scholarly journals Levee breach-induced compound flood modeling in Qianbujing Creek, Shanghai during Typhoon "Fitow"

2021 ◽  
Author(s):  
Yuhan Yang ◽  
Jie Yin ◽  
Weiguo Zhang ◽  
Yan Zhang ◽  
Yi Lu ◽  
...  
Keyword(s):  
Spatial Patterns ◽  
Heavy Rainfall ◽  
Critical Time ◽  
Dynamic Nature ◽  
Levee Breach ◽  
Typical Event ◽  
Simulation Results ◽  
Compound Effect ◽  
Dike Failure ◽  
Inundation Model

Abstract. Levee breach-induced flooding occurs occasionally but always causes considerable losses. A serious flood event occurred due to the collapse of a 15-m-long levee section in Qianbujing Creek, Shanghai, China, during typhoon "Fitow" in Oct, 2013. Heavy rainfall associated with the typhoon intensified the flood severity (extent and depth). This study investigates the flood evolution to understand the dynamic nature of flooding and the compound effect using a well-established 2D hydro-inundation model (Floodmap) to reconstruct this typical event. Our simulation results provide a comprehensive view of the spatial patterns of the flood evolution. The worst-hit areas are predicted to be low-lying settlement and farmland. Temporal evaluations suggest that the most critical time for flooding prevention is in the early hours after dike failure. In low-elevation areas, temporary drainage measures and flood defenses are equally important. The validation of the model demonstrates the reliability of the approach.

scholarly journals Levee breach-induced compound flood modeling in Qianbujing Creek, Shanghai during Typhoon “Fitow”

2021 ◽  
Author(s):  
Yuhan Yang ◽  
Jie Yin ◽  
Weiguo Zhang ◽  
Yan Zhang ◽  
Yi Lu ◽  
...  
Keyword(s):  
Spatial Patterns ◽  
Heavy Rainfall ◽  
Critical Time ◽  
Dynamic Nature ◽  
Levee Breach ◽  
Typical Event ◽  
Simulation Results ◽  
Compound Effect ◽  
Dike Failure ◽  
Inundation Model

Levee breach-induced flooding occurs occasionally but always causes considerable losses. A serious flood event occurred due to the collapse of a 15-m-long levee section in Qianbujing Creek, Shanghai, China, during typhoon “Fitow” in Oct, 2013. Heavy rainfall associated with the typhoon intensified the flood extent. This study investigates the flood evolution to understand the dynamic nature of flooding and the compound effect using a well-established 2D hydro-inundation model (Floodmap) to reconstruct this typical event. Our simulation results provide a comprehensive view of the spatial patterns of the flood evolution. The worst-hit areas are predicted to be low-lying farmland. Temporal evaluations suggest that the most critical time for flooding prevention is in the early hours after dike failure. In low-elevation areas, temporary drainage measures and flood defenses are equally important. The validation of the model demonstrates the reliability of the approach.

scholarly journals Modeling of a compound flood induced by the levee breach at Qianbujing Creek, Shanghai, during Typhoon Fitow

2021 ◽  
Vol 21 (11) ◽  
pp. 3563-3572
Author(s):  
Yuhan Yang ◽  
Jie Yin ◽  
Weiguo Zhang ◽  
Yan Zhang ◽  
Yi Lu ◽  
...  
Keyword(s):  
Heavy Rainfall ◽  
Critical Time ◽  
Flood Inundation ◽  
Dynamic Nature ◽  
Levee Breach ◽  
Typical Event ◽  
Simulation Results ◽  
Compound Effect ◽  
Dike Failure ◽  
Inundation Model

Abstract. Levee-breach-induced flooding occurs occasionally but always causes considerable losses. A serious flood event occurred due to the collapse of a 15 m long levee section in Qianbujing Creek, Shanghai, China, during Typhoon Fitow in October 2013. Heavy rainfall associated with the typhoon intensified the flood severity (extent and depth). This study investigates the flood evolution to understand the dynamic nature of flooding and the compound effect using a well-established 2D hydro-inundation model (FloodMap) to reconstruct this typical event. This model coupled urban hydrological processes with flood inundation for high-resolution flood modeling, which has been applied in a number of different environments, and FloodMap is now the mainstream numerical simulation model used for flood scenarios. Our simulation results provide a comprehensive view of the spatial patterns of the flood evolution. The worst-hit areas are predicted to be low-lying settlements and farmland. Temporal evaluations suggest that the most critical time for flooding prevention is in the early 1–3 h after dike failure. In low-elevation areas, temporary drainage measures and flood defenses are equally important. The validation of the model demonstrates the reliability of the approach.

scholarly journals Clustering of Maxima: Spatial Dependencies among Heavy Rainfall in France

2013 ◽  
Vol 26 (20) ◽  
pp. 7929-7937 ◽  
Author(s):  
Elsa Bernard ◽  
Philippe Naveau ◽  
Mathieu Vrac ◽  
Olivier Mestre
Keyword(s):  
Spatial Patterns ◽  
Extreme Value Theory ◽  
Heavy Rainfall ◽  
Spatial Clustering ◽  
Relevant Information ◽  
Value Theory ◽  
Research Field ◽  
Multivariate Extreme Value Theory ◽  
Spatial Dependencies ◽  
The Mean

Abstract One of the main objectives of statistical climatology is to extract relevant information hidden in complex spatial–temporal climatological datasets. To identify spatial patterns, most well-known statistical techniques are based on the concept of intra- and intercluster variances (like the k-means algorithm or EOFs). As analyzing quantitative extremes like heavy rainfall has become more and more prevalent for climatologists and hydrologists during these last decades, finding spatial patterns with methods based on deviations from the mean (i.e., variances) may not be the most appropriate strategy in this context of studying such extremes. For practitioners, simple and fast clustering tools tailored for extremes have been lacking. A possible avenue to bridging this methodological gap resides in taking advantage of multivariate extreme value theory, a well-developed research field in probability, and to adapt it to the context of spatial clustering. In this paper, a novel algorithm based on this plan is proposed and studied. The approach is compared and discussed with respect to the classical k-means algorithm throughout the analysis of weekly maxima of hourly precipitation recorded in France (fall season, 92 stations, 1993–2011).

PID Control Strategy of Vehicle Active Suspension Based on Considering Time-Delay and Stability

2013 ◽  
Vol 706-708 ◽  
pp. 901-906
Author(s):  
Guang Hui Yan ◽  
Shao Hua Wang ◽  
Zhi Wei Guan ◽  
Chen Fu Liu
Keyword(s):  
Time Delay ◽  
Pid Control ◽  
Stability Criterion ◽  
Control Method ◽  
Critical Time ◽  
Active Suspension ◽  
Vertical Acceleration ◽  
Hurwitz Stability ◽  
Critical Instability ◽  
Simulation Results

The stability conditions of 1/4 vehicle active suspension with time-delay were deduced by the theory of Routh-Hurwitz stability criterion and the critical instability time-delay was discussed and calculated. Compared with PID control method of without time-delay the simulation results show that when the critical time-delay is 0.153s, the amplitude range and its root mean square value of spring load quality vertical acceleration were increased 1.2 times or so and the system was being on the critical stability. The calculation and simulation results proved that the theory of Routh-Hurwitz stability criterion laid a foundation for the design and instability mechanism of active suspension.

Wind Energy Resources Prediction Based on EOF Method and RBF Neural Network

2013 ◽  
Vol 281 ◽  
pp. 550-553
Author(s):  
Xiao Cao ◽  
Zhi Bao Chen ◽  
Hai Zhou ◽  
Jie Ding
Keyword(s):  
Neural Network ◽  
Spatial Patterns ◽  
Rbf Neural Network ◽  
Energy Resources ◽  
Orthogonal Function ◽  
Time Coefficient ◽  
Prediction Time ◽  
Simulation Results ◽  
Wind Energy Resources ◽  
Prediction Approach

In this paper, research starts from the data captured from several wind measuring stations. Firstly, the main spatial Patterns are extracted by EOF (empirical orthogonal function) method, and then the time coefficient series corresponding to principal spatial patterns are processed and predicted by RBF (radial basis function) neural network. Furthermore, according to the EOF decomposition method, inversely the new prediction time coefficient series are used to calculate the wind speed values in the future. Finally, the validity and advantages of this prediction approach are tested by the simulation results.

scholarly journals Co-Evolution of Predator-Prey Ecosystems by Reinforcement Learning Agents

Entropy ◽  
2021 ◽  
Vol 23 (4) ◽  
pp. 461
Author(s):  
Jeongho Park ◽  
Juwon Lee ◽  
Taehwan Kim ◽  
Inkyung Ahn ◽  
Jooyoung Park
Keyword(s):  
Reinforcement Learning ◽  
Expected Returns ◽  
Dynamic Nature ◽  
Predator Prey ◽  
Learning Agents ◽  
Complex Interactions ◽  
Multi Agent ◽  
Simulation Results ◽  
Multiple Species ◽  
And Robotics

The problem of finding adequate population models in ecology is important for understanding essential aspects of their dynamic nature. Since analyzing and accurately predicting the intelligent adaptation of multiple species is difficult due to their complex interactions, the study of population dynamics still remains a challenging task in computational biology. In this paper, we use a modern deep reinforcement learning (RL) approach to explore a new avenue for understanding predator-prey ecosystems. Recently, reinforcement learning methods have achieved impressive results in areas, such as games and robotics. RL agents generally focus on building strategies for taking actions in an environment in order to maximize their expected returns. Here we frame the co-evolution of predators and preys in an ecosystem as allowing agents to learn and evolve toward better ones in a manner appropriate for multi-agent reinforcement learning. Recent significant advancements in reinforcement learning allow for new perspectives on these types of ecological issues. Our simulation results show that throughout the scenarios with RL agents, predators can achieve a reasonable level of sustainability, along with their preys.

scholarly journals Analysis of Slope Stability and Disaster Law under Heavy Rainfall

Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Pengfei Guo ◽  
Yadi Yuan ◽  
Yanyan Peng ◽  
Haijiag Zhang ◽  
Yongxu Zhao
Keyword(s):  
Numerical Simulation ◽  
Slope Stability ◽  
Physical Model ◽  
Model Experiment ◽  
Heavy Rainfall ◽  
Transportation Network ◽  
Stress Raiser ◽  
Physical Model Experiment ◽  
Analysis Laboratory ◽  
Simulation Results

Based on this, the slope stability and disaster law under the condition of heavy rainfall are studied. With the slope of Shangge Village as the background, the slope stability under the condition of heavy rainfall is deeply studied through theoretical analysis, laboratory physical model experiment, and numerical simulation. Results showed that due to the heavy rainfall within 2 h, the deformation of the slope is not obvious in the rain 2 h~7 h period, first of all in the position of slope toe of slope stress raiser; As the rainfall continued, the infiltration of rainwater led to weakening of the rock mass strength, and the cracks in the slope fracture zone further expanded and extended to the top of the slope. After 7 hours of rainfall, the slope formed a sliding surface. The physical model experiment and the numerical simulation results are in good agreement, which can provide the basis for slope reinforcement under heavy rainfall conditions and have important scientific significance and social value for the reasonable site selection of housing construction, transportation network, and disaster prevention and mitigation in coastal areas.

Impact of traffic lights on car accidents at intersections

2018 ◽  
Vol 29 (12) ◽  
pp. 1850121
Author(s):  
R. Marzoug ◽  
N. Lakouari ◽  
O. Oubram ◽  
H. Ez-Zahraouy ◽  
A. Khallouk ◽  
...  
Keyword(s):  
Cellular Automata ◽  
Green Light ◽  
Critical Time ◽  
Injection Rate ◽  
Traffic Lights ◽  
High Injection ◽  
Car Accidents ◽  
Simulation Results ◽  
The Impact ◽  
Injection Rates

Using the cellular automata Nagel–Schreckenberg (NaSch) model, we numerically study the impact of traffic lights on the probability of car accidents ([Formula: see text]) at the intersection of two roads. It is found that, the probability [Formula: see text] is more stable with variation of the green light ([Formula: see text]) when the symmetric lights are adopted. Moreover, simulation results show the existence of a critical time [Formula: see text], below which ([Formula: see text]) [Formula: see text] increases as the injection rate ([Formula: see text]) increases, however, above which ([Formula: see text]) the growing of [Formula: see text] has for effect the decrease of [Formula: see text]. Furthermore, the decrease of [Formula: see text] is almost always accompanied by a loss of the flux, especially with asymmetrical lights. To overcome this problem, we proposed a strategy that can greatly increase the flux and keep the probability [Formula: see text] as small as possible, especially for the low and high injection rates.

Event ambiguity fuels the effective spread of rumors

2015 ◽  
Vol 26 (03) ◽  
pp. 1550033 ◽  
Author(s):  
Jiuping Xu ◽  
Yi Zhang
Keyword(s):  
Random Network ◽  
Critical Time ◽  
Critical Event ◽  
Rumor Spreading ◽  
Spreading Model ◽  
Simulation Results ◽  
Regular Network ◽  
Regular Networks ◽  
The Impact ◽  
Effective Spread

In this paper, a new rumor spreading model which quantifies a specific rumor spreading feature is proposed. The specific feature focused on is the important role the event ambiguity plays in the rumor spreading process. To study the impact of this event ambiguity on the spread of rumors, the probability p(t) that an individual becomes a rumor spreader from an initially unaware person at time t is built. p(t) reflects the extent of event ambiguity, and a parameter c of p(t) is used to measure the speed at which the event moves from ambiguity to confirmation. At the same time, a principle is given to decide on the correct value for parameter c A rumor spreading model is then developed with this function added as a parameter to the traditional model. Then, several rumor spreading model simulations are conducted with different values for c on both regular networks and ER random networks. The simulation results indicate that a rumor spreads faster and more broadly when c is smaller. This shows that if events are ambiguous over a longer time, rumor spreading appears to be more effective, and is influenced more significantly by parameter c in a random network than in a regular network. We then determine parameters of this model through data fitting of the missing Malaysian plane, and apply this model to an analysis of the missing Malaysian plane. The simulation results demonstrate that the most critical time for authorities to control rumor spreading is in the early stages of a critical event.

Time-Delay Effects on Controlled Seismically Excited Linear and Nonlinear Structures

2016 ◽  
Vol 16 (07) ◽  
pp. 1550031 ◽  
Author(s):  
Helmi Temimi ◽  
Mohamed Ben-Romdhane ◽  
Sami El-Borgi ◽  
Young-Jin Cha
Keyword(s):  
Time Delay ◽  
Eigenvalue Problem ◽  
Seismic Response ◽  
Critical Time ◽  
Control Design ◽  
Nonlinear Structures ◽  
Stability Criteria ◽  
Delay Effects ◽  
Linear And Nonlinear ◽  
Simulation Results

The main purpose of this paper is to examine the influence of time delay associated with a semi-active variable viscous (SAVV) damper on the response of seismically excited linear and nonlinear structures. The maximum time delay is estimated on the basis of stability criteria, which consist of analyses of structural modal properties. Numerical computation of the critical time delay is performed by using dichotomic approach, which is based on multiple solving of the eigenvalue problem. Simulation results indicate that variable dampers can be effective in reducing the seismic response of structures, and that time-delay effects are important factors in control design of seismically excited structures. Furthermore, simulation results show degradation of performance whenever the actual delay exceeds the calculated critical time delay, which shows the accuracy and reliability of the proposed approach.

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