Development of a computational fluid dynamics model for predicting fouling process using dynamic mesh model

This article presents a comprehensive computational model capable of simulating fouling layer thickness evolution using dynamic mesh model. This computational methodology has been developed to reproduce the deposit generation during fouling process with an innovated work method. Dynamic mesh model, from Ansys Fluent software, and external routines have been used to implement this advanced numerical model which allows to move the boundaries of a region relative to other boundaries of the zone. The displacement of the nodes of the mesh is the mechanism that this model uses to adjust the geometry according to the fouling layer evolution. During the simulation process, the geometry under investigation is modified to reproduce the emergence and gradual change of the fouling layer. Different rules of deposition and removal of the fouling process can be implemented in the proposed algorithm. The direct interaction between fouling expressions and governing equations of the main flow is used to predict deposits formation and growth. In this article, numerical simulations of soot fouling layer formation have been presented. Deposit evolution has been calculated inside different heat exchanger technologies used in exhaust gas recirculation systems to analyze fouling process and to verify the advantages of this new computational strategyMinisterio de Economía y Competitividad | Ref. ENE2014-60046-

Experimental investigation and CFD analysis of pressure drop in an ORC boiler for a WHRS implementation

Waste heat dissipated in the exhaust system of a combustion engine represents a major source of energy to be recovered and converted into useful work. The Waste Heat Recovery System (WHRS) based in an Organic Rankine Cycle (ORC) is an approach for recovering energy from heat sources, achieving a significant reduction in fuel consumption and, as a result, exhaust emissions. This paper studies pressure drop in an ORC shell-and-tubes boiler for a WHRS implementation experimentally and with computational simulations based on a 1-dimensional heat transfer model coupled with 3D calculations. An experimental database is developed, using ethanol in a pressure range of 10–15 absolute bar as working fluid, with mass fluxes inside the tubes in the range of 349.31 kg/s-m2 and 523.97 kg/s-m2, and inlet temperatures in the range of 60 °C and 80 °C. Thus, the friction factor of different regions of the boiler were estimated using both CFD simulations, experimental data, and bibliographic correlations. Simulations of operating points and the results of the experimental test bench showed good agreement in pressure drop results, with a mean absolute error of 15.47%, without a significant increment in the computational cost

Development of a pattern recognition methodology with thermography and implementation in an experimental study of a boiler for a WHRS-ORC

Waste heat dissipated in the exhaust system in a combustion engine represents a major source of energy to be recovered and converted into useful work. A waste heat recovery system (WHRS) based on an Organic Rankine Cycle (ORC) is a promising approach, and it gained interest in the last few years in an automotive industry interested in reducing fuel consumption and exhaust emissions. Understanding the thermodynamic response of the boiler employed in an ORC plays an important role in steam cycle performance prediction and control system design. The aim of this study is, therefore, to present a methodology to study these devices by means of pattern recognition with infrared thermography. In addition, the experimental test bench and its operating conditions are described. The methodology proposed identifies the wall coordinates, traces the paths, and tracks the wall temperature along them in a way that can be exported for subsequent post-processing and analysis. As for the results, through the wall temperature paths on both sides (exhaust gas and working fluid), it was possible to quantitatively estimate the temperature evolution along the boiler and, in particular, the beginning and end of evaporation

Application of supervised learning algorithms for temperature prediction in nucleate flow boiling

This work investigates the use of supervised learning algorithms to predict temperatures in an experimental test bench, which was initially designed for studying nucleate boiling phenomena with ethylene glycol/water mixtures. The proposed predictive model consists of three stages of machine learning. In the first one, a supervised algorithm block is employed to determine whether the critical heat flux (CHF) will be reached within the test bench limits. This classification relies on input parameters including bulk temperature, tilt angle, pressure, and inlet velocity. Once the CHF condition is established, another machine learning algorithm predicts the specific heat flux at which CHF will occur. Subsequently, based on the classification generated by the first block, the evolution of temperature in response to increases in heat flux is predicted using either the previously estimated heat flux or the physical limits of the experimental facility as the stopping criterion. To accomplish all these predictions, the study compares the performance of various algorithms including artificial neural networks, random forest, support vector machine, AdaBoost, and XGBoost. These algorithms were specifically trained using cross-validation and grid search methods to optimize their effectiveness. Results for the CHF classification purpose demonstrate that the support vector machine algorithm performs the best, achieving an F1-score of 0.872 on the testing dataset, while the boosting methods (AdaBoost and XGBoost) exhibit signs of overfitting. In predicting the CHF value, the artificial neural network achieved the lower nMAE on the testing dataset (6.18%). Finally, the validation of the temperature forecasting models, trained on a dataset composed of 314,476 samples, reveals similar performances across all methods, with R2 values greater than 0.95.Agencia Estatal de Investigación | Ref. RTC2019-006955-4Agencia Estatal de Investigación | Ref. PID2020-114742RB-I00Universidade de Vigo/CISU

Numerical study of a thrombus migration risk in aneurysm after coil embolization in patient cases: FSI modelling

Purpose There are still many challenges for modelling a thrombus migration process in aneurysms. The main novelty of the present research lies in the modelling of aneurysm clot migration process in a realistic cerebral aneurysm, and the analysis of forces sufered by clots inside an aneurysm, through transient FSI simulations. Methods The blood fow has been modelled using a Womersley velocity profle, and following the Carreau viscosity model. Hyperelastic Ogden model has been used for clot and isotropic linear elastic model for the artery walls. The FSI coupled model was implemented in ANSYS® software. The hemodynamic forces sufered by the clot have been quantifed using eight diferent clot sizes and positions inside a real aneurysm. Results The obtained results have shown that it is almost impossible for clots adjacent to aneurysm walls, to leave the aneurysm. Nevertheless, in clots positioned in the centre of the aneurysm, there is a real risk of clot migration. The risk of migration of a typical post-coiling intervention clot in an aneurysm, in contact with the wall and occupying a signifcant percentage of its volume is very low in the case studied, even in the presence of abnormally intense events, associated with sneezes or impacts. Conclusions The proposed methodology allows evaluating the clot migration risk, vital for evaluating the progress after endovascular interventions, it is a step forward in the personalized medicine, patient follow-up, and helping the medical team deciding the optimal treatment.Universidade de Vigo/CISU

Experimental evaluation of the effect of ozone treatment on the oxidation and removal of dry soot deposits of the exhaust gas recirculation system

The integration of alternative energy sources as a replacement for fossil fuels across various industrial sectors, including power generation, emergency systems, or marine applications, is uncertain. As a result, the utilization of traditional fuels is not anticipated to be fully phased out in the near future. To address this, new technologies, such as those that employ oxidising atmospheres, have been explored as a means to enhance the pollution control capabilities of existing technologies, as the Exhaust Gas Recirculation (EGR) system. In this regard, the present study has assessed the efficacy of ozone atmosphere exposure in mitigating the formation of undesired fouling deposits within the system, with the aim of facilitating more efficient operation of EGR devices and extending their service life. To this end, dry soot samples have been exposed to various ozone atmospheres at different temperatures and ozone concentrations through the utilization of an experimental test bench. The oxidation potential of these atmospheres has been evaluated through the analysis of the deposit mass loss. Likewise, confocal microscopy techniques have been employed to obtain the 3D topography of the fouling samples before and after the ozone treatment, allowing the assessment of the deposit thickness reduction, as well as the surface roughness variation. Additionally, thermogravimetric analysis has been conducted to examine the effects of the oxidation processes on fouling samples composition. The findings of this study have revealed that ozone atmospheres have been effective in reducing deposit mass at ozone treatment temperatures above 100 °C. The reduction in mass has reached 78.5% and 91.8% with treatment temperature of 140 °C with ozone concentrations of 30 gO3/m³ and 50 gO3/m³, respectively. It has also been established that treatment conditions with ozone concentrations of 30 gO3/m³ and 50 gO3/m³ are effective in reducing the thickness of deposits even at intermediate treatment temperatures, resulting in a thickness reduction of 78.6% and 81.1% at 80 °C, respectively. Additionally, it has been observed that the ozone exposure leads to the increase in the proportion of volatile material within the deposiUniversidade de Vigo/CISUGAgencia Estatal de Investigación | Ref. PDC2021-121778-10

Analysis of the local growth and density evolution of soot deposits generated under hydrocarbon condensation: 3D simulation and detailed experimental validation

The utilization of the Exhaust Gas Recirculation (EGR) system during atypical engine operating conditions in order to meet future type-approval criteria exposes the internal surfaces of the devices to exhaust gas with elevated concentrations of particulate matter and greater amounts of hydrocarbon species, leading to the formation of dense and wet sludge deposits. To broaden the understanding of this phenomenon and contribute to the development of advanced EGR devices, this study presents an extended Computational Fluid Dynamics (CFD) model that, in addition to simulating the growth of fouling deposits caused by the accumulation of soot particles, also takes into account the condensation of hydrocarbons. Two scenarios with varying hydrocarbon concentrations in the exhaust flow are analysed, and the evolution of the deposit's thickness and density is determined. A sequential validation process is carried out by comparing the numerical results to actual deposit profiles at different stages of the fouling process. Additionally, hyperspectral images of the fouling layer have been acquired and analysed to validate the regions where hydrocarbon condensation is predicted to play a crucial role, enabling the verification of the hydrocarbon condensation phenomenon predicted by the numerical model. The results obtained under the studied conditions indicate that, on average, 77.4% of the analysed area exhibits a low level of relative error, demonstrating that the proposed model and the methodology used serve as a valuable tool for examining the propensity for deposit formation in devices subjected to fouling exacerbated by hydrocarbon condensation.Agencia Estatal de Investigación | Ref. PDC2021-121778-10

Sistemas fluidomecánicos no transporte: prácticas de simulacións numéricas

A tecnoloxía CFD, sigla de Computational Fluid Dynamics, en galego Dinámica de Fluídos Computacional, é unha técnica de análise numérica que permite determinar o comportamento dos fluídos mediante a realización de experimentos virtuais no ordenador. Esta técnica conta con varias décadas de desenvolvemento científico de respaldo, converténdose a día de hoxe nun dos estándares de análise para numerosos sectores industriais. É por iso que as simulacións numéricas son empregadas actualmente como eficaces ferramentas de diagnóstico nas etapas de deseño, mellora e optimización de produtos e procesos de fabricación en industrias como a naval, a automobilística, a aeroespacial, a hidráulica, as enerxías renovables, a enxeñería biomédica ou a construción. Co fin de achegar o emprego desta técnica ao alumnado do grado de Enxeñería Mecánica, este manual foi creado para servir de apoio á docencia da materia Sistemas fluidomecánicos e materiais avanzados para o transporte, enfocándose na aplicación práctica de simulacións numéricas en casos reais da enxeñería nos que se atopan involucrados fluxos de fluídos. Esta colección de exercicios prácticos pretende servir de axuda na etapa formativa do alumnado, facilitándolle a información necesaria e a metodoloxía que deberá empregar para levar a cabo o estudo de diferentes casos, e favorecendo así unha comprensión intuitiva dos problemas propostos mediante a análise dos resultados obtidos nas simulacións numéricas. Por tratarse dun dos programas de CFD máis empregados na industria, o software utilizado nas actividades deste manual é ANSYS Fluent 2020. Así tamén, as actividades propostas neste manual foron deseñadas para poder ser levadas a cabo contando cunhas esixencias computacionais accesibles para o alumnado, o cal poderá realizar nun tempo axeitado os exercicios aquí recollidos

Transcranial static magnetic stimulation reduces seizures in a mouse model of Dravet syndrome

Dravet syndrome is a rare form of severe genetic epilepsy characterized by recurrent and long-lasting seizures. It appears around the first year of life, with a quick evolution toward an increase in the frequency of the seizures, accompanied by a delay in motor and cognitive development, and does not respond well to antiepileptic medication. Most patients carry a mutation in the gene SCN1A encoding the α subunit of the voltage-gated sodium channel Nav1.1, resulting in hyperexcitability of neural circuits and seizure onset. In this work, we applied transcranial static magnetic stimulation (tSMS), a non-invasive, safe, easy-to-use and affordable neuromodulatory tool that reduces neural excitability in a mouse model of Dravet syndrome. We demonstrate that tSMS dramatically reduced the number of crises. Furthermore, crises recorded in the presence of the tSMS were shorter and less intense than in the sham condition. Since tSMS has demonstrated its efficacy at reducing cortical excitability in humans without showing unwanted side effects, in an attempt to anticipate a possible use of tSMS for Dravet Syndrome patients, we performed a numerical simulation in which the magnetic field generated by the magnet was modeled to estimate the magnetic field intensity reached in the cerebral cortex, which could help to design stimulation strategies in these patients. Our results provide a proof of concept for nonpharmacological treatment of Dravet syndrome, which opens the door to the design of new protocols for treatmentXunta de Galicia | Ref. ED431C 2022/05 (CR)Instituto de Salud Carlos III | Ref. PI16/00425Agencia Estatal de Investigación | Ref. PID2019-108250RJ-100Agencia Estatal de Investigación | Ref. RYC2019–026380-

CFD transient simulation of the cough clearance process using an Eulerian wall film model

In this study, a cough cycle is reproduced using a computational methodology. The Eulerian wall film approach is proposed to simulate airway mucus flow during a cough. The reproduced airway domain is based on realistic geometry from the literature and captures the deformation of flexible tissue. To quantify the overall performance of this complex phenomenon, cough efficiency (CE) was calculated, which provided an easily reproducible measurement parameter for the cough clearance process. Moreover, the effect of mucus layer thickness was examined. The relationship between the CE and the mucus viscosity was quantified using reductions from 20 to 80%. Finally, predictions of CE values based on healthy person inputs were compared with values obtained from patients with different respiratory diseases, including chronic obstructive pulmonary disease (COPD) and respiratory muscle weakness (RMW). It was observed that CE was reduced by 50% in patients with COPD compared with that of a healthy person. On average, CE was reduced in patients with RMW to 10% of the average value of a healthy person