scholarly journals The catastrophe of the Niedów dam – the dam break causes, development and consequences

2020 ◽  
Author(s):  
Stanisław Kostecki ◽  
Robert Banasiak
Keyword(s):  
Numerical Approach ◽  
Dam Failure ◽  
Water Volume ◽  
Empirical Formulas ◽  
Dam Breach ◽  
Data Set ◽  
Local Conditions ◽  
The Earth ◽  
Rapid Release ◽  
Downstream Area

Abstract. Due to extreme rainfalls in 2010 in the Lusatian Neisse river catchment, a flood event with a return period of over 100 years took place leading to the failure of the Niedów dam. The earth type dam was washed away with a result of a rapid release of nearly 8.5 million m3 of water volume and flooding of the downstream area with substantial material losses. The paper analyses the conditions and causes of the dam’s failure, while special attention is given to the mechanism and dynamics of the compound breaching process. Several empirical formulas for the dam breach prediction are tested with regards to their usefulness in assessing breach dimensions and outflow peak discharge. The paper also describes a numerical approach to simulate the flood propagation downstream the dam with the use of a two-dimensional hydrodynamic model. Considering the specific local conditions and available data set, an iterative, reversed solution of the unsteady state problem is made. This approach enabled to deliver realistic flood propagation estimates, verification of the dam breach outflow, and several important answers on the dam failure consequences.

scholarly journals The Catastrophe of the Niedów Dam—The Causes of the Dam’s Breach, Its Development, and Consequences

Water ◽  
2021 ◽  
Vol 13 (22) ◽  
pp. 3254
Author(s):  
Stanisław Kostecki ◽  
Robert Banasiak
Keyword(s):  
Extreme Rainfall ◽  
Iterative Solution ◽  
Numerical Approach ◽  
Flood Event ◽  
Dam Breach ◽  
Data Set ◽  
Local Conditions ◽  
The Earth ◽  
Rapid Release ◽  
Downstream Area

Due to extreme rainfall in 2010 in the Lusatian Neisse River catchment area (in Poland), a flood event with a return period of over 100 years occurred, leading to the failure of the Niedów dam. The earth-type dam constructed for cooling the Turów power plant was washed away, resulting in the rapid release of nearly 8.5 million m3 of water and the flooding of the downstream area with substantial material losses. Here we analyze the conditions and causes of the dam’s failure, with special attention given to the mechanism and dynamics of the compound breaching process, in which the dam’s upstream slope reinforcement played a specific and remarkable role. The paper also describes a numerical approach for simulating a combined flood event downstream from the dam with the use of a two-dimensional hydrodynamic model (MIKE21). Considering the specific local conditions, i.e., wide floodplain, meandering character of the main channel, embankment overtopping, and available data set, an iterative solution of the unsteady state problem is proposed. This approach enables realistic flood propagation estimates to be delivered, the dam breach outflow to be reconstructed, and several important answers concerning the consequences of the dam’s failure to be provided. Finally, the paper presents the reconstruction of the dam that is more resilient to extreme hydrological conditions under changing climate.

scholarly journals The catastrophe of the Niedów dam – the causes of the dam's breach, its development and consequences

2021 ◽  
Author(s):  
Stanisław Kostecki ◽  
Robert Banasiak
Keyword(s):  
Extreme Rainfall ◽  
Iterative Solution ◽  
Numerical Approach ◽  
Flood Event ◽  
Dam Breach ◽  
Data Set ◽  
Local Conditions ◽  
The Earth ◽  
Rapid Release ◽  
Downstream Area

Abstract. Due to extreme rainfall in 2010 in the Lusatian Neisse River catchment area, a flood event with a return period of over 100 years occurred, leading to the failure of the Niedów dam. The earth-type dam was washed away, resulting in the rapid release of nearly 8.5 million m3 of water and the flooding of the downstream area with substantial material losses. The paper analyses the conditions and causes of the dam’s failure, with special attention given to the mechanism and dynamics of the compound breaching process, in which the dam’s upstreeam slope reinforcement played a remarkable role. The paper also describes a numerical approach for simulating a combined flood event along the Lusatian Neisse River with the use of a two-dimensional hydrodynamic model (MIKE21). The flood event occurred downstream from the dam. Considering the specific local conditions and available data set, an iterative solution of the unsteady state problem is proposed. This approach enables realistic flood propagation estimates to be delivered, the dam breach outflow to be reconstructed, and several important answers concerning the consequences of the dam’s failure to be provided.

scholarly journals Gene expression models for prediction of dam breach parameters

2013 ◽  
Vol 16 (3) ◽  
pp. 550-571 ◽  
Author(s):  
Ahmed M. A. Sattar
Keyword(s):  
Gene Expression ◽  
Gene Expression Programming ◽  
Dam Failure ◽  
Large Database ◽  
Dam Breach ◽  
Data Set ◽  
Error Analyses ◽  
Output Uncertainty ◽  
Uncertainty Analyses ◽  
Breach Parameters

Data from a large database of 140 dam failure cases are used with gene expression programming (GEP) to develop new empirical formulae of physical meaning for prediction of non-dimensional key dam breach parameters. The GEP models are trained on 75% of the data set and validated on the remaining 25%. Parametric and error analyses are conducted to confirm the robustness of the developed relations. Moreover, uncertainty analyses using the Monte Carlo technique is performed to check for the output uncertainty of key dam breach parameters and the contribution of various input parameters to the overall output uncertainty. It is found that uncertainties of 20 to 40% are calculated for the developed GEP models with reservoir shape factor and dam erodibility being main influential predictors.

scholarly journals An efficient technique for CT scan images classification of COVID-19

2020 ◽  
pp. 1-14
Author(s):  
Esraa Hassan ◽  
Noha A. Hikal ◽  
Samir Elmuogy
Keyword(s):  
Neural Network ◽  
Diagnostic Tool ◽  
Deep Neural Network ◽  
Data Augmentation ◽  
Performance Metrics ◽  
Classification Model ◽  
Data Set ◽  
Training Models ◽  
The Earth ◽  
Diagnostic Time

Nowadays, Coronavirus (COVID-19) considered one of the most critical pandemics in the earth. This is due its ability to spread rapidly between humans as well as animals. COVID_19 expected to outbreak around the world, around 70 % of the earth population might infected with COVID-19 in the incoming years. Therefore, an accurate and efficient diagnostic tool is highly required, which the main objective of our study. Manual classification was mainly used to detect different diseases, but it took too much time in addition to the probability of human errors. Automatic image classification reduces doctors diagnostic time, which could save human’s life. We propose an automatic classification architecture based on deep neural network called Worried Deep Neural Network (WDNN) model with transfer learning. Comparative analysis reveals that the proposed WDNN model outperforms by using three pre-training models: InceptionV3, ResNet50, and VGG19 in terms of various performance metrics. Due to the shortage of COVID-19 data set, data augmentation was used to increase the number of images in the positive class, then normalization used to make all images have the same size. Experimentation is done on COVID-19 dataset collected from different cases with total 2623 where (1573 training,524 validation,524 test). Our proposed model achieved 99,046, 98,684, 99,119, 98,90 In terms of Accuracy, precision, Recall, F-score, respectively. The results are compared with both the traditional machine learning methods and those using Convolutional Neural Networks (CNNs). The results demonstrate the ability of our classification model to use as an alternative of the current diagnostic tool.

scholarly journals Normalized nonzero-lag crosscorrelation elastic full-waveform inversion

Geophysics ◽  
2019 ◽  
Vol 84 (1) ◽  
pp. R1-R10 ◽  
Author(s):  
Zhendong Zhang ◽  
Tariq Alkhalifah ◽  
Zedong Wu ◽  
Yike Liu ◽  
Bin He ◽  
...  
Keyword(s):  
Field Data ◽  
Extreme Values ◽  
Time Lag ◽  
Waveform Inversion ◽  
Optimal Time ◽  
Full Waveform Inversion ◽  
Data Set ◽  
Velocity Models ◽  
Full Waveform ◽  
The Earth

Full-waveform inversion (FWI) is an attractive technique due to its ability to build high-resolution velocity models. Conventional amplitude-matching FWI approaches remain challenging because the simplified computational physics used does not fully represent all wave phenomena in the earth. Because the earth is attenuating, a sample-by-sample fitting of the amplitude may not be feasible in practice. We have developed a normalized nonzero-lag crosscorrelataion-based elastic FWI algorithm to maximize the similarity of the calculated and observed data. We use the first-order elastic-wave equation to simulate the propagation of seismic waves in the earth. Our proposed objective function emphasizes the matching of the phases of the events in the calculated and observed data, and thus, it is more immune to inaccuracies in the initial model and the difference between the true and modeled physics. The normalization term can compensate the energy loss in the far offsets because of geometric spreading and avoid a bias in estimation toward extreme values in the observed data. We develop a polynomial-type weighting function and evaluate an approach to determine the optimal time lag. We use a synthetic elastic Marmousi model and the BigSky field data set to verify the effectiveness of the proposed method. To suppress the short-wavelength artifacts in the estimated S-wave velocity and noise in the field data, we apply a Laplacian regularization and a total variation constraint on the synthetic and field data examples, respectively.

scholarly journals The particle and magnetic environments surrounding close-in exoplanets

2015 ◽  
Vol 11 (S320) ◽  
pp. 397-402
Author(s):  
A. A. Vidotto ◽  
R. Fares ◽  
M. Jardine ◽  
C. Moutou ◽  
J.-F. Donati
Keyword(s):  
Magnetic Fields ◽  
Radio Emission ◽  
Magnetic Field Intensity ◽  
Three Dimensional ◽  
Stellar Winds ◽  
Local Conditions ◽  
Hot Jupiters ◽  
The Earth ◽  
Weather Events ◽  
Host Stars

AbstractThe proper characterisation of stellar winds is essential for the study of propagation of eruptive events (flares, coronal mass ejections) and the study of space weather events on exoplanets. Here, we quantitatively investigate the nature of the stellar winds surrounding the hot Jupiters HD46375b, HD73256b, HD102195b, HD130322b, HD179949b. We simulate the three-dimensional winds of their host stars, in which we directly incorporate their observed surface magnetic fields. With that, we derive the wind properties at the position of the hot-Jupiters’ orbits (temperature, velocity, magnetic field intensity and pressure). We show that the exoplanets studied here are immersed in a local stellar wind that is much denser than the local conditions encountered around the solar system planets (e.g., 5 orders of magnitude denser than the conditions experienced by the Earth). The environment surrounding these exoplanets also differs in terms of dynamics (slower stellar winds, but higher Keplerian velocities) and ambient magnetic fields (2 to 3 orders of magnitude larger than the interplanetary medium surrounding the Earth). The characterisation of the host star's wind is also crucial for the study of how the wind interacts with exoplanets. For example, we compute the exoplanetary radio emission that is released in the wind-exoplanet interaction. For the hot-Jupiters studied here, we find radio fluxes ranging from 0.02 to 0.13 mJy. These fluxes could become orders of magnitude higher when stellar eruptions impact exoplanets, increasing the potential of detecting exoplanetary radio emission.

Monitoring the Ocean Heat Content and the Earth Energy imbalance from space altimetry and space gravimetry: the MOHeaCAN product

2021 ◽  
Author(s):  
Marti Florence ◽  
Ablain Michaël ◽  
Fraudeau Robin ◽  
Jugier Rémi ◽  
Meyssignac Benoît ◽  
...  
Keyword(s):  
Time Scales ◽  
Radiant Energy ◽  
Heat Content ◽  
Ocean Heat Content ◽  
Global Ocean ◽  
Argo Data ◽  
Data Set ◽  
Energy Imbalance ◽  
Temporal Sampling ◽  
The Earth

<p>The Earth Energy Imbalance (EEI) is a key indicator to understand climate change. However, measuring this indicator is challenging since it is a globally integrated variable whose variations are small, of the order of several tenth of W.m<sup>-2</sup>, compared to the amount of energy entering and leaving the climate system of ~340 W.m<sup>-2</sup>. Recent studies suggest that the EEI response to anthropogenic GHG and aerosols emissions is 0.5-1 W.m<sup>-2</sup>. It implies that an accuracy of <0.3 W.m<sup>-2</sup> at decadal time scales is necessary to evaluate the long term mean EEI associated with anthropogenic forcing. Ideally an accuracy of <0.1 W.m<sup>-2</sup> at decadal time scales is desirable if we want to monitor future changes in EEI.</p><p>In the frame of the MOHeaCAN project supported by ESA, the EEI indicator is deduced from the global change in Ocean Heat Content (OHC) which is a very good proxy of the EEI since the ocean stores 93% of the excess of heat  gained by the Earth in response to EEI. The OHC is estimated from space altimetry and gravimetry missions (GRACE). This “Altimetry-Gravimetry'' approach is promising because it provides consistent spatial and temporal sampling of the ocean, it samples nearly the entire global ocean, except for polar regions, and it provides estimates of the OHC over the ocean’s entire depth. Consequently, it complements the OHC estimation from the ARGO network. </p><p>The MOHeaCAN product contains monthly time series (between August 2002 and June 2017) of several variables, the main ones being the regional OHC (3°x3° spatial resolution grids), the global OHC and the EEI indicator. Uncertainties are provided for variables at global scale, by propagating errors from sea level measurements (altimetry) and ocean mass content (gravimetry). In order to calculate OHC at regional and global scales, a new estimate of the expansion efficiency of heat at global and regional scales have been performed based on the global ARGO network. </p><p>A scientific validation of the MOHeaCAN product has also been carried out performing thorough comparisons against independent estimates based on ARGO data and on the Clouds and the Earth’s Radiant energy System (CERES) measurements at the top of the atmosphere. The mean EEI derived from MOHeaCAN product is 0.84 W.m<sup>-2</sup> over the whole period within an uncertainty of ±0.12 W.m<sup>-2</sup> (68% confidence level - 0.20 W.m<sup>-2</sup> at the 90% CL). This figure is in agreement (within error bars at the 90% CL) with other EEI indicators based on ARGO data (e.g. OHC-OMI from CMEMS) although the best estimate is slightly higher. Differences from annual to inter-annual scales have also been observed with ARGO and CERES data. Investigations have been conducted to improve our understanding of the benefits and limitations of each data set to measure EEI at different time scales.</p><p><strong>The MOHeaCAN product from “altimetry-gravimetry” is now available</strong> and can be downloaded at https://doi.org/10.24400/527896/a01-2020.003. Feedback from interested users on this product are welcome.</p>

scholarly journals Risk Analysis of Earth-Rock Dam Breach Based on Dynamic Bayesian Network

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2305 ◽  
Author(s):  
Li ◽  
Wang ◽  
Ge ◽  
Wei ◽  
Li
Keyword(s):  
Risk Analysis ◽  
Bayesian Network ◽  
Dynamic Bayesian Network ◽  
Time Factors ◽  
Extended Model ◽  
Bayesian Network Model ◽  
Dam Breach ◽  
The Earth ◽  
Operation Period ◽  
Static Risk

Despite the fact that the Bayesian network has great advantages in logical reasoning and calculation compared with the other traditional risk analysis methods, there are still obvious shortcomings in the study of dynamic risk. The risk factors of the earth-rock dam breach are complex, which vary with time during the operation period. Static risk analysis, limited to a specific period of time, cannot meet the needs of comprehensive assessment and early warning. By introducing time factors, a dynamic Bayesian network model was established to study the dynamic characteristics of dam-breach probability. Combined with the calculation of the conditional probability of nodes based on the Leaky Noisy-Or gate extended model, the reasoning results of Bayesian networks were modified by updating the data of different time nodes. Taking an earth-rock dam as an example, the results show that it has less possibility to breach and keep stable along the time axis. Moreover, the factors with vulnerability and instability were found effective, which could provide guidance for dam risk management.

scholarly journals Heights of SuperDARN F region echoes estimated from the analysis of HF radio wave propagation

2007 ◽  
Vol 25 (9) ◽  
pp. 1987-1994 ◽  
Author(s):  
A. V. Koustov ◽  
D. André ◽  
E. Turunen ◽  
T. Raito ◽  
S. E. Milan
Keyword(s):  
Electron Density ◽  
Hf Radar ◽  
Field Of View ◽  
Data Set ◽  
Density Distributions ◽  
F Region ◽  
The Earth ◽  
Earth Magnetic Field ◽  
Field Lines ◽  
Radar Wave

Abstract. Tomographic estimates of the electron density altitudinal and latitudinal distribution within the Hankasalmi HF radar field of view are used to predict the expected heights of F region coherent echoes by ray tracing and finding ranges of radar wave orthogonality with the Earth magnetic field lines. The predicted ranges of echoes are compared with radar observations concurrent with the tomographic measurements. Only those events are considered for which the electron density distributions were smooth, the band of F region HF echoes existed at ranges 700–1500 km, and there was a reasonable match between the expected and measured slant ranges of echoes. For a data set comprising of 82 events, the typical height of echoes was found to be 275 km.

Predict Research for Loss of Life Due to Dam Breach for Guangxi Luocheng Kama Reservoir

2011 ◽  
Vol 243-249 ◽  
pp. 3877-3882
Author(s):  
Rong Yong Ma ◽  
Xiang Chen ◽  
Lei Lei Yang ◽  
Xiao Qing Zhang
Keyword(s):  
Calculation Result ◽  
Dam Break ◽  
Dam Failure ◽  
Suitable Model ◽  
Actual Situation ◽  
Dam Breach ◽  
Loss Of Life ◽  
At Home

In this paper，the basic situation of Guangxi luocheng Kama reservoir and the potential dangers are introduced firstly, and then，different models often used to estimate the loss of life in dam failure at home and abroad are introduced and analysed.Based on the above, a suitable model for national actual situation is chosen to predict the loss due to this reservoir dam breach，and the severity according to the calculation result of assuming Kama reservoir dam-break is assessed. Finally, the relevant departments’s measures of rescuing and evacuating downstream masses etc. at danger in 2009 are proved to be correct，necessary and timely.

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