MON5.5: Megadisasters and cascading effects
Black swans, shapeshifters and flexibility
Logical Management Systems, Corp., United States of America
Is your organization plagued by shapeshifters? It is naïve to try to predict the effects of a change in the competitive landscape entirely on the basis of relationships observed in historical data, especially highly aggregated historical data. Unpredictability is the new norm. “Because we are asking the wrong questions precisely, we are getting the wrong answers precisely; and as a result we are creating false positives.” Unless we change the paradigm of competitive intelligence, we will continue to get false positives and find ourselves reacting to events instead of being proactive. This session presents a discussion of 12 steps to refocus competitive intelligence and temper the impact of shapeshifters. The session take-away inlcudes (1) 12 steps for competitive intelligence program development; (2) “Active Analysis” framework and analysis tools; (3) 11 shapeshifters that will affect competitive intelligence.
Global perspective on seismic risk reduction and resilient disaster reconstruction
Miyamoto International, United States of America
Worldwide, nearly 40% of the largest cities and hundreds of millions of people live in areas that can experience major earthquakes, resulting in large of casualties, interruption of lifelines, and placing large burden on the regional and national economy. Earthquakes in Haiti, Christchurch and East Japan have had long-term impact on societies. The 2010 Haiti Earthquake affected 3 million people and has still left over 300,000 displaced. An unprecedented reconstruction, incorporating local materials and masons but based on international earthquake-resistant principals, is currently underway to repair and strengthen 120,000 damaged buildings and allows people to return to safe homes and produce a seismically resilient community in this developing country. The 2011 earthquakes effecting Japan and New Zealand showed the need for seismic risk mitigation in developed countries. In New Zealand, older and newer buildings were damaged. The damage to newer buildings is not unexpected because the modern building codes intend is life safety and not resilient communities. Over 50% of 2400 buildings in the city center required demolition. Over $20 billion insurance loss is expected, resulting in a drop in the insurance capacity to be dropped and threatening the national investment environment. This issue is currently under discussion with the goal of reducing seismic risk for the existing buildings using high performance seismic protective devices. In Japan, large earthquake and tsunami were expected. However, the M9 East Japan earthquake caused a much higher Tsunami which overcame the sea walls and devastated over 500 km of coast line with major cities. The process of recovery and reconstruction has begun using commercial sector causing an economic boom. The observations show the need for: systematic seismic risk reduction especially in developing countries, understanding the limitations building codes, c) reconstruction by activating commercial sector: A resilient and economically vibrant society can arise from tragedies
Simulation and optimization of cascading effects - strategic multilayered risk management
Universität der Bundeswehr München, Germany, Federal Republic of
Society depends decisively on the availability of infrastructures such as energy, telecommunication, transportation, banking and finance, health care and governmental and public administration. Even selective disruption of one of these infrastructures may result in disruptions of governmental, industrial or public functions. Vulnerability of infrastructures therefore offers spectacular leverage for natural disasters as well as criminal actions. Threats and risks are part of the technological, economical, and societal development. Increasing complexity of our critical infrastructures exacerbates consequences of natural and/or man-made disasters. Not only primary effects but also cascading effects as a result of increasing dependencies and interdependencies of our technological and societal systems demand intelligent simulation and optimization techniques in the area of operations research and a comprehensive safety and security management. This talk bases on the simulation and optimization of complex networks. New methods like computational intelligence, evolutionary algorithms, system dynamics and data farming should be combined within new heuristics to master such complex networks via modern soft computing approaches. It presents actual decision support approaches - in the area of modern transportation systems, energy networks and aviation management. New innovative heuristics and first computational results for special multilayered decision problems will be presented.
Severe accidents of nuclear power plants in Europe: possible consequences and mapping of risk
1Institute of Meteorology, BOKU, Austria, Republic of; 2Institute for Security and Risk Sciences, BOKU, Austria, Republic of; 3Austrian Institute of Ecology, Austria, Republic of; 4Institute of Energy Technologies (INTE), Technical University of Catalonia (UPC), Barcelona, Spain
In the past three years, an interdisciplinary project to assess the risks and hazards associated with potential severe accidents in nuclear power plants in Europe and adjacent regions (Turkey, Iran) has been carried out which will finish soon. For 82 sites with a total of about 220 reactor units under operation or construction, detailed studies have been carried out. For each unit, a severe accident scenario with substantial release of radioactivity was identified, and inventories, release fractions & probabilities were either taken from publicly available sources or estimated on the base of similar facilities. Then, numerical dispersion calculations were carried out with the Lagrangian particle dispersion model FLEXPART for a domain covering whole of Europe and the Mediterranean, for 2800 real cases distributed over eleven years, using the Vienna Scientific Cluster supercomputing facility. The output in terms of air concentration and ground contamination is gathered with 1 degree resolution on the whole domain and on a nested grid (10W-32E, 36N-61N) with about 10 km grid size. From these results, statistics about contamination exceeding thresholds, for example for the ground contamination with Cs-137, are derived and presented in maps. Furthermore, effective and thyroid doses are calculated for different integration periods, relevant to different emergency measures, and statistics are built for them as well. These tools allow to see, inter alia, the geographical distribution of risks (considering also estimates for accident frequency) and hazards ("worst cases") as well as the changes for future scenarios of nuclear power development and the import and export of risk by country. The most important results will be made available through the project web site flexrisk.boku.ac.at, where some preliminary results are already available.
Risk of large oil spills: A statistical analysis in the aftermath of Deep Water Horizon
Paul Scherrer Institute, Switzerland
Following the explosion of the exploration drill rig Deep Water Horizon (DWH) in April 2010 that killed eleven workers, 670000 tons of oil were spilled in the Gulf of Mexico (GOM). This event was a reminder of the inherent risk of large spills in oil production and transport. The two biggest accidental spills in the period from 1974 to 2010 occurred on the exploration drill rigs Deepwater Horizon and Ixtoc I (1979, GOM, Mexico, 480000 t), accounting for 11.4% of total spill volume of accidental (≥ 200 t) spills. This high contribution of single events to the total spill volume underlines the need to analyze the risk of such rare but very severe events. The quantification of this risk is particularly important in view of the rapid increase in deep (> 305 m depth) and ultra-deep (> 1524 m) offshore drilling, where both a geographical expansion as well as a trend towards drilling at ever greater depths can be seen over the last decade.
Formation mechanism, process and risk evaluation system of disaster chain
1State Key Laboratory of Earth Surface Processes and Resource Ecology of Beijing Normal University, China; 2Key Laboratory of Environmental Change and Natural Disaster of Ministry of Education, Beijing Normal University, China; 3Academy of Disaster Reduction and Emergency Management of Ministry of Civil Affairs and Ministry of Education, Beijing Normal University, China; 4School of Geography, Beijing Normal University, China; 5The University of Maryland, USA
Though there have been different views on the disaster chain in the academic field, basically it can be summed up into two categories. One is mass phenomenon of hazards caused by the triggering of a factor in the earth system; the other is a chain of series of secondary disaster caused by hazard factors. The former is called hazard chain, the latter is disaster chain. The disaster chain can be divided into two types, namely serials one and parallel one, and the former one is usually caused by hazard chain. The formation of the hazard chain mainly relates to physical hazard-formative environments, and the formation of disaster chain is closely related to physical hazard-formative environments and exposures. The evolution of the hazard chain is the result of physical process changes of the earth system, while the change of the disaster chain is mainly the result of surface processes of the earth system, especially its geographic processes. Disaster chain risk assessment and multi-disaster risk assessment are fundamentally different. For the risk assessment of hazard chain, besides considering the probability of each hazard, it shall be assessed in a certain spatial-temporal condition, then the risk is assessed by combining the vulnerability curve of each hazard. However, for risk assessment of a disaster chain, in addition to the probability of the first hazard, possibility that lead to secondary hazard shall also be assessed in a certain spatial-temporal condition, then to assess the disaster chain risk according to the vulnerability curve of each hazard under background of the disaster chain. Enhancement of disaster chain risk assessment has a significant theoretical and practical value for large-scale disasters, as well as the scientific basis of foundation of integrated risk governance mode.