Study on Prediction Method of Infrasound Waves for Concrete Structure Destruction in Underground Space

The water leakage in an underground space cannot easily be repaired owing to the characteristics of the underground space, which not only causes continuous inconvenience to the apartment residents but also facilitates condensation. Thus, the effects of different waterproofing methods in underground spaces on changes in temperature and humidity should be quantitatively studied to establish strong measures for the condensation issue. In this study, two types of specimens were produced separately by dividing the waterproofing materials applied to underground structures into exterior and interior waterproofing construction methods; thereafter, changes in the temperature and humidity inside the specimens were observed. The test results of the evaluation regarding condensation in underground structures indicated that when exterior waterproofing materials are applied, thermal insulation maintains a steady interior temperature and keeps the humidity at an appropriate level, thereby preventing the creation of an environment conducive to the occurrence of condensation.

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Evaluation and Prediction Method on Neutralization of Supplied Long-term Hydraulic Concrete Structure

International Journal of Geomate ◽

10.21660/2012.6.287 ◽

2012 ◽

Author(s):

Man-Kwon Choi

Keyword(s):

Concrete Structure ◽

Prediction Method ◽

Hydraulic Concrete

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Durability Prediction Method of Concrete Soil Based on Deep Belief Network

Advances in Civil Engineering ◽

10.1155/2022/4338306 ◽

2022 ◽

Vol 2022 ◽

pp. 1-7

Author(s):

Xiao Tian ◽

Niankun Zhu

Keyword(s):

Environmental Conditions ◽

Concrete Structure ◽

Prediction Accuracy ◽

Prediction Method ◽

Chloride Ions ◽

Deep Belief Network ◽

Concrete Durability ◽

Belief Network ◽

Structural Durability ◽

Durability Prediction

To truly reflect the durability characteristics of concrete subjected to multiple factors under complex environmental conditions, it is necessary to discuss the prediction of its durability. In response to the problem of durability prediction of traditional concrete structures, there is a low prediction accuracy, and the predicted time is long, and a concrete structural durability prediction method based on the deep belief network is proposed. The influencing factors of the concrete structural durability parameters are analyzed by two major categories of concrete material and external environmental conditions, and the transmission of chloride ions in the concrete structure is described. According to the disconnection of the steel bars, the durability of the concrete structure is started, and the determination is determined. The concrete structural antiflexural strength, using a deep belief network training concrete structural antiflexural strength judgment data, constructs a concrete structural durability predictive model and completes the durability prediction of the concrete structure based on the deep belief network. The proposed prediction method based on the deep belief network has a high prediction accuracy of 98% for the durability of concrete column structures. The simulation results show that the concrete structural durability’s prediction accuracy is high and the prediction time is short. The prediction of concrete durability discussed here has important guiding significance for the improvement of concrete durability test methods and the improvement of concrete durability evaluation standards in China.

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Designing our Underground Space

10.1061/9780784409183 ◽

2007 ◽

Keyword(s):

Underground Space

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Selection of a leading edge noise prediction method for PNoise

The Academic Society Journal ◽

10.32640/tasj.2018.4.214 ◽

2018 ◽

pp. 214-223

Author(s):

AM Faria ◽

MM Pimenta ◽

JY Saab Jr. ◽

S Rodriguez

Keyword(s):

Wind Turbine ◽

Turbine Blades ◽

Prediction Method ◽

Leading Edge ◽

Wind Farms ◽

Broadband Noise ◽

Turbulence Energy ◽

Noise Prediction ◽

Migration Routes ◽

Turbulent Inflow

Wind energy expansion is worldwide followed by various limitations, i.e. land availability, the NIMBY (not in my backyard) attitude, interference on birds migration routes and so on. This undeniable expansion is pushing wind farms near populated areas throughout the years, where noise regulation is more stringent. That demands solutions for the wind turbine (WT) industry, in order to produce quieter WT units. Focusing in the subject of airfoil noise prediction, it can help the assessment and design of quieter wind turbine blades. Considering the airfoil noise as a composition of many sound sources, and in light of the fact that the main noise production mechanisms are the airfoil self-noise and the turbulent inflow (TI) noise, this work is concentrated on the latter. TI noise is classified as an interaction noise, produced by the turbulent inflow, incident on the airfoil leading edge (LE). Theoretical and semi-empirical methods for the TI noise prediction are already available, based on Amiet’s broadband noise theory. Analysis of many TI noise prediction methods is provided by this work in the literature review, as well as the turbulence energy spectrum modeling. This is then followed by comparison of the most reliable TI noise methodologies, qualitatively and quantitatively, with the error estimation, compared to the Ffowcs Williams-Hawkings solution for computational aeroacoustics. Basis for integration of airfoil inflow noise prediction into a wind turbine noise prediction code is the final goal of this work.

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