Relevant bibliographies by topics / Risk management Computer simulation

Academic literature on the topic 'Risk management Computer simulation'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Risk management Computer simulation"

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Bučková, Monika, Miroslav Fusko, Gabriela Gabajová, Martin Gašo, Branislav Mičieta, and Milan Martinkovič. "MANAGING RISK WITH THE USE OF COMPUTER SIMULATION." Proceedings of CBU in Economics and Business 2 (October 24, 2021): 17–23. http://dx.doi.org/10.12955/peb.v2.250.

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Internal and external risk management has become an important issue in today's global business environment, which is fraught with health, natural, political, economic and technical threats. This article deals with the design of a methodology for problem-solving and risk management in connection with computer simulation. The risk management methodology proposed by us consists of individual steps, which are summarized into three stages - risk assessment, risk analysis and risk management. The proposed computer simulation methodology consists of several steps, for example creating a parametric simulation model, designing experiments, analysis of the simulation model results or the evaluation of the simulation results. These steps are described in the article. After completing the previous steps, we describe the points of an action plan and what it must contain to avoid consequences and the impact of risks at the lowest possible level. An example of the use of computer simulation is the risk situation associated with the fluctuation of employees. In the end, the proposed methodology is supported by the results of our research and its further direction.
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BETTER, MARCO, FRED GLOVER, GARY KOCHENBERGER, and HAIBO WANG. "SIMULATION OPTIMIZATION: APPLICATIONS IN RISK MANAGEMENT." International Journal of Information Technology & Decision Making 07, no. 04 (December 2008): 571–87. http://dx.doi.org/10.1142/s0219622008003137.

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Simulation optimization is providing solutions to important practical problems previously beyond reach. This paper explores how new approaches are significantly expanding the power of simulation optimization for managing risk. Recent advances in simulation optimization technology are leading to new opportunities to solve problems more effectively. Specifically, in applications involving risk and uncertainty, simulation optimization surpasses the capabilities of other optimization methods not only in the quality of solutions but also in their interpretability and practicality. In this paper, we demonstrate the advantages of using a simulation optimization approach to tackle risky decisions, by showcasing the methodology on two popular applications from the areas of finance and business process design.
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Ashton, David, Gregory B. Getts, Peter H. Ritchken, and Harvey M. Salkin. "Portfolio Risk Management: A Computer Simulation for Stocks and Options." Economic Journal 100, no. 401 (June 1990): 655. http://dx.doi.org/10.2307/2234170.

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Thornton, A. C. "Variation Risk Management Using Modeling and Simulation." Journal of Mechanical Design 121, no. 2 (June 1, 1999): 297–304. http://dx.doi.org/10.1115/1.2829457.

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Design and manufacturing firms are under significant pressure to simultaneously increase product complexity, reduce design cycles, decrease cost, and improve quality. A key enabler to reduce cost without sacrificing quality is the control of variation during both design and manufacturing. The best time to reduce the impact of variation is in the early stages of design. This paper presents a tool set used to identify, early in the design process, where variation will have significant impact on the final cost and quality of a product. It presents the design team with a graphical view of variation risk, enabling them to quickly identify high-risk areas. The uncertainty about process capability and risk is also quantified and presented to the user.
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Landström, Catharina, and Sarah J. Whatmore. "Virtually Expert: Modes of Environmental Computer Simulation Modeling." Science in Context 27, no. 4 (November 13, 2014): 579–603. http://dx.doi.org/10.1017/s0269889714000210.

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ArgumentThis paper challenges three assumptions common in the literature on expertise: that expertise is linearly derived from scientific knowledge; that experts always align with the established institutional order; and that expertise is a property acquired by individuals. We criticize these ideas by juxtaposing three distinct expert practices involved with flood risk management in England. Virtual engineering is associated with commercial consultancy and relies on standardized software packages to assess local flood inundation. Mathematical experimentation refers to academic scientists creating new digital renderings of the physical dynamics of flooding. Participatory modeling denotes research projects that aim to transform the relationships between experts and local communities. Focusing on different modes of modeling we contribute an analysis of how particular models articulate with specific politics of knowledge as experts form relationships with flood risk management actors. Our empirical study also shows how models can contribute to re-distribution of expertise in local flood risk management.
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Kok, Bethany E., Declan Dagger, Conor Gaffney, and Austin Kenny. "Experiential Learning at Scale with Computer-Based Roleplay Simulations." International Journal of Advanced Corporate Learning (iJAC) 11, no. 2 (December 19, 2018): 24. http://dx.doi.org/10.3991/ijac.v11i2.9364.

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<p class="0BodyText">Experiential learning is an effective method for changing behavior and teaching new material at work. Unfortunately, experiential learning is difficult to deliver at scale as it requires hands-on participation and interactivity.</p><p class="0BodyText">EmpowerTheUser (ETU)’s computer-based roleplay simulations enable experiential learning at scale. In a simulation, learners take on a role and have to react to various situations and make choices that have downsteam consequences. ETU Simulations engage the learner in cycles of assessment and practice, with summative scoring in the assessment mode and real time coaching and feedback in the practice mode. </p><p class="0BodyText">ETU partnered with one of the oldest custodian banks headquartered in New York to deliver a series of three simulations on risk management to nearly 6,000 managers on five continents. User feedback shows that learners are highly satisfied with the program. Performance improved from simulation I to simulation II, indicating transfer of learning. Underperforming learners were remediated using the assess/practice/assess learning loop, resulting in a 227% improvement in performance.</p><p class="0BodyText">EmpowerTheUser Simulations provided fast, consistent training in risk management. Feedback was overwhelmingly favorable and decision tracking within the simulations demonstrated effective learning.</p>
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Lamé, Guillaume, and Rebecca K. Simmons. "From behavioural simulation to computer models: how simulation can be used to improve healthcare management and policy." BMJ Simulation and Technology Enhanced Learning 6, no. 2 (October 20, 2018): 95–102. http://dx.doi.org/10.1136/bmjstel-2018-000377.

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Simulation is a technique that evokes or replicates substantial aspects of the real world, in order to experiment with a simplified imitation of an operations system, for the purpose of better understanding and/or improving that system. Simulation provides a safe environment for investigating individual and organisational behaviour and a risk-free testbed for new policies and procedures. Therefore, it can complement or replace direct field observations and trial-and-error approaches, which can be time consuming, costly and difficult to carry out. However, simulation has low adoption as a research and improvement tool in healthcare management and policy-making. The literature on simulation in these fields is dispersed across different disciplinary traditions and typically focuses on a single simulation method. In this article, we examine how simulation can be used to investigate, understand and improve management and policy-making in healthcare organisations. We develop the rationale for using simulation and provide an integrative overview of existing approaches, using examples of in vivo behavioural simulations involving live participants, pure in silico computer simulations and intermediate approaches (virtual simulation) where human participants interact with computer simulations of health organisations. We also discuss the combination of these approaches to organisational simulation and the evaluation of simulation-based interventions.
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Frolova, Nina, Valery Larionov, Jean Bonnin, Sergey Suchshev, Alexander Ugarov, and Nataliya Malaeva. "Impact database application for natural and technological risk management." Natural Hazards and Earth System Sciences 20, no. 1 (January 13, 2020): 95–106. http://dx.doi.org/10.5194/nhess-20-95-2020.

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Abstract. Impact database development and application for risk analysis and management promote the usage of self-learning computer systems with elements of artificial intelligence. Such system learning could be successful when the databases store the complete information about each event, parameters of the simulation models, the range of its application, and residual errors. Each new description included in the database could increase the reliability of the results obtained with application of simulation models. The calibration of mathematical models is the first step to self-learning of automated systems. The article describes the events' database structure and examples of calibrated computer models as applied to the impact of expected emergencies and risk indicator assessment. Examples of database statistics usage in order to rank the subjects of the Russian Federation by the frequency of emergencies of different character as well as risk indicators are given.
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Landström, Catharina, Sarah J. Whatmore, and Stuart N. Lane. "Virtual Engineering." Science & Technology Studies 24, no. 2 (January 1, 2011): 3–22. http://dx.doi.org/10.23987/sts.55261.

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This paper discusses computer simulation modelling in the context of environmental risk management. Approaching computer simulation as practice, performed in networks of heterogeneous elements, we examine the modelling undertaken by engineering consultants commissioned to provide knowledge about local flood risk to the Environment Agency of England and Wales (EA), the public body responsible for flood risk management. We propose that this simulation modelling is best understood as a form of engineering, work geared to solving the problems of clients. It is also a ‘virtual’ activity, articulating risks and possibilities in the digital space of the computer. We find that this ‘virtual engineering’ is shaped by the demands and protocols of the EA, first, by the establishment of long-term contractual agreements for delivering knowledge and second, by an EA requirement to use particular software packages. Fashioned between long-term contracts and black-boxed software virtual engineering becomes stabilised as ‘the’ way in which knowledge about flood risk in actual localities is generated and, consequently, becomes ‘hard-wired’ into flood risk management in England.
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Shao, Xin Peng, Hui Ji, Shu Ming Yan, Qi Qian Li, Ning Jia, Min Jing, Liang Ma, Kun Jing, Ya Ping Liang, and Hai Xia Yu. "Correlation Analysis of Computer Simulation with Full-Scale Impact Test for Barrier Safety Evaluation." Applied Mechanics and Materials 94-96 (September 2011): 2092–101. http://dx.doi.org/10.4028/www.scientific.net/amm.94-96.2092.

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In order to analyze the feasibility of barrier safety performance evaluation with computer simulation method, finite-element models of various vehicles and barriers were set up and simulations results are compared to multiple full-scale impact test data. The results indicate that all safety performance index such as vehicle trajectory, structural adequacy, occupant risk and dynamic deformation can be extracted from computer simulation and FEA results are coincident with those of tests with error less than 10%. Computer simulation method is proved to be highly feasible for safety performance evaluation of barriers. The concept that simulation models must be verified through tests is stressed and the suggestion that laws and regulations on professional audit and management of CAE engineers should be completed is brought out.
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Dissertations / Theses on the topic "Risk management Computer simulation"

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Wray, Vicki Lorraine. "Cattle price risk management strategies-using computer simulation to educate Iowa producers of available tools." Thesis, Manhattan, Kan. : Kansas State University, 2008. http://hdl.handle.net/2097/759.

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Reddy, Praneel. "Cognitive Biases, Volatility, and Risk in Capital Markets: Revealing Risk through Simulation." Diss., The University of Arizona, 2011. http://hdl.handle.net/10150/202772.

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The modeling of financial risk, whose shortcomings came to the fore during the financial crisis, generally understands risk from the history of prices and returns. However, the state space of risk is not fully revealed from the history of prices and returns. In this dissertation, certain cognitive biases were modeled, and the simulation results were quantitatively characterized to reveal risk not revealed from the history of prices and returns. This contribution adds to the extant literature on the modeling of financial risk by showing how to reveal parts of the state space of risk not revealed from other methods in use today.
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Carlsson, Elin, and Moa Mattsson. "The MaRiQ model: A quantitative approach to risk management." Thesis, Uppsala universitet, Avdelningen för datalogi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-385257.

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In recent years, cyber attacks and data fraud have become major issues to companies, businesses and nation states alike. The need for more accurate and reliable risk management models is therefore substantial. Today, cybersecurity risk management is often carried out on a qualitative basis, where risks are evaluated to a predefined set of categories such as low, medium or high. This thesis aims to challenge that practice, by presenting a model that quantitatively assesses risks - therefore named MaRiQ (Manage Risks Quantitatively). MaRiQ was developed based on collected requirements and contemporary literature on quantitative risk management. The model consists of a clearly defined flowchart and a supporting tool created in Excel. To generate scientifically validated results, MaRiQ makes use of a number of statistical techniques and mathematical functions, such as Monte Carlo simulations and probability distributions. To evaluate whether our developed model really was an improvement compared to current qualitative processes, we conducted a workshop at the end of the project. The organization that tested MaRiQexperienced the model to be useful and that it fulfilled most of their needs. Our results indicate that risk management within cybersecurity can and should be performed using more quantitative approaches than what is praxis today. Even though there are several potential developments to be made, MaRiQ demonstrates the possible advantages of transitioning from qualitative to quantitative risk management processes.
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Ayres, Kelley. "Simulation models of bank risk management." Thesis, Kansas State University, 2015. http://hdl.handle.net/2097/18969.

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Master of Agribusiness
Department of Agricultural Economics
Bryan Schurle
Quantifying the impact of various economic events is essential for risk management in community banks. Interest rate shocks of either rapidly increasing or decreasing rates, in magnitudes of at least 200 basis points, is one of the more common risks modeled. Liquidity crises that impact deposits or loan demand can arise from either local or national economic events is another risk factor that regulators are requiring banks to quantify and plan for. Excel spreadsheets can be used to develop models to measure and quantify these risks. Simulation tools and what-if analysis using data table and scenario manager identify possible outcomes for differing interest rate scenarios, interest rate shocks and liquidity stresses. Data table was used for simulation of a stochastic model to produce a cumulative distribution function of two hundred results each on three different interest rate environments. Scenario manager was used to narrow the simulation to a certain set of expectations affecting the balance sheet of the bank and another set of expectations from an interest rate shock. Changes in the bank’s balance sheet resulting from three different commodity price expectations were modeled. An interest rate shock of four hundred basis points over a two year period was also modeled. These models are simple and cost effective. Once data are captured, the time required to develop and generate scenarios is manageable. The model can be used for a wide range of what-if alternatives as an individual bank may see fit. These models are adequate to meet present regulatory requirements for a community bank of smaller size that is not complex and does not possess a high risk profile.
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Tena-Chollet, Florian. "Elaboration d'un environnement semi-virtuel de formation à la gestion stratégique de crise, basé sur la simulation multi-agents." Phd thesis, Ecole Nationale Supérieure des Mines de Saint-Etienne, 2012. http://tel.archives-ouvertes.fr/tel-00741941.

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Les crises projettent la plupart du temps le décideur sur une durée plus ou moins longue dans l'urgence de la décision, avec l'obligation de minimiser les conséquences possibles sur les enjeux. Une équipe de gestion de crise est organisée en cellule et a pour objectif de construire des stratégies de réponse concertées et appropriées. Or, il s'avère que certaines des compétences nécessaires ne peuvent être acquises que par expérience. Ce travail s'attache ainsi à améliorer les processus de formation des décisionnaires en définissant, suivant quatre étapes, un environnement semi-virtuel de formation à la gestion stratégique de crise. Une phase de conception sert tout d'abord de point de départ au cahier des charges d'une implantation physique, d'une ingénierie système et d'une ingénierie pédagogique dédiées. Puis, une étape de modélisation d'un exercice de gestion de crise structure une méthodologie visant à définir les objectifs pédagogiques retenus, et propose une méthode appliquée de génération semi-automatique d'un scénario didactique. Une attention particulière est notamment portée sur l'élaboration d'une typologie d'évènements et d'éléments logiciels permettant la simulation multi-agents de crises virtualisées. Enfin, une méthodologie d'évaluation des participants est proposée dans le but d'enrichir la phase classique de débriefing. Seize indicateurs sont définis et permettent en particulier de construire des arbres de compétences. Une phase de validation porte sur trois de ces quatre axes méthodologiques, et il est montré que les premiers résultats obtenus tendent à valider les spécifications retenues pour l'environnement semi-virtuel de formation développé.
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Al-Shawi, S. N. A. "Management cybernetics : computer simulation models of operational management organizations." Thesis, Brunel University, 1986. http://bura.brunel.ac.uk/handle/2438/5015.

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Cybernetics is the science of effective organization, i.e. the science that describes the general principles of growth, learning and adaptation in complex, dynamical systems. Stafford Beer regards his viable system model as a design for effective formal organization. He also declares that since his model is explicitly based upon the principles of cybernetics, it facilitates consideration of what is and is not possible within formal organizations and provides guidance in creating efficient structures. The purpose of this research is to demonstrate and test Stafford Beer's ideas on the viable system model via the simulation of certain business activities. A methodology for getting access to the cybernetic body of knowledge is given as well as examples of cybernetic laws relevant to managerial and business practice. An important part of the work is devoted to the explanation and discussion of Stafford Beer's viable system model, and the importance it represents as a cybernetic method for the design of organizational structures. Simulation models incorporating the major activities of a business firm are represented and used as case studies to investigate how basic industrial organizations based on Beer's viable system model work under operational conditions.
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List, Hans-Fredo. "Limited risk arbitrage investment management." Thesis, Imperial College London, 1996. http://hdl.handle.net/10044/1/8651.

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Koskela, Niklas, and Carolina Aspfjäll. "Agile Risk Management." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-44975.

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This thesis was done in collaboration with Volvo Cars to inspect their risk management process in light of their recent change to an agile way of working. The question was if their actual risk management differentiates from their directive and if the company could in any way improve their agile risk management. By having qualitative semi-structured interviews with employees in the IT section of the company, we got the picture that not many knew about the IT Risk Management Directive that explains the process, but they are still working within its guidelines. Other sections of the company that is still working traditionally might also benefit from changing to an agile way. However, that would depend on the size of their projects and what kind of work they do since the agile methodology is more turned towards smaller projects that can change direction quickly.
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Aryal, Babu Ram. "Developing the computer simulation model of buzz electronics simulation." Online version, 2009. http://www.uwstout.edu/lib/thesis/2009/2009aryalb.pdf.

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Hong, Seng-Phil. "Data base security through simulation." Virtual Press, 1994. http://liblink.bsu.edu/uhtbin/catkey/902465.

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This research explores the complexities of database security, encompassing both the computer hardware and software. Also important is its nature as a people oriented issue. A risk analysis of a database system's security can be examined by creating a simulation model. Though, in order for it to be truly meaningful and accurate, all aspects of design, performance and procedure must be thoroughly and carefully scrutinized.Computer or data security is a major problem in today's world of data processing. This thesis outlines the security problem' and presents trends and issues. It also addresses current trends in computer security environments, database risk analysis, and simulations.Risk analysis is a technique used to quantitatively assess the relative value of protective measures. It is useful when appropriately applied and is in some cases required by regulatory agencies.The goal of security environments is to outline the framework which is valuable in assessing security issues and in establishing partitions in the overall environment within which this and other approaches to security can be examined.A simulation prototype is given which demonstrates the concepts of risk analysis for a database system.
Department of Computer Science
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Books on the topic "Risk management Computer simulation"

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Getts, Gregory B. Portfolio risk management: A computer simulation for stock and options. Reading, Mass: Addison-Wesley Pub. Co., 1989.

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International Emergency Management and Engineering Conference (1992 Orlando, Fla.). Proceedings of the 1992 International Emergency Management and Engineering Conference: Managing risk with computer simulation, April 6-9, 1992, Sheraton World Resorts, Orlando, Florida. San Diego, Calif: Society for Computer Simulation, 1992.

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Computer simulation in financial risk management: A guide for business planners and strategists. New York: Quorum Books, 1991.

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Dailami, Mansoor. INFRISK: A computer simulation approach to risk management in infrastructure project finance transactions. Washington, DC: World Bank, 1999.

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Singh, G. Venturer: Micro based appraisal of risk. (Leeds): SAR Investment Properties, 1985.

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Bjornar, Solhaug, and Stølen Ketil, eds. Model-driven risk analysis: The CORAS approach. Berlin: Springer, 2010.

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Kukurić, Nebojša. Development of a decision support system for groundwater pollution assessment. Rotterdam: Balkema, 1999.

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Stephens, M. E. The SYVAC3-CC3 database management system: Volume 1 - description. Pinawa, Man: AECL, Whiteshell Laboratories, 1995.

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Dejan, Skanata, Byrd Daniel M, NATO Public Diplomacy Division, and NATO Science for Peace and Security Programme., eds. Computational models of risks to infrastructure. Amsterdam, Netherlands: IOS Press, 2007.

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Fernández, Juan F. Gómez. Maintenance Management in Network Utilities: Framework and Practical Implementation. London: Springer London, 2012.

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Book chapters on the topic "Risk management Computer simulation"

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Hatayama, Michinori, and Fuko Nakai. "Using Computer Simulation for Effective Tsunami Risk Communication." In Integrated Disaster Risk Management, 39–50. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-13-2318-8_3.

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Zhang, Li, Lu Wang, and Jianping Zhang. "A Computer Auditing Model of the Balance Sheet Parallel Simulation Based On Data Mining." In Computational Risk Management, 567–76. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-18387-4_62.

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Taillandier, Franck, and Patrick Taillandier. "Risk Management in Construction Project Using Agent-Based Simulation." In Communications in Computer and Information Science, 34–43. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07767-3_4.

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Chen, Hsin-Hung, Ben-Chang Shia, and Hsiu-Yu Lee. "A Comparative Analysis of Credit Risk Management Models for Banking Industry Using Simulation." In Communications in Computer and Information Science, 554–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23023-3_83.

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Ortiz-Barrios, Miguel, Genett Jiménez-Delgado, Sally McClean, and Giselle Polifroni-Avendaño. "Using Computer Simulation for Reducing the Appointment Lead-Time in a Public Pediatric Outpatient Department." In Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management. Healthcare Applications, 75–86. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-22219-2_6.

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Mori, Midori, and Noboru Kubo. "Ergonomics Study of Direct and Indirect Visibility Evaluation at Uncontrolled Intersections Based on Three-Dimensional Computer Simulation." In Digital Human Modeling and Applications in Health, Safety, Ergonomics, and Risk Management. Healthcare and Safety of the Environment and Transport, 70–77. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39173-6_9.

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Browne, Jim. "Simulation and Simulation Models." In Computer-Aided Production Management, 123–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-73318-5_8.

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Olson, David L., and Desheng Wu. "Simulation of Supply Chain Risk." In Enterprise Risk Management Models, 115–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-11474-8_9.

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Jacobson, Robert V., and Susan Baumes. "Quantitative Risk Assessment and Risk Management." In Computer Security Handbook, 62.1–62.26. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2015. http://dx.doi.org/10.1002/9781118820650.ch62.

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Roncalli, Thierry. "Monte Carlo Simulation Methods." In Handbook of Financial Risk Management, 787–891. Boca Raton : CRC Press, 2020. | Series: Chapman and Hall/CRC financial mathematics series: Chapman and Hall/CRC, 2020. http://dx.doi.org/10.1201/9781315144597-13.

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Conference papers on the topic "Risk management Computer simulation"

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Sonchan, Pontakorn, and Sakgasit Ramingwong. "ARMI 2.0: An online risk management simulation." In 2015 12th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON). IEEE, 2015. http://dx.doi.org/10.1109/ecticon.2015.7207043.

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Usmanova, Zlata, and Anna Khanova. "Risk Management of a Commercial Bank’s Project Portfolio through Simulation." In Proceedings of the Fourth Workshop on Computer Modelling in Decision Making (CMDM 2019). Paris, France: Atlantis Press, 2019. http://dx.doi.org/10.2991/ahcs.k.191206.011.

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Vojnovic, Djordje, and Mitja Kozuh. "THE BASIS FOR DEVELOPMENT OF ADVISORY SYSTEM FOR PLANT RISK MANAGEMENT." In Second International Forum on Expert System and Computer Simulation in Energy Engineering. Connecticut: Begellhouse, 1992. http://dx.doi.org/10.1615/ichmt.1992.intforumexpsyscompsimee.140.

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Yang, Yu, Yan Chen, and Hanxin Zhang. "Social Network Management of Safety Risk in Prefabricated Building Construction Based on Computer Simulation." In AIAM2021: 2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3495018.3495060.

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Vojnovic, Djordje, and Mitja Kozuh. "The Basis for Development of Advisory System for Plant Risk Management." In Expert Systems and Computer Simulation in Energy Engineering: Selected Papers from the Second International Forum. Connecticut: Begellhouse, 1992. http://dx.doi.org/10.1615/ichmt.1992.expsystcomputsimenergengin.160.

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Kostopoulos, D., G. Leventakis, Vasilis Tsoulkas, and N. Nikitakos. "An Intelligent Fault Monitoring and Risk Management Tool for Complex Critical Infrastructures: The SERSCIS Approach in Air-Traffic Surface Control." In 2012 UKSim 14th International Conference on Computer Modelling and Simulation (UKSim). IEEE, 2012. http://dx.doi.org/10.1109/uksim.2012.37.

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Liu, Wei, Mujin Yuan, and Hong Zhou. "The Evaluation System of the Social Development Risk Based on the Factor Analysis and Monte Carlo Simulation." In 2011 International Conference on Information Technology, Computer Engineering and Management Sciences (ICM). IEEE, 2011. http://dx.doi.org/10.1109/icm.2011.48.

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Ibrahim, Ilham H., and Constantin Chassapis. "Quantitative Assessment of the Risk of Variations During Medical Device Lifecycle." In ASME 2013 Conference on Frontiers in Medical Devices: Applications of Computer Modeling and Simulation. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/fmd2013-16109.

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The majority of medical devices are monitoring devices. Therefore, data communication and analysis are playing a crucial rule in predicting the effectiveness and reliability of a device. Device related data, patient related data and device-patient related data stored in Data Bases (DBs) are great sources for enhancing either new designs or improving already existing ones. Analyzing such data can provide researchers and device development teams with a complete justification and patterns of interest about a device’s performance, life and reliability. Data can be formulated into stochastic models based their statistical characteristics to consider the variability in data and the uncertainty about processes and procedures during early stages of the design process. This strengthens the device’s ability to function under a broader range of operating conditions. The work herein aims at targeting unwanted variations in device performance during the device development process. It employs a novel technique for variation risk management of device performance based historical process data modeling and visualization. The introduced technique is a proactive systematic procedure comprises a tool set that is being placed in the larger framework of the risk management procedure and fully utilizing data from the DBs to predict and address the risk of variations at the early stages of the design process rather than at the end of each major stage.
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Wang, Junmei, Lin Guo, Chao Ma, Chuncheng Gao, Dunnan Liu, and Mo Yang. "The provincial power grid monthly purchasing risk management model based on Monte-Carlo stochastic simulation technology and wind power uncertainty." In 2016 6th International Conference on Machinery, Materials, Environment, Biotechnology and Computer. Paris, France: Atlantis Press, 2016. http://dx.doi.org/10.2991/mmebc-16.2016.323.

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Voza´r, Pavol, Vladimi´r Sleza´k, and Kamil Krava´rik. "Advanced 3D Modeling and Simulation Techniques for Decommissioning of A-1 NPP." In ASME 2003 9th International Conference on Radioactive Waste Management and Environmental Remediation. ASMEDC, 2003. http://dx.doi.org/10.1115/icem2003-4762.

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This paper deals with advanced 3D computer-aided technologies used for modelling and simulation for decommissioning purposes. Within the A-1 NPP decommissioning process a set of activities is needed to perform successful dismantling and decontamination of rooms and equipment. Optimal process of performance of D&D of underground storage tanks and auxiliary rooms were used on the base of simulation outputs. The mockup tests were performed before using remotely controlled manipulators. The human presence during decontamination and dismantling is case by case excluded due to the radiation safety and ALARA approach. Within Bohunice A-1 Decommissioning Project an advanced computer-aided technologies were/are developed and used. Modelling software packages EUCLID and 3Dipsos together with 3D-laser scanner SOISIC are used for creating of 3D models and also for the verification of as-built state of selected systems and facilities. Software IGRIP is used for computer simulations of all D&D tasks. The 3D modelling and simulation of selected rooms and technological equipment of the A-1 NPP are used consequently in the process of decommissioning preparation and implementation. 3D modelling for the verification and simulation of operating steps is presented in the paper and its contribution to avoiding of collisions and non-optimal interventions into the building and technological parts during performing particular works is evaluated. The application of 3D models for the verification and simulation of operating steps significantly contribute to the optimal planning of D&D procedures. Minimisation of occupation doses of realisation personnel is main reason why the 3D modelling and simulations are used. The paper also presented 3D models of rooms chosen to simulate specific operations (decontamination, handling of radioactive wastes and/or dismantling by remote controlled manipulators) without risk accident, high dose rates of personnel etc. Process of selection of optimal operating procedure for decontamination and dismantling is presented as well as achieved experiences and recommendations for further work.
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Reports on the topic "Risk management Computer simulation"

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Melby, Jeffrey, Thomas Massey, Abigail Stehno, Norberto Nadal-Caraballo, Shubhra Misra, and Victor Gonzalez. Sabine Pass to Galveston Bay, TX Pre-construction, Engineering and Design (PED) : coastal storm surge and wave hazard assessment : report 1 – background and approach. Engineer Research and Development Center (U.S.), September 2021. http://dx.doi.org/10.21079/11681/41820.

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The US Army Corps of Engineers, Galveston District, is executing the Sabine Pass to Galveston Bay Coastal Storm Risk Management (CSRM) project for Brazoria, Jefferson, and Orange Counties regions. The project is currently in the Pre-construction, Engineering, and Design phase. This report documents coastal storm water level and wave hazards for the Port Arthur CSRM structures. Coastal storm water level (SWL) and wave loading and overtopping are quantified using high-fidelity hydrodynamic modeling and stochastic simulations. The CSTORM coupled water level and wave modeling system simulated 195 synthetic tropical storms on three relative sea level change scenarios for with- and without-project meshes. Annual exceedance probability (AEP) mean values were reported for the range of 0.2 to 0.001 for peak SWL and wave height (Hm0) along with associated confidence limits. Wave period and mean wave direction associated with Hm0 were also computed. A response-based stochastic simulation approach is applied to compute AEP runup and overtopping for levees and overtopping, nappe geometry, and combined hydrostatic and hydrodynamic fluid pressures for floodwalls. CSRM structure crest design elevations are defined based on overtopping rates corresponding to incipient damage. Survivability and resilience are evaluated. A system-wide hazard level assessment was conducted to establish final recommended system-wide CSRM structure elevations.
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Stehno, Abigail, Jeffrey Melby, Shubhra Misra, Norberto Nadal-Caraballo, and Victor Gonzalez. Sabine Pass to Galveston Bay, TX Pre-construction, Engineering and Design (PED) : coastal storm surge and wave hazard assessment : report 2 – Port Arthur. Engineer Research and Development Center (U.S.), September 2021. http://dx.doi.org/10.21079/11681/41901.

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The US Army Corps of Engineers, Galveston District, is executing the Sabine Pass to Galveston Bay Coastal Storm Risk Management (CSRM) project for Brazoria, Jefferson, and Orange Counties regions. The project is currently in the Pre-construction, Engineering, and Design phase. This report documents coastal storm water level and wave hazards for the Port Arthur CSRM structures. Coastal storm water level (SWL) and wave loading and overtopping are quantified using high-fidelity hydrodynamic modeling and stochastic simulations. The CSTORM coupled water level and wave modeling system simulated 195 synthetic tropical storms on three relative sea level change scenarios for with- and without-project meshes. Annual exceedance probability (AEP) mean values were reported for the range of 0.2 to 0.001 for peak SWL and wave height (Hm0) along with associated confidence limits. Wave period and mean wave direction associated with Hm0 were also computed. A response-based stochastic simulation approach is applied to compute AEP values for overtopping for levees and overtopping, nappe geometry, and combined hydrostatic and hydrodynamic fluid pressures for floodwalls. CSRM crest design elevations are defined based on overtopping rates corresponding to incipient damage. Survivability and resilience are evaluated. A system-wide hazard level assessment was conducted to establish final recommended system-wide elevations.
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Stehno, Abigail, Jeffrey Melby, Shubhra Misra, Norberto Nadal-Caraballo, and Victor Gonzalez. Sabine Pass to Galveston Bay, TX Pre-construction, Engineering and Design (PED) : coastal storm surge and wave hazard assessment : report 4 – Freeport. Engineer Research and Development Center (U.S.), September 2021. http://dx.doi.org/10.21079/11681/41903.

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The US Army Corps of Engineers, Galveston District, is executing the Sabine Pass to Galveston Bay Coastal Storm Risk Management (CSRM) project for Brazoria, Jefferson, and Orange Counties regions. The project is currently in the Pre-construction, Engineering, and Design phase. This report documents coastal storm water level (SWL) and wave hazards for the Freeport CSRM structures. Coastal SWL and wave loading and overtopping are quantified using high-fidelity hydrodynamic modeling and stochastic simulations. The CSTORM coupled water level and wave modeling system simulated 195 synthetic tropical storms on three relative sea level change scenarios for with- and without-project meshes. Annual exceedance probability (AEP) mean values were reported for the range of 0.2 to 0.001 for peak SWL and wave height (Hm0) along with associated confidence limits. Wave period and mean wave direction associated with Hm0 were also computed. A response-based stochastic simulation approach is applied to compute AEP values for overtopping for levees and overtopping, nappe geometry and combined hydrostatic and hydrodynamic fluid pressures for floodwalls. CSRM crest design elevations are defined based on overtopping rates corresponding to incipient damage. Survivability and resilience are evaluated. A system-wide hazard level assessment was conducted to establish final recommended system-wide elevations.
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Stehno, Abigail, Jeffrey Melby, Shubhra Misra, Norberto Nadal-Caraballo, and Victor Gonzalez. Sabine Pass to Galveston Bay, TX Pre-construction, Engineering and Design (PED) : coastal storm surge and wave hazard assessment : report 3 – Orange County. Engineer Research and Development Center (U.S.), September 2021. http://dx.doi.org/10.21079/11681/41902.

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The US Army Corps of Engineers, Galveston District, is executing the Sabine Pass to Galveston Bay Coastal Storm Risk Management (CSRM) project for Brazoria, Jefferson, and Orange Counties regions. The project is currently in the Pre-construction, Engineering, and Design phase. This report documents coastal storm water level (SWL) and wave hazards for the Orange County CSRM structures. Coastal SWL and wave loading and overtopping are quantified using high-fidelity hydrodynamic modeling and stochastic simulations. The CSTORM coupled water level and wave modeling system simulated 195 synthetic tropical storms on three relative sea level change scenarios for with- and without-project meshes. Annual exceedance probability (AEP) mean values were reported for the range of 0.2 to 0.001 for peak SWL and wave height (Hm0) along with associated confidence limits. Wave period and mean wave direction associated with Hm0 were also computed. A response-based stochastic simulation approach is applied to compute AEP values for overtopping for levees and overtopping, nappe geometry, and combined hydrostatic and hydrodynamic fluid pressures for floodwalls. CSRM crest design elevations are defined based on overtopping rates corresponding to incipient damage. Survivability and resilience are evaluated. A system-wide hazard level assessment was conducted to establish final recommended system-wide elevations.
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Semerikov, Serhiy, Illia Teplytskyi, Yuliia Yechkalo, Oksana Markova, Vladimir Soloviev, and Arnold Kiv. Computer Simulation of Neural Networks Using Spreadsheets: Dr. Anderson, Welcome Back. [б. в.], June 2019. http://dx.doi.org/10.31812/123456789/3178.

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The authors of the given article continue the series presented by the 2018 paper “Computer Simulation of Neural Networks Using Spreadsheets: The Dawn of the Age of Camelot”. This time, they consider mathematical informatics as the basis of higher engineering education fundamentalization. Mathematical informatics deals with smart simulation, information security, long-term data storage and big data management, artificial intelligence systems, etc. The authors suggest studying basic principles of mathematical informatics by applying cloud-oriented means of various levels including those traditionally considered supplementary – spreadsheets. The article considers ways of building neural network models in cloud-oriented spreadsheets, Google Sheets. The model is based on the problem of classifying multi-dimensional data provided in “The Use of Multiple Measurements in Taxonomic Problems” by R. A. Fisher. Edgar Anderson’s role in collecting and preparing the data in the 1920s-1930s is discussed as well as some peculiarities of data selection. There are presented data on the method of multi-dimensional data presentation in the form of an ideograph developed by Anderson and considered one of the first efficient ways of data visualization.
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Shani, Uri, Lynn Dudley, Alon Ben-Gal, Menachem Moshelion, and Yajun Wu. Root Conductance, Root-soil Interface Water Potential, Water and Ion Channel Function, and Tissue Expression Profile as Affected by Environmental Conditions. United States Department of Agriculture, October 2007. http://dx.doi.org/10.32747/2007.7592119.bard.

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Constraints on water resources and the environment necessitate more efficient use of water. The key to efficient management is an understanding of the physical and physiological processes occurring in the soil-root hydraulic continuum.While both soil and plant leaf water potentials are well understood, modeled and measured, the root-soil interface where actual uptake processes occur has not been sufficiently studied. The water potential at the root-soil interface (yᵣₒₒₜ), determined by environmental conditions and by soil and plant hydraulic properties, serves as a boundary value in soil and plant uptake equations. In this work, we propose to 1) refine and implement a method for measuring yᵣₒₒₜ; 2) measure yᵣₒₒₜ, water uptake and root hydraulic conductivity for wild type tomato and Arabidopsis under varied q, K⁺, Na⁺ and Cl⁻ levels in the root zone; 3) verify the role of MIPs and ion channels response to q, K⁺ and Na⁺ levels in Arabidopsis and tomato; 4) study the relationships between yᵣₒₒₜ and root hydraulic conductivity for various crops representing important botanical and agricultural species, under conditions of varying soil types, water contents and salinity; and 5) integrate the above to water uptake term(s) to be implemented in models. We have made significant progress toward establishing the efficacy of the emittensiometer and on the molecular biology studies. We have added an additional method for measuring ψᵣₒₒₜ. High-frequency water application through the water source while the plant emerges and becomes established encourages roots to develop towards and into the water source itself. The yᵣₒₒₜ and yₛₒᵢₗ values reflected wetting and drying processes in the rhizosphere and in the bulk soil. Thus, yᵣₒₒₜ can be manipulated by changing irrigation level and frequency. An important and surprising finding resulting from the current research is the obtained yᵣₒₒₜ value. The yᵣₒₒₜ measured using the three different methods: emittensiometer, micro-tensiometer and MRI imaging in both sunflower, tomato and corn plants fell in the same range and were higher by one to three orders of magnitude from the values of -600 to -15,000 cm suggested in the literature. We have added additional information on the regulation of aquaporins and transporters at the transcript and protein levels, particularly under stress. Our preliminary results show that overexpression of one aquaporin gene in tomato dramatically increases its transpiration level (unpublished results). Based on this information, we started screening mutants for other aquaporin genes. During the feasibility testing year, we identified homozygous mutants for eight aquaporin genes, including six mutants for five of the PIP2 genes. Including the homozygous mutants directly available at the ABRC seed stock center, we now have mutants for 11 of the 19 aquaporin genes of interest. Currently, we are screening mutants for other aquaporin genes and ion transporter genes. Understanding plant water uptake under stress is essential for the further advancement of molecular plant stress tolerance work as well as for efficient use of water in agriculture. Virtually all of Israel’s agriculture and about 40% of US agriculture is made possible by irrigation. Both countries face increasing risk of water shortages as urban requirements grow. Both countries will have to find methods of protecting the soil resource while conserving water resources—goals that appear to be in direct conflict. The climate-plant-soil-water system is nonlinear with many feedback mechanisms. Conceptual plant uptake and growth models and mechanism-based computer-simulation models will be valuable tools in developing irrigation regimes and methods that maximize the efficiency of agricultural water. This proposal will contribute to the development of these models by providing critical information on water extraction by the plant that will result in improved predictions of both water requirements and crop yields. Plant water use and plant response to environmental conditions cannot possibly be understood by using the tools and language of a single scientific discipline. This proposal links the disciplines of soil physics and soil physical chemistry with plant physiology and molecular biology in order to correctly treat and understand the soil-plant interface in terms of integrated comprehension. Results from the project will contribute to a mechanistic understanding of the SPAC and will inspire continued multidisciplinary research.
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Alt, Jonathan, Willie Brown, George Gallarno, John Richards, and Titus Rice. Risk-based prioritization of operational condition assessments : Jennings Randolph case study. Engineer Research and Development Center (U.S.), April 2022. http://dx.doi.org/10.21079/11681/43862.

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The US Army Corps of Engineers (USACE) operates, maintains, and manages over $232 billion worth of the Nation’s water resource infrastructure. Using Operational Condition Assessments (OCA), the USACE allocates limited resources to assess asset condition in efforts to minimize risks associated with asset performance degradation, but decision makers require a greater understanding of those risks. The analysis of risk associated with Flood Risk Management assets in the context of its associated watershed system includes understanding the consequences of the asset’s failure and a determination of the likelihood that the asset will perform as expected given the current OCA ratings of critical components. This research demonstrates an application of a scalable methodology to model the probability of a dam performing as expected given the state of its subordinate gates and their components. The research team combines this likelihood with consequences generated by the application of designed simulation experiments with hydrological models to develop a measure of risk. The resulting risk scores serve as an input for an optimization program that outputs the optimal set of components to conduct OCAs on to minimize risk in the watershed. Proof-of-concept results for an initial case study on the Jennings Randolph Dam are provided.
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Alt, Jonathan, Willie Brown, George Gallarno, John Richards, Jennifer Olszewski, and Titus Rice. Risk-based prioritization of operational condition assessments : methodology and case study results. Engineer Research and Development Center (U.S.), November 2022. http://dx.doi.org/10.21079/11681/46123.

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USACE operates, maintains, and manages more than $232 billion of the Nation’s water resource infrastructure. USACE uses the Operational Condition Assessment (OCA) to allocate limited resources to assess condition of this infrastructure in efforts to minimize risks associated with performance degradation. The analysis of risk associated with flood risk management (FRM) assets includes consideration of how each asset contributes to its associated FRM watershed system, understanding the consequences of the asset’s performance degradation, and a determination of the likelihood that the asset will perform as expected given the current OCA condition ratings of critical components. This research demonstrates a proof-of-concept application of a scalable methodology to model the probability of a dam performing as expected given the state of its gates and their components. The team combines this likelihood of degradation with consequences generated by the application of designed simulation experiments with hydrological models to develop a risk measure. The resulting risk scores serve as an input for a mixed-integer optimization program that outputs the optimal set of components to conduct OCAs on to minimize risk in the watershed. This report documents the results of the application of this methodology to two case studies.
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Melby, Jeffrey, Thomas Massey, Fatima Diop, Himangshu Das, Norberto Nadal-Caraballo, Victor Gonzalez, Mary Bryant, et al. Coastal Texas Protection and Restoration Feasibility Study : Coastal Texas flood risk assessment : hydrodynamic response and beach morphology. Engineer Research and Development Center (U.S.), July 2021. http://dx.doi.org/10.21079/11681/41051.

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The US Army Corps of Engineers, Galveston District, is executing the Coastal Texas Protection and Restoration Feasibility Study coastal storm risk management (CSRM) project for the region. The project is currently in the feasibility phase. The primary goal is to develop CSRM measures that maximize national net economic development benefits. This report documents the coastal storm water level and wave hazard, including sea level rise, for a variety of flood risk management alternatives. Four beach restoration alternatives for Galveston Island and Bolivar peninsula were evaluated. Suites of synthetic tropical and historical non-tropical storms were developed and modeled. The CSTORM coupled surge-and-wave modeling system was used to accurately characterize storm circulation, water level, and wave hazards using new model meshes developed from high-resolution land and sub-aqueous surveys for with- and without-project scenarios. Beach morphology stochastic response was modeled with a Monte Carlo life-cycle simulation approach using the CSHORE morphological evolution numerical model embedded in the StormSim stochastic modeling system. Morphological and hydrodynamic response were primarily characterized with probability distributions of the number of rehabilitations and overflow.
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Khvostina, Inesa, Serhiy Semerikov, Oleh Yatsiuk, Nadiia Daliak, Olha Romanko, and Ekaterina Shmeltser. Casual analysis of financial and operational risks of oil and gas companies in condition of emergent economy. [б. в.], October 2020. http://dx.doi.org/10.31812/123456789/4120.

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The need to control the risk that accompanies businesses in their day- to-day operations, and at the same time changing economic conditions make risk management an almost indispensable element of economic life. Selection of the main aspects of the selected phases of the risk management process: risk identification and risk assessment are related to their direct relationship with the subject matter (risk identification to be managed; risk analysis leading to the establishment of a risk hierarchy, and, consequently, the definition of risk control’ methods) and its purpose (bringing the risk to acceptable level). It is impossible to identify the basic patterns of development of the oil and gas industry without exploring the relationship between economic processes and enterprise risks. The latter are subject to simulation, and based on models it is possible to determine with certain probability whether there have been qualitative and quantitative changes in the processes, in their mutual influence on each other, etc. The work is devoted to exploring the possibilities of applying the Granger test to examine the causal relationship between the risks and obligations of oil and gas companies. The analysis is based on statistical tests and the use of linear regression models.
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