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Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
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The link model is a fundamental pharmacokinetic-pharmacodynamic (PK–PD) approach to account for delayed drug responses when the observed effect does not immediately correlate with the drug's plasma concentration peak. This delay is mathematically addressed by introducing an effect compartment concentration, Ce, which is kinetically linked to the plasma concentration, Cp, via a first-order rate constant, ke0. The linkage allows for a more accurate prediction of drug effects over time. A...
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Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
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Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
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Risk Modeling of Interdependent Complex Systems of Systems: Theory and Practice.

Yacov Y Haimes1

  • 1L.R. Quarles Professor of Systems & Information Engineering, and of Civil & Environmental Engineering, Founding Director (1987), Center for Risk Management of Engineering Systems.

Risk Analysis : an Official Publication of the Society for Risk Analysis
|April 25, 2017
PubMed
Summary
This summary is machine-generated.

Current risk analysis models fail for complex systems of systems (SoS). Understanding shared states and interdependencies is key to developing effective risk assessment frameworks for emergent SoS.

Keywords:
Complex systems of systemsinterdepencency and interconnectednessrevised risk questions

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Area of Science:

  • Systems Engineering
  • Risk Management
  • Complexity Science

Background:

  • Modern systems of systems (SoS) exhibit emergent complexity.
  • Existing risk analysis models are inadequate for SoS due to their focus on single systems.
  • These models overlook the intricate interdependencies and interconnectedness (I-I) inherent in SoS.

Purpose of the Study:

  • To reevaluate risk analysis methodologies for complex SoS.
  • To comprehend the unique complexities of emergent SoS.
  • To develop a novel framework for modeling SoS risk.

Main Methods:

  • Building upon state-space theory.
  • Developing a theoretical and analytical framework for SoS risk modeling.
  • Conducting case studies with the MITRE Corporation.

Main Results:

  • Shared states and essential entities are pivotal in modeling SoS risk.
  • Demonstrated the contribution of shared states to risk analysis in complex SoS.
  • Highlighted the need to harmonize risk analysis for SoS with single-system approaches.

Conclusions:

  • A new framework based on state-space theory enhances SoS risk modeling.
  • Understanding interdependencies and shared states is crucial for SoS risk assessment.
  • Harmonizing risk analysis across different system complexities is essential.