Typically, component-oriented acausal hybrid modeling of complex dynamic systems is implemented by specialized modeling languages. A well-known example is the Modelica language. The specialized nature, complexity of i...
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Typically, component-oriented acausal hybrid modeling of complex dynamic systems is implemented by specialized modeling languages. A well-known example is the Modelica language. The specialized nature, complexity of implementation and learning of such languages somewhat limits their development and wide use by developers who know only general-purpose languages. The paper suggests the principle of developing simple to understand and modify Modelica-like system based on the general-purpose programming language Python. The principle consists in: (1) Python classes are used to describe components and their systems, (2) declarative symbolic tools SymPy are used to describe components behavior by difference or differential equations, (3) the solution procedure uses a function initially created using the SymPy lambdify function and computes unknown values in the current step using known values from the previous step, (4) Python imperative constructs are used for simple events handling, (5) external solvers of differential-algebraic equations can optionally be applied via the Assimulo interface, (6) SymPy package allows to arbitrarily manipulate model equations, generate code and solve some equations symbolically. The basic set of mechanical components (1D translational "mass", "spring-damper" and "force") is developed. The models of a sucker rods string are developed and simulated using these components. The comparison of results of the sucker rod string simulations with practical dynamometer cards and Modelica results verify the adequacy of the models. The proposed approach simplifies the understanding of the system, its modification and improvement, adaptation for other purposes, makes it available to a much larger community, simplifies integration into third-party software.
Thermoelectric (TE) devices are used in the form of Peltier coolers and as TE generators, with the latter producing electrical energy from waste heat, based on the Seebeck effect. In both cases, modeling of the TE dev...
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Thermoelectric (TE) devices are used in the form of Peltier coolers and as TE generators, with the latter producing electrical energy from waste heat, based on the Seebeck effect. In both cases, modeling of the TE device is a prerequisite for the design and control verification of the resulting overall energy system. To this end, the model has to be integrated seamlessly in an overall system model containing other electrical, thermodynamic, or even mechanical components. Following this premise, this paper presents a component-based model for TE devices described in the Modelica language. The model incorporates the temperature dependences of decisive material properties (Seebeck coefficient, thermal conductivity, and electrical resistivity) in 1-D spatial resolution. With the help of few additional geometrical parameters, e. g., the thickness of TE legs, the model is capable of describing the dynamic behavior of the TE device in accordance with the experimental results.
The first stage of creating the foundations of component-oriented modeling of hydrological and geochemical processes in catchments has been implemented. The potential of a system of related and` for some processes, in...
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The first stage of creating the foundations of component-oriented modeling of hydrological and geochemical processes in catchments has been implemented. The potential of a system of related and` for some processes, interchangeable, models of different levels of discreteness, intended for describing various processes of formation of biogenic element runoff from reservoir catchments, have been demonstrated. The models developed at the Institute of Geography, the Institute of Limnology, and the Institute for Engineering and Environmental Problems in Agricultural Production have been used. The proposed set of models allows selecting a number of algorithms optimally adapted to solving a problem under conditions of often limited initial data. The selection of individual blocks of the system, their integration into a single model for subsequent calculations of nutrient input with varying degrees of detail are shown for the catchments of the rivers of the Cheboksary Reservoir basin: the Linda (1681 km(2)) and the Kudma (3246 km(2)), flowing into the Volga River upstream and downstream of Nizhny Novgorod. Examples of model synthesis are given for solving the problem of predictive assessment of river runoff changes taking into account its distribution parameters on experimental catchments in the future, the problem of calculating the average annual nutreint export by different types of runoff from catchments, the problem of assessing the intra-annual distribution of nitrogen and phosphorus losses of agricultural origin on the studied catchments using calculations of the runoff hydrograph components taken from a hydrological model. It is shown that the proposed method of predictive assessment of changes in runoff from a river catchment under the influence of climate change can be used to calculate not only the general trend of changes in runoff characteristics, but also to assess the runoff distribution parameters in the future.
Accurate and efficient simulations facilitate cost-effective design and analysis of large, complex, embedded systems, whose behaviors are typically hybrid, i.e. continuous behaviors interspersed with discrete mode cha...
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Accurate and efficient simulations facilitate cost-effective design and analysis of large, complex, embedded systems, whose behaviors are typically hybrid, i.e. continuous behaviors interspersed with discrete mode changes. In this paper we present an approach for deriving component-based computational models of hybrid systems using hybrid bond graphs (HBGs), a multi-domain, energy-based modeling language that provides a compact framework for modeling hybrid physical systems. Our approach exploits the causality information inherent in HBGs to derive component-based computational models of hybrid systems as reconfigurable block diagrams. Typically, only small parts of the computational structure of a hybrid system change when mode changes occur. Our key idea is to identify the bonds and elements of HBGs whose causal assignments are invariant across system modes, and use this information to derive space-efficient reconfigurable block diagram models that may be reconfigured efficiently when mode changes occur. This reconfiguration is based on the incremental reassignment of causality implemented as the Hybrid Sequential Causal Assignment Procedure, which reassigns causality for the new mode based on the causal assignment of the previous mode. The reconfigurable block diagrams are general, and they can be transformed into simulation models for generating system behavior. Our modeling and simulation methodology, implemented as the modeling and Transformation of HBGs for Simulation (MoTHS) tool suite, includes a component-based HBG modeling paradigm and a set of model translators for translating the HBG models into executable models. In this work, we use MoTHS to build a high-fidelity MATLAB Simulink model of an electrical power distribution system.
A new approach for component-oriented modeling of asynchronous discrete-event systems is presented where input-output (I/O) automata are used for representing the components. Coupling signals are introduced to describ...
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A new approach for component-oriented modeling of asynchronous discrete-event systems is presented where input-output (I/O) automata are used for representing the components. Coupling signals are introduced to describe the interactions among the components. The resulting network of I/O-automata has a direct correspondence to the block diagram. By using the parallel composition rule known from standard automata modeling as an example, it is shown that the new model is applicable for at least the same class of asynchronous discrete-event systems as the known modeling formalisms.
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