Linköping Electronic Conference Proceedings
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CFD validation of optimized compact heat exchanger designs
Full text linkIn offshore oil and gas production gas turbines are used for both power production and to provide process heat. CO2 emissions from the gas turbines accounts for about 25 % of the total Norwegian emissions and installing a bottoming cycle to produce power by recovering heat from the gas turbine exhaust is one way to reduce these missions. When installing a steam bottoming cycle offshore, the total weight and size will be important, and there is a need for a compact heat recovery steam generator (HRSG). A compact HRSG will often need to be designed with smaller tube diameters than conventional on-shore steam generators. To increase confidence in the compact design, the heat transfer and pressure loss models need to be accurate for the relevant geometry ranges. In this work, a compact Once Through Steam Generator (OTSG) is designed using optimisation procedures where the total weight of the steam generator has been minimised for a desired duty with restrictions for pressure losses. A range of correlations from the literature were used for the calculation of the performance. The results from the optimisation show that the ’heaviest’ results were about three times the minimum weight than the ’lightest’. To increase confidence in the results, and to provide arecommendation for design models, a validated CFD model was used to perform a numerical analysis of the optimised geometry and compare this with the correlations
Simulation of ammonia cracker process with Aspen HYSYS
Full text linkThis paper presents simulations of an ammonia cracker process using Aspen HYSYS. Ammonia is identified as both a promising low-emission maritime fuel and an energy carrier. This study focuses on converting ammonia to hydrogen through an ammonia cracker process. In the literature, there are found simulations of similar processes, but not much about optimization of the ammonia cracker process. A centralized ammonia cracking process was designed using the Peng-Robinson fluid package and Gibbs reactor in Aspen HYSYS. Gibbs reactors were employed to simulate both the cracker and the furnace (ammonia combustion reaction). Simplified assumptions included using a 100 % efficient splitter instead of a pressure swing adsorber. The ammonia feed had a molar flow rate of 500 kmole/h. The simulations included a base case scenario and an improved case for energy optimization. The base case scenario resulted in a total production of 0.13 kg of hydrogen per kg of ammonia feed. The improved case resulted in a production of 0.14 kg hydrogen. This was due to using the energy content present in the hydrogen and nitrogen product streams for warming up the ammonia before entering the cracker. This work demonstrates that Aspen HYSYS is a useful tool for optimizing the energy efficiency of an ammonia cracker process
Performance Analysis of Advanced Wells in Reservoirs Using CO2 Enhanced Oil Recovery
Full text linkOil and gas will remain an important source of energy for years and it is crucial to improve oil recovery with less carbon footprint. Carbon capture utilization and storage offers a potential solution to mitigate the effects of anthropogenic CO2. The captured CO2 can be utilized to enhanced oil recovery (EOR) and is injected into the oil fields for storage and/or EOR. However, the injected CO2 can be reproduced without contributing to EOR. This is due to the breakthrough of CO2 into the well. Also, the corrosive mixture of CO2 and water can be produced from the production well. This may cause damages to the pipeline and process equipment on the platform. Autonomous inflow control valves (AICVs) can mitigate these problems. They may reduce or stop the reproduction of CO2 from the zones with CO2 breakthrough and reduce the production of mixture of CO2 and water. The main objective of this study is modelling and simulation of oil production in a heterogenous reservoir using CO2-EOR in combination with AICVs. The outcome of numerical simulations is analyzed to study the effect of various parameters on oil recovery. In addition, the impact of AICVs on EOR is assessed against perforated casing completion (without AICV). The results demonstrate that oil recovery factor, water cut, and cumulative gas production are better in the wells completed with AICVs than perforated casing completion. This will result into both increased oil production and a better CO2 storage potential
Utilizing computational thermodynamics in characterization and classification of non-metallic inclusions in Ti-deoxidized steels
Full text linkNon-metallic inclusions (NMIs) are micrometer-sized particles observed in all steel materials, often considered detrimental. In this study, NMIs in titanium-deoxidized steels were investigated, complemented with thermodynamic assessment for more accurate phase characterization. The NMIs were analyzed with a Jeol JSM-7900F FESEM-EDS (Field Emission Scanning Electron Microscope equipped with Energy Dispersive X-ray Spectroscope). For automated particle analyses on FESEM, Aztec Feature runs were carried out on polished steel samples, providing the elemental composition, in addition to morphological data, for each observed NMI. Utilizing the obtained EDS analyses, the fractions of oxides (Al2O3, MnO, TiOx), manganese sulfide (MnS), and titanium nitride (TiN) in each NMI are estimated with a MATLAB script. Based on the estimated phase contents, a composition-based classification method for the NMIs is presented. To visualize the phase contents of the observed NMIs, the calculated compositions are plotted on MnO–TiO2–Ti2O3 ternary diagrams. Computational thermodynamics software FactSage 8.3 was firstly utilized to estimate the fully liquid NMI composition region at steelmaking temperatures in the considered ternary oxide system of MnO–TiO2–Ti2O3. Secondly, the thermodynamic stability of NMI phases in the steel was assessed with decreasing temperature during the solidification of steel. The current study demonstrates how computational thermodynamics can be utilized in characterization and classification of non-metallic inclusions and giving insight on their formation during solidification of steel
Cellular automata model for austenite formation and grain growth during heating and holding above austenization temperature
Full text linkUnderstanding the steel microstructure formation during thermal treatments is crucial for controlling the mechanical properties of a steel product. One of the important factors affecting the subsequent microstructure development is the austenite grain size. To gain understanding of the effect of temperature dependent nucleation and growth rates, as well as providing the tools for quantitatively control the austenite grain size distribution, we have implemented a cellular automata (CA) model for describing austenite nucleation and growth during heating, as well as austenite grain growth during holding in temperatures above the austenitization temperature. The model implementation is based on previous study of Sieradzki and Madej for grain growth during recrystallization now augmetned with the relevant equations for describing the austenite nucleation and growth. The model parameters and their effect on austenite grain size distributions are tested with numerical experiments. The developed computational tool will serve as a basis that can be parameterized with experimental data in the future, which will then enable quantitative predictions for austenite phase transformation and grain size development
Evaluation of model uncertainty propagation in mineral process flowsheet designs
Full text linkIncreasing demand for critical raw materials and energy transition metals sets new targets for the mineral processing, also resulting as higher requirements for the simulation tools during process design and optimization. This study presents a framework for global uncertainty evaluation of modelled plant-wide processes, where the propagation of uncertainty sources is addressed. The uncertainties exist, for example in operational and design parameters and in material properties. The approach was demonstrated with a typical mineral processing flowsheet simulated with commercial software. First, domain knowledge was adopted to screen the parameter space and then Monte Carlo simulation was performed. After this, the generated data set was used to identify surrogate models between the uncertain inputs and process performance indicators. Finally, a global sensitivity analysis was conducted to identify the effects of uncertainties to the decision-making in process design. The results were particularly used to locate the process points where accurate information is needed for the robust process design, or where on-line measurements would be preferred to establish on-line optimization
GPU acceleration of average gradient method for solving partial differential equations
Full text linkPreviously presented method of calculating local average gradients for solvingpartial differential equations (PDEs) is enhanced by accelerating it with graphics processingunits (GPUs) and combining a previous technique of interpolating between grid points in thecalculation of the gradients instead of using interpolation to create a denser grid.For accelerating the calculation with GPUs, we have ported the original naive Matlabimplementation to C++ and CUDA, and after optimizing the code we observe a speedupfactors more than two thousand, which is largely due to the original code not being optimized
FAIR Tool Discovery: an automated software metadata harvesting pipeline for CLARIAH
Full text linkWe present the Tool Discovery pipeline, a core component of the CLARIAH infrastructure in the Netherlands. This pipeline harvests software metadata from the source, detects existing heterogeneous metadata formats already in use by software developers, and converts them to a single uniform representation based on schema.org and codemeta. The resulting data is then made available for further ingestion into other user-facing catalogue/portal systems
Adapting UPSKILLS Learning Modules to the University Curricula: Best Practices and Lessons Learnt from the H2IOSC Training Experience at the University of Ferrara
Full text linkThis paper details the steps taken to adapt and integrate the training materials developed by CLARIN ERIC in two bachelor’s degree courses and one master’s degree course at the University of Ferrara. The workflow applies the shared methodology developed within the Humanities and Heritage Italian Open Science Cloud project. It modifies the training materials of the UPSKILLS course “Introduction to Language Data: Standards and Repositories” according to the needs of three target courses focusing on English to Italian translation: English Language Course for Tourism, English Language for Translation and English Language and Linguistics for Humanities, Arts and Archaeology. The result of this pilot is a documented example of how CLARIN services can be integrated into university teaching, including initial teacher training, and providing an opportunity to discuss the topic and a use case for trainers who intend to include CLARIN in their courses
Managing Access to Language Resources in a Corpus Analysis Platform
Full text link"Corpus query tools are crucial to CLARIN’s mission of facilitating the sharing and use of language data for research. It is a huge challenge for online corpus platforms to manage user access rights for large corpora with complex licenses and heterogeneous restrictions on access methods and purposes. This paper presents an approach to maximize user access to corpus data while protecting rights holders’ legitimate interests. Query rewriting techniques and authorization procedures allow for modelling license terms in detail, enabling broader applications. This offers an alternative to methods that only model a greatest common denominator of licenses, thereby limiting the possibilities for using the data. Our approach constitutes a flexible and extensible corpus license and user rights management component applicable for other language research environments.