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In this study, steel fiber-reinforced concrete (SFRC) beam structures with regular oriented steel fibers are designed and prepared by using an assembled solenoid device. Fiber orientation is not arranged in a single direction but is similar to the direction of tensile stress of the beam in bending load conditions. With application of inductive test method and image processing technology, fiber orientation coefficient of SFRC was evaluated and increased from 0.5 to 0.7–0.8 after fiber alignment. To describe and analyze the flexural behavior of SFRC beams with regular oriented fibers and glass fiber-reinforced polymer (GFRP) rebars, 14 concrete beams with different parameters were fabricated and subjected to a four-point bending test. Specifically, the parameters included fiber content, fiber orientation, GFRP reinforcement ratio and different layer sections. The results showed that optimizing fiber orientations to the tension zone of the section led to a higher flexural strength and can well restrain the development of crack widths with comparison to randomly distributed fibers. The peak load and energy absorption increased by 7 % and 12.4 % after fiber alignment with a fiber volume fraction of 1.5 %. The combination of randomly and regularly distributed steel fibers in the form of two-layer composite members can be an efficient solution to improve the flexural performance for purpose of the optimum distribution and direction of steel fibers, and reduce the engineering cost. • A magnetic orientation device is designed for SFRC beams with regular oriented fibers. • Fibers had well arrangements with high fiber orientation coefficient. • A flexural test of the ASFRC beams was conducted and investigated. • ASFRC improved the first cracking load and initial stiffness of beams. • The experimental results indicated great flexural performance after aligning fibers to the tension zone. [ABSTRACT FROM AUTHOR]

Highlights • A method for simulation of spatial variability of gravity dams was established. • Mean value of the tensile strength has a great influence on the plastic damage. • Research results can be used as a reference for gravity dams with similar profiles. Abstract A method to simulate the random field of the strength parameters of gravity dams considering their spatial variability based on the theory of random fields and the autocorrelation function is proposed. Taking a gravity dam project as an example, the elastic modulus and tensile strength are selected as random variables and the corresponding random fields are generated. Based on the concrete damage plasticity (CDP) model, the effects of the spatial variability of parameters on the dynamic response characteristics of gravity dams are expressed from the standpoints of damage development, residual displacement, and energy dissipation. The impacts of the mean value, coefficients of variation, autocorrelation distance, realizations of the tensile strength random field, and seismic inputs on the structural damage are also investigated. It is found that the spatial variability of parameters, especially the tensile strength, has a great influence on the dynamic damage of gravity dams, and that increasing the mean value of the tensile strength can improve their seismic performance. [ABSTRACT FROM AUTHOR]

It is very important to estimate the mechanical parameters based on monitoring data for investigating the operation behavior of concrete dams. In this paper, an advanced Bayesian parameter estimation method for concrete dams is proposed. The Empirical Mode Decomposition (EMD) is adopted to extract the aging component of the observed deformation sequence, and the hydrostatic component is separated from the remaining periodic term through the statistical regression model (SRM). A hybrid response surface method (HRSM) is proposed as a surrogate model for finite element method (FEM) simulation. The likelihood function, which reflects the error between the observed and simulated deformation, is constructed, then the Bayesian formula for parameter estimation is established. The transitional Markov chain Monte Carlo (TMCMC) algorithm is used to obtain the parameter posterior distribution. The proposed method is applied to estimate the elastic modulus of the GD concrete dam, the parameter posterior distribution is obtained through the fusion of monitoring information and parameter prior information. This method can also avoid the issues of multiple solutions and unreasonable parameter combinations, which may exist in traditional deterministic inversion methods. The case study shows that the proposed method has good applicability in the parameter estimation of concrete dams. [ABSTRACT FROM AUTHOR]

• Data-based models with EMD are proposed for deformation monitoring of concrete dams. • The proposed models can well simulate the irreversible component of concrete dam deformation and significantly decrease the over-fitting levels. • A new model selection criterion, namely Over-fitting coefficient, is proposed for evaluating and selecting dam health monitoring models. • The Over-fitting coefficient can better reflect over-fitting levels of individual monitoring models compared to traditional model selection criteria. Data-based models are extensively applied in concrete dam health monitoring. In this paper, the Empirical Mode Decomposition (EMD) is adopted to extract and visualize the irreversible component of deformation monitoring sequence. Consequently proper mathematical formulation of the irreversible component of deformation monitoring model for concrete dams can be established, and the problem of improperly assuming the mathematical form of irreversible component when constructing data-based models is well addressed. The periodic component of the deformation time series is modelled by regression and three machine learning algorithms (i.e., Extreme learning machine, Support Vector Machine based on Grid search and Cross-Verification, and Back Propagation Neural Networks optimized by Genetic Algorithm and Simulated Annealing) respectively. The data-based models with the EMD are able to effectively improve the performance of formulating irreversible component of concrete dam deformation and decrease the over-fitting levels. A new model selection criterion, namely Over-fitting coefficient, is proposed for evaluating and selecting the optimum model among candidate monitoring models. The Over-fitting coefficient can better reflect over-fitting levels of individual monitoring models compared to traditional model selection criteria. As a case study, the displacement and strain monitoring data from the YL gravity dam are modeled by data-based models with the EMD and machine learning algorithms. It is shown that data-based models with the EMD are of higher prediction accuracy and lower rate of false alarm in deformation monitoring than traditional models. The Over-fitting coefficient can better reflect over-fitting levels of monitoring models compared to the error measurement criteria and information criteria. The case study highlights the merits of the proposed data-based models and the model selection criterion for health monitoring of concrete dams. [ABSTRACT FROM AUTHOR]

• The transverse impact response of hybrid biaxial/uniaxial braided tube was studied. • The effects of architecture hybridization and stacking sequence were identified. • Proposed FE model provided accurate predication of the impact behaviors. Tubular composites in automobile engineering are susceptible to transverse loading events. This paper deals with transverse low-velocity impacts on interply hybrid tubes made of biaxial/uniaxial braided fabric layers. For comparison, drop weight tests were performed on hybrid tubes with biaxial braided surface layers and uniaxial braided inner layer (BUB), with contrary stacking sequence (UBU), pure biaxial and uniaxial braided tubes (BBB and UUU). Numerical models were established to predict the impact behaviors and evaluate the hybrid effects. X-ray micro-computed tomography (Micro-CT) was also employed to identity the cracking location and characterize the damage mechanism. The results showed that the impact response of braided tube was related to its structural deformation resistance, which was determined by properties of reinforced layers varying with different stacking sequence. The hybrid effect became more obvious at higher impact energy. At impact energy of 15.4 J, hybrid tube (BUB) yielded the highest impact resistance with small structural deformation. The biaxial braided layer protected the specimen surface by constraining intralaminar crack propagation through the interlacing patterns. Meanwhile, it promoted crack tip propagating to the subsequent uniaxial braided layer and transferred the impact load. Thus, the material involvement of the inner layer was improved, which was responsible for providing a higher in-plane tensile property due to its low yarn crimp. [ABSTRACT FROM AUTHOR]