damping ratio and reveal significant potential in the proposed solution. Preliminary feasibility analysis for seismic meta-structures and low frequency acoustic isolation-damping confirm the strong potential and applicability of this concept.Comment: Keywords: Acoustic meta-materials, elastic meta-materials, low-frequency vibration absorption, seismic meta-structures, noise absorptio

On the use of nonlinear normal modes for nonlinear reduced order modelling

In many areas of engineering, nonlinear numerical analysis is playing an increasingly important role in supporting the design and monitoring of structures. Whilst increasing computer resources have made such formerly prohibitive analyses possible, certain use cases such as uncertainty quantification and real time high-precision simulation remain computationally challenging. This motivates the development of reduced order modelling methods, which can reduce the computational toll of simulations relying on mechanistic principles. The majority of existing reduced order modelling techniques involve projection onto linear bases. Such methods are well established for linear systems but when considering nonlinear systems their application becomes more difficult. Targeted schemes for nonlinear systems are available, which involve the use of multiple linear reduction bases or the enrichment of traditional bases. These methods are however generally limited to weakly nonlinear systems. In this work, nonlinear normal modes (NNMs) are demonstrated as a possible invertible reduction basis for nonlinear systems. The extraction of NNMs from output only data using machine learning methods is demonstrated and a novel NNM-based reduced order modelling scheme introduced. The method is demonstrated on a simulated example of a nonlinear 20 degree-of-freedom (DOF) system

Urinary metabolic profiles in early pregnancy are associated with preterm birth and fetal growth restriction in the Rhea mother-child cohort study

Syftet med studien var att undersöka vilka möjligheter matematikundervisning utomhus kan ge för elevernas utveckling och lärande. Syftet var även att undersöka hur utomhusmatematik kan användas som ett komplement till den traditionella inomhusundervisningen i ämnet matematik. Studien baserades på en kvalitativ forskningsansats där kvalitativa semistrukturerade intervjuer och ostrukturerade observationer användes som metoder för att besvara studiens forskningsfrågor. Sex lärare i F-3 intervjuades och två observationer på två olika skolor genomfördes. Resultatet visar att utomhusmatematiken kompletterar matematikundervisningen inomhus genom ett samspel mellan arbetssätt och miljöer. Resultatet visar även på flera positiva effekter med utomhusmatematik så som verklighetsanknytning, motivation, fysisk aktivitet, hälsa, sinnligt lärande, tillåtande miljö och sociala effekter.  De positiva effekter utomhusmatematiken medföljer för elevernas utveckling och lärande bör uppmärksamma fler lärare om dess möjligheter.

A hysteretic multiscale formulation for validating computational models of heterogeneous structures

A framework for the development of accurate yet computationally efficient numerical models is proposed in this work, within the context of computational model validation. The accelerated computation achieved herein relies on the implementation of a recently derived multiscale finite element formulation, able to alternate between scales of different complexity. In such a scheme, the micro-scale is modelled using a hysteretic finite elements formulation. In the micro-level, nonlinearity is captured via a set of additional hysteretic degrees of freedom compactly described by an appropriate hysteric law, which gravely simplifies the dynamic analysis task. The computational efficiency of the scheme is rooted in the interaction between the micro- and a macro-mesh level, defined through suitable interpolation fields that map the finer mesh displacement field to the coarser mesh displacement field. Furthermore, damage related phenomena that are manifested at the micro-level are accounted for, using a set of additional evolution equations corresponding to the stiffness degradation and strength deterioration of the underlying material. The developed modelling approach is utilized for the purpose of model validation; firstly, in the context of reliability analysis; and secondly, within an inverse problem formulation where the identification of constitutive parameters via availability of acceleration response data is sought