From Hybrid Simulation to Hybrid Systems Modelling

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this record.Hybrid Simulation (HS) is the combined application of simulation approaches like SD, DES and ABS in the model implementation stage of a simulation study. Its objective is to better represent the system under scrutiny. Hybrid Systems Modelling (HSM), on the other hand, is the combined application of simulation with methods and techniques from disciplines such as Applied Computing, Computer Science, Engineering and the wider OR. HSM can be applied to multiple stages of a simulation study. In this paper, we present a classification of HS and extend it to include HSM approaches which use simulation with other OR techniques. The paper contributes to the debate on what constitutes HS and offers a unifying conceptual representation for mixing simulation approaches with HSM methods and techniques

Construction and analysis of causally dynamic hybrid bond graphs

Engineering systems are frequently abstracted to models with discontinuous behaviour (such as a switch or contact), and a hybrid model is one which contains continuous and discontinuous behaviours. Bond graphs are an established physical modelling method, but there are several methods for constructing switched or ‘hybrid’ bond graphs, developed for either qualitative ‘structural’ analysis or efficient numerical simulation of engineering systems. This article proposes a general hybrid bond graph suitable for both. The controlled junction is adopted as an intuitive way of modelling a discontinuity in the model structure. This element gives rise to ‘dynamic causality’ that is facilitated by a new bond graph notation. From this model, the junction structure and state equations are derived and compared to those obtained by existing methods. The proposed model includes all possible modes of operation and can be represented by a single set of equations. The controlled junctions manifest as Boolean variables in the matrices of coefficients. The method is more compact and intuitive than existing methods and dispenses with the need to derive various modes of operation from a given reference representation. Hence, a method has been developed, which can reach common usage and form a platform for further study

A strategic study of energy efficient and hybrid energy system options for a multi-family building in Korea

This study is to identify performance of energy efficiency measures and to match low-carbon and renewable energy (RE) systems supplies to demands in the context of multi-family residential buildings in Korea. An approach to the evaluation of the hybrid energy systems was investigated, including consideration of heat and power demand profiles, energy system combinations, building design options and strategies for matching supply to demand. The approach is encapsulated within an integrated software environment. Building energy simulation technology was exploited to make virtual energy use data. Low-carbon and RE system modelling techniques were used to predict energy supply profiles. A series of demand/supply matching-based analyses were made to identify the effect of energy efficient demand measures (e.g. roof-top gardens, innovative underfloor heating system) and evaluate the capacity utilisation factor from the hybrid energy systems. On the basis of performance information obtained at the conceptual design stage, the design team can pinpoint the most energy efficient demand/supply combination, and consequently, maximise the impact of hybrid energy systems adoption

A modular hybrid simulation framework for complex manufacturing system design

For complex manufacturing systems, the current hybrid Agent-Based Modelling and Discrete Event Simulation (ABM–DES) frameworks are limited to component and system levels of representation and present a degree of static complexity to study optimal resource planning. To address these limitations, a modular hybrid simulation framework for complex manufacturing system design is presented. A manufacturing system with highly regulated and manual handling processes, composed of multiple repeating modules, is considered. In this framework, the concept of modular hybrid ABM–DES technique is introduced to demonstrate a novel simulation method using a dynamic system of parallel multi-agent discrete events. In this context, to create a modular model, the stochastic finite dynamical system is extended to allow the description of discrete event states inside the agent for manufacturing repeating modules (meso level). Moreover, dynamic complexity regarding uncertain processing time and resources is considered. This framework guides the user step-by-step through the system design and modular hybrid model. A real case study in the cell and gene therapy industry is conducted to test the validity of the framework. The simulation results are compared against the data from the studied case; excellent agreement with 1.038% error margin is found in terms of the company performance. The optimal resource planning and the uncertainty of the processing time for manufacturing phases (exo level), in the presence of dynamic complexity is calculated

Meta-modelling hybrid formalisms

Proceedigns of 2004 IEEE International Symposium on Computer Aided Control Systems DesignPersonal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. S. Lacoste-Julien, H. Vangheluwe J. de Lara, and P. J. Mosterman, "Meta-modelling hybrid formalisms", 2004 IEEE International Symposium on Computer Aided Control Systems Design, Taipei, China, 2004, pp. 65-70This article demonstrates how meta-modelling can simplify the construction of domain-and formalism-specific modelling environments. Using AToM3 (a tool for multi-formalism and meta-modelling developed at McGill University), a model is constructed of a hybrid formalism, HS, that combines event scheduling constructs with ordinary differential equations. From this specification, an HS-specific visual modelling environment is synthesized. For the purpose of this demonstration, a simple hybrid model of a bouncing ball is modelled in this environment. It is envisioned that the future of modelling and simulation in general, and more specifically in hybrid dynamic systems design lies in domain-specific computer automated multi-paradigm modelling (CAMPaM) which combines multi-abstraction, multi-formalism, and meta-modelling. The small example presented in this article demonstrates the feasibility of this approac

Simulation in manufacturing and business: A review

Copyright @ 2009 Elsevier B.V.This paper reports the results of a review of simulation applications published within peer-reviewed literature between 1997 and 2006 to provide an up-to-date picture of the role of simulation techniques within manufacturing and business. The review is characterised by three factors: wide coverage, broad scope of the simulation techniques, and a focus on real-world applications. A structured methodology was followed to narrow down the search from around 20,000 papers to 281. Results include interesting trends and patterns. For instance, although discrete event simulation is the most popular technique, it has lower stakeholder engagement than other techniques, such as system dynamics or gaming. This is highly correlated with modelling lead time and purpose. Considering application areas, modelling is mostly used in scheduling. Finally, this review shows an increasing interest in hybrid modelling as an approach to cope with complex enterprise-wide systems

A framework for conceptualising hybrid system dynamics and agent-based simulation models

The growing complexity of systems and problems that stakeholders from the private and public sectors have sought advice on has led systems modellers to increasingly use multimethodology and to combine multiple OR/MS methods. This includes hybrid simulation that combines two or more of the following methods: system dynamics (SD), discrete-event simulation, and agent-based models (ABM). Although a significant number of studies describe the application of hybrid simulation across different domains, research on the theoretical and practical aspects of combining simulation modelling methods, particularly the combining of SD and ABM, is still limited. Existing frameworks for combining simulation methods are high-level and lack methodological clarity and practical guidance on modelling decisions and elements specific to hybrid simulation that modellers need to consider. This paper proposes a practical framework for developing a conceptual hybrid simulation model that is built on reviews and reflections of theoretical and application literature on combining methods. The framework is then used to inform and guide the process of conceptual model building for a case study in controlling the spread of COVID-19 in care homes. In addition, reflection on the use of the framework for the case study led to refining the framework itself. This case study is also used to demonstrate how the framework informs the structural design of a hybrid simulation model and relevant modelling decisions during the conceptualisation phase

The blending region hybrid framework for the simulation of stochastic reaction-diffusion processes

The simulation of stochastic reaction-diffusion systems using fine-grained representations can become computationally prohibitive when particle numbers become large. If particle numbers are sufficiently high then it may be possible to ignore stochastic fluctuations and use a more efficient coarse-grained simulation approach. Nevertheless, for multiscale systems which exhibit significant spatial variation in concentration, a coarse-grained approach may not be appropriate throughout the simulation domain. Such scenarios suggest a hybrid paradigm in which a computationally cheap, coarse-grained model is coupled to a more expensive, but more detailed fine-grained model enabling the accurate simulation of the fine-scale dynamics at a reasonable computational cost. In this paper, in order to couple two representations of reaction-diffusion at distinct spatial scales, we allow them to overlap in a "blending region". Both modelling paradigms provide a valid representation of the particle density in this region. From one end of the blending region to the other, control of the implementation of diffusion is passed from one modelling paradigm to another through the use of complementary "blending functions" which scale up or down the contribution of each model to the overall diffusion. We establish the reliability of our novel hybrid paradigm by demonstrating its simulation on four exemplar reaction-diffusion scenarios.Comment: 36 pages, 30 figure

Benchmarks for Hybrid Modelling

Hybrid Modelling is getting more and more important in technical and natural sciences. In these fields very complex systems and processes have to be simulated and therefore proper models must be developed. For complex systems different model structures for dynamical systems are available. One of the important model structures regarding complex dynamical systems are hybrid models. A hybrid model consists of several dynamical models and a state diagram where each state is described by a differential algebraic equation (DAE). This paper deals with benchmarks out of different fields of applications of this modelling approach. The first benchmark is an electrical circuit with linear devices and a diode as a nonlinear component. This example will show the influence of a simple model to the state space description or the corresponding differential algebraic description. The different models for the nonlinear behaviour of the diode influences the states of the state diagram. It is remarkable, that the different models for the diode results in a different hybrid model. The influence from these models on the diode can be observed. Another benchmark is the rotating pendulum. It is also described by a state diagram, in this special academic example a state diagram with two states. The two examples are representative, one out of the field of electrical engineering, one typical mechanical scenario. In the article two aspects will be considered. On the one side the modelling process of the electrical circuit will be observed in detail, especial the influence of different diode models on the structure of the states, and the state transition between the two states of the mechanical pendulum. On the other side also the need of a mathematical notation and description of the states and their transition will be discussed. In the end of the article some comments to the simulation of hybrid systems will be given

A generic approach to behaviour-driven biochemical model construction

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Modelling of biochemical systems has received considerable attention over the last decade from bioengineering, biochemistry, computer science, and mathematics. This thesis investigates the applications of computational techniques to computational systems biology, for the construction of biochemical models in terms of topology and kinetic rates. Due to the complexity of biochemical systems, it is natural to construct models representing the biochemical systems incrementally in a piecewise manner. Syntax and semantics of two patterns are defined for the instantiation of components which are extendable, reusable and fundamental building blocks for models composition. We propose and implement a set of genetic operators and composition rules to tackle issues of piecewise composing models from scratch. Quantitative Petri nets are evolved by the genetic operators, and evolutionary process of modelling are guided by the composition rules. Metaheuristic algorithms are widely applied in BioModel Engineering to support intelligent and heuristic analysis of biochemical systems in terms of structure and kinetic rates. We illustrate parameters of biochemical models based on Biochemical Systems Theory, and then the topology and kinetic rates of the models are manipulated by employing evolution strategy and simulated annealing respectively. A new hybrid modelling framework is proposed and implemented for the models construction. Two heuristic algorithms are performed on two embedded layers in the hybrid framework: an outer layer for topology mutation and an inner layer for rates optimization. Moreover, variants of the hybrid piecewise modelling framework are investigated. Regarding flexibility of these variants, various combinations of evolutionary operators, evaluation criteria and design principles can be taken into account. We examine performance of five sets of the variants on specific aspects of modelling. The comparison of variants is not to explicitly show that one variant clearly outperforms the others, but it provides an indication of considering important features for various aspects of the modelling. Because of the very heavy computational demands, the process of modelling is paralleled by employing a grid environment, GridGain. Application of the GridGain and heuristic algorithms to analyze biological processes can support modelling of biochemical systems in a computational manner, which can also benefit mathematical modelling in computer science and bioengineering. We apply our proposed modelling framework to model biochemical systems in a hybrid piecewise manner. Modelling variants of the framework are comparatively studied on specific aims of modelling. Simulation results show that our modelling framework can compose synthetic models exhibiting similar species behaviour, generate models with alternative topologies and obtain general knowledge about key modelling features