scholarly journals A Simplified Representation of Pressure Flow from Surface Slopes in Urban Sewer Systems

Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2778
Author(s):  
Huabing Huang ◽  
Yu Pan ◽  
Xianwei Wang
Keyword(s):  
Numerical Models ◽  
Velocity Ratio ◽  
Volume Estimate ◽  
Pressure Flow ◽  
Storm Water Management Model ◽  
Sewer Systems ◽  
Flood Volume ◽  
Surface Slopes ◽  
Effective Representation

A Constant Pipe Drainage (CPD) capacity for sewer systems is commonly applied when undertaking flood risk assessment, however data that are needed for calibration and validation of numerical models are scarce or unavailable. The CPD model neglects the effect of pressure flow and leads to significant deviation in flood volume estimate. This study proposes a new index Velocity Ratio (VR) to approximate pressure flow. A case study in Guangzhou, China is used to investigate the capability of reproducing a reasonable flood volume for two models, the CPD and the VR-based. Compared to the flood volume simulated by the Storm Water Management Model (SWMM), the CPD model shows a significant overestimation, Mean Relative Deviation (MRD) 192%. The VR-based model has a much better performance, MRD 18%. Therefore, the VR-based model is a simple and effective representation of pressure flow in urban sewer systems and can be easily applied in areas lacking detailed pipe data, especially for planning new pipe networks or updating the old pipes.

SEISMIC RISK AND RESILIENCE ASSESSMENT OF INDUSTRIAL FACILITIES: CASE STUDY ON A BLACK CARBON PLANT

2020 ◽  
Author(s):  
George Karagiannakis
Keyword(s):  
Seismic Risk ◽  
Numerical Models ◽  
Fragility Curves ◽  
Human Life ◽  
Mitigation Strategies ◽  
Economic Losses ◽  
Risk And Resilience ◽  
Industrial Plants ◽  
Plant Equipment

This paper deals with state of the art risk and resilience calculations for industrial plants. Resilience is a top priority issue on the agenda of societies due to climate change and the all-time demand for human life safety and financial robustness. Industrial plants are highly complex systems containing a considerable number of equipment such as steel storage tanks, pipe rack-piping systems, and other installations. Loss Of Containment (LOC) scenarios triggered by past earthquakes due to failure on critical components were followed by severe repercussions on the community, long recovery times and great economic losses. Hence, facility planners and emergency managers should be aware of possible seismic damages and should have already established recovery plans to maximize the resilience and minimize the losses. Seismic risk assessment is the first step of resilience calculations, as it establishes possible damage scenarios. In order to have an accurate risk analysis, the plant equipment vulnerability must be assessed; this is made feasible either from fragility databases in the literature that refer to customized equipment or through numerical calculations. Two different approaches to fragility assessment will be discussed in this paper: (i) code-based Fragility Curves (FCs); and (ii) fragility curves based on numerical models. A carbon black process plant is used as a case study in order to display the influence of various fragility curve realizations taking their effects on risk and resilience calculations into account. Additionally, a new way of representing the total resilience of industrial installations is proposed. More precisely, all possible scenarios will be endowed with their weighted recovery curves (according to their probability of occurrence) and summed together. The result is a concise graph that can help stakeholders to identify critical plant equipment and make decisions on seismic mitigation strategies for plant safety and efficiency. Finally, possible mitigation strategies, like structural health monitoring and metamaterial-based seismic shields are addressed, in order to show how future developments may enhance plant resilience. The work presented hereafter represents a highly condensed application of the research done during the XP-RESILIENCE project, while more detailed information is available on the project website https://r.unitn.it/en/dicam/xp-resilience.

Sediment transport under dry weather conditions in a small sewer system

1998 ◽  
Vol 37 (1) ◽  
pp. 155-162
Author(s):  
Flemming Schlütter ◽  
Kjeld Schaarup-Jensen
Keyword(s):  
Sediment Transport ◽  
Field Data ◽  
Field Measurements ◽  
Weather Conditions ◽  
Sewer System ◽  
Transport Models ◽  
Sewer Systems ◽  
Combined Sewer ◽  
Initial Results

Increased knowledge of the processes which govern the transport of solids in sewers is necessary in order to develop more reliable and applicable sediment transport models for sewer systems. Proper validation of these are essential. For that purpose thorough field measurements are imperative. This paper renders initial results obtained in an ongoing case study of a Danish combined sewer system in Frejlev, a small town southwest of Aalborg, Denmark. Field data are presented concerning estimation of the sediment transport during dry weather. Finally, considerations on how to approach numerical modelling is made based on numerical simulations using MOUSE TRAP (DHI 1993).

Pollution based real time control strategies for combined sewer systems

1997 ◽  
Vol 36 (8-9) ◽  
pp. 331-336 ◽  
Author(s):  
Gabriela Weinreich ◽  
Wolfgang Schilling ◽  
Ane Birkely ◽  
Tallak Moland
Keyword(s):  
Real Time ◽  
Control Strategies ◽  
Ammonia Nitrogen ◽  
Simple Extension ◽  
Real Time Control ◽  
Time Control ◽  
Sewer Systems ◽  
Receiving Waters ◽  
Tunnel System

This paper presents results from an application of a newly developed simulation tool for pollution based real time control (PBRTC) of urban drainage systems. The Oslo interceptor tunnel is used as a case study. The paper focuses on the reduction of total phosphorus Ptot and ammonia-nitrogen NH4-N overflow loads into the receiving waters by means of optimized operation of the tunnel system. With PBRTC the total reduction of the Ptot load is 48% and of the NH4-N load 51%. Compared to the volume based RTC scenario the reductions are 11% and 15%, respectively. These further reductions could be achieved with a relatively simple extension of the operation strategy.

scholarly journals Estimation of Damage Induced by Single-Hole Rock Blasting: A Review on Analytical, Numerical, and Experimental Solutions

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 29
Author(s):  
Mahdi Shadabfar ◽  
Cagri Gokdemir ◽  
Mingliang Zhou ◽  
Hadi Kordestani ◽  
Edmond V. Muho
Keyword(s):  
Structural Reliability ◽  
Numerical Models ◽  
Experimental Models ◽  
Rock Blasting ◽  
Discussion Section ◽  
Reliability Models ◽  
Fine Grain ◽  
Experimental Approaches ◽  
Engineering Projects

This paper presents a review of the existing models for the estimation of explosion-induced crushed and cracked zones. The control of these zones is of utmost importance in the rock explosion design, since it aims at optimizing the fragmentation and, as a result, minimizing the fine grain production and recovery cycle. Moreover, this optimization can reduce the damage beyond the set border and align the excavation plan with the geometric design. The models are categorized into three groups based on the approach, i.e., analytical, numerical, and experimental approaches, and for each group, the relevant studies are classified and presented in a comprehensive manner. More specifically, in the analytical methods, the assumptions and results are described and discussed in order to provide a useful reference to judge the applicability of each model. Considering the numerical models, all commonly-used algorithms along with the simulation details and the influential parameters are reported and discussed. Finally, considering the experimental models, the emphasis is given here on presenting the most practical and widely employed laboratory models. The empirical equations derived from the models and their applications are examined in detail. In the Discussion section, the most common methods are selected and used to estimate the damage size of 13 case study problems. The results are then utilized to compare the accuracy and applicability of each selected method. Furthermore, the probabilistic analysis of the explosion-induced failure is reviewed using several structural reliability models. The selection, classification, and discussion of the models presented in this paper can be used as a reference in real engineering projects.

scholarly journals Assessing storm surge hazard and impact of sea level rise in the Lesser Antilles case study of Martinique

2017 ◽  
Vol 17 (9) ◽  
pp. 1559-1571 ◽  
Author(s):  
Yann Krien ◽  
Bernard Dudon ◽  
Jean Roger ◽  
Gael Arnaud ◽  
Narcisse Zahibo
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Storm Surge ◽  
Numerical Models ◽  
Lesser Antilles ◽  
Adaptation Measures ◽  
Worst Case ◽  
Mitigation And Adaptation ◽  
The Impact

Abstract. In the Lesser Antilles, coastal inundations from hurricane-induced storm surges pose a great threat to lives, properties and ecosystems. Assessing current and future storm surge hazards with sufficient spatial resolution is of primary interest to help coastal planners and decision makers develop mitigation and adaptation measures. Here, we use wave–current numerical models and statistical methods to investigate worst case scenarios and 100-year surge levels for the case study of Martinique under present climate or considering a potential sea level rise. Results confirm that the wave setup plays a major role in the Lesser Antilles, where the narrow island shelf impedes the piling-up of large amounts of wind-driven water on the shoreline during extreme events. The radiation stress gradients thus contribute significantly to the total surge – up to 100 % in some cases. The nonlinear interactions of sea level rise (SLR) with bathymetry and topography are generally found to be relatively small in Martinique but can reach several tens of centimeters in low-lying areas where the inundation extent is strongly enhanced compared to present conditions. These findings further emphasize the importance of waves for developing operational storm surge warning systems in the Lesser Antilles and encourage caution when using static methods to assess the impact of sea level rise on storm surge hazard.

scholarly journals Influence of foundation settlements in load redistribution on columns in a monitoring construction - Case Study

2010 ◽  
Vol 3 (3) ◽  
pp. 346-356 ◽  
Author(s):  
G. Savaris ◽  
P. H. Hallak ◽  
P. C. A. Maia
Keyword(s):  
Numerical Analysis ◽  
Numerical Model ◽  
Finite Elements ◽  
Load Distribution ◽  
Numerical Models ◽  
Normal Load ◽  
Finite Elements Method ◽  
Load Redistribution

The objective of this article is to present the results obtained in a study on the interaction between the behavior of the structure and the foundation settlements and verify the influence of normal load distribution on the columns. In this mechanism, known as structure soil interaction (SSI), as the building is constructed, a transfer of loads occurs from the columns which tend to settle more to those that tend to settle less. The study was conducted in a building which had its settlements monitored from the beginning of construction. For this purpose, a linear tridimensional numerical model was constructed and numerical analysis was performed, using the finite elements method. In these analyses, numerical models corre- sponding to the execution of each floor were used, considering the settlements measured in each stage of the construction. The results of analy- ses showed that the effect of SSI are significant for calculating the normal efforts on the columns, particularly on those located in the first floors.

scholarly journals Towards an objective assessment of climate multi-model ensembles – a case study: the Senegalo-Mauritanian upwelling region

2020 ◽  
Vol 13 (6) ◽  
pp. 2723-2742
Author(s):  
Juliette Mignot ◽  
Carlos Mejia ◽  
Charles Sorror ◽  
Adama Sylla ◽  
Michel Crépon ◽  
...  
Keyword(s):  
Numerical Models ◽  
Objective Assessment ◽  
Cmip5 Models ◽  
Model Ensemble ◽  
Self Organizing Maps ◽  
Climate Simulations ◽  
Mean Sea Surface ◽  
The Mean ◽  
Model Ensembles

Abstract. Climate simulations require very complex numerical models. Unfortunately, they typically present biases due to parameterizations, choices of numerical schemes, and the complexity of many physical processes. Beyond improving the models themselves, a way to improve the performance of the modeled climate is to consider multi-model combinations. In the present study, we propose a method to select the models that yield a multi-model ensemble combination that efficiently reproduces target features of the observations. We used a neural classifier (self-organizing maps), associated with a multi-correspondence analysis to identify the models that best represent some target climate property. We can thereby determine an efficient multi-model ensemble. We illustrated the methodology with results focusing on the mean sea surface temperature seasonal cycle in the Senegalo-Mauritanian region. We compared 47 CMIP5 model configurations to available observations. The method allows us to identify a subset of CMIP5 models able to form an efficient multi-model ensemble. The future decrease in the Senegalo-Mauritanian upwelling proposed in recent studies is then revisited using this multi-model selection.

Sharing transferable methods in environmental data science: A Fuzzy changepoint approach to numerical model evaluation over Greenland.

2021 ◽  
Author(s):  
Michael Hollaway ◽  
Peter Henrys ◽  
Rebecca Killick ◽  
Amber Leeson ◽  
John Watkins
Keyword(s):  
Numerical Model ◽  
Data Science ◽  
Environmental Science ◽  
Numerical Models ◽  
Environmental Data ◽  
Resolution Model ◽  
Changepoint Analysis ◽  
Temperature Records ◽  
Temporal Events

<p>     Numerical models are essential tools for understanding the complex and dynamic nature of the natural environment and how it will respond to a changing climate. With ever increasing volumes of environmental data and increased availability of high powered computing, these models are becoming more complex and detailed in nature. Therefore the ability of these models to represent reality is critical in their use and future development. This has presented a number of challenges, including providing research platforms for collaborating scientists to explore big data, develop and share new methods, and communicate their results to stakeholders and decision makers. This work presents an example of a cloud-based research platform known as DataLabs and how it can be used to simplify access to advanced statistical methods (in this case changepoint analysis) for environmental science applications.</p><p>     A combination of changepoint analysis and fuzzy logic is used to assess the ability of numerical models to capture local scale temporal events seen in observations. The fuzzy union based metric factors in uncertainty of the changepoint location to calculate individual similarity scores between the numerical model and reality for each changepoint in the observed record. The application of the method is demonstrated through a case study on a high resolution model dataset which was able to pick up observed changepoints in temperature records over Greenland to varying degrees of success. The case study is presented using the DataLabs framework, demonstrating how the method can be shared with other users of the platform and the results visualised and communicated to users of different areas of expertise.</p>

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