Combining Data-Driven Methods with Finite Element Analysis for Flood Early Warning Systems

Pyayt, A.L.; Shevchenko, D.; Kozionov, A.P.; Mokhov, I.I.; Lang, Bernhard; Krzhizhanovskaya, Valeria V.; Sloot, Peter M. A.

doi:10.1016/j.procs.2015.05.404

Cited by 11 publications

(4 citation statements)

References 14 publications

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“…Furthermore, if a public place has perfect anti-riot equipment and high monitoring coverage, the probability of social safety emergencies is low. Moreover, the pre-alarm system in public spaces can also avoid some emergencies [30], such as the emergency braking button of the elevator, door closing prompt of the subway, etc.…”

Section: Construction Equipmentmentioning

confidence: 99%

“…The impact of the urban environment on the safety of urban public space is mainly reflected in the climatic conditions, geographical location, drainage system, and whether there are instructions in dangerous areas. Urban climate disasters are mainly manifested in floods caused by heavy rainfall and storms, fires caused by high temperatures and drought, and climate disasters also easily lead to other urban safety accidents, such as flood and waterlogging meteorological disasters, which induce geological disasters such as water and soil loss [27,30]. The impact of an urban geographical location on the safety of urban public space is mainly reflected in earthquakes [31].…”

Section: Urban Environmentmentioning

confidence: 99%

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Safety Risk Assessment in Urban Public Space Using Structural Equation Modelling

Chen

Kassem

et al. 2022

Applied Sciences

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Urban public space is essential in improving population carrying capacity and economic efficiency. However, the characteristics of urban public space, such as complex structure, relatively close and large population mobility, make it prone to fire, stampedes and other safety accidents. This study aims to develop a systematic approach to identify the key factors that affect the safety risk of urban public spaces and assess the risk. Based on the literature review, 250 structured questionnaires were randomly distributed. Finally, 219 available questionnaires were collected. Based on the above data, a model of urban public space is built using SEM. The results show that construction equipment, road traffic, social governance, urban environment and behaviour significantly affect public space (from high to low). Specifically, regardless of the model or actual situation, we should pay attention to fire awareness and empirical prevention awareness. Based on previous studies, this study considers the influencing factors of urban public safety risks hierarchically and more practically and makes contributions to the field of urban safety. In addition, governments and developers can conduct valuable actual scenario analysis from this study.

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Section: Construction Equipmentmentioning

confidence: 99%

Section: Urban Environmentmentioning

confidence: 99%

Safety Risk Assessment in Urban Public Space Using Structural Equation Modelling

Chen

Kassem

et al. 2022

Applied Sciences

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“…Usually data-driven (model-free methods) and model-based (numerical or physical modelling) approaches are applied in order to detect failure development or flood embankment stability loss [Pyayt et al 2015]. Both these methods are used in the ISMOP project.…”

Section: Failure Detectionmentioning

confidence: 99%

Reducing Flood Risk using Computer System for Monitoring River Embankments

Chuchro

Franczyk

Bukowska-Belniak

et al. 2017

Ochrona Srodowiska I Zasobów Naturalnych

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In order to learn about the phenomena occurring in flood embankment under the influence of external factors, including the increasing water level in the river during floods, a Computer System for Monitoring River Embankment (ISMOP) was developed using an experimental flood embankment. The project was carried out by a consortium consisting of AGH University of Science and Technology departments (Computer Science, Hydrogeology and Engineering Geology, Geoinformatics and Applied Computer Science and two companies (NEOSENTIO and SWECO Hydroprojekt Kraków) in co-operation with the Czernichów Community Council.An experimental flood embankment was built with two parallel sections with a length of 150 m and a height of 4.5 m, connected by a meandering, creating a reservoir that can be filled with water. For the construction of the embankment, different types of soils were used in all the five sections. Inside the flood embankment 1300 sensors are placed, including sensors for temperature, pore pressure, vertical displacements, as well as inclinometers. Also fiber optic strands, capable of measuring the temperature of the flood embankment on the upstream side, are located inside the experimental embankment [ismop.pl].Together with the real experiments, numerical modelling using the Itasca Flac 2D 7.0 was performed in order to describe the impact of water pressing on the flood embankment and the impact of increasing and decreasing reservoir water level on the phenomena that occur within the embankment.The results of modelling compared with the real sensor data allowed the evaluation of the current and future state of the embankment. Based on the data measured by the sensors and data received during the numerical modelling, a group of algorithms that allowed detection of anomaly phenomena was developed.

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“…Numerical modelling and information about phenomena inside the embankment due to external factors and changes in the riverbed can be used to assess the state of a flood embankment (Pyayt et al 2015). The aim of the model-driven module is to perform a comparison between time series of measured parameters from sensors and numerical models.…”

Section: Model-driven Analysismentioning

confidence: 99%

A Big Data processing strategy for hybrid interpretation of flood embankment multisensor data

Chuchro

Franczyk

Dwornik³

et al. 2016

geol

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Abstract:The assessment of flood embankments is a key component of a country's comprehensive flood protection. Proper and early information on the possible instability of a flood embankment can make it possible to take preventative action. The assessment method proposed by the ISMOP project is based on a strategy of processing huge data sets (Big Data). The detection of flood embankment anomalies can take two analysis paths. The first involves the computation of numerical models and comparing them with real data measured on a flood embankment. This is the path of model-driven analysis. The second solution is data-driven, meaning time series are analysed in order to detect deviations from average values.Flood embankments are assessed based on the results of model-driven and data-driven analyses and information from preprocessing. An alarm is triggered if a critical value is exceeded in one or both paths of analysis.Tests on synthetic data demonstrate the high efficiency of the chosen methods for assessing the state of flood embankments.

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Combining Data-Driven Methods with Finite Element Analysis for Flood Early Warning Systems

Cited by 11 publications

References 14 publications

Safety Risk Assessment in Urban Public Space Using Structural Equation Modelling

Safety Risk Assessment in Urban Public Space Using Structural Equation Modelling

Reducing Flood Risk using Computer System for Monitoring River Embankments

A Big Data processing strategy for hybrid interpretation of flood embankment multisensor data

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