Linköping Electronic Conference Proceedings
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LS-SA: Developing an FMI layered standard for holistic & efficient sensitivity analysis of FMUs
Full text linkThe Functional Mock-up Interface (FMI) is the standard forexchanging industrial simulation models in a variety ofdifferent applications. Although sensitivity analysis forcontinuously differentiable systems is directly supportedby the standard, for systems with state discontinuities, itis only possible to determine correct sensitivities to alimited extent. In this position paper, we investigate howsensitivity analysis for discontinuous Functional Mock-upUnits (FMUs), i.e. including state and time events, worksin theory and which additional steps are required to obtaincorrect results in practice. We further investigate thatthese steps are unnecessarily computationally intensivefrom a mathematical point of view, but cannot beimplemented in a more efficient way under the currentrestrictions of the standard. We therefore make a concreteproposal for the new layered standard sensitivity analysis(LS-SA) that remedies the current deficits of FMI in thesensitivity analysis of discontinuous systems. In this way,LS-SA opensFMI towards a variety of next-level applications —including (scientific) machine learning and optimal control— by providing fully differentiable FMUs under highcomputational performance
Shared sea-environment definition and realization for maritime and offshore co-simulations
Full text linkMarine operations are often developed with the use ofnumeric simulation, in particular lifting operations andtransfer of cargo between different units at sea. Theeffect of the environmental conditions is often thelimiting factor and must be included together with modelsof different components and sub-systems. This paperdescribes an approach to synchronize spatial and temporalenvironment information such as universal constants,current, wind, and wave for use in co-simulations of marineoperations. Co-simulation models in marine operations willinherently use physical constants, wind and currentvelocities to calculate forces. Wind and current velocitiescan have spatial and temporal variations that require themodels to synchronize the values. In the event ofsimulations in waves, the position of the ocean surface,wave particle velocities must be coherent betweenindividual co-simulation models. Further complicatingmatters is the case of propulsors that produce forces bycreating local currents. This paper suggests a structureddescription of an environment for co-simulation of marineoperations. This is exemplified by the implementation of aco-simulation of an offshore lifting operation wherevessel, crane, propulsors and lifting load are allintegrated with a common environment
Decreasing Risk in the Design of Large Coupled Systems via Co-Simulation-Based Optimization and Adaptive Stress Testing
Full text linkOptimization and stress testing are key aspects of thedesign and verification process for large, high-risksystems. Optimization is about improving the capabilitiesand performance of a system; stress testing is aboutuncovering its weaknesses and faults. Both require aquantitative representation of the system's behavior, andfor complex, multi-physical systems, co-simulation can be avery powerful method to create such a representation.However, co-simulation frequently involves the use ofblack-box subsystem models, which poses challenges totraditional optimization and stress testing methods. Here,we review the state of the art in co-simulation-basedoptimization and stress testing, focusing especially on\emph{adaptive stress testing} in the latter case, anddiscuss open research questions and promising researchdirections. In particular, we make the case that aco-simulation is not an entirely black box even when someor all of its subsystems are; it may be possible to exploitthe visible system structure, coupling variable values, andpartial subsystem information. We use examples from themaritime industry to motivate and illustrate thediscussion, centering on the highly contemporary designcase of an autonomous ferry
Solid-State Battery-Systems and Thermal Management for Electric Long-Distance Buses
Full text linkSolid-state batteries are promising for electric mobilityas they potentially offer higher energy densities andtherefore driving range, long-life and safety. They comewith changed thermal properties and thermal managementrequirements. In this paper a comparison of a solid-statebattery system with a state-of-the-art liquid batterysystem is presented. This study compares a solid-statebattery with a state-of-the-art liquid NMC battery for anelectric coach on typical real-world long-distance routes,including fast-charging. The thermal management isperformed by a reversible R744 heat pump. By designing bothbattery systems for the same energy capacity, thesolid-state battery releases more heat duringfast-charging. At the same battery system size, thesolid-state battery significantly outperforms the liquidbattery system in driving range and does not need morecooling
Rumoca: Towards a Translator from Modelica to Algebraic Modeling Languages
Full text linkWe present Rumoca, a translator written in Rust that formsthe basis of a symbolic toolchain, automatically convertingModelica models into a variety of target algebraic modelinglanguages. Rumoca is demonstrated on three models andtranslated into two different algebraic representations:CasADi and Sympy. Designed for generalizability, Rumoca hasthe potential to accommodate increasingly complex Modelicamodels and additional target languages
Building Power System Models for Stability and Control Design Analysis using Modelica and the OpenIPSL
Full text linkEnsuring 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
CO2 Enhanced Oil Recovery in Reservoirs with Advanced Wells: Simulations and Sensitivity Analysis
Full text linkInjection of CO2 for enhanced oil recovery (CO2-EOR) is used in fields with high amount of residual oil. CO2-EOR refers to a technology where supercritical CO2 is injected into an oil reservoir to increase the oil production. Utilizing autonomous inflow control valves (AICVs) in CO2-EOR projects contributes to a better distribution of CO2 in the reservoir, reduction in production of water and CO2 mixture, and thereby increased storage capacity of CO2. The main objective of this study is modelling and simulation of oil production from an oil reservoir using CO2 water alternating gas (CO2 WAG) injection in combination with advanced wells that are completed with AICVs. The results from the simulations indicate that well completion with AICV can maintain good oil production while the production of water is decreased from 3e+06 m3 to 9.8e+04 m3 which corresponds to 97% reduction in water production. The sensitivity analysis of the simulation results affirms that permeability, well placement, and well spacing have impact on oil recovery and water production. The results indicate that permeability increase has a slight increment effect on oil recovery. The well spacing analysis shows that increasing the distance between the wells will increase the oil recovery and delay the water breakthrough. Lastly the well placement analysis shows that vertical injection of miscible CO2 produces more oil than horizontal injection of miscible CO2. AICVs restrict the production of mixture of CO2 and water, and thereby cause a better distribution of CO2 in the reservoir
Non-interacting lattice random walks for calculating diffusion controlled growth in solid state for dilute concentrations
Full text linkTo connect the molecular length scale phenomena to the macroscopic length scale in diffusion controlled growth in solid state, there is need to consider the movement of individual atoms in the crystal lattice and examine the length scale effect where the average density of the atoms approaches to the continuum macro scale. For this purpose a lattice random walk model has been constructed to represent the diffusion of atoms to form a precipitate. Once the atom is in contact with the precipitate surface, the precipitate grows and the atom is not anymore contributing to the random walk. Through the model, it is possible to evaluate the concentration fluctuations at different length scales in diffusion controlled growth and connect the continuum description of diffusion to the atomic level description. We connect the different length scales in theoretical description from atomistic scale through random atom movements to macroscale. In the current study, two-dimensional lattice random walks and growth are considered. The study contributes to the modelling efforts of understanding diffusion controlled precipitate growth in steels
Optimizing Energy Consumption in Hydrogen Reduction of Iron Ore Pellet: Insights from HSC Chemistry Analysis
Full text linkIron ore pellet reduction in shaft furnaces represents a critical process in the steelmaking industry, with energy consumption being a key factor influencing both economic viability and environmental sustainability. This study employs HSC Chemistry software to model and simulate the energy consumption of hydrogen reduction of iron ore pellets under varying water vapor content within the shaft furnace. Thermodynamic modeling was carried out as the first step to analyze the effect of water vapor on the thermodynamic equilibrium, determining the possible range of water vapor content. Subsequently, energy consumption of the process was modeled based on heat and mass balance. Through comprehensive analysis, we investigate the impact of water vapor on the overall energy efficiency of the process based on the two scenarios of supplying the required heat by preheating the feed materials or injection of oxygen to the furnace. Our findings reveal significant insights into optimizing energy consumption and operational parameters to enhance the sustainability and cost-effectiveness of iron ore pellet reduction. This research contributes to the ongoing efforts towards achieving greater efficiency and reduced environmental footprint in the steelmaking industry
Computational analysis of conjugate heat transfer in a 2D rectangular channel with mounted obstacles using lattice Boltzmann method
Full text linkThe objective of this paper is to investigate the fluid flow and conjugate heat transfer in a 2D channel using lattice Boltzmann method (LBM). In this work, fluid flow and heat transfer are studied for the Reynolds numbers varying between 250 and 1000. The working fluid in the simulations is air with the Prandtl number of 0.72. At the Reynolds number of 600, the effect of different conductivity ratio (1, 10, 100, 400) between solid and fluid are investigated. Furthermore, at this Reynolds number, the distance between obstacles for the conductivity ratio of 10 is evaluated. The results show that any increase in Reynolds number leads to a heat transfer improvement. Moreover, increase in the conductivity ratio leads to an isothermal surface and enhanced heat transfer. The more the distance between the obstacles, the better the heat transfer rate. The results obtained from LBM are in good agreement with experimental and conventional computational fluid dynamics methods