ResearchResearch Areas
Simulation for Transportation and Operations

Planning and Simulation for Optimal Design and Operations

© Ricardo Gomez Angel (CC0)

Design and operation of infrastructure do not only target at providing and maintaining a reliable service over a desired timeframe, but they also involve an optimal allocation and utilisation of resources for this purpose. Typically, optimal solutions are approached through complex multi-criteria decision-making processes. However, the derivation of rigorous solutions requires a realistic and efficient modelling and simulation not only of the infrastructure’s performance but also of its interaction with its environment and operators including all uncertainties and risks. A particular challenge for optimal resource allocation and risk control is the cross disciplinary nature of the problem, which requires a quantitative connection of the engineering performance and reliability analysis with economic, social and perhaps even political aspects. Besides technical matters, human behaviour and even cultural aspects need to be considered. Comprehensive monitoring and control concepts are part of this challenge.

We develop numerical approaches for optimal design and operations, which aim at rigorous and efficient solutions based on a combination of engineering, mathematical and computer-science concepts. Our multi-disciplinary solutions include physics-based models in association with stochastic simulation and machine learning approaches to form efficient numerical technologies for multi-criteria optimization. We complement this approach by analysing accidents to identify and eliminate critical issues, in particular with focus on human factors in design and operations. Our developments serve as decision-support technology for application by engineers as well as by stakeholders, operators or authorities.

The fields of application cover engineering system and structural design optimization and optimal maintenance scheduling, reduction of development time & costs using computer experiments, robust and reliable product life-cycle management, decision-making under uncertainty, health monitoring, project management, optimal traffic routing and navigation, logistics optimization, process control, risk communication and more.

We provide tailored solutions for a variety of problems from this spectrum and beyond.

SELECTED REFERENCES

  • Morais, C.; Moura, R.; Beer, M.; Patelli, E. (2020): Analysis and Estimation of Human Errors From Major Accident Investigation ReportsASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 6, 011014-1, 1–16.
    DOI: 10.1115/1.4044796
  • Nieto-Cerezo, O.; Wenzelburger, J.; Patelli, E.; Beer, M. (2020): Optimal regulation of the construction of reliable sea defencesASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 6(2), Article, 04020023, 1–12.
  • Salomon, J.; Broggi, M.; Kruse, S.; Weber, S.; Beer, M. (2019): Resilience Decision-Making Method For Complex SystemsASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 6(2), Article 020901. | File |
    DOI: 10.1115/1.4044907
  • Berthold, T.; Milbradt, P.; Berkhahn, V. (2018): Valid approximation of spatially distributed grain size distributions – A priori information encoded to a feedforward networkComputers & Geosciences, 113: 23–32.
    DOI: 10.1016/j.cageo.2018.01.007
  • Zhong, S.; Pantelous, A.A.; Beer, M.; Zhou, J. (2018): Constrained non-linear multi-objective optimisation of preventive maintenance scheduling for offshore wind farmsMechanical Systems and Signal Processing, 104: 347-369.
    DOI: 10.1016/j.ymssp.2017.10.035
  • Attarzadeh, M.; Chua, D.; Beer, M.; Abbott, E.L.S. (2017): Options-based negotiation management of PPP-BOT infrastructure projectsConstruction Management and Economics, 35(11–12), 676–692.
    DOI: 10.1080/01446193.2017.1325962
  • de Angelis, M.; Patelli, E.; Beer, M. (2017): Forced Monte Carlo Simulation Strategy for the Design of Maintenance Plans with Multiple InspectionsASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 3(2), D4016001, 1–9.
    DOI: 10.1061/AJRUA6.0000868
  • Moura, R.; Beer, M.; Patelli, E.; Lewis, J. (2017): Learning from major accidents: Graphical representation and analysis of multi-attribute events to enhance risk communicationSafety Science, Volume 99, Part A, Pages 58-70.
    DOI: 10.1016/j.ssci.2017.03.005
  • Moura, R.; Beer, M.; Patelli, E.; Lewis, J., Knoll, F. (2017): Learning from accidents: interactions between human factors, technology and organisations as a central element to validate risk studiesSafety Science, 99, 196–214.
    DOI: 10.1016/j.ssci.2017.05.001
  • Rinke, N.; von Gösseln, I.; Kochkine, V.; Schweitzer, J.; Berkhahn, V.; Berner, F.; Kutterer, H.; Neumann, I.; Schwieger, V. (2017): Simulating quality assurance and efficiency analysis between construction management and engineering geodesyAutomation in Construction, 76: 24-35.
    DOI: 10.1016/j.autcon.2017.01.009
  • Mitseas, I. P.; Kougioumtzoglou, I. A.; Beer, M. (2016): An approximate stochastic dynamics approach for nonlinear structural system performance-based multi-objective optimum designStructural Safety; 60: 67-76.
    DOI: 10.1016/j.strusafe.2016.01.003
  • Moura, R.; Beer, M.; Patelli, E.; Lewis, J.; Knoll, F. (2016): Learning from major accidents to improve system designSafety Science; 84: 37-45.
    DOI: 10.1016/j.ssci.2015.11.022
  • Schiermeyer, C.; Pascucci, F.; Rinke, N. (2016): A genetic algorithm approach for the calibration of a social force based model for shared spacesProceedings of Pedestrian and Evacuation Dynamics 2016, University of Science and Technology of China Press
  • Bode, M.; Berkhahn, V. (2014): Multiskalenansatz für reaktive Prozess- und AblaufplanungASIM 2014, 22. Symposium Simulationstechnik.
  • Rinke, N.; Gösseln, I.; Berkhahn, V. (2012): High-level Petri nets for modeling of geodetic processes and their integration into construction processesECPPM 2012 - eWork and eBusiness in Architecture, Engineering and Construction, Reykjavik.
  • Berkhahn, V.; Berner, F.; Kuttner, H.; Schwieger, V.; Hirschner, J.; Rehr, I.; Rinke, N.; Schweitzer, J. (2010): Effizienzoptimierung und Qualitätssicherung ingenieurgeodätischer Prozesse im HochbauBauingenieur; 85(11).
Prof. Dr.-Ing. Michael Beer
Professors
Address
Callinstraße 34
30167 Hannover
Building
Room
110
Prof. Dr.-Ing. Michael Beer
Professors
Address
Callinstraße 34
30167 Hannover
Building
Room
110
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