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The degradation of bridge structural performance arises from the combined influence of various factors. Performance assessment and reliable prediction of bridge performance degradation through effective utilizing of detection information updates is a challenging problem. In this paper, the concept of performance indicators is redefined, employing to delineate bridge performance degradation. A bridge performance degradation model (the error ≤8%) is formulated, considering the multiple-variable Bayesian dynamic linear method (MBDLM) and revealing the coupling mechanisms among factors influencing bridge performance degradation. On this basis, the prediction performance of the model is quantitatively evaluated by three metrics: mean squared error, predictive mean squared error and mean absolute percentage error. A methodology is presented for the assessment, prediction, and maintenance reinforcement of in-service bridge structural performance degradation. This approach holds promise for future applications in safety assessments and the decision-making process for preventive maintenance of operational bridges. [ABSTRACT FROM AUTHOR]

In order to study the failure mechanism of a finned pile foundation under horizontal cyclic loads, a physical model test of the pile–soil interaction of finned pile is designed in this paper. Based on the model tests, the pile top displacement, the cyclic stiffness of the pile foundation, and the response of pore water pressure within the soil around the pile were fully studied for the finned pile foundation under horizontal cyclic loads. It is found that the cyclic stiffness attenuation of the finned pile foundation is more severe than that of a regular single pile foundation, but the final stiffness at equilibrium is still greater than that of a regular single pile foundation. The accumulation of horizontal displacement at the pile top and pore water pressure within the soil around the pile mainly occurs in the first 1000 loading cycles, and an increase in fin plate size will reduce the magnitude of pore water pressure and pile top displacement. This study can not only deepen the understanding of the failure mechanism of finned pile foundation under horizontal cyclic loads, but also provide guidance for the design of the finned pile foundation. [ABSTRACT FROM AUTHOR]

The dynamic characteristics of long-span suspension bridges are complex. The natural vibration frequency is changed with different structural parameters, and the sensitivity to different parameters is different. In order to solve this problem, the spatial model of a long-span suspension bridge was established by using finite element software, and the first 20 natural vibration periods, natural vibration frequencies and vibration modes were analyzed and calculated. The accuracy of the obtained natural vibration frequency data was verified through field tests. Finally, based on the model, the stiffness of structural components is studied by one -factor-at-one-time, and the influence of various variables on the frequency and mode of a certain mode is studied by one-factor-at-one-time method. The results show that different structural parameters have different effects on the vibration frequency. When the stiffness of stiffening girder and main tower is changed, with the increase of stiffness, the variation of frequency mostly presents an upward trend, and the range is large. With the change of the secondary dead load, most of the frequencies decrease first and then tend to be stable. It can be seen from the field test results that the vibration shapes and frequencies measured by numerical simulation and test are close to each other, which can meet the requirements of engineering precision. The stiffness of the main cable and the main tower has a great influence on the modes and periods corresponding to them. The increase of the secondary dead load can reduce the natural vibration frequency of the suspension bridge, but it is not unlimited to increase the secondary dead load to reduce the frequency. The stiffness of the stiffening girder has a great influence on the frequency of the suspension bridge. When the bending stiffness of the stiffening girder increases to 3 times of the original one, the order of vibration modes of the structure will change. The research results can provide references for structural design and dynamic parameter adjustment of long-span suspension bridge.

Brillouin scattering (BS)–based distributed optical fiber sensors (DOFS) provide distributed sensing capabilities by monitoring the strain along entire segments of structures. Large cracks, such as those with large crack opening displacements (COD) can be detected by strain peaks or singularities along the measurement length of distributed sensors. Microcracks do not provide visible pronounced local peaks along the length of measured distributed strains. The peaks corresponding to microcracks are submerged within the measurement noise due to low signal-to-noise ratio (SNR) of BS systems. Deep learning (DL) methods have the potential to automatically extract feature representations from data exhibiting lower SNRs, and improve classification accuracy. Accordingly, a novel DL method is proposed in this study to improve the crack detection sensitivity of the BS-based DOFS. Development of the proposed DL method includes construction of model architecture, design of a training algorithm and the detection process. A 15 m-long wide-flange steel beam with artificial defects is built and employed in this study. A comprehensive experimental program is undertaken in order to train, validate and test the generality of the proposed DL method. Experimental results demonstrate that the DL method is capable of extracting highly discernable microcrack features from the distributed strains, and distinguish the crack-induced local peaks from the noise. Microcracks with CODs as small as 23 microns are accurately detected in the present work. [ABSTRACT FROM AUTHOR]

Fluid catalytic cracking (FCC) is one of the most important conversion processes in petroleum refineries, and FCC regenerator is a key component of an FCC unit to recover the solid catalyst reactivity by burning off the deposited coke on the catalyst. In this paper, a three-dimensional multi-phase flow computational fluid dynamics (CFD) model was established to simulate the flow inside a commercial FCC regenerator. The two phases involved in the flow are gas phase and solid phase. The Eulerian-Eulerian approach, where the two phases are considered to be continuous and fully inter-penetrating, was employed. The effects of different drag models on the flow characteristics were firstly investigated. A modified drag force model was applied by using user define function (UDF) in ANSYS Fluent, which provides a better prediction on the solid volume fraction profile along the regenerator height. Particle clustering phenomena was taken into consideration through the adjustment of effective particle cluster diameters. The appropriate effective cluster diameters in the dense bed and the dilute phase are 300 μm and 200 μm, respectively. Catalyst solid volume fraction profile indicates that there are four zones in the computational domain: dense zone, sub-dense zone, dilute zone and sub-dilute zone. The developed CFD model was validated by plant data. The effect of air superficial velocity on the fluidization was also investigated and the results shown that the total flow rate of catalysts goes through the cyclone increases linearly with increasing air superficial velocity from a range of 0.6 to 1.03. [ABSTRACT FROM AUTHOR]

For a 230t large steel ingot which is firstly manufactured in one industrial plant, both of the analytical calculation and the numerical simulation methods were adopted to predict the total solidification time based on their own physical and mathematical models. The results showed that the total solidification time calculated by the analytical method was 46.0 h, and that was 40.2 h by the numerical method. Comparing with the actual stripping time of 45.8 h for the 230t large steel ingot, both of the estimated values agreed reasonably well with the actual one. For the purpose of practical utilization, the analytical method tends to be more convenient rather than the numerical one. This study can provide a kind of reference for the prediction on the total solidification time of large steel ingots. [ABSTRACT FROM AUTHOR]

Abstract: Finite element model updating is the important foundation of structural damage detection, condition assessment for engineering structure. A new method for finite element model updating based on the quasi-static generalized influence line (QSGIL) residual objection is presented to update the finite element model in order to improve the quality of finite element algorithm. The experimental study shows that the method can efficiently update the finite element model. [Copyright &y& Elsevier]

During the electric arc furnace (EAF) refining stage, coherent jets are used to increase the depth of oxygen jet penetration for better oxygen efficiency and stirring of the liquid steel. A coherent jet is defined when the supersonic jet is shrouded by a flame envelope, which leads to a higher potential core length (the length up to which the axial jet velocity equals the exit velocity at the nozzle). In this paper, a coherent jet computational fluid dynamics (CFD) model is developed with detailed consideration of compressible flow properties and combustion effects. The model is validated by comparing the coherent jet axial velocity profile with experimental measurements. Simulation results show that the combustion reaction mechanism used has a significant effect on prediction of flame temperature, which will affect potential core length. The current model uses a 28‐step reaction mechanism to achieve both computational efficiency and model accuracy. Turbulence model modification is necessary for accurately predicting the flow properties. The current proposed modifications are needed for accurate prediction of both compressibility and temperature gradient effects. In this paper, a coherent jet CFD model is developed with detailed consideration of compressible flow properties and combustion effects. The model is validated against experimental measurements. The current model‐proposes a modified standard k‐epsilon turbulence model with modifications of both compressibility and temperature gradient effects. Different CH4‐O2 combustion mechanisms are also investigated. [ABSTRACT FROM AUTHOR]

In steel rolling mills, reheat furnaces are used to reheat slabs to high temperatures in a highly oxidizing environment; this results in the formation of iron oxide scale on the slab surface. Scale formation poses an ongoing material and economic loss to industry and should be minimized where feasible. The kinetics of scale growth are complex and still not fully understood. Previous studies that modeled scale formation with mathematical methods are limited to simple case studies. Here, computational fluid dynamics (CFD) is used to simulate slab reheat furnace operations and to investigate complicated physical phenomenon. This paper proposes a new numerical method to model scale growth under varying conditions/characteristics including temperature, gas atmosphere composition, and steel grade. This method uses a mixed linear‐parabolic equation to model both the initial surface reaction (and scale formation) and the subsequent solid‐state ion diffusion through the developed scale. This model can be used to predict the amount of scale that will form on a slab under certain conditions. Model predictions were found to be consistent with experimental data. In this paper, a new numerical method to simulate scale formation is introduced. An acceptable agreement between CFD model results and actual experimental measurements is achieved for the scale formation model under different gas conditions. The model estimates the scale thickness with fair accuracy compared with both in‐lab experimental work and industrial reheat furnace data. [ABSTRACT FROM AUTHOR]

With the rapid depletion of high-yield copper mineral resources and the accumulation of secondary copper resources, the recycling of secondary copper is gaining popularity in the copper industry. A copper anode furnace, often used in copper recycling, usually relies on methane combustion to melt copper scraps. In this work, a computational fluid dynamics (CFD) model of pure oxy-methane combustion is established to investigate the combustion characteristics of the CH 4 /O 2 combustor in the copper anode furnace. The model is validated by comparing the simulation results with experimental measurements. The effects on flame length and temperature distribution are investigated under various fuel velocities, oxidizer velocities, and oxidizer temperatures. The results indicate that flame length and temperature distribution increase as the fuel velocity and oxidizer temperature increase, and decrease with the increase in oxidizer velocity. The flame length and temperature distribution always show an increasing trend with the increasing equivalence ratio. Based on the recycling capacity of the copper anode furnace, this validated CFD model can be used to optimize the operation parameters for controlling flame length and temperature distribution., Competing Interests: The authors declare no competing financial interest.