Linköping Electronic Conference Proceedings
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Accelerating the simulation of equation-based models by replacing non-linear algebraic loops with error-controlled machine learning surrogates
Get PDFWhen simulating a Modelica model, non-linear algebraic loops may be present, which involves solving multiple equations simultaneously. The classical Newton-Raphson method is commonly employed for solving a non-linear equation system (NLS). However, the computational burden of using this method during simulation can be significant. To tackle this issue, utilizing artificial neural networks (ANNs) to approximate the solution of algebraic loops is a promising approach. While ANN surrogates offer fast performance, ensuring the correctness of the computed solution or quantifying reliability can be challenging. This publication presents a prototype, based on the OpenModelica compiler (OMC), that automates the extraction of time-consuming algebraic loops. It generates training data, trains ANNs using machine learning (ML) methods, and replaces the algebraic loops with ANN surrogates in the simulation code. A hybrid approach, combining the trained surrogate with the nonlinear Newton solver, is then used to compute the solution with a desired level of accuracy
Dynamic Modeling and Experimental Validation of Dishwasher with Heat Pump System
Get PDFIntegration of heat pump systems with conventional dishwashers or household water heaters using electric heaters offers a promising solution to significantly reduce expected energy consumption. In this study, a comprehensive approach was undertaken to develop sub-models for each component of the heat pump dishwasher. These sub-models were subsequently integrated to form a complete cycle model of the heat pump dishwasher. The specific components modeled included the compressor, evaporator, condenser, and capillary tube. Furthermore, an algorithm was devised to ensure the proper functioning of all the individual models, in accordance with the operational principles of the dishwasher. To validate the model, the temperature variation within the dishwasher during the heating and cooling phases was compared against experimental data. The maximum deviation observed in the cabinet temperature of the dishwasher was found to be 1 °C, with a corresponding deviation of 0.5 minutes in the cycle duration. Moreover, the maximum deviation in power consumption amounted to 2.4%, while a maximum deviation of 2.9% was noted in energy consumption. The results obtained from the model closely aligned with the experimental outcomes, thereby confirming its accuracy and reliability
Beyond FMI - Towards New Applications with Layered Standards
Get PDFThe FMI standard - just like any other standard - faces the challenge of balancing generality with enabling specific use cases. Including every domain or use-case specific extension in the core standard would significantly increase its length, making it unreadable and unimplementable. To allow for extensions of the core standard for specific use cases, the Modelica Association developed the concept of layered standards, first in the SSP standard and later in FMI. This paper presents the concept of layered standards and describes the layered standards currently under development by the FMI Project: XCP support of FMUs, network communication, and structured variables and regular maps in FMI 3.0
Secure Exchange of Black-Box Simulation Models using FMI in the Industrial Context
Get PDFFMI is a standard for exchanging simulation models in a platform-agnostic way, also in form of black-box models. In the industrial context, it is common to exchange such black-box simulation models especially between partners. Using and running such models, though, is a security issue as there is no way to verify and validate the content of the models. This security issue must be addressed especially in the industrial context where security is considered high priority in general. Based on an exemplary model exchange, possible attacks are analyzed in this work. By using cryptography, three different approaches to pack the additional metadata are presented that aim at providing end-to-end integrity checks to a black-box simulation models. Together with administrative measures, this allows to define those FMUs to be trusted and executed. For sake of completeness, a prototype was implemented to help with the cryptographic processes and show the effectiveness of the provided solution.
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DroneLibrary: Multi-domain Drone Modeling in Modelica
Get PDFIn the development of complex, novel electrified aerial systems such as Unmanned Aerial Vehicles (UAVs) and electric vertical take-off and landing (eVTOL) systems, multi-domain modeling and simulation studies can provide indispensable insight on system design and performance. In this paper, a Modelica library used to model multi-domain drone models is introduced. This library models a drone in the electrical, mechanical, and control domains, with examples for applications such as battery-power analysis, virtual reality simulation and user interaction
A distantly supervised Grammatical Error Detection/Correction system for Swedish
Get PDFThis paper presents our submission to the first Shared Task on Multilingual Grammatical Error Detection (MultiGED-2023). Our method utilizes a transformer-based sequence to-sequence model, which was trained on a synthetic dataset consisting of 3.2 billion words. We adopt a distantly supervised approach, with the training process relying exclusively on the distribution of language learners’ errors extracted from the annotated corpus used to construct the training data. In the Swedish track, our model ranks fourth out of seven submissions in terms of the target F0.5 metric, while achieving the highest precision. These results suggest that our model is conservative yet remarkably precise in its predictions
Response Surface Modelling to Reduce CO2 Capture Solvent Cost by Conversion of OZD to MEA
Get PDFThe increasing CO2 concentration in the atmosphere is the most urgent global challenge. The most mature CO2 abatement option is post-combustion CO2 capture employing Monoethanolamine (MEA) solvent. One challenge of using MEA is its in-service degradation to 2-oxazolidinone (OZD), a heterocyclic five-membered organic ring compound. Furthermore, OZD degrades more MEA leading to CO2 capture solvent loss and hence increased operational cost. It is therefore of interest to investigate methods to convert OZD back to MEA. This work reports the conversion of 2-oxazolidinone to MEA by heat treatment at an alkaline condition. Raman spectroscopy and Ion-Exchange chromatography were applied to qualify and quantify the reaction. The optimal reaction parameters were identified by an experimental design model using the Response Surface Methodology (RSM). A second-order model with three variables and five levels of focus was employed, with the OZD conversion percentage as the response. This methodology was chosen because such a model could estimate the main effects, interactions and quadratic terms by relying on a relatively small number of experiments. 17 experimental runs were designed by the software using this method. At a reaction time of 35 minutes, reaction temperature of 100°C, and 2.5 mole of hydroxide per mole of OZD resulted in a complete conversion of OZD to MEA
Economic investigation of heat pumps for heat recovery from data center
Get PDFThe rapid growth of technology and digitalization lead to an increase in the number of data centers around the world. Data centers produce a considerable amount of heat because of their servers and a large number of electric components. The heat generated by the data centers can be used as a potential source of heating, but the quality (temperature level) of the heat is normally low. In this work, the temperature of the excess (cooling) water from a data center is 45 °C. Generally, there is a possibility to use heat pumps to improve the quality of the heat. To obtain a district heating temperature of 60 °C, 70 °C and 80 °C, the coefficient of performance (COP) was calculated to 5.5, 4.3 and 3.5, respectively. This work is about utilization of the excess heat from a data center with three alternative heat pump solutions with a payback period and economic potential for 10 and 20 years. The simulation process was done by Aspen HYSYS. It was observed that the payback period as expected increases with decreasing COP. The payback period was calculated to values between 2.6 and 5.5 years, depending on the market situation and the delivery temperature. In this work, it is shown that Aspen HYSYS is a reasonable tool to calculate alternatives for heat recovery from data centers based on heat pumps
Simulation of Oil Recovery Through Advanced Wells Using a Transient Fully Coupled Well-Reservoir Model
Get PDFOil recovery can be enhanced by maximizing the well-reservoir contact using long horizontal wells. One of the main challenges of using such wells is the early breakthrough of unwanted fluids due to the heel-toe effect and heterogeneity along the well. To tackle this problem, advanced wells are widely applied today. The successful design of such wells requires an accurate integrated dynamic model of the well and reservoir. This paper aims at developing appropriate integrated well-reservoir models for achieving optimal long-term oil recovery from advanced well models.In this study, OLGA® which is a dynamic multiphase flow simulator is implicitly coupled to ECLIPSETM which is a dynamic reservoir simulator for developing accurate models to simulate oil production from advanced wells under various production/injection strategies. A realistic heterogeneous light oil reservoir with an advanced horizontal well is used as a case study. Flow Control Devices (FCDs) are the key component of advanced wells and the functionality of the main types of FCDs in improving the oil production, minimizing the cost and carbon footprint is investigated.According to the obtained results, by implementation of FCDs the water breakthrough time is delayed by 180 days and the cumulative water production with ICD, AICD, and AICV completions is reduced by 26.8%, 33.1%, and 49.1%, respectively, compared to the open-hole case. Besides, the results show that linking OLGA and ECLIPSE is a numerically stable and accurate approach for modeling the interaction between the dynamic reservoir and dynamic well behavior for simulation oil recovery from advanced wells
Developing a Multi-Building Scale Energy Model for a University Campus using URBANopt
Get PDFBuilding energy models are developed to describe energy performance. The energy performance of buildings is influenced by physical and human influenced factors. Therefore, to improve energy efficiency and renewable energy implementation in buildings on large scale, there is a need to analyze buildings on a large scale. In this study, URBANopt, a multi-building energy evaluation tool, was used to develop an accurate Multi building scale energy model for a university campus. This model will be useful in the future work to evaluate various available and emerging building-level and district-level technologies and retrofitting options to improve energy performance. URBANopt is a unique tool that leverages high-fidelity simulations of buildings, community-scale systems, distributed energy resources, and the associated interactions with local distribution electric infrastructure. A university campus in Norway was chosen as a case study. Results obtained from URBANopt were compared with a typical building energy simulation model in IDA-ICE for a representative building. This representative building was developed based on building characteristics, functionality, and geographic location, including indoor and outdoor climate conditions. Both models were validated by using measurement data. The results showed better simulation accuracy of the multi-building method of URBANopt with the measurement data, mainly due to the averaging of the characteristics of all buildings in the development of the representative building. Furthermore, the URBANopt allowed assigning a different scenario of technologies and retrofit options to each building in the evaluation process, which is impossible in the typical model due to its nature. However, it should be pointed out that the computational time of the model developed in URBANopt was higher and will increase more with the increased number of buildings