Modelica Conferences

Model-Based Design and Characterization of an Actuator with Low-Boiling Liquid

2025-01-16T10:40:52+01:00

Visually impaired people rely on special equipment for access to graphic representations in digital form. The available devices are very large and expensive. A simple and cost-effective alternative to the existing concepts for haptic displays is therefore desirable. This paper evaluates the concept of a lifting actuator based on a fluid with a low boiling point for this purpose. A functional prototype is constructed and its behavior is characterized. A corresponding model is built and validated to simulate the actuator and to analyze its operation. It provides detailed information about the actuator that can be used to further develop the design and to make decisions on the usability of the new actuator in the product design process. Following test runs and investigations on the model, the actuator concept proved to be suitable for haptic display devices under certain assumptions. Therefore the newly developed model presents a good starting point for future revisions of the concept.

Dynamic Modeling Methodology for Near Isothermal Compressor

2025-01-16T10:40:53+01:00

Compressors are the vital component of the vapor compression systems and account for the majority of energy consumption. Developing appropriate controllers or optimizing compressor design can significantly reduce the carbon emissions. The isothermal compressor combines the compressor chamber and gas cooler, using the liquid piston to compress the working fluid for nearisothermal compression. This methodology can reach up to 30% energy saving compared to the traditional isentropic compression work. This paper leverages the CEEE Modelica Library (CML) to demonstrate a detailed isothermal compressor model that captures the nearisothermal compression process of transcritical carbon dioxide (CO₂) cycle. The model uses the real experimental data as the boundary conditions, and the relevant component-level experimental validation was carried out by using a prototype with 1-ton nominal capacity. The results proved the accuracy of the dynamic model (7.5% relative error for chamber pressure and 0.74 K deviation for chamber temperature), and provide a guideline for designing the isothermal compressor chamber. Finally, the modeling for the isothermal compression cycle is ongoing and the field is still in its infancy.

Fluid Property Functions in Polar and Parabolic Coordinates

2025-01-16T10:40:54+01:00

This paper presents two methods for reallizing fluid property functions in Modelica simulation models. Each makes use of a coordinate transformation that aligns one coordinate with the saturation curve. This provides for a precise representation of the fluid property function at the saturation curve, and for connected domains of interest including the liquid, vapor, supercritical and two-phase regions. Both approaches make use of spline function approximation in the aligned coordinates, and are numerically efficient, well conditioned, and allow for efficient calculation of derivatives up to any desired order that are precise up to processor numerical tolerance.

Objectively Defined Intended Uses, a Prerequisite to Efficient MBSE

2025-01-16T10:40:55+01:00

This article proposes a method for improved model verification within Large-Scale Simulators (LSS). The approach relies on machine-interoperable traceability of model verification information, such as model Operational Domains (ODs). This enables automated evaluation of model relevance and facilitates the combination of models for a broader evaluation of credible simulation results. The paper introduces a proof-of-concept testbed for verification of black-box models against model requirements. Furthermore, the results also include a proposal for a machine-readable format to capture model requirement Verification & Validation (V&V) results, along with the resulting model and updated model OD information.

Modelica Supported Automated Design

2025-01-16T10:40:55+01:00

We propose a component-based, automated, bottom-up method to system design, using models expressed in the Modelica language. This bottom-up approach is based on a meta-topology that is iteratively refined via optimization. Each topology link is described by a universal component that is defined in terms of atomic components (e.g., resistors, capacitors for the electrical domain) or more complex canonical components with a well-defined function (e.g., operational amplifier-based inverters). The activation of such links is done via discrete switches. To address the combinatorial explosion in the resulting mixed-integer optimization problems, we convert the discrete switches into continuous switches that are physically realizable and formulate a parameter optimization problem that learns the component and switch parameters. We encourage topology sparsity through an L₁ regularization term applied to the continuous switch parameters. We improve the time complexity of the optimization problem by reconstructing intermediate design models when components become redundant and by simplifying topologies through collapsing components and removing disconnected ones. To demonstrate the efficacy of our approach, we apply it to the design of various electrical circuits.

Proposal for A Context-oriented Modelica Contributing to Variable Structure Systems

2025-01-16T10:40:56+01:00

Context-aware systems are widespread in our daily lives, but modeling languages that address the notion of context are rare. Variable structure systems (VSS) allow for structural and behavioral changes in physical models at runtime (while the simulation is running) based on different situations. It is desirable to explicitly describe under which contextual situation a specific variant of the simulation model should be used and how to implement the switching between these variants at runtime. In this case, contexts could be used to control the variability of context-aware systems. Equation-based modeling languages are suitable for modeling complex multi-domain, multi-physical systems, and among them, Modelica is the state-of-the-art. Unfortunately, the capabilities for VSS in Modelica are strongly limited. As a result, several frameworks have been proposed to address this problem by supporting different VSS types. However, it remains unclear which framework contributes to which VSS type. Furthermore, approaches have been developed to support VSS, but none can explicitly describe contexts and their transitions. In this work, we first introduce VSS and its different types. Then, we provide an overview of which framework targets which VSS type. Finally, we propose a new language extension based on Modelica, ContextModelica, that provides semantics for the direct context definition, enabling the use of context to control and manage variability.

Building Power System Models for Stability and Control Design Analysis using Modelica and the OpenIPSL

2025-01-16T10:40:57+01:00

Ensuring the stability of complex power system models is a critical challenge in the field of electrical power engineering, and the tuning of Power System Stabilizers (PSS) plays a pivotal role in this endeavor. Modelica, an open-access modeling language, emerges as a powerful tool for this purpose due to its distinctive features that facilitate efficient power system modeling. This paper explores the capabilities of Modelica using the OpenIPSL library to create models to analyze control system designs developed for a multi-machine power system model. It particularly focuses on using the features of Modelica for the linearization, control-oriented analysis, and time-simulation of the model. The results demonstrate the effectiveness of using Modelica for control system design analysis and performing linear model-based analysis. This work aims to show how Modelica can be used to perform these tasks on a single platform efficiently, thereby streamlining the process of power system design and analysis.

Integrating the IEEE/CIGRE DLL Modeling Standard to Use “Real Code” Models for Power System Analysis in Modelica Tools

2025-01-16T10:40:58+01:00

Vendors of power system simulation tools are investigating the incorporation of actual controller code into specialized simulation environments. To facilitate this, IEEE and CIGRE have collaboratively created the IEEE/CIGRE DLL Modeling Standard. However, adoption by simulation tool providers has been minimal. The limited adoption is because 'real code' models per the IEEE/CIGRE DLL Modeling Standard must be provided as DLLs by equipment vendors. Thus, to support the standard, tools need to support a standard-specific interface and provide additional functions to execute the models.

This paper presents a method for integrating 'real controller code' models (RCMs) built according to the IEEE/CIGRE DLL Modeling Standard into Modelica-based tools. This is achieved by linking precompiled C code to Modelica models and using components from the OpenIPSL library. The approach is demonstrated with an RCM of a simplified silicon-controlled rectifier excitation system (SCRX). The paper discusses the details of the implementation, challenges, and solutions. The findings show that this method allows RCMs to be used in Modelica tools for power system simulations, providing a valuable alternative to specialized simulation tools.

Decentralised Hydrogen Fuelled Gas Engine CHP Units: A Feasibility Study with Modelica

2025-01-16T10:40:59+01:00

The use of hydrogen gas as an alternative fuel to power energy systems has been a topic of research over the last few decades and is currently gaining importance, even more due to current circumstances related to decarbonising energy supply. One focus of research is the use of hydrogen gas in combined heat and power gas engines, as this type of energy conversion is known for its high efficiency. For this reason, a cross-border project between France and Germany is developing a living laboratory in the Upper Rhine region to investigate the feasibility of hydrogen gas as an alternative fuel in a holistic decentralised energy system. It consists of several energy components, including a polymer electrolyte membrane electrolyser (PEMEC), gas engine combined heat and power (CHP) unit, photovoltaic (PV) panels, hydrogen storage, thermal and electrical energy storage. To enable and demonstrate multiple what-if scenarios of possible variations of the energy system, a simulation model was developed using Modelica. Users, e.g. local authorities, landlords, businessmen, etc., of this simulation model could utilize it as a decision support tool for designing a carbon-neutral energy system for their own use. This paper describes the development of the model and its application with real measured data from municipal buildings in the city of Offenburg, Germany. The results indicate that the suitability of the model and the use of hydrogen CHPs can be beneficial for this specific use case.

FMI-3.0 Export for Models with a Clock in a Signal Flow Diagram Environment

2025-01-16T10:41:00+01:00

The FMI-3.0 standard, recently released, introduces several promising features, such as clocks and arrays. FMI-3.0 supports various clock types, including time-based clocks, triggered input, and triggered output clocks. Altair Twin Activate (TA), as a modeling and simulation environment, inherently supports hybrid systems combining continuous-time and discrete-time models. The discrete-time part is typically activated by events and clocks. The clock types provided by FMI-3.0, however, may differ from those in TA. In the paper (Najafi and Nikoukhah 2022), we explained how different clocks defined in FMI-3.0 can be successfully imported into TA. Building upon this, our current paper aims to demonstrate how various clocks used in TA can be used in the export of a subsystem in both FMI-3.0 and FMI-2.0 formats. Specifically, we will explain the way input periodic clocks and input triggered clocks are exported.

Event Support for Simulation and Sensitivity Analysis in CasADi for use with Modelica and FMI

2025-01-16T10:41:00+01:00

CasADi is an open-source framework that can be used to efficiently solve optimization problems involving user-defined ODE/DAE models. Supported solution methods include so-called shooting methods, where solvers for initial-value problems in ODEs or DAEs are referenced inside nonlinear programming (NLP) formulations. In order to solve such NLP formulations with gradient-based algorithms, CasADi implements a fully automatic sensitivity analysis. This analysis includes forward sensitivity analysis, adjoint sensitivity analysis as well as the calculation of higher-order sensitivities for the ODE/DAE models. Because of the variational (differentiate-then-integrate) approach used, the numerical solution can be performed with variable-step size, variable-order integrators such as those from the SUNDIALS suite.

In this work, we present a generalization of the sensitivity analysis support in CasADi to systems with events, as are common in real-world cyber-physical models. In particular, the event extension enables us to formulate and solve optimization problems with such event systems, without a priori knowledge of the number and ordering of events. Ultimately, we expect the proposed approach to be compatible with general cyber-physical models formulated in Modelica or available as model-exchange FMUs.

We demonstrate the proposed approach for two proof-of-concept examples; the classical bouncing ball written in CasADi directly and a simple hybrid DAE describing a breaking spring formulated in Modelica and imported symbolically into CasADi. In the examples, we show that the forward sensitivities calculated to high precision using the proposed approach are consistent with a cruder finite-difference approximation and provide an example of how they can be embedded into optimization formulations. We discuss how the approach can be extended to handle standard FMUs, adhering to FMI 2 or FMI 3, as well as non-trivial Modelica models imported via a symbolic interface based on the emerging Base Modelica standard.

Steady-state Optimization of Modelica Models and Functional Mockup Units with Pyomo

2025-01-16T10:41:01+01:00

This paper describes two ways on how to interface Functional Mockup Units (FMUs) and Modelica models through the Pyomo’s foreign function interface with Pyomo. Pyomo is a Python-based, open-source optimization modeling language with a diverse set of optimization capabilities. Modelica has arguably much better modeling capabilities than Pyomo, but Pyomo integrates excellent optimization solvers, such as Ipopt (Wächter et al. 2006), and provides a good optimization infrastructure. The Interface has been developed in the context of a NAWI, (National Alliance Water Innovation) Hub project in collaboration with the University of Connecticut and Sandia National Labs. The optimization has been set up and tested within Modelon’s Modelica platform Modelon Impact. An unpublished, detailed multi-effect desalination plant developed by Prof. Matt Stuber in the context of (Stuber et al., 2015) has been used to demonstrate the capabilities, as well as simple test models, and design models from Modelon’s commercial Libraries.

Development and Validation of a Water-to-Air Heat Pump Model using Modelica

2025-01-16T10:41:02+01:00

Water-to-air heat pumps are widely used Heating, Ventilation, and Air Conditioning (HVAC) devices due to their versatility and energy efficiency. However, there is a scarcity of readily available Modelica models that support reversible operation (heating and cooling modes), use compressor speed as the control signal, and accurately predict the system performance. To address this gap, this paper presents a speed-input water-to-air heat pump model developed using Modelica. Performance curves are employed to represent the functionality and predict the system’s capacity and power usage. To validate the proposed model’s effectiveness, manufacturer-provided data are used to generate the performance curves. The model, based on these curves, is then used to simulate testing conditions, which are implemented in a real heat pump testbed. The comparison between simulated and measured values shows that the errors during normal operation stages are within an acceptable range, demonstrating the effectiveness of the developed water-to-air heat pump model.

A Modelica Implementation of an Organic Rankine Cycle

2025-01-16T10:41:03+01:00

Organic Rankine cycle (ORC) systems generate power from low-grade heat sources, such as geothermal sources and industrial waste heat. A key feature is that a working fluid is selected to match the temperature of the source. With the vast pool of candidate working fluids comes the challenge of developing a large number of robust thermodynamic media models. We implemented a subcritical ORC model in Modelica that uses working fluid data records and interpolation schemes in lieu of thermodynamic medium evaluation for energy recovery estimation. This is a component model that can be integrated into a larger energy system model. It does not require detailed thermodynamic, heat transfer, or machine analysis. Our ORC model fills a gap where working fluids are ready to choose or easy to add, and at the same time can be integrated into an energy system.

Advancements in Building-to-Grid Interactions: Thermo-Electric Coupling Models of Motor-Driven Devices

2025-01-16T10:41:03+01:00

Building-to-grid (B2G) integration transforms buildings into active components of the electricity grid, enhancing dynamic energy management and optimizing usage to reduce operational costs and carbon emissions. However, existing modeling tools for building and power systems often overlook or oversimplify the interactions between power system dynamics and building dynamics. This paper introduces Modelica-based thermo-electric coupling models for motor-driven devices in buildings, such as pumps and heat pumps. The developed models assess transient oscillations and negative active power in these devices within B2G systems. We compare the proposed models with a base model from the Modelica Building Library that uses a radiator and heat pump to maintain room temperature. The simulation results demonstrate that the motor-driven models effectively capture transient oscillations in current and power when the systems are activated and deactivated. Additionally, the occurrence of negative power when systems turn off is a critical factor in enhancing B2G system stability and energy efficiency. These findings underscore the model’s ability to improve grid support, advancing energy management practices in B2G applications.

Modelica as Model Aggregator for Holistic Architecture Validation of Electric Vehicles

2025-01-16T10:41:04+01:00

Automotive OEMs and suppliers are facing recent challenges in the development process, induced by ever shortened product cycles, further distributed development as well as increasing demands for virtual testing and certification using virtual proving grounds or digital twins.

This paper presents a real-life demonstration of a federated, seamlessly integrated design process for a complex cyberphysical system (electric truck), where simulation is used for early-stage performance validation and decision making. Since holistic, but abstract architecture models created in systems engineering discipline contain relevant information with respect to logical system structure and allocated requirements, the simulation domain will benefit from a cross domain linking of model artefacts. By aligning system interfaces across model abstractions and augmenting logical models with physical information, behavioural model templates for design can be generated in a smart, traceable and automated fashion. With the additional information of requirements allocated to certain architectural components in those abstract architecture models, it is demonstrated how scenario-based component and system simulation will contribute to analysis tasks like architecture exploration or specific design optimization in efficient, continuous engineering environments.

Multiphysics Acausal Modeling and Simulation of Satellites using a Modelica Library

2025-01-16T10:41:05+01:00

The multiphysics modeling has a great importance when a complex space system (as a satellite) is considered. Indeed, it is necessary to analyse how the system’s behavior is affected by the space environment or by on board failures. In this paper, the Modelica Library is used to hierarchically build and connect the main subsystems that can be found in a traditional satellite. Specifically, the modeling and simulation of the entire system is carried out in the Dymola environment. Finally, the FMI is applied to simulate in Dymola some specific satellite models/logics created with higher fidelity in the Matlab/Simulink domain.

Advanced Edge Deployment: Abstracting Cyber-Physical Models via FMU Mastery

2025-01-16T10:41:06+01:00

Deploying cyber-physical models at the edge or in the cloud as software components is the key step of modelbased- design. Depending on run-time environment, an extensive customization often needs to be made. To streamline and facilitate the deployment of models and simulators in production, a unified framework is developed. The implementation utilizes functional mockup units (FMUs) as the executable binary for the models and JavaFMI as the simulation engine. Each model deployment is encapsulated inside a microservice with all the software dependencies, with communication realized through RabbitMQ. A generalized approach to manage the model namespace has been implemented, ensuring that the FMU executor remains agnostic to changes in both model and application, as long as the AsyncAPI specification includes a mapping of the model's input-output space to the protocol’s topics. Two examples are presented to illustrate the convenience and effectiveness of the proposed framework: a winch controller at the edge for oil and gas wireline operation and a wireline logging unit simulator in the Azure DevOps pipeline for software-in-the-loop testing.

Integrating Generative Machine Learning Models and Physics-Based Models for Building Energy Simulation

2025-01-16T10:41:06+01:00

This paper describes the integration of generative deep learning models for data-driven building energy simulation. The generative models (GMs) are trained to learn distributions of building input signals from data using Python and PyTorch and interfaced with physics-based Modelica models. The developed integration requirements provide background on typical needs that focus on building energy simulation performance. Simulation examples using models from the Buildings library, refactored to receive GM inputs, are presented to illustrate the benefits of the proposed integration approach and how GMs can be used for building energy performance analysis.

Pipeline-Based Automated Integration and Delivery Testing of Simulation Assets with FMI/SSP in a Railway Digital Twin

2025-01-16T10:41:07+01:00

Railway infrastructure systems have recently been enhanced through the use of the digital twin (DT) concept, enabling visualization and control in a virtual environment while effectively mitigating life cycle costs. This work provides insights into the development and operations (DevOps) of a railway DT platform and highlights the automation and management of asset integration and processing based on the FMI and SSP interface standards through the use of the Continuous Integration / Continuous Delivery pipeline technology. This offers long-term durability, pausability, remote triggering, open-source and workflow design capabilities, and connectivity to other tools such as version control systems and code analysis tools. In this research paper, we present an anti-slip cosimulation model of a railway vehicle as a use case example to demonstrate the pipeline-oriented automation and management in combination with a version control system and code analysis tool within the platform.

Thermo-Fluid Modeling Framework for Supercomputer Digital Twins: Part 1, Demonstration at Exascale

2025-01-16T10:41:08+01:00

A thermo-fluid modeling framework is being developed for ExaDigiT—an open-source framework for developing comprehensive digital twins of liquid-cooled supercomputers. The work is being conducted in two parts, and discussion is divided into two companion papers. The work documented in this paper focuses on the development of a cooling system library in Dymola for the Frontier supercomputer at Oak Ridge National Laboratory. The second part, outlined in a companion paper, focuses on a templating structure called Auto-CSM for easily creating modelagnostic, physics-based thermo-fluid cooling system models for liquid-cooled supercomputers using a text-based schema. The cooling model is being developed using primarily the open-source Transient Simulation Framework of Reconfigurable Models (TRANSFORM) library. The library follows the templating architecture developed within the TRANSFORM library for modeling subsystems. A full-system validation was performed to validate a very simple model that is integrated with the system controls, and the results are presented herein.

Thermo-Fluid Modeling Framework for Supercomputer Digital Twins: Part 2, Automated Cooling Models

2025-01-16T10:41:09+01:00

The development of digital twins for the purpose of improving the energy efficiency of supercomputing facilities is a non-trivial endeavor that is complicated by the difficulty of creating physics-based thermo-fluid cooling system models (CSMs). Within ExaDigit—an opensource framework for liquid-cooled supercomputing digital twins—a thermo-fluid modeling framework is being developed. This effort has been segmented into two with two companion papers describing each portion of the overall effort. Part 1 focuses on the development of a cooling system library in Dymola for the Frontier supercomputer at Oak Ridge National Laboratory (Kumar et al. 2024). Part 2, this paper, describes an effort to create a templatebased auto-generation methodology for CSMs, called AutoCSM. In this paper, an overview of the initial AutoCSM architecture and workflow is provided, along with a practical example using the Oak Ridge Leadership Computing Facility’s (OLCF) Frontier supercomputer CSM. AutoCSM will (1) improve ExaDigiT’s user accessibility by providing a flexible workflow for modularizing the creation of the CSM system and control logic, (2) decrease the development time of CSMs, and (3) standardize the method for incorporating CSMs into the ExaDigiT framework.