A Framework for the Simulation-Based Selection of Social Models for Socio-Technical Models of Infrastructures Using Technical Requirements Analysis
- a Bernhard Jonathan Sattler ,
- b Jannik Stadler,
- c Andrea Tundis,
- d John Friesen,
- e Peter F. Pelz
- a,b,c Institute for the Protection of Terrestrial Infrastructures, German Aerospace Center (DLR), Rathausallee 12, Sankt Augustin, 53757, Germany
- d Chair of Fluid Systems, Technical University of Darmstadt, Otto-Berndt-Str. 2, Darmstadt, 64287, Germany
Cite as
Sattler, B.J., Stadler, J., Friesen, J., Tundis, A., Pelz, P.F. (2023). A Framework for the Simulation-Based Selection of Socio-Technical Models Using Technical Requirements Analysis. Proceedings of the 22nd International Conference on Modeling & Applied Simulation (MAS 2023).,010. DOI: https://doi.org/10.46354/i3m.2023.mas.010
Abstract
Urbanization increases the importance of urban infrastructures, with computer models and simulation being important tools for their planning and management. Human factors are increasingly included into infrastructure models, creating socio-technical models. This paper proposes a novel framework for selecting these social (sub-)models. For this, requirements analysis of the technical system is
used to identify critical physical parameters. The impact of different assumptions in the social model on the critical physical parameters are determined using simulation and hypothesis testing. This impact is used to determine the relevance of the differing assumptions and to select the right social model. Finally, a preliminary case study of the water distribution system of Darmstadt, Germany, is used to show the efficacy of the framework by comparing two water demand models. The results of the case study show, that the framework can be used to quantify the relevant system behavior and test the significance of model assumptions.
References
- Axtell, R., Axelrod, R., Epstein, J. M., and Cohen, M. D. (1996). Aligning simulation models: A case study and results. Computational & mathematical organization the ory, 1:123–141.
- Brucherseifer, E., Winter, H., Mentges, A., Mühlhäuser, M., and Hellmann, M. (2021). Digital twin concep tual framework for improving critical infrastructure resilience. at - Automatisierungstechnik, 69(12):1062– 1080.
- DIN Deutsches Institut für Normung e. V. (2000). Din en 805:2000-03: Water supply - requirements for systems and components outside buildings.
- DVGW Deutscher Verein des Gas- und Wasserfaches e.V. (2015). Dvgw w 400-1 (a): Technische regeln wasserverteilungsanlagen (trwv); teil 1: Planung.
- Edmonds, B. and Moss, S. (2005). From kiss to kids–an ‘anti-simplistic’modelling approach. In Multi-Agent and Multi-Agent-Based Simulation: Joint Workshop MABS 2004, New York, NY, USA, July 19, 2004, Revised Selected Papers 5, pages 130–144.
- Grimm, N. B., Faeth, S. H., Golubiewski, N. E., Redman, C. L., Wu, J., Bai, X., and Briggs, J. M. (2008). Global change and the ecology of cities. Science (New York, N.Y.), 319(5864):756–760.
- Healy, K. (2017). Fuck nuance. Sociological Theory, 35(2):118–127.
- Heinrichs, M. (2011). Tapas: Travel-activity-pattern simulation-parallelisiertes mikroskopisches verkehrsnachfragemodell. In Next GEneration Fo rum 2011, page 74.
- International Organization for Standardization (2007). Iso 24510:2007: Activities relating to drinking water and wastewater services — guidelines for the assessment and for the improvement of the service to users.
- International Organization for Standardization (2011). Sys tems and software engineering — systems and software quality requirements and evaluation (square) — evalu ation process.
- Klingel, P. (2018). Modellierung von Wasserverteilungssys temen. Springer Fachmedien Wiesbaden, Wiesbaden.
- Klise, K. A., Bynum, M., Moriarty, D., and Murray, R. (2017). A software framework for assessing the resilience of drinking water systems to disasters with an example earthquake case study. Environmental modelling & soft ware : with environment data news, 95:420–431.
- Logan, K. T., Leštáková, M., Thiessen, N., Engels, J. I., and Pelz, P. F. (2021). Water distribution in a socio-technical system: Resilience assessment for critical events caus ing demand relocation. Water, 13(15):2062.
- Ottens, M., Franssen, M., Kroes, P., and van de Poel, I. (2006). Modelling infrastructures as socio-technical systems. International journal of critical infrastructures, 2(2-3):133–145.
- Regierungspräsidium Darmstadt (2022). Wasserbilanz rhein-main 2021.
- Rehm, I.-S., Friesen, J., Pouls, K., Busch, C., Taubenböck, H., and Pelz, P. F. (2021). A method for modeling urban water infrastructures combining geo-referenced data. Water, 13(16):2299.
- Sattler, B. J., Friesen, J., Tundis, A., and Pelz, P. F. (2023). Modeling and validation of residential water demand in agent-based models: A systematic literature review. Water, 15(3):579.
- Molenda, P., Jugenheimer, A., Haefner, C., Oechsle, O., & Karat, R. (2019). Methodology for the visualization, analysis and assessment of information processes in manufacturing companies. Procedia CIRP, 84, 5–10. https://doi.org/10.1016/j.procir.2019.04.291
- Schwarz, N., Dressler, G., Frank, K., Jager, W., Janssen, M., Müller, B., Schlüter, M., Wijermans, N., and Groen eveld, J. (2019). Formalising theories of human decision making for agent-based modelling of social-ecological systems: practical lessons learned and ways forward. Socio-Environmental Systems Modelling, 2:16340.
- Todini, E. (2000). Looped water distribution networks design using a resilience index based heuristic approach. Urban Water, 2(2):115–122.
- van Dam, K. H., Nikolic, I., and Lukszo, Z. (2013). Agent based modelling of socio-technical systems, volume 9 of Agent-based social systems. Springer, Dordrecht.
- Vespignani, A. (2012). Modelling dynamical processes in complex socio-technical systems. Nature Physics, 8(1):32–39.
Volume Details
Volume Title
Proceedings of the 22nd International Conference on Modelling and Applied Simulation MAS 2023)
Conference Location and Date
Athens, Greece
September 18-20, 2023
Conference ISSN
2724-0037
Volume ISBN
978-88-85741-91-1
Volume Editors
Agostino G. Bruzzone
MITIM-DIME, University of Genoa, Italy
Francesco Longo
University of Calabria, Italy
Fabio De Felice
University of Cassino, Italy
Marina Massei
Liophant Simulation, Italy
Adriano Solis
York University, Canada
MAS 2023 Board
Adriano Solis
General Co-Chair
York University, Canada
Marina Massei
General Co-Chair
Liophant Simulation, Italy
Fabio De Felice
Program Co-Chair
University of Cassino, Italy
Copyright
© 2023 The Authors. The articles are open access and distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) license.