Application of the Improved POA-RF Model in Predicting the Strength and Energy Absorption Property of a Novel Aseismic Rubber-Concrete Material

Mei, Xiancheng; Cui, Zhen; Sheng, Qian; Zhou, Jian; Li, Chuanqi

doi:10.3390/ma16031286

Cited by 23 publications

(10 citation statements)

References 62 publications

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“…The error functions were employed to evaluate the fit of the isotherm to the experimental equilibrium data. In this study, the residual root mean square error ( RMSE —Equation (9)), the chi-square test (Equation (10)) and the linear regression were used [ 36 , 37 ]:

where n is the number of observations in the experimental isotherm, and q e,exp and q e,cal stand for experimental and calculated values, respectively. The better the curve fitting, the smaller the RMSE and χ 2 values.…”

Section: Methodsmentioning

confidence: 99%

Municipal Sewage Sludge as a Source for Obtaining Efficient Biosorbents: Analysis of Pyrolysis Products and Adsorption Tests

et al. 2023

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In the 21st century, the development of industry and population growth have significantly increased the amount of sewage sludge produced. It is a by-product of wastewater treatment, which requires appropriate management due to biological and chemical hazards, as well as several legal regulations. The pyrolysis of sewage sludge to biochar can become an effective way to neutralise and use waste. Tests were carried out to determine the effect of pyrolysis conditions, such as time and temperature, on the properties and composition of the products obtained and the sorption capacity of the generated biochar. Fourier transform infrared analysis (FTIR) showed that the main components of the produced gas phase were CO2, CO, CH4 and to a lesser extent volatile organic compounds. In tar, compounds of mainly anthropogenic origin were identified using gas chromatography mass spectrometry (GC-MS). The efficiency of obtaining biochars ranged from 44% to 50%. An increase in the pyrolysis temperature resulted in a decreased amount of biochar produced while improving its physicochemical properties. The biochar obtained at high temperatures showed the good adsorption capacity of Cu2+ (26 mg·g−1) and Zn2+ (21 mg·g−1) cations, which indicates that it can compete with similar sorbents. Adsorption of Cu2+ and Zn2+ proceeded according to the pseudo-second-order kinetic model and the Langmuir isotherm model. The biosorbent obtained from sewage sludge can be successfully used for the separation of metal cations from water and technological wastewater or be the basis for producing modified and mixed carbon sorbents.

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Section: Methodsmentioning

confidence: 99%

Municipal Sewage Sludge as a Source for Obtaining Efficient Biosorbents: Analysis of Pyrolysis Products and Adsorption Tests

et al. 2023

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“…Wanhui Feng et al [32] investigated the dynamic fracture toughness of RC using the drop weight test, which showed that the fracture toughness of RC increased to 30% at the time of the increase in rubber content. In the rest of the studies, the RC also showed excellent thermal insulation [33] and energy absorption properties [20,34].…”

Section: Introductionmentioning

confidence: 93%

Rubberized Concrete: Effect of the Rubber Size and Content on Static and Dynamic Behavior

Du,

Yang,

Cao

et al. 2024

Buildings

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Rubberized concrete (RC) has received widespread attention due to its energy absorption and crack resistance properties. However, due to its low compressive strength, it is not recommended for structural applications. The rubber size and content affect RC’s mechanical properties. This study investigated and formulated the behavior of RC with different particle sizes and contents under dynamic and static loading. Quasi-static compressive and dynamic tests were conducted on RC with varying content of rubber (0–30%) and rubber sizes (0.1–20 mm). It was found that the rubber particle size was 0.5mm and the rubber content was 2%. An equation was derived from the experimental data to forecast the impact of rubber size and content on compressive strength. Additionally, by combining the literature and this research’s data, a model was established based on neural networks to predict the strength of RC. SHPB tests were carried out to study the stress–strain curves under dynamic load. The peak stress, fragment analysis, and energy absorption of RC with varying content of rubber and rubber sizes at three different strain rates (100 s−1, 160 s−1, and 290 s−1) were investigated. Equations describing the relationship between dynamic increase factor (DIF), rubber material content, and strain rate on different particle sizes were obtained by fitting. The DIF increased as the content of the rubber increased. By analyzing energy absorption data, it was found that the optimal ratio for energy absorption was RC-0.5-30, RC-0.1-30, and RC-10-30 at strain rates of 100 s−1, 160 s−1, and 290 s−1. This study could be a good guideline for other researchers to easily select the content and size of the rubber in RC for their applications. It also has a positive significance in promoting the development of green building materials.

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“…The authors [73] proposed Pelican Optimization Algorithm (POA) that tries to imitate the behavior of pelicans during hunting. Some recent applications of COA in optimization problems are described in [109][110][111][112][113][114]. The positions of the pelican will be the variables of this problem of searching for the optimal value of the objective function.…”

Section: Pelican Optimization Algorithm (Poa)mentioning

confidence: 99%

Load Margin Assessment of Power Systems Using Physics-Informed Neural Network with Optimized Parameters

Bento

2024

Energies

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Challenges in the operation of power systems arise from several factors such as the interconnection of large power systems, integration of new energy sources and the increase in electrical energy demand. These challenges have required the development of fast and reliable tools for evaluating the operation of power systems. The load margin (LM) is an important index in evaluating the stability of power systems, but traditional methods for determining the LM consist of solving a set of differential-algebraic equations whose information may not always be available. Data-Driven techniques such as Artificial Neural Networks were developed to calculate and monitor LM, but may present unsatisfactory performance due to difficulty in generalization. Therefore, this article proposes a design method for Physics-Informed Neural Networks whose parameters will be tuned by bio-inspired algorithms in an optimization model. Physical knowledge regarding the operation of power systems is incorporated into the PINN training process. Case studies were carried out and discussed in the IEEE 68-bus system considering the N-1 criterion for disconnection of transmission lines. The PINN load margin results obtained by the proposed method showed lower error values for the Root Mean Square Error (RMSE), Mean Square Error (MSE) and Mean Absolute Percentage Error (MAPE) indices than the traditional training Levenberg-Marquard method.

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Application of the Improved POA-RF Model in Predicting the Strength and Energy Absorption Property of a Novel Aseismic Rubber-Concrete Material

Cited by 23 publications

References 62 publications

Municipal Sewage Sludge as a Source for Obtaining Efficient Biosorbents: Analysis of Pyrolysis Products and Adsorption Tests

Municipal Sewage Sludge as a Source for Obtaining Efficient Biosorbents: Analysis of Pyrolysis Products and Adsorption Tests

Rubberized Concrete: Effect of the Rubber Size and Content on Static and Dynamic Behavior

Load Margin Assessment of Power Systems Using Physics-Informed Neural Network with Optimized Parameters

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