Numerical computation for vibration characteristics of long-span bridges with considering vehicle-wind coupling excitations based on finite element and neural network models

CA (Cellular Automaton) model was applied to the simulation of random traffic flow to develop a model considering the randomness of traffic flow and apply it to wind-vehicle-bridge coupling vibration. Finite element and neural network models were adopted respectively to numerically compute the vibration characteristics of bridges under wind and vehicle loads, verify the correctness of model. Subspace iteration method was used for the modal analysis of bridges. Natural frequencies of the top 8 orders were 0.21 Hz, 0.27 Hz, 0.36 Hz, 0.45 Hz, 0.56 Hz, 0.66 Hz, 0.87 Hz and 1.02 Hz respectively. The vibration frequency of the long-span bridge was consistent with the vibration characteristics of large-scale complex structures. Natural modes mainly reflected the torsion and bending of main beam and the swinging vibration of side and main towers. Fluctuation wind time-history presented periodic characteristics. The maximum and minimum values of fluctuation wind were about 20 m/s and –20 m/s respectively. The target and simulation values of power spectral density of wind speed were basically the same in change trend, which indicated that the fluctuation wind time-history computed in this paper was reliable. The model of dense traffic flow based on CA more truly described the running status like accelerating, decelerating and changing lanes of vehicles on the bridge, also contained the density information of vehicles and more truly reflected traffic characteristics. Vibration accelerations of the long-span bridge were symmetrically distributed. Vibration acceleration of central position in the left main span was the largest and near 50 cm/s2; vibration acceleration on the main tower was the smallest. The curve of vibration displacement with considering wind loads presented some fluctuations, while the vibration displacement of bridges without considering wind loads was very smooth. In addition, the amplitude of vibration displacement without considering wind loads moved laterally towards the left compared with that with considering wind loads. Therefore, wind loads must be considered when the vibration characteristics of the long-span bridge were computed. Otherwise, the accuracy of computational results would be reduced. It only took 0.5 hours to use neural network to predict the vibration acceleration of the long-span bridge. In the case of the same computer performance, it took 5 hours to use finite element model to predict the vibration acceleration of the long-span bridge. The advantage of neural network model in predicting the performance of large-scale complex structures like a long-span bridge could be obviously found. In the future, we will consider using neural network model to systematically study and optimize the long-span bridge

Research on the computational method of vibration impact coefficient for the long-span bridge and its application in engineering

To compute vibration impact coefficient at each part of the long-span bridge more accurately, this paper proposed a computational method based on vehicle-bridge coupling vibration. Firstly, the general equations of vehicle-bridge coupling vibration were derived based on the standard fatigue vehicle and multi-scale model of bridges. Secondly, the corresponding program of vehicle-bridge coupling vibration was designed. Thirdly, the computational method of vibration impact coefficient for the long-span bridge was introduced and obtained. The proposed computation method of vibration impact coefficient based on vehicle-bridge coupling vibration was finally verified by the corresponding experiment. They were consistent with each other, and the computational method was reliable and can be used to analyze the bridge. Based on the verified method, a lot of influence factors on vibration impact coefficient were analyzed. As a result, we can obtain a bridge with the smallest vibration impact coefficient. Finally, the remaining life of bridges was computed and evaluated based on the smallest vibration impact coefficient

Solving multiple-criteria R&D project selection problems with a data-driven evidential reasoning rule

In this paper, a likelihood based evidence acquisition approach is proposed to acquire evidence from experts'assessments as recorded in historical datasets. Then a data-driven evidential reasoning rule based model is introduced to R&D project selection process by combining multiple pieces of evidence with different weights and reliabilities. As a result, the total belief degrees and the overall performance can be generated for ranking and selecting projects. Finally, a case study on the R&D project selection for the National Science Foundation of China is conducted to show the effectiveness of the proposed model. The data-driven evidential reasoning rule based model for project evaluation and selection (1) utilizes experimental data to represent experts' assessments by using belief distributions over the set of final funding outcomes, and through this historic statistics it helps experts and applicants to understand the funding probability to a given assessment grade, (2) implies the mapping relationships between the evaluation grades and the final funding outcomes by using historical data, and (3) provides a way to make fair decisions by taking experts' reliabilities into account. In the data-driven evidential reasoning rule based model, experts play different roles in accordance with their reliabilities which are determined by their previous review track records, and the selection process is made interpretable and fairer. The newly proposed model reduces the time-consuming panel review work for both managers and experts, and significantly improves the efficiency and quality of project selection process. Although the model is demonstrated for project selection in the NSFC, it can be generalized to other funding agencies or industries.Comment: 20 pages, forthcoming in International Journal of Project Management (2019

Infrared Extinction Coefficients of Artificial Aerosol

The artificial aerosol is widely used in the modern battlefields to protect the potentialtargets and to conceal the movement of personnel and materials. In this paper, the double-bandinfrared extinction coefficients of the artificial aerosol have been calculated and compared withthe experimental data. The particulates were assumed to be small spheres and Mie's theory wasemployed with the grain size distribution function being lognormal. The numerical and theexperimental results show that the size distribution and the materials of the particles are decisiveof their infrared extinction capability

Minimally invasive surgery for uterine fibroids

The incidence of uterine fibroids, which comprise one of the most common female pelvic tumors, is almost 70–75% forwomen of reproductive age. With the development of surgical techniques and skills, more individuals prefer minimallyinvasive methods to treat uterine fibroids. There is no doubt that minimally invasive surgery has broad use for uterinefibroids. Since laparoscopic myomectomy was first performed in 1979, more methods have been used for uterine fibroids,such as laparoscopic hysterectomy, laparoscopic radiofrequency volumetric thermal ablation, and uterine artery embolization,and each has many variations. In this review, we compared these methods of minimally invasive surgery for uterinefibroids, analyzed their benefits and drawbacks, and discussed their future development

A reading model of young EFL learners regarding attention, cognitive-load and auditory-assistance

Audio-assisted reading (reading-while-listening) was commonly used as a pedagogical method in English (L2) learning. Numerous studies had reported its efficacy in English (L2) reading. Its efficacy in reading comprehension has been inconclusive due to the lack of studies on the relationship among attention, cognitive load and L2 reading comprehension, with the possibility that the synchronous auditory input lessens attention to the visual input. We present a study of 41 Mandarin-speaking 8-year-old children reading English texts in three modes in a between-participants design. Data of cognitive load, comprehension scores and attention were fitted to a formal mathematical model, which confirmed that influences on L2 reading comprehension could be captured by interactions between attention and cognitive load. Based on the findings, three implications regarding how to appropriately apply auditory-assistant tools to L2 reading were generated

2,4,5-Tris(pyridin-4-yl)-1H-imidazole monohydrate

In the crystal structure of the title compound, C18H13N5·H2O, adjacent mol­ecules are linked by O—H⋯N and N—H⋯O hydrogen bonds, generating a chain propagating along [001]