|
Beate Rottkemper, & Kathrin Fischer. (2013). Decision making in humanitarian logistics – A multi-objective optimization model for relocating relief goods during disaster recovery operations. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 647–657). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Disaster recovery operations rarely proceed smoothly and disruptions often require the redistribution of relief items. Such a redistribution has to be carried out taking into account both the current disruption and the uncertainty regarding possible future incidents in the respective area. As decisions have to be made fast in humanitarian operations, extensive optimization runs cannot be conducted in such a situation. Nevertheless, sensible decisions should be made to ensure an efficient redistribution, considering not only satisfaction of needs but also operational costs, as the budget is usually scarce in the recovery phase of a disaster. In this work, different scenarios are generated and then solved with a multiobjective optimization model to explore possible developments. By evaluating the results of these scenarios, decision rules are identified which can support the decision maker in the actual disaster situation in making fast, but nevertheless well-founded, decisions.
|
|
|
Santiago Pantano Calderón, Claude Baron, Jean-Charles Chaudemar, Élise Vareilles, & Rob Vingerhoeds. (2022). Regarding the COVID-19 Crisis from a Systems Engineering Perspective. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 154–161). Tarbes, France.
Abstract: In the beginning of 2022, the world is still fighting the crisis caused by the COVID-19 o utbreak. The scientific community is still dedicating significant efforts to identify which are the better strategies to mitigate the pandemic and establish how and when to apply them. Modeling and simulation are a common method to replicate and foresee the behavior of the epidemic curve, but traditional analytical models are not capable to explain and reproduce the real evolution of the number of infections and deaths as they only concentrate in the epidemiological aspects of the virus. The COVID-19 crisis has an impact in all fundamental levels of society, and this is the reason why its modeling requires a global perspective and a holistic approach. Though the engineering scope is not common in the study of public health crises, this paper concludes that some engineering tools such as systems analysis and control theory may be the answer to build a high-fidelity model to support the decision-making facing the emergency.
|
|
|
Alexei Sharpanskykh. (2012). An agent-based approach for safety analysis of safety-critical organizations. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: Modern safety-critical organizations are characterized by complex, nonlinear dynamics involving many interrelated actors and processes. Safety issues that emerge from these complex dynamics increasingly remain hidden, until an incident or even a serious accident occurs. Traditional safety analysis methods developed long ago for much simpler organizations cannot help identifying, explaining and predicting many safety-related properties of modern organizations. To address this issue, in the paper a formal approach is proposed to establish relations between local dynamics of actors of a complex safety-critical organization and global safetyrelated properties that emerge from these dynamics. In contrast to the traditional approaches, the organizational dynamics are specified by taking the agent perspective with an organizational layer. The application of the approach is illustrated by a simulation case study, in which spread of safety-critical information in an air navigation service provider is investigated. © 2012 ISCRAM.
|
|
|
Takuya Tsuchiya, Toshihiro Osaragi, & Takuya Oki. (2015). Influence of Information-Hearsay on Wide-Area Evacuation at a Large Earthquake. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: In order to evacuate smoothly and safely at a large earthquake, it is important to obtain the information on property damages (such as street-blockage and fire) and on evacuation areas by hearsay, guidance and bulletin boards. In this paper, we construct a model, which describes wide-area evacuation, information-hearsay among evacuees and guidance behavior. Using this model, we evaluate the influence of information-hearsay on wide-area evacuation in terms of the evacuation time and the risk on evacuation routes. Simulation results demonstrate that the locational information of evacuation areas and damages is the most helpful for people who are unfamiliar with an area. In addition, we discuss the effective and efficient methods of evacuation guidance. The results show that the guides contribute to reducing the evacuation time and the risk on evacuation routes of evacuees, and sharing information among guides enables more efficient and safer evacuation / guidance.
|
|
|
Wolfgang Raskob, Stefan Wandler, & Evgenia Deines. (2015). Agent-based modelling to identify possible measures in case of Critical Infrastructure disruption. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: Understanding critical infrastructures and in particular protecting them in case of natural or man-made threats or disasters is the objective of our research. As use case, the security of the power supply in the year 2030 for the city of Karlsruhe was selected. This scenario contains interdependencies between the electrical power grid and IT components as well as critical infrastructures such as water supply and health care. To simulate the critical infrastructure, their dependencies and potential measures to mitigate effects, agent based simulation models have been developed and applied. The ultimate objective of the research activity is to develop a holistic analysis framework to quantify and evaluate requirements and design decisions of the many players in such complex infrastructures.
|
|
|
Yan Wang, Hong Huang, & Wei Zhu. (2015). Stochastic source term estimation of HAZMAT releases: algorithms and uncertainty. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: Source term estimation (STE) of hazardous material (HAZMAT) releases is critical for emergency response. Such problem is usually solved with the aid of atmospheric dispersion modelling and inversion algorithms accompanied with a variety of uncertainty, including uncertainty in atmospheric dispersion models, uncertainty in meteorological data, uncertainty in measurement process and uncertainty in inversion algorithms. Bayesian inference methods provide a unified framework for solving STE problem and quantifying the uncertainty at the same time. In this paper, three stochastic methods for STE, namely Markov chain Monte Carlo (MCMC), sequential Monte Carlo (SMC) and ensemble Kalman filter (EnKF), are compared in accuracy, time consumption as well as the quantification of uncertainty, based on which a kind of flip ambiguity phenomenon caused by various uncertainty in STE problems is pointed out. The advantage of non-Gaussian estimation methods like SMC is emphasized.
|
|
|
Selim Serhan Yildiz, & Himmet Karaman. (2012). Developing a physics-based model for post-earthquake ignitions. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: Earthquakes not only cause damages by shaking, but secondary disasters like fire following earthquake (FFE), tsunami, liquefaction, land slide etc. also cause large-scale losses. In some cases, FFEs result in losses more than shaking do as seen in the 1906 San Francisco earthquake and the 1923 Kanto earthquake. FFEs are generally caused by strong ground shakings. Strong shakings damage the structures and infrastructures. As a consequence of earthquake, many ignitions can occur due to damaged gas systems and electrical systems, overturning of electrical appliances and heating equipments and falling of flammable materials from shelves in structures. In addition to interior structure ignitions, damaged infrastructure elements such as gas pipelines and electric transmission lines can also cause ignitions. Some of these ignitions spread due to amount of fuel load (combustible materials), construction material, direction and speed of wind etc. in the environment and they can turn into large urban conflagrations. This paper proposes a physics-based post-earthquake fire ignition model in order to estimate number and location of ignitions in urban areas. © 2012 ISCRAM.
|
|
|
Ying Zhao, Mengqi Yuan, Guofeng Su, & Tao Chen. (2015). Crowd Security Detection based on Entropy Model. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: Identifying the terror attack, illegal public gathering or other mass events risks by utilizing cameras is an important concern both in crowd security area and in pattern recognition research area. This paper provides a physical entropy model to measure the crowd security level.The entropy model was created by identifying individuals?moving velocity and the related probability. The individuals are represented by Harris Corners in videos, thus to avoid the time-consuming human recognition task. Simulation experiment and video detection experiments were conducted, verified that in the disordered state, the entropy is higher; while in ordered state, the entropy is much lower; when the crowd security has a sudden change, the entropy will change. It was verified that the entropy is the applicable indicator of crowd security. By recognizing the entropy mutation, it is possible to automatically detect the abnormal crowd behavior and to set the warning alarm.
|
|
|
Yue Guan, Shifei Shen, & Hong Huang. (2015). Assessment of the radiation doses to the public from the cesium in oceans after Fukushima Nuclear Accident. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: A great number of radioactive cesium were released into sea water after Fukushima Accident. We modified the Regional Oceanic Modelling System (ROMS) to reproduce the dispersion process of the cesium in oceans. The simulated water concentration was in good agreement with observation. In order to explore the nuclear impact of these contaminant in ocean, we established a food web model to calculate the concentration in marine organisms and assess the internal dose rate to the public. The estimated internal dose rate is small compared with the recommended limit by International Atomic Energy Agency (IAEA). Then, we employed the Monte Carlo N Particle Transport Code (MCNP) to calculate the transfer coefficient. The external dose rate could be estimated by this coefficient and simulated water concentration.
|
|
|
X.L. Zhang, Jian Guo Chen, Guofeng Su, & Hongyong Yuan. (2013). Study on source inversion technology for nuclear accidents based on gaussian puff model and ENKF. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 634–639). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: For nuclear power plant (NPP) accident, the assessment of the radiation consequences plays an important role in the emergency response system. However, the source characteristics which greatly influence thhe accuracy of the assessment result is poorly known or even unknown at the early phase of accident, wich can cause poorly understanding of the situation and delay the response activities. In this paper, source inversion technology in analyzing nuclear accidents based on Gaussian puff model and ensemble Kalman filter (EnKF) is proposed. The method is validated with simulated measurements and the results show that it can give reasonable estimations of the change in release rate and height simultaneously, though the first guess of release rate is 102 larger than the true value. The investigation of the influence of sharp change in source term shows that the method is robust to capture the sharp change, but there is a delay of response when the release height increases simultaneously.
|
|
|
Dimitris Zisiadis, Spyros Kopsidas, Vassilis Grizis, George Thanos, George Leventakis, & Leandros Tassiulas. (2012). STAR-TRANS Modeling Language (STML) modeling risk in the STAR-TRANS risk assessment framework for interconnected transportation systems. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: The present paper introduces a high level modeling language, capable of expressing the concepts and processes of the Strategic Risk Assessment and Contingency Planning in Interconnected Transportation Networks (STAR-TRANS) framework. STAR-TRANS is a comprehensive transportation security risk assessment framework for assessing related risks that provides cohered contingency management procedures for interconnected, interdependent and heterogeneous transport networks. STAR-TRANS modeling Language (STML) is a domain specific language combining language simplicity with a very clear syntax, providing all the necessary elements (assets, threats, incidents, consequences etc.) to model the STAR-TRANS risk assessment framework. © 2012 ISCRAM.
|
|
|
Christopher W. Zobel. (2013). Analytically comparing disaster recovery following the 2012 derecho. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 678–682). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: This work in progress paper discusses analytically characterizing nonlinear recovery behavior through the context of the derecho windstorm that struck the mid-Atlantic United States in the summer of 2012. The focus is on the recovery efforts of the Appalachian Power Company, and the discussion includes a look at the need for communicating the progress of such recovery efforts to the public. Publicly available recovery data is analyzed and compared with respect to the relative behaviors exhibited by two different nonlinear recovery processes, and some of the implications for understanding the efficiency of different disaster recovery operations are discussed.
|
|
|
Christopher W. Zobel, Stanley E. Griffis, Steven A. Melnyk, & John R. MacDonald. (2012). Characterizing disaster resistance and recoveryusing outlier detection. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: Most definitions of disaster resilience incorporate both the capacity to resist the initial impact of a disaster and the ability to recover after it occurs. Being able to characterize and analyze resilient behavior can lead to improved understanding not only of the capabilities of a given system, but also of the effectiveness of different strategies for improving its resiliency. This paper presents an approach for quantifying the transient behavior resulting from a disaster event in a way that allows researchers to not only describe the transient response but also assess the impact of various factors (both main and interaction effects) on this response. This new approach combines simulation modeling, time series analysis, and statistical outlier detection to differentiate between disaster resistance and disaster recovery. Following the introduction of the approach, the paper provides a preliminary look at its relationship to the existing concept of predicted disaster resilience. © 2012 ISCRAM.
|
|