Explore the vast range of titles available.

This paper reveals the failure characteristic points of the spiral reinforced column during the damage process by modeling and analyzing the stressing state of the column with the test and finite element output data. At the same time, the structural stressing state theory and the correlation modeling analysis method’s applicability to spiral reinforced concrete columns are verified. First, a finite element model was established based on the literature’s spiral reinforced concrete column tests. Then, correlation modeling was performed on the test strain data to obtain correlation characteristic pairs (mode-characteristic parameters), and stressing state modeling was performed on the internal energy and element strain energy data from the finite element model to obtain stressing state characteristic pairs. The slope increment criterion is applied to the obtained stressing state characteristic parameter curves to reveal the characteristic point Q, defined as the failure starting point. The reasonableness of the failure starting point is further verified by observing the cloud diagram of the finite element model in the vicinity of the characteristic point Q. In general, the correlation modeling method proposed in this paper can provide a new reference for structural stressing state analysis. In addition, the failure starting point of spiral reinforced concrete columns revealed in this paper can be used as a design reference.

The National Airport Pavement Test Facility (NAPTF) in USA obtained the strain and deformation data of the asphalt airport pavement numbered as Track 3 under the wheel load traveling in the north area of Construction Cycle 7 (CC7). But, the classic theories and methods still could not find out the definite and essential working characteristics, such as the starting point of the asphalt pavement’s failure process and the ending point of the normal working process. This study reveals the essential working characteristics of the asphalt airport pavement by modeling the tested strain and deformation data based on structural state-of-stress theory. Firstly, the tested data are modeled as state variables to build the state-of-stress mode and the parameter characterizing the mode. Then, the slope increment criterion detects the mutation points in the evolution curve of the characteristic parameter with a wheel load traveling number increase. Correspondingly, the mutation features are verified by investigating the evolution curves of the state-of-stress modes. The mutation points define the failure starting point and the elastoplastic branch (EPB) point in the working process of the asphalt airport pavements. The strain state-of-stress mode (Δεt) and characteristic parameters (Ej and Φj) presented an obvious mutation feature around the EPB point; in addition, the deformation state-of-stress mode (ΔDt) showed that the total deformation of the pavement changed evidently before and after the failure starting point, and the characteristic parameters (Ej and Φj) also presented an obvious mutation feature around the failure starting point, so both characteristic points could address the classic issues in the load-bearing capacity of asphalt airport pavements. Furthermore, the EPB point could be directly taken as the design point, and the failure starting point could be taken as the limit-bearing traffic capacity. Hence, this study could open a new way to address the classic issues in the load-bearing capacity of asphalt airport pavements and provide a new reference for their safe estimation and rational design.

This paper conducts the experimental and simulative analysis of stressing state characteristics for parabolic concretefilled steel tubular (CFST) arches undergoing vertical loads. The measured stain data is firstly modeled as the generalized strain energy density (GSED) to describe structural stressing state mode. Then, the normalized GSED sum Ej,norm at each load Fj derives the Ej,norm-Fj curve reflecting the stressing state characteristics of CFST arches. Furthermore, the Mann-Kendall criterion is adopted to detect the stressing state change of the CFST arch during its load-bearing process, leading to the revelation of a vital stressing state leap characteristic according to the natural law from quantitative change to qualitative change of a system. The revealed qualitative leap characteristic updates the existing definition of the CFST arch’s failure load. Finally, the accurate formula is derived to predict the failure/ultimate loads of CFST arches. Besides, a method of numerical shape function is proposed to expand the limited strain data for further analysis of the stressing state submodes. The GSED-based analysis of structural stressing state opens a new way to recognize the unseen working behavior characteristics of arch structures and the updated failure load could contribute to the improvement on the structural design codes.

This study reveals the essential load-bearing characteristics of the steel–concrete composite floor system under fire conditions applying the structural stressing state theory. Firstly, the strain data in the entire process of the fire test are modeled as state variables which can present the slab’s stressing state evolution characteristics. Then, the state variables are used to build the stressing state mode and the parameter characterizing the mode. Further, the Mann–Kendall criterion is adopted to detect the leap points in the evolution curves of the characteristic parameters during the entire fire exposure process. Also, the evolution curves of the stressing state modes are investigated to verify the leap profiles around the leap/characteristic points. Finally, the detected leap points are defined as the failure starting points and elastoplastic branching points, which is unseen in past research focusing on the failure endpoint defined at the ultimate load-bearing state of the composite floor system. The failure starting point and the elastoplastic branching point are the embodiment of natural law from quantitative change to quality change in a system rather than an empirical and statistical judgment. Hence, both characteristic points avoidably exist in the strain data of the composite floor system undergoing the fire process, which can be revealed through the proper modeling methods and update the existing theories and methods on structural analysis and design in fire.

This paper experimentally analyzes the working behavior characteristics of a large-curvature continuous prestressed concrete box-girder (CPCBG) bridge model based on structural stressing state theory. First, the measured strain data is modeled as generalized strain energy density (GSED) to characterize the stressing state of the bridge model. Then, the Mann-Kendall (M-K) criterion is adopted to detect the stressing state leaps of the bridge model according to the natural law from quantitative change to qualitative change of a system, which derives the new definition of structural failure load. Correspondingly, the stressing state modes for the bridge model’s sections and internal forces are proposed to verify their changing characteristics and the coordinate working behavior around the characteristic loads. The analytical results reveal the working behavior characteristics of the bridge mode unseen in traditional structural analysis, which provides a new angle of view to conduct structural analysis and a reference to the improvement of design codes.

MicroRNAs have recently reported playing a vital role in the development of cancers. However, the role of miR-592 in renal cell carcinoma (RCC) has not been explored. In this study, the potential role of miR-592 was investigated in RCC. The expression of miR-592 was evaluated in RCC tissues and cell lines using qRT-PCR assays. The Kaplan-Meier analysis and Cox proportional hazards model analysis was used to analyze the prognostic value of miR-592 in RCC. The effects of miR-592 on cell proliferation, migration, and invasion were determined by cell counting kit-8 (CCK-8) and Transwell assays in vitro. The results showed that miR-592 was significantly increased both in RCC tissues and cell lines. Overexpression of miR-592 was significantly associated with lymph node metastasis, TNM stage, and poor overall survival. And functional studies in two RCC cell lines (786-O and Caki-1) have shown that overexpression of miR-592 promoted cell proliferation, migration, and invasion, while silence of miR-592 inhibited cell proliferation, migration, and invasion. SPRY2 was a direct target of miR-592. Overall, overexpression of miR-592 may be a prognostic biomarker and therapeutic strategy for patients with RCC, which is correlated with the progression of RCC.

This study develops a modified multi-support response spectrum (MSRS) method, in order to efficiently and accurately calculate the response of multi-support structures under incoherent ground motions. The modified MSRS method adopts three ancillary processes, constructing structural displacement vectors or constructing infinite stiffness members or increasing the degrees of freedom at structural supports. Then, the modified MSRS method is verified in a comparison with the existing MSRS method through a model of a five-span reinforced concrete continuous rigid frame bridge. Finally, the collective structural response spectrum, the structural power spectrum, and the simplified structural power spectrum are deduced from the equation of the motion taking ground motion displacements as the input, and validated through the same bridge model.

This paper investigates structural performance of five reinforcement concrete (RC) box-girders under a combination loading of bending, shear and torsion, applying the structural stressing state theory. The measured strain data is modeled as generalized strain energy density (GSED) to characterize the structural stressing state mode. Then the Mann-Kendall (M-K) criterion is innovatively applied to detect the leap characteristics of RC box-girders’ stressing state from the E’-T curves, deriving the new definition of structural failure load. Furthermore, the reinforcement effects of different Carbon Fiber Reinforced Plastic (CFRP) wrapping schemes on the behaviors of experimental RC box-girders are revealed through comparing strain modes of stirrup and longitudinal reinforcement. Finally, the method of numerical shape function is applied to reasonably expand the limited strain data for further exploring the strain distribution of cross section and analyzing the stressing state characteristics of the RC box-girders. The research results provide a new angle of view to conduct structural analysis and a reference to the improvement of reinforcement scheme. First published online 29 November 2019

Rice husks as common agricultural remnants with low density and good thermal conductivity properties have been used in infill walls in the northern area of China. Accordingly, many tests and numerical simulations were conducted to address a difficult issue, the inaccurate estimation on the lateral load-bearing capacity of different types of husk mortar energy-saving (HMES) wallboards. The difficulty has not been overcome so far, implying that the novel methods are anticipated to achieve the accurate estimation. This paper tests the full-scale HMES wallboards with different openings and obtains the strains at the points distributed on the wallboard sides. The experimental strains are modeled as the approximate strain energy values to produce the characteristic parameter of the HMES wallboard’s stressing state. Furthermore, the inherent working state characteristic points of HMES wallboards are revealed from the evolution of the characteristic parameter called as the normalized approximate strain energy sum, leading to the redefinition of the failure loads for the HMES wallboards. Finally, it investigates the stressing state mode evolution of the HMES wallboard around the failure loads. The achieved results provide the reference to the accurate estimation of the bearing capacity of the HMES wallboards.

The intricate interplay between the microscopic constituents and their macroscopic properties for masonry structures complicates their failure analysis modelling. A composite strategy incorporating neural network (NN) and cellular automata (CA) is developed to predict the failure load for masonry panels with and without openings subjected to lateral loadings. The discretized panels are modelled by the CA methodology using nine neighbour cells, which derive their state values from geometric parameters and opening location placement for the panels. An identification coefficient dictated by these geometric parameters and experimental data is fed together as the input training data for the NN. The NN uses a backpropagation algorithm and two hidden layers with sigmoid activation functions to predict failure loads. This method achieves greater accuracy in prediction when compared with the yield line and finite elemental analysis (FEA) methods. The results attained elucidate the feasibility of the current methodology to complement conventional approaches such as FEA to provide additional insight into the failure mechanism of masonry panels under varied loading conditions.