{"title":"Linearization for Analysis of a Hydropower Model using Python API for OpenModelica","authors":"Liubomyr Vytvytskyi, B. Lie","doi":"10.3384/ECP18153216","DOIUrl":"https://doi.org/10.3384/ECP18153216","url":null,"abstract":"Even though almost all processes in the real world are described by nonlinear models, nonlinear theory for analysis of these models is far less developed than the theory for linear models. Therefore model linearization is important in order to make efficient analysis tools for these models. This paper describes the possibility of automatic linearization in Python for a hydropower system modeled in OpenModelica using our in-house hydropower Modelica library OpenHPL. Linearization is made using a Python API. Simple uses of the linearized model for analysis and synthesis are indicated.","PeriodicalId":350464,"journal":{"name":"Proceedings of The 59th Conference on imulation and Modelling (SIMS 59), 26-28 September 2018, Oslo Metropolitan University, Norway","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123097802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Web Enabled High Fidelity Drilling Computer Model with User-Friendly Interface for Education, Research and Innovation","authors":"Robert Ewald, Jan Einar Gravdal, D. Sui, R. Shor","doi":"10.3384/ECP18153162","DOIUrl":"https://doi.org/10.3384/ECP18153162","url":null,"abstract":"Next generation intelligent software for drilling control systems together with automated monitoring and analysis systems is expected to save costs for the drilling industry. However, the transition from monitoring a process, which today is controlled manually, to automating the process requires a step-change in education of personnel as well as in infrastructure for development and testing new technology. The lack of high quality field data from drilling and well operations is a major problem in research and innovation projects within the oil & gas and geothermal drilling sector, as well as in education within these areas. Since 2015, IRIS and the University of Stavanger have developed a web enabled high fidelity drilling simulator as part of the OpenLab Drilling project1. This paper describes the objectives of the project, the technical solutions of the web enabled drilling simulator, and the results obtained during the first year after deployment to the users.","PeriodicalId":350464,"journal":{"name":"Proceedings of The 59th Conference on imulation and Modelling (SIMS 59), 26-28 September 2018, Oslo Metropolitan University, Norway","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134576289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xu Cheng, R. Skulstad, Guoyuan Li, Shengyong Chen, H. P. Hildre, Houxiang Zhang
{"title":"A Data-Driven Sensitivity Analysis Approach for Dynamically Positioned Vessels","authors":"Xu Cheng, R. Skulstad, Guoyuan Li, Shengyong Chen, H. P. Hildre, Houxiang Zhang","doi":"10.3384/ECP18153156","DOIUrl":"https://doi.org/10.3384/ECP18153156","url":null,"abstract":"For safety-critical marine operations, the dynamically positioned (DP) vessel should maintain a predetermined heading and position for varying environmental conditions using the thrusters. Studying the effect of each thruster to the capability of DP vessels is significance but challenging. This paper presents a data-driven and variance-based sensitivity analysis (SA) approach that can dig into the ship sensor data to estimate the influence of each thruster for DP operations. Considering high-computational cost of variance-based SA, an Extreme Learning Machine (ELM) -based SA is proposed. To apply the SA to sensor data, an ANN is built and trained on the basis of ship sensor data and then employed as a surrogate model to generate Monte Carlo (MC) samples. A benchmark test shows the correctness of the proposed approach. A case study of SA in DP operation is conducted and the experimental results show that the proposed approach can rank and identify the most sensitive factors. The proposed approach highlights the application of variance-based SA in data-driven modeling for ship intelligence.","PeriodicalId":350464,"journal":{"name":"Proceedings of The 59th Conference on imulation and Modelling (SIMS 59), 26-28 September 2018, Oslo Metropolitan University, Norway","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115747896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The impact of the weather data file on the energy performance certificate, the case of Norway","authors":"A. Cáceres, D. Zenginis, T. Vik","doi":"10.3384/ECP18153342","DOIUrl":"https://doi.org/10.3384/ECP18153342","url":null,"abstract":"Energy Performance Building Directive (EPBD) ask the Member of States to develop a mandatory energy labelling scheme for new and existing buildings, which should include a label rating of the energy efficiency of the building and a list of recommended energy saving measures. The label will provide prospective buyers and tenants of a building with correct information about the energy performance of the building to compare with other options. However, some countries use only one or a limited number of weather zones. In a country like Norway, with significant variations in weather conditions between locations, this is likely to cause a deviation when comparing with the reality. This study aims to present the implication of using only one weather zone in Norway. The method used is based on the comparison of three types of weather files. The first one is used in the labelling system, which is a typical year, while the others are typical reference years from the local site from different providers. The results show significant differences in energy consumption, savings and labelling ratings when applying files with local weather data instead of the official weather data file used in Norway.","PeriodicalId":350464,"journal":{"name":"Proceedings of The 59th Conference on imulation and Modelling (SIMS 59), 26-28 September 2018, Oslo Metropolitan University, Norway","volume":"25 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132398324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Second Order KP Scheme for the Solution of flow in a Venturi Channel","authors":"S. Dissanayake, Roshan Sharma, B. Lie","doi":"10.3384/ECP18153193","DOIUrl":"https://doi.org/10.3384/ECP18153193","url":null,"abstract":"","PeriodicalId":350464,"journal":{"name":"Proceedings of The 59th Conference on imulation and Modelling (SIMS 59), 26-28 September 2018, Oslo Metropolitan University, Norway","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128795330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"System Development for On-line Monitoring using Raman Spectroscopy for CO2 Absorption by MEA","authors":"M. Jinadasa, K. Chandra, M. Halstensen","doi":"10.3384/ECP18153328","DOIUrl":"https://doi.org/10.3384/ECP18153328","url":null,"abstract":"Among various kinds of technologies available, carbon dioxide (CO2) capture by monoethanolamine (MEA) is considered to be the most technically and scientifically matured technology which can be tested in industrial scale. When CO2 is absorbed by an MEA, a chemical reaction takes place which results to form different carbon and amine species in the system. In this work, Raman spectroscopy has been used to measure those concentrations in-situ. Since the instrument does not provide direct measurements, multivariate analysis has been used to develop models and predictions are made using these models for future measurements. This study presents the methodology of acquiring measurements by the Raman spectroscopy for MEA-CO2-H2O system, transferring the measurement data into Matlab/Labview, converting data into concentration values and presenting the results in a graphical user interface. This software based platform makes the Raman spectroscopy to be accessed as a real-time instrument in CO2 capture plants.","PeriodicalId":350464,"journal":{"name":"Proceedings of The 59th Conference on imulation and Modelling (SIMS 59), 26-28 September 2018, Oslo Metropolitan University, Norway","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124415364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Comparison of simulation tools for dynamic models","authors":"S. M. Sund, Marianne Plouvier, B. Lie","doi":"10.3384/ECP18153177","DOIUrl":"https://doi.org/10.3384/ECP18153177","url":null,"abstract":"Macroscopic models are used extensively in process engineering, and can often be posed as DAE (Differential Algebraic Equation) models. Three generic tools for solving such DAEs are compared: OpenModelica, Julia, and MATLAB. To make the comparison concrete, a simple non-linear process model from the literature was extended by removing simplifying assumptions; the more complex model was posed as DAEs. Some implementation details of DAE models in OpenModelica, Julia, and MATLAB are given. Selected simulation results are given, with resulting execution time. The three tools gave identical simulation results. The tools are then compared wrt. cost, ease of use, documentation, numeric quality, Eco-system , and possibility for reuse of models/library. Overall, Julia appears may appear as the best choice. However, Modelica is found to be easier to use, so an ideal solution would probably be some tight integration of Modelica with Julia.","PeriodicalId":350464,"journal":{"name":"Proceedings of The 59th Conference on imulation and Modelling (SIMS 59), 26-28 September 2018, Oslo Metropolitan University, Norway","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116815632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}