scholarly journals Characterizing Uncertainty in City-Wide Disaster Recovery through Geospatial Multi-Lifeline Restoration Modeling of Earthquake Impact in the District of North Vancouver

2020 ◽  
Vol 11 (6) ◽  
pp. 807-820
Author(s):  
Andrew Deelstra ◽  
David Bristow
Keyword(s):  
Power Distribution ◽  
Water Distribution ◽  
Discrete Event ◽  
Graph Model ◽  
Transport Systems ◽  
Complex Interactions ◽  
Lifeline System ◽  
Model And Simulation ◽  
System Functioning ◽  
Lifeline Systems

AbstractRestoring lifeline services to an urban neighborhood impacted by a large disaster is critical to the recovery of the city as a whole. Since cities are comprised of many dependent lifeline systems, the pattern of the restoration of each lifeline system can have an impact on one or more others. Due to the often uncertain and complex interactions between dense lifeline systems and their individual operations at the urban scale, it is typically unclear how different patterns of restoration will impact the overall recovery of lifeline system functioning. A difficulty in addressing this problem is the siloed nature of the knowledge and operations of different types of lifelines. Here, a city-wide, multi-lifeline restoration model and simulation are provided to address this issue. The approach uses the Graph Model for Operational Resilience, a data-driven discrete event simulator that can model the spatial and functional cascade of hazard effects and the pattern of restoration over time. A novel case study model of the District of North Vancouver is constructed and simulated for a reference magnitude 7.3 earthquake. The model comprises municipal water and wastewater, power distribution, and transport systems. The model includes 1725 entities from within these sectors, connected through 6456 dependency relationships. Simulation of the model shows that water distribution and wastewater treatment systems recover more quickly and with less uncertainty than electric power and road networks. Understanding this uncertainty will provide the opportunity to improve data collection, modeling, and collaboration with stakeholders in the future.

Dynamic updating of post-earthquake damage and functional restoration forecasts of water distribution systems using Bayesian inferencing

2021 ◽  
pp. 875529302110380
Author(s):  
Agam Tomar ◽  
Henry V Burton ◽  
Ali Mosleh
Keyword(s):  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Epistemic Uncertainty ◽  
Discrete Event ◽  
Complete Recovery ◽  
Current Data ◽  
Functional Restoration ◽  
Mitigation Measures ◽  
Total Recovery

A framework for dynamically updating post-earthquake functional recovery forecasts is presented to reduce the epistemic uncertainty in the predictive model. A Bayesian Network (BN) model is used to provide estimates of the total recovery time, and a process-based discrete event simulation (PBDES) model generates forecasts of the complete recovery trajectory. Both models rely on component damage and duration-based input parameters that are dynamically updated using Bayes’ theorem, as information becomes available throughout the recovery process. The effectiveness of the proposed framework is demonstrated through an application to the pipe network of the City of Napa water distribution system. More specifically, pipe damage and repair data from the 2014 earthquake are used as a point of comparison for the dynamic forecasts. It is shown that, over time, the mean value of the total recovery duration generated by the BN-based model converges to the observed value and the dispersion is reduced. Also, despite a crude initial estimate, the median trajectory generated by the PBDES model provides a reasonable approximation of the observed recovery within 30 days following the earthquake. The proposed framework can be used by emergency managers to investigate the efficacy of post-event mitigation measures (e.g. crew allocation, resource prioritization) utilizing the most current data and knowledge.

Performance of lifelines during the 1994 Northridge earthquake

1995 ◽  
Vol 22 (2) ◽  
pp. 438-451 ◽  
Author(s):  
David L. Lau ◽  
Alex Tang ◽  
Jean-Robert Pierre
Keyword(s):  
Los Angeles ◽  
Electric Power ◽  
System Performance ◽  
Water Distribution ◽  
Lessons Learned ◽  
Northridge Earthquake ◽  
Epicentral Area ◽  
Lifeline Systems ◽  
Earthquake Damages ◽  
The Impact

Lifelines are essential infrastructures and facilities that are considered vital to the rescue effort and recovery of the affected community in the event of a natural disaster or emergency. The lifeline systems in a densely populated area, such as the Los Angeles basin, are very complex. The Northridge earthquake, which occurred in southern California on January 17, 1994, caused extensive damage to many of these lifeline facilities in the epicentral area. Effects of the damages were felt not only in the vicinity area of the earthquake but also in areas far from the earthquake site. This paper describes the earthquake damage to and performance of gas and water distribution and electric power and telecommunication systems. The impact of these failures on the overall system performance are presented. The significance and effect of the interdependency of life systems in an integrated urban environment are discussed. Lessons learned on system performance, seismic risk, and reliability of lifeline systems from the Canadian perspective are presented. Key words: earthquake damages, electric power, gas, lifelines, performance, risk, telecommunication, water.

scholarly journals Modeling and Robustness Study of Railway Transport Networks Using P-Timed Petri Nets

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Anis Mhalla ◽  
Mohanned Gaied
Keyword(s):  
Petri Nets ◽  
Traffic Management ◽  
Control Strategies ◽  
Discrete Event ◽  
Transport Systems ◽  
Population Mobility ◽  
Railway Transport ◽  
Transport Networks ◽  
Modeling And Analysis ◽  
Increasing Demand

The importance of public transport systems continues to grow. These systems must respond to an increasing demand for population mobility and traffic disturbances. Rail transport networks can be considered as Discrete Event Systems (DES) with time constraints. The time factor is a critical parameter, since it includes dates to be respected in order to avoid overlaps, delays, and collisions between trains. P-time Petri Nets have been recognized as powerful modeling and analysis tools for railway transport systems. Temporal disturbances in these systems include railway infrastructure, traffic management, and disturbances (weather, obstacles on the tracks, malice, social movement, etc.). The developments presented in this paper are devoted to the modeling and the study of the robustness of the railway transport systems in order to evaluate the stability and the efficiency of these networks. In this study two robust control strategies towards time disturbances are presented. The first one consists of compensating the disturbance as soon as it is observed in order to avoid constraints violation. The second one allows generating, by the control, a temporal lag identical to the disturbance in order to avoid the death of marks on the levels of synchronization transitions of the P-time Petri net model.

scholarly journals Prognosis of Water Quality Sensors Using Advanced Data Analytics: Application to the Barcelona Drinking Water Network

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1342 ◽  
Author(s):  
Diego Garcia ◽  
Vicenç Puig ◽  
Joseba Quevedo
Keyword(s):  
Water Quality ◽  
Distribution System ◽  
Data Analytics ◽  
Water Distribution ◽  
Discrete Event ◽  
Spatial Models ◽  
Remaining Useful Life ◽  
Health State ◽  
Using Data ◽  
Water Quality Sensors

Water Utilities (WU) are responsible for supplying water for residential, commercial and industrial use guaranteeing the sanitary and quality standards established by different regulations. To assure the satisfaction of such standards a set of quality sensors that monitor continuously the Water Distribution System (WDS) are used. Unfortunately, those sensors require continuous maintenance in order to guarantee their right and reliable operation. In order to program the maintenance of those sensors taking into account the health state of the sensor, a prognosis system should be deployed. Moreover, before proceeding with the prognosis of the sensors, the data provided with those sensors should be validated using data from other sensors and models. This paper provides an advanced data analytics framework that will allow us to diagnose water quality sensor faults and to detect water quality events. Moreover, a data-driven prognosis module will be able to assess the sensitivity degradation of the chlorine sensors estimating the remaining useful life (RUL), taking into account uncertainty quantification, that allows us to program the maintenance actions based on the state of health of sensors instead on a regular basis. The fault and event detection module is based on a methodology that combines time and spatial models obtained from historical data that are integrated with a discrete-event system and are able to distinguish between a quality event or a sensor fault. The prognosis module analyses the quality sensor time series forecasting the degradation and therefore providing a predictive maintenance plan avoiding unsafe situations in the WDS.

scholarly journals Analysis of assessment criteria for selected systems of transport means operation

2018 ◽  
Vol 182 ◽  
pp. 02003
Author(s):  
Łukasz Muślewski ◽  
Leszek Knopik ◽  
Bogdan Landowski ◽  
Oleh Polishchuk
Keyword(s):  
Time Moment ◽  
Transport Systems ◽  
Time Interval ◽  
Sociotechnical System ◽  
Human Driver ◽  
System Functioning ◽  
Technical Systems

The problems discussed in the study are connected with evaluation of complex technical systems functioning, in particular, transport systems. It was assumed that evaluation of their functioning depends on fulfilment degree of selected criteria. Therefore, it is important to determine a set of criteria including their type, number and importance. Since the research object is a public city transport system considered to be a sociotechnical system of the type: human (driver) –machine (vehicle) and the environment <H-M-E>, the criteria to be used for the assessment must include behavior of humans, operation of transport means, and the environmental impact. Thus, selection and determination of importance of significant, time variable, measurable and independent characteristics whose values, in a given time moment or a given time interval, define fulfillment degree of the criteria provide the basis for evaluation of such systems functioning. The quality of technical systems functioning in time is assessed on the basis of the criteria fulfilment degree or comparison and classification of different systems of the same type. It needs to be emphasized that the choice of optimal methods for selection of relevant criteria and determination of their impact on the analyzed system functioning is the research subject of study.

Sequential Propagation of Seismic Fragility across Interdependent Lifeline Systems

2011 ◽  
Vol 27 (1) ◽  
pp. 23-43 ◽  
Author(s):  
Isaac Hernandez-Fajardo ◽  
Leonardo Dueñas-Osorio
Keyword(s):  
Network Performance ◽  
Fragility Curves ◽  
Mitigation Strategies ◽  
System Management ◽  
Seismic Action ◽  
Water Network ◽  
Service Networks ◽  
Lifeline System ◽  
Failure Propagation ◽  
Lifeline Systems

Realistic models of service networks must consider the evolution of interactions with external systems to evaluate emergent response effects on individual network performance. This paper introduces a new dynamic methodology for the assessment of systemic fragility propagation across interdependent networks subjected to seismic action that improves existing static methodologies. Interdependencies are discrete, unidirectional relationships between elements of distinct networks, which are able to influence response evolution from transient to steady-state stages. Comparisons of systemic fragility curves results for isolated and interdependent power and water networks display the importance of interdependence strength and density properties. For the test water network, inter-systemic failure propagation increases its connectivity loss by up to 24%, while high interdependence strengths make the median fragility rise up to 56.2%. In contrast, reductions of interdependence density improve the median water fragility up to 81.7%. Insights obtained from this model, and its associated sequential fragility algorithm, reveal complex coupling patterns and interdependence-based mitigation strategies that are essential for lifeline system management.

Further theoretical analysis of concentration–pressure–flux waves in phloem transport systems

1978 ◽  
Vol 56 (8) ◽  
pp. 1086-1090 ◽  
Author(s):  
Jack M. Ferrier
Keyword(s):  
Hydrostatic Pressure ◽  
Water Flux ◽  
Sieve Tube ◽  
Phloem Transport ◽  
Time Dependent ◽  
Transport Systems ◽  
Flux Variation ◽  
Complex Interactions ◽  
Theoretical Results ◽  
Sugar Source

Theoretical results show that waves involving complex interactions between osmotic pressure, hydrostatic pressure, and fluxes of water and solute can occur in any phloem transport system surrounded by a semipermeable membrane. These results show that such waves can travel from sugar sink to sugar source as well as from sugar source to sugar sink. The time-dependent sugar concentration variation is shown to be caused largely by the time-dependent variation of the gradient of mass flow velocity in the sieve tube which is produced by the time-dependent variation of water flux across the membrane. This water flux variation is produced by a slight phase difference between osmotic and hydrostatic pressure variation. It is proposed that this phenomenon be called the concentration–pressure–flux (CPJ) wave.

scholarly journals A Cooperative Intermodal Transportation Network Flow Control Method Based on Model Predictive Control

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Yuankai Huang ◽  
Qicai Zhou ◽  
Xiaolei Xiong ◽  
Jiong Zhao
Keyword(s):  
Model Predictive Control ◽  
Flow Control ◽  
Real Time ◽  
Predictive Control ◽  
Dynamic Optimization ◽  
Network Flow ◽  
Control Method ◽  
Discrete Event ◽  
Transport Systems ◽  
Intermodal Transport

With the development of information technology, intermodal transport research pays more attention to dynamic optimization and multi-role cooperation. The core issue of this paper was to realize container routing with dynamic adjustment, real-time optimization, and multi-role cooperation characteristics in the intermodal transport network. This paper first introduces the Intermodal Transport Cooperation Protocol (ITCP) that describes the operation and analysis of intermodal transport systems with the concept of encapsulation and layering. Then, a new network flow control method was built based on Model Predictive Control (MPC) in the ITCP framework. The method takes real-time information from all ITCP layers as input and generates flow control decisions for containers. To evaluate the method’s effectiveness, a discrete event simulation experiment is applied. The results show that the proposed method outperforms the all-or-nothing method in scenarios with high freight volume, which means the method proposed in this paper can effectively balance the network transport load and reduce network operating costs. The research of this paper may throw some new light on intermodal transport research from the perspectives of digitization, multi-role cooperation, dynamic optimization, and system standardization.

scholarly journals Transportation, Germs, Culture: A Dynamic Graph Model of 2019-nCoV Spread

2020 ◽  
Author(s):  
Xiaofei Yang ◽  
Tun Xu ◽  
Peng Jia ◽  
Han Xia ◽  
Li Guo ◽  
...  
Keyword(s):  
Graph Model ◽  
Emergency Situation ◽  
Contributing Factors ◽  
Dynamic Graph ◽  
Model And Simulation ◽  
Health Authorities ◽  
Public Health Authorities ◽  
Precise Prediction ◽  
Novel Coronavirus ◽  
Major Factors

Since the outbreak of 2019 novel coronavirus (2019-nCoV) at the hardest-hit city of Wuhan, the fast-moving spread has killed over three hundred people and infected more than ten thousands in China1. There are more than one hundred cases outside of China, affecting a dozen of countries globally2. The genome sequence of 2019-nCoV has been reported and fast diagnostic kits, effective treatment as well as preventive vaccines are rapidly being developed3. Initial fast-growing confirmed cases triggered lock-down of Wuhan as well as nearby cities in Hubei Province. Mathematical models have been proposed by scientists around the world to project the numbers of infected cases in the coming days 4,5. However, major factors such as transportation and cultural customs have not been weighed enough. Our model is not set out for precise prediction of the number of infected cases, rather, it is meant for a glance of the dynamics under a public epidemic emergency situation and of different contributing factors. We hope that our model and simulation would provide more insights and perspective information to public health authorities around the globe for better informed prevention and containment solution.

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