Summary
This article proposes an approach to resolve the dynamic fracture of brittle materials by incorporating eigenerosion into the material point method (MPM) framework. The eigenerosion approach ...links the crack propagation to energy conservation based on the variational theory of fracture mechanics. This idea closely resembles the conventional treatment for the phase‐field method. The major difference is that the effective energy release rate of each particle that controls the crack propagation is only calculated within its neighborhood domain for the eigenerosion approach. Because evaluation of the material's fracture behavior can be decoupled from the governing equations as a separate solution step, the eigenerosion scheme allows straightforward implementation into any standard MPM solver with minor modifications. In addition, a phantom‐node method is employed to handle the preexisting crack. With these settings, the proposed model can capture complex fracture behaviors. Several representative benchmark tests demonstrate the efficiency and validity of the proposed model.
► Performed strength and microstructure tests of geopolymer brick. ► Explain role of liquid alkaline activator on strength development. ► Explain role of heat temperature and duration on strength ...development. ► Analyze strength of the clay–fly ash geopolymer samples. ► Suggest a relationship between strength and heat energy.
This paper presents the role of influential factors on the strength development in a clay–fly ash geopolymer that a silty clay is used as fine aggregates and fly ash, FA is used as a pozzolanic material. A liquid alkaline activator, L is a mixture of sodium silicate solution (Na2SiO3) and sodium hydroxide solution (NaOH). The studied influential factors are Na2SiO3/NaOH ratio, L/FA ratio and heat conditions. The optimum ingredient for the clay–FA geopolymer is the Na2SiO3/NaOH ratio of 0.7 and the L/FA ratio of 0.6. The Na2SiO3/NaOH ratio required for the clay–FA geopolymer is less than that of the FA geopolymer because the clay has high cation absorption ability and then absorbs some of the input NaOH. For a given Na2SiO3/NaOH content, the strength increases with increasing the liquid alkaline activator. The excess input alkaline activator causes the precipitation at very early stage before the condensation process in geopolymerization and results in the cracks on the FA particles. The overheating (very high temperature) and excess heat duration cause the micro-cracks on the specimens. The relationship between the strength and heat energy is proposed to integrate the role of heat temperature and duration on the geopolymerization. The compressive strength increases with increasing heat energy up to a certain level. Beyond this level, the specimens shrink and crack due to the reduction in pore fluid, which results in the strength reduction. The relationship between strength and heat energy can be used as fundamental for further study on the strength development and the mix design method for the clay–FA geopolymer with different specimen dimensions, clay minerals, liquid alkaline activators, pozzolanic materials and clay:FA ratios.
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•Developed a method to assess risk of infrastructures using trapezoidal FAHP•Proposed a new questionnaire to determine trapezoidal fuzzy numbers in trapezoidal ...FAHP•Land-subsidence-induced risk in Shanghai is assessed using trapezoidal FAHP and AHP•The results were validated by the current prevention zone of land subsidence in Shanghai.
This study presents an improved trapezoidal fuzzy analytic hierarchy process (FAHP) to assess the risk of mega-city infrastructures related to land subsidence. The trapezoidal fuzzy numbers are used to express the relative importance between assessment factors. A new questionnaire is proposed in this study to collect judgements from consulting experts. Both the original AHP and the trapezoidal FAHP with the new questionnaire are applied to assess the risk of infrastructures in relation to land subsidence in Shanghai. The risks assessed using the trapezoidal FAHP at locations with significant infrastructures are higher than those assessed using the original AHP. This indicates that the trapezoidal FAHP method with the new questionnaire can be used to effectively capture the high risks for significant industrial infrastructures related to land subsidence. Moreover, the obtained results were compared with the current land subsidence prevention zone, and it was observed that the existing land subsidence prevention zone in government management guidelines does not sufficiently consider the vulnerability of significant infrastructures.
The stratigraphic uncertainty and rotated anisotropy of soil properties exist widely in nature. Recent studies have shown that the slope stability was significantly influenced by these two ...uncertainties. However, there is no proper method for simulating these two uncertainties at the same time, and the influence of the two uncertainties has not been considered in previous unsaturated soil slope stability analysis. This paper aims to propose a coupled method for characterizing the stratigraphic uncertainty and rotated anisotropy of soil properties, and investigate the unsaturated soil slope stability considering the two uncertainties. Through a slope case, the proposed method for characterizing the two uncertainties is examined. The effect of rotational angle on the slope stability and groundwater table is studied. In addition, four different uncertainty considerations are chosen to compare their influence on the slope stability and groundwater table. The results show that the proposed method can well characterize the two uncertainties at the same time. The rotational anisotropy of soil properties has a substantial impact on the slope stability and groundwater table. The rotational angles corresponding to the maximum and minimum reliability index of slope depend on the uncertainty considerations in the slope stability analysis. The slope reliability index only considering stratigraphic uncertainty is the highest, and the slope reliability index considering stratigraphic uncertainty and rotated anisotropy of soil properties is the lowest.
•Evaluation of Fly Ash (FA) based geopolymer stabilized lateritic soil/GBFS blend.•Role of L, NaOH/Na2SiO3, GBFS content, and curing time were investigated.•Microstructural development was examined ...via XRD and SEM analyses.•UCS of FA geopolymer stabilized blends was compared with road authorities requirements.
Granulated Blast Furnace Slag (GBFS) was used as a replacement material in marginal lateritic soil (LS) while class C Fly Ash (FA) was used as a precursor for the geopolymerization process to develop a low-carbon pavement base material at ambient temperature. Unconfined Compression Strength (UCS) tests were performed to investigate the strength development of geopolymer stabilized LS/GBFS blends. Scanning Electron Microscopy and X-ray Diffraction analysis were undertaken to examine the role of the various influencing factors on UCS development. The influencing factors studied included GBFS content, Na2SiO3:NaOH ratio (NS:NH) and curing time. The 7-day soaked UCS of FA geopolymer stabilized LS/GBFS blends at various NS:NH ratios tested was found to satisfy the specifications of the Thailand national road authorities. The GBFS replacement was found to be insignificant for the improvement of the UCS of FA geopolymer stabilized LS/GBFS blends at low NS:NH ratio of 50:50. Microstructural analysis indicated the coexistence of Calcium Silicate Hydrate (CSH) and Sodium Alumino Silicate Hydrate products in FA geopolymer stabilized LS/GBFS blends. This research enables GBFS, which is traditionally considered as a waste material, to be used as a replacement and partially reactive material in FA geopolymer pavement applications.
Water quality assessment is critical to better recognise the importance of water in human society. In this study, a new framework to predict long-term water quality is proposed by using ...Bayesian-optimised machine learning methods and key pollution indicators collected from monitoring stations in the Pearl River Estuary, Guangdong, China. The optimised stacked generalisation (SG-op) model achieved the best performance with the highest accuracy (0.992) and Kappa coefficient (0.987). Feature importance of the prediction model was consistent with key pollution indicators. The Spearman rank correlation coefficient was used to determine the significance level of the variation trends of different pollution indicators. The results show that the total phosphorus (TOP), dissolved oxygen (DO), chemical oxygen demand (COD), and petroleum (PET) among the key pollution indicators were on an upward trend in the study area. This framework can be applied to efficiently predict future water quality and to provide technical support for emergency pollution control.
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•Developed a framework to predict water quality levels and reveal pollution trends.•Model integrates machine learning methods with Bayesian optimisation algorithm.•Consistency between feature importance and key pollution indicators was analysed.•Provided technical support for emergency pollution control and water quality management.
•Regional flood risk level was evaluated using both AHP and I-AHP methods.•Flood risk level of metro system was evaluated based on flood risks within 500 m range from metro lines.•Comparative results ...between AHP and I-AHP assessment results were analyzed.•Results were validated using the observed flood hazards on May 10, 2016, in Guangzhou, China.
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Metro system is a vital component of mass transportation infrastructure, providing crucial social and economic service in urban area. Flood events may cause functional disruptions to metro systems; therefore, a better understanding of their vulnerability would enhance their resilience. A comparative study of flood risk in metro systems is presented using the analytic hierarchy process (AHP) and the interval AHP (I-AHP) methods. The flood risk in the Guangzhou metro system is evaluated according to recorded data. Evaluated results are validated using the flood event occurred in Guangzhou on May 10, 2016 (hereinafter called “May 10th event”), which inundated several metro stations. The flood risk is assessed within a range of 500 m around the metro line. The results show that >50% of metro lines are highly exposed to flood risk, indicating that the Guangzhou metro system is vulnerable to flood events. Comparisons between results from AHP and I-AHP show that the latter yields a wider range of high flooding risk than the former.
•Current research on regional flood risk assessment methods is summarized.•An approach for evaluating flood risk for metro systems in mega-cities is proposed.•Two characteristics of the approach are: ...(i) regional to local, (ii) qualification to quantification.•Perspectives for risk prevention procedure, which uses an iterative cycle, are proposed.
This paper presents an overview on the risk assessment approaches for inundation of metro systems based on regional flood risk assessment methods. Detailed summarization is conducted based on four types of regional flood risk assessment methods, including (i) statistical methods, (ii) multi-criteria analysis, (iii) analysis using geographical information system (GIS) and/or remote sensing (RS), and (iv) scenario-based analysis. After reviewing of the existing methods in literatures, a perspective approach of evaluating inundation risk for metro systems is proposed. The proposed approach has the following two characteristics: (i) from regional to local, and (ii) from qualification to quantification. The Guangzhou Metro System is used to demonstrate the application of the perspective methods for flood risk assessment of metro system. The risk prevention procedure uses an iterative cycle that includes risk assessment, precaution, prediction, and technical countermeasures. The integration of GIS, global position system (GPS) and build information modelling (BIM) for development of early warning and risk management systems is recommended to manage the risks of inundation of metro system.
This paper presents a new trial to reproduce soil stress–strain behaviour by adapting a long short-term memory (LSTM) deep learning method. LSTM is an approach that employs time sequence data to ...predict future occurrences, and it can be used to consider the stress history of soil behaviour. The proposed LSTM method includes the following three steps: data preparation, architecture determination, and optimisation. The capacity of the adapted LSTM method is compared with that of feedforward and feedback neural networks using a new numerical benchmark dataset. The performance of the proposed LSTM method is verified through a dataset collected from laboratory tests. The results indicate that the LSTM deep-learning method outperforms the feed forward and feedback neural networks based on both accuracy and the convergence rate when reproducing the soil’s stress–strain behaviour. One new phenomenon referred to as “bias at low stress levels”, which was not noticed before, is first discovered and discussed for all neural network-based methods.
•We proposed an approach to model the stress–strain behaviour using LSTM deep learning method.•The superiority of LSTM method was testified based on the designed numerical experiments.•A laboratory test on saturated sand was studied to demonstrate capability of LSTM model.•A common phenomenon called the bias at low stress levels for NN method was discussed.
•Approach for eutrophication levels evaluation is developed;•Developed approach merges TOPSIS and MCS method;•It can increase the reliability of evaluated result;•Evaluation of eutrophication level ...in Lake Erhai is performed;•Sensitivity of coefficient P in membership function is conducted.
This study presents an approach for eutrophication evaluation based on the technique for order preference by similarity to an ideal solution (TOPSIS) method and Monte Carlo simulation (MCS). The MCS is employed to produce a normally distributed dataset based on the observed data while the TOPSIS method and membership function are used to evaluate the level of eutrophication. Herein, a eutrophication problem in Lake Erhai is evaluated to check the performance of the proposed approach. The evaluation results were consistent with the real situation when the coefficient P in the membership function is equal to 1. Moreover, the developed approach is able to (i) deal with evaluation items with inherent fuzziness and uncertainties, (ii) improve the reliability of evaluation results via MCS, and (iii) raise the tolerance to errors in measured data. A global sensitivity analysis indicated that the potassium permanganate index (CODMn) and Secchi disc (SD) are the most sensitive factors in the developed approach. Finally, a range for the coefficient P value in the membership function was recommended.
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