1,720,969 research outputs found
Size effect in single layer graphene sheets and transition from molecular mechanics to continuum theory
No full textThe size-dependent mechanical response of graphene is investigated with an entirely nonlinear molecular mechanics approach. Finite element (FE) simulations under uniaxial and equibiaxial tensile loads are carried out on graphene sheets with increasing size. It is found that the response of graphene remains unchanged after a threshold size. Furthermore, anisotropy is observed for large deformations and a negative Poisson's ratio is found after a critical strain for the zigzag uniaxial load case. The threshold size defines the transition to the continuum theory, which is developed as a membrane model in the fully nonlinear context of finite elasticity. The constitutive parameters of the model are calibrated by fitting the results of the FE simulations. The proposed model represents the basis for accurate predictions of the response of graphene subjected to large in-plane deformations. Nonlinear laws for the size-dependent elastic properties of graphene are derived. These laws can be used in linear elasticity-based models to take into account for material nonlinearity, anisotropy and size effect. Finally, a sensitivity analysis of the molecular mechanics model to the parameters of the interatomic potentials is carried out. The discussion of the results gives insights into the influence of each parameter and useful remarks for the molecular mechanics modeling of graphene
Bayesian estimate of the elastic modulus of concrete box girders from dynamic identification: a statistical framework for the A24 motorway in Italy
No full textThis paper delivers a reliability-based method for the assessment of the elastic modulus (EM) of concrete in simply supported girders from dynamic identification. The correlation between the natural frequencies of the first bending modes and the concrete EM supports the use of the first natural frequency as a predictor of the EM value, which is a well-acknowledged indicator of the state of concrete. In the current application, the EMs of seven girders provide the prior state of knowledge about the considered bridge class, possibly to be obtained by more samples in working applications. The identified natural frequencies update the prior probability distribution of the EMs using Bayes inference. The resulting probability of exceeding a specific EM value expresses the degree of belief of the inspector in the obtained EM. The posterior probability, compared to a proper threshold, could be used in decision-making processes when prioritising the interventions in the maintenance plans
Dynamic Characterization of Timber Floor Subassemblies: Sensitivity Analysis and Modeling Issues
No full textTimber floors are prone to exhibit vibration levels, which can cause discomfort to the occupants. In the last 20 years, ambient vibration tests have become very popular due to the many advantages they have over traditional forced vibration tests when dealing with civil engineering structures. Furthermore, sensitivity analyses and black-box"optimization algorithms can support the development of refined finite-element models that accurately predict the structures' responses based on the experimental modal parameters. However, applications of these methods and techniques to timber structures are scarce compared with traditional materials. This paper presents and discusses the findings of an experimental testing campaign on a lightweight timber floor. At first, each component of the assembly was tested separately under different boundary conditions. Then, the authors evaluated the behavior of the whole floor assembly. In a second step, the authors carried out a covariance-based sensitivity analysis of finite element (FE) models representative of the tested structures by varying the different members' mechanical properties. The results of the sensitivity analysis highlighted the most influential parameters and supported the comparison among diverse FE models. As expected, the longitudinal modulus of elasticity is the most critical parameter, although the results are very dependent on the boundary conditions. Then automatic modal updating algorithms tuned the numerical model to test results. As a concluding remark, the experimental and numerical results were compared with the outcomes of a simplified analytical approach for the floor's first natural frequency estimate based on current European standards
Structural Health Monitoring with Artificial Neural Network and Subspace-Based Damage Indicators
No full textIn recent years, different structural health monitoring (SHM) systems have been proposed to assess the actual conditions of existing bridges and effectively manage maintenance programmes. Nowadays, artificial intelligence (AI) tools represent the frontier of research providing innovative non-invasive and non-destructive evaluations directly based on output-only vibration measures. This is one of the key aspects of smart structures of the future. In the current study, an artificial neural network (ANN) method has been proposed in order to perform damage detection based on subspace-based damage indicators (DIs) and other statistical indicators. A numerical case study example has been analysed with simulated damaged conditions. Based on a comparison between a reference situation and a new one, the greatest advantage in adopting these particular DIs is because they are able to point out significant changes, i.e. possible damage, without requiring a beforehand modal identification procedure, which may introduce further noise and modelling errors inside the traditional damage detection process
One-Year Dynamic Monitoring of an Eight Story CLT Building
Full text linkThis paper outlines the initial findings derived from a year-long dynamic monitoring of an eight-story Cross-Laminated Timber (CLT) building situated in As, Norway. The authors conducted bi-daily dynamic response measurements of the structure since November 2022. In tandem, the environmental humidity, and wind speed were also monitored. A key aspect of the study lies in examining of the interplay between environmental factors and modal parameters, with a specific emphasis on temperature. The analysis reveals that the first two bending modes of the structure exhibit a positive correlation with external temperature, with coefficients of determination of 0.44 and 0.25, respectively. The study also discusses the expected negative correlation between the natural frequencies and moisture content of wood, based on general wood behavior principles
FE Model Updating of Cable-Stayed Bridges Based on the Experimental Estimate of Cable Forces and Modal Parameters
Full text linkThe paper presents an example of model updating of both the mass and stiffness parameters of a curved cable-stayed bridge in Venice (Italy). Conventional optimization problems of mass and stiffness using ambient vibration data are prone to ill-posedness and ill-conditioning, and generally, the scholar must assume one of the two to achieve a reliable estimate. However, it is possible to assess the mass and stiffness from ambient vibration tests in cable-stayed bridges following a two-step procedure. In the first step, the scholar can assess the mass matrix from the cable forces estimated from the natural frequencies of the cables. Then, the unscaled mode shapes and natural frequencies are used to tune the stiffness matrix in a second step. The authors proved this updating approach with two variance-based sensitivity analyses. The former is the sensitivity of the cable forces to the specific mass and bearing deformability. The latter is the sensitivity of the natural frequencies to Young’s moduli. Two global optimization algorithms for mutual validation, differential evolution (DE) and particle swarm optimization (PSO), are then implemented for the model calibration
Timber-to-timber composite floors connection optimization for vibration and deflection reduction
Full text linkGoing Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
- …
