Application of a Bayesian hierarchical modeling for risk assessment of accidents at hydropower dams

Калинина, А. М.; Spada, Matteo; Burgherr, Peter

doi:10.1016/j.ssci.2018.08.006

Cited by 27 publications

(18 citation statements)

References 26 publications

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“…In total, 522 new accidents were added to the dam accident data set compared to the 569 already existing accidents (Kalinina et al, 2018a(Kalinina et al, , 2018b. One reason for this substantial increase in the number of records is related to the availability of new information sources (e.g., NPDP, 2016), which were not accessible during previous updates.…”

Section: Data Collection and Characterizationmentioning

confidence: 99%

“…This approach has been extensively discussed in the literature (Eckle & Burgherr, 2013;Gelman, Carlin, Stern, & Rubin, 2003) and has been successfully adopted in other fields (Coles & Powell, 1996). An application of this modeling approach for analysis of hydropower dam accidents (with fatalities) was demonstrated in an earlier work by the authors (Kalinina, Spada, & Burgherr, 2016;Kalinina, Spada, & Burgherr, 2018a). In a Bayesian hierarchical model, accident data is treated in the form of a multilevel system with subsets sharing specific characteristics (e.g., accident cause or infrastructure type).…”

Section: Introductionmentioning

confidence: 99%

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Probabilistic Analysis of Dam Accidents Worldwide: Risk Assessment for Dams of Different Purposes in OECD and Non‐OECD Countries with Focus on Time Trend Analysis

2020

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This study presents probabilistic analysis of dam accidents worldwide in the period 1911-2016. The accidents are classified by the dam purpose and by the country cluster, where they occurred, distinguishing between the countries of the Organization for Economic Cooperation and Development (OECD) and nonmember countries (non-OECD without China). A Bayesian hierarchical approach is used to model distributions of frequency and severity for accidents. This approach treats accident data as a multilevel system with subsets sharing specific characteristics. To model accident probabilities for a particular dam characteristic, this approach samples data from the entire data set, borrowing the strength across data set and enabling to model distributions even for subsets with scarce data. The modelled frequencies and severities are combined in frequency-consequence curves, showing that accidents for all dam purposes are more frequent in non-OECD (without China) and their maximum consequences are larger than in OECD countries. Multipurpose dams also have higher frequencies and maximum consequences than single-purpose dams. In addition, the developed methodology explicitly models time dependence to identify trends in accident frequencies over the analyzed period. Downward trends are found for almost all dam purposes confirming that technological development and implementation of safety measures are likely to have a positive impact on dam safety. The results of the analysis provide insights for dam risk management and decision-making processes by identifying key risk factors related to country groups and dam purposes as well as changes over time.

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Section: Data Collection and Characterizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Probabilistic Analysis of Dam Accidents Worldwide: Risk Assessment for Dams of Different Purposes in OECD and Non‐OECD Countries with Focus on Time Trend Analysis

2020

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“…In particular, in [20], credibility intervals (e.g., 5-95%) were firstly constructed for point estimates using a Chi-square distribution [21]; however, without considering that the uncertainty is a combination, among others, of epistemic and aleatory factors [22]. In order to consider a more complex uncertainty assessment, [13,[23][24][25] analysed the risk of accidents in different energy chains chains using a Bayesian inference. In this way, the authors could estimate the risk indicators and their uncertainties, since the latter is intrinsically assessed through a Bayesian approach.…”

Section: Introductionmentioning

confidence: 99%

Comparative Risk Assessment for Fossil Energy Chains Using Bayesian Model Averaging

Spada

Burgherr

2020

Energies

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The accident risk of severe (≥5 fatalities) accidents in fossil energy chains (Coal, Oil and Natural Gas) is analyzed. The full chain risk is assessed for Organization for Economic Co-operation and Development (OECD), 28 Member States of the European Union (EU28) and non-OECD countries. Furthermore, for Coal, Chinese data are analysed separately for three different periods, i.e., 1994–1999, 2000–2008 and 2009–2016, due to different data sources, and highly incomplete data prior to 1994. A Bayesian Model Averaging (BMA) is applied to investigate the risk and associated uncertainties of a comprehensive accident data set from the Paul Scherrer Institute’s ENergy-related Severe Accident Database (ENSAD). By means of BMA, frequency and severity distributions were established, and a final posterior distribution including model uncertainty is constructed by a weighted combination of the different models. The proposed approach, by dealing with lack of data and lack of knowledge, allows for a general reduction of the uncertainty in the calculated risk indicators, which is beneficial for informed decision-making strategies under uncertainty.

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“…Accidents due to a high level of energy being stored in the reservoir will give a negative impact on the downstream area and have disastrous effects on environment, society and economy [2]. Provision of a hydraulically efficient and structurally strong discharge structure is very significant for the safety of the dam, the life and property along the river down below [3][4][5]. It is crucial that these structures are optimized functionally and economically in the individual project.…”

Section: Introductionmentioning

confidence: 99%

“…The surface spillway and the bottom outlet can be utilized to release the surplus flood. The dam is a roller-compacted concrete gravity dam with a maximum height of 120 m, a crest length of 727 m and a reservoir capacity of 572 million m 3 . The powerhouse at the dam toe is installed with a capacity of 150,000 KW.…”

Section: Introductionmentioning

confidence: 99%

Three-Dimensional Numerical Simulation of Dam Discharge and Flood Routing in Wudu Reservoir

Rong

Zhang

Peng

et al. 2019

Water

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The main objectives of the present work are to investigate the hydraulic characteristics of the dam discharge flow and its impact downstream. Building information modeling technology is adopted to generate the terrain entity and hydraulic structures. The calculation of the dam discharge and flood routing simulation is achieved by employing Reynolds-Averaged Navier-Stokes equations with the RNG k-ε eddy viscosity model for its turbulence closure, as well as the Volume of Fluid method. An urban flood experiment and the field measurement records are utilized and validated the model accuracy. The flow field is obtained to assess the dam working conditions under different water levels. The results show that the maximum downstream flow depth, the maximum discharge capacity and the hydraulic jump length under normal water level is 18.6 m, 13,800 m 3 /s, and 108 m, respectively. The dam satisfies the safety demand under different water levels but close attention should be paid to the dam foundation, especially around the incident points of the discharge flow. Complex turbulent flow patterns, including collision, reflection, and vortices, are captured by three-dimensional simulation. The numerical simulation can assist the reservoir management vividly, so as to guarantee the stability of the dam operation. 2 of 20 experiments and confinements of empirical equations, researchers have attempted to adopt numerical simulation to check the working conditions of hydraulic structures [9-11]. Li et al. [12] simulated the joint flood discharge with the surface outlet and bottom outlet of a dam. The energy dissipation rate is enhanced by effective operation rules to stabilize the downstream flow regimes.Rapidly varied flow having large streamline curvatures exerts non-hydrostatic pressure distribution over the dam discharge structure surface. The enormous three-dimensional (3D) effect of dam discharge flow reveals that two-dimensional (2D) assumptions in solving such problems are inadequate [13][14][15]. 3D numerical simulation comes into sight gradually because it can yield a high-resolution outcome and vividly display the variation of physical parameters in the flow field [16]. In fact, 3D flood numerical simulation can be used to judge disaster losses in terms of visual experience. More concretely, it can qualitatively and quantitatively assess flood hazards and render visual reference for the development of flood control schemes, providing an important foundation for flood forecasting, dam design, and flood control system application [17]. The 3D simulation is approximately equivalent to the reality in terms of landform and boundary conditions. Therefore, the results are more accurate and convincing, and it is widely available in practical engineering [18][19][20][21].Dam discharge simulation requires an integrated tool that can handle both terrain entities and hydraulic structures. The building information modeling (BIM) method renders an effective approach for the generation of these models. It can provide detailed structure ...

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Application of a Bayesian hierarchical modeling for risk assessment of accidents at hydropower dams

Cited by 27 publications

References 26 publications

Probabilistic Analysis of Dam Accidents Worldwide: Risk Assessment for Dams of Different Purposes in OECD and Non‐OECD Countries with Focus on Time Trend Analysis

Probabilistic Analysis of Dam Accidents Worldwide: Risk Assessment for Dams of Different Purposes in OECD and Non‐OECD Countries with Focus on Time Trend Analysis

Comparative Risk Assessment for Fossil Energy Chains Using Bayesian Model Averaging

Three-Dimensional Numerical Simulation of Dam Discharge and Flood Routing in Wudu Reservoir

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