S. Kenjeres
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15 records found
1
Solving the Linear Boltzmann Transport Equation in the Presence of a Magnetic Field
Development of a deterministic Boltzmann framework for radiotherapy in the presence of a magnetic field
The results acquired with the algorithm based on the DGFEM method were compared to exact solutions, these results were consistent with the exact solutions and reported high levels of accuracy. The accuracy of these methods was comparable to those achieved by using discrete ordinates. Furthermore, the cost of the DGFEM algorithm were compared to those of the discrete ordinate method, here it has been shown that the DGFEM algorithm is only slightly more computationally expensive.
The DGFEM based solution algorithm was extended by implementing the magnetic field operator into the algorithm. The deterministic results in the presence of a magnetic field were compared against the MCNP and TOPAS Monte Carlo codes. These results showed similar dose distributions compared to MCNP, however, the deterministic results were not in accordance with the TOPAS simulation. It is suspected that the discrepancy in dose distribution originates from the difference in source spectrum between the two methods.
In order to investigate the influence of a magnetic field, dose distributions were determined with a magnetic field perpendicular to the photon beam. The results showed that the buildup region decreases for stronger magnetic fields and that higher values for the dose are formed at the boundaries between materials with different densities. This increased dose is caused by the electron return effect and becomes more condensed for stronger magnetic fields. Furthermore, a lateral shift in the dose distribution has been observed in the direction of the Lorentz force. These results show that the developed deterministic Boltzmann solver is able to generate accurate dose distributions in the presence of a magnetic field. ...
The results acquired with the algorithm based on the DGFEM method were compared to exact solutions, these results were consistent with the exact solutions and reported high levels of accuracy. The accuracy of these methods was comparable to those achieved by using discrete ordinates. Furthermore, the cost of the DGFEM algorithm were compared to those of the discrete ordinate method, here it has been shown that the DGFEM algorithm is only slightly more computationally expensive.
The DGFEM based solution algorithm was extended by implementing the magnetic field operator into the algorithm. The deterministic results in the presence of a magnetic field were compared against the MCNP and TOPAS Monte Carlo codes. These results showed similar dose distributions compared to MCNP, however, the deterministic results were not in accordance with the TOPAS simulation. It is suspected that the discrepancy in dose distribution originates from the difference in source spectrum between the two methods.
In order to investigate the influence of a magnetic field, dose distributions were determined with a magnetic field perpendicular to the photon beam. The results showed that the buildup region decreases for stronger magnetic fields and that higher values for the dose are formed at the boundaries between materials with different densities. This increased dose is caused by the electron return effect and becomes more condensed for stronger magnetic fields. Furthermore, a lateral shift in the dose distribution has been observed in the direction of the Lorentz force. These results show that the developed deterministic Boltzmann solver is able to generate accurate dose distributions in the presence of a magnetic field.
Computed Tomography of Simulated Bubble Columns
Validating Reconstructions and Quantifying Errors
design correlations or computational fluid dynamics, have been shown to break down when
air-water systems are replaced with systems containing actual fermentation broth. The additional broth components can significantly affect interphase mass transfer through e.g. limiting bubble breakup, which can in turn make or break the economics of a bioprocess [1]. Experimental data on the effects of broth components on the physics in bubble columns is essential to develop better models. Gathering such data requires experimental methods capable of penetrating the industrially-relevant but opaque churn-turbulent flows. A promising method for determining the state of a large section of the bubble field in a bubble column is X-ray computed tomography. The TU Delft X-ray tomography setup seeks to achieve this using three source-detector pairs capable of capturing X-ray data at high frame rates. However, in order to be able to apply any experimental technique, it must first be validated and the sources of and magnitude of its various measurement errors must be quantified.
This thesis uses computational fluid dynamics to validate tomographic reconstruction algorithms.
The computational fluid dynamics model was validated using experimental data from
Sanyal et al.[2] Furthermore, this thesis finds ways of improving tomographic reconstructions
through discovering which reconstruction algorithms perform best for different datasets. It was found that for time-resolved bubble fields, a version of SIRT (Simultaneous Iterative Reconstruction Technique) with generalised Tikhonov regularisation using the derivative operator performed best with a NRMSE (Normalised Root Mean Squared Error) of 0.0867 over a baseline value of 0.1123 using the default SIRT method and an F-score of 0.641 for the binary
classification of air and water. For time-averaged reconstructions of the gas holdup, an SIRT
with standard Tikhonov regularisation with an offset to the mean gas holdup was found to
perform best with a NRSME of 0.0137 over a SIRT baseline of 0.0160. Finally, this thesis
shows the improvement to tomographic reconstructions for an upgraded version of the TU
Delft X-ray tomography setup and provides recommendations for future research on this topic.
It was shown that increasing the number of source-detector pairs to five, leads to significant
improvements in the time-resolved bubble field reconstructions, with a new NRMSE of 0.0617
(-28%) and F-score of 0.823 (+28%) ...
design correlations or computational fluid dynamics, have been shown to break down when
air-water systems are replaced with systems containing actual fermentation broth. The additional broth components can significantly affect interphase mass transfer through e.g. limiting bubble breakup, which can in turn make or break the economics of a bioprocess [1]. Experimental data on the effects of broth components on the physics in bubble columns is essential to develop better models. Gathering such data requires experimental methods capable of penetrating the industrially-relevant but opaque churn-turbulent flows. A promising method for determining the state of a large section of the bubble field in a bubble column is X-ray computed tomography. The TU Delft X-ray tomography setup seeks to achieve this using three source-detector pairs capable of capturing X-ray data at high frame rates. However, in order to be able to apply any experimental technique, it must first be validated and the sources of and magnitude of its various measurement errors must be quantified.
This thesis uses computational fluid dynamics to validate tomographic reconstruction algorithms.
The computational fluid dynamics model was validated using experimental data from
Sanyal et al.[2] Furthermore, this thesis finds ways of improving tomographic reconstructions
through discovering which reconstruction algorithms perform best for different datasets. It was found that for time-resolved bubble fields, a version of SIRT (Simultaneous Iterative Reconstruction Technique) with generalised Tikhonov regularisation using the derivative operator performed best with a NRMSE (Normalised Root Mean Squared Error) of 0.0867 over a baseline value of 0.1123 using the default SIRT method and an F-score of 0.641 for the binary
classification of air and water. For time-averaged reconstructions of the gas holdup, an SIRT
with standard Tikhonov regularisation with an offset to the mean gas holdup was found to
perform best with a NRSME of 0.0137 over a SIRT baseline of 0.0160. Finally, this thesis
shows the improvement to tomographic reconstructions for an upgraded version of the TU
Delft X-ray tomography setup and provides recommendations for future research on this topic.
It was shown that increasing the number of source-detector pairs to five, leads to significant
improvements in the time-resolved bubble field reconstructions, with a new NRMSE of 0.0617
(-28%) and F-score of 0.823 (+28%)
Improving Data-Driven RANS Turbulence Modelling For Separated Flow Scenarios
In Support of Formula 1 Aerodynamic Development
Recent advances in data-driven RANS turbulence modeling have enabled partial correction of these uncertainties. However, obtaining a correction that is generalizable under different geometries and flow conditions remains a challenge. Turbulence models are calibrated to fit specific flow regimes, so correcting these models across the entire domain can disturb these calibrations, worsening performance. A solution is to divide the domain into regions based on identifiable physical phenomena and apply local corrections without disturbing calibrated regions. In Formula 1 race car design, the most critical region is the shear layer, where RANS shows the largest discrepancies.
In this thesis, a classifier was developed to distinguish the shear layer from the rest of the domain based on the ratio between turbulent kinetic energy production and destruction, as well as turbulence intensity. Within this classifier region, corrections to the k-ω SST turbulence model are made by extracting model form errors from high-fidelity data using k-corrective-frozen RANS. These corrections include a residual term added to both the k and equations and a term for the anisotropy of the Reynolds stress tensor. The Spars Regression of Turbulent Stress Anisotropy (SpaRTA) framework, based on elastic-net regularization, was used to regress symbolic expressions for the corrections, enabling their application to simulations of unseen test cases.
The models discovered with the SpaRTA framework for the shear layer show promising results, improving the prediction of separation and reattachment positions. These models were tested on various geometries and simulations at different Reynolds numbers, demonstrating a certain level of generalizability. While there is room for further improvement, this thesis shows that integrating targeted model corrections into RANS simulations, informed by isolated shear layer data, can enhance the understanding and prediction of shear layer dynamics in 2D-separated flows. ...
Recent advances in data-driven RANS turbulence modeling have enabled partial correction of these uncertainties. However, obtaining a correction that is generalizable under different geometries and flow conditions remains a challenge. Turbulence models are calibrated to fit specific flow regimes, so correcting these models across the entire domain can disturb these calibrations, worsening performance. A solution is to divide the domain into regions based on identifiable physical phenomena and apply local corrections without disturbing calibrated regions. In Formula 1 race car design, the most critical region is the shear layer, where RANS shows the largest discrepancies.
In this thesis, a classifier was developed to distinguish the shear layer from the rest of the domain based on the ratio between turbulent kinetic energy production and destruction, as well as turbulence intensity. Within this classifier region, corrections to the k-ω SST turbulence model are made by extracting model form errors from high-fidelity data using k-corrective-frozen RANS. These corrections include a residual term added to both the k and equations and a term for the anisotropy of the Reynolds stress tensor. The Spars Regression of Turbulent Stress Anisotropy (SpaRTA) framework, based on elastic-net regularization, was used to regress symbolic expressions for the corrections, enabling their application to simulations of unseen test cases.
The models discovered with the SpaRTA framework for the shear layer show promising results, improving the prediction of separation and reattachment positions. These models were tested on various geometries and simulations at different Reynolds numbers, demonstrating a certain level of generalizability. While there is room for further improvement, this thesis shows that integrating targeted model corrections into RANS simulations, informed by isolated shear layer data, can enhance the understanding and prediction of shear layer dynamics in 2D-separated flows.
...
Computational modeling of hepatic blood flow in Fontan circulations
The influence of respiration
Convection in porous media
A numerical study of a side heated cavity with spatially varying conductivities using the conjugate heat transfer model
The porous medium is simplified to a side heated cavity filled with water as fluid (Pr = 7), 32 aluminum objects with a thermal conductivity ratio of λ* = λal/λf = 337.33 and 32 wooden objects at thermal conductivity ratio λ* = λw/λf = 0.29. 4 cases, each with the aluminum and wooden cubes differently configured are simulated at a Rayleigh number(Ra) of 105, 106 and 107. Conjugate heat transfer (the fluid fase and solid fase are modelled as separate regions) simulations are done with direct Navier-Stokes where Ra = 105 and 106 are run steady and Ra = 107 is run transient. There are two different geometries simulated. One when the objects are unattached (heat cannot directly conduct into the objects from the walls) to the wall and when they are attached (heat can directly conduct into the objects) to the wall. From these simulations the temperature profile, the velocity field and the Nu profile is obtained. Also the average Nu at the hot wall and the Urms are calculated and compared between the different cases. Lastly the thermal disequilibrium %|DT| between the solid temperature and fluid temperature is calculated and compared between place of the object in the cavity and between the cases. The simulations show that conductive objects increased heat transfer at Ra = 105 when they are close to the wall. This is because they decrease the thermal resistance heat travels in the thermal boundary layer. Insulating objects on the other hand show decreased heat transfer as they increase the thermal resistance in the thermal boundary layer. At Ra = 106 and at Ra = 107 the circulation is to strong and the thermal boundary layer is mostly in between the wall and the objects so there is little difference seen in the flow and heat transfer. When the objects are attached to the wall the simulations show very different results for the flow and heat transfer and is very dependent on the conductivity and position of the object. Conductive objects attached at the wall, especially at the bottom of the wall where the temperature-gradient is the biggest, greatly improve the flow and heat transfer. They improve the area heat is transported from the wall to the fluid and thus increase the buoyancy force significantly. Insulting objects attached to the wall on the other hand prevent heat from flowing through the object and also prevents flow from reaching the wall. A big decrease in velocity and heat transfer is seen for all Ra values. For a case where conductive objects are placed against the wall and there are insulating objects in the middle, heat transfer can be improved compared to a fluid-only cavity for Ra ≥106. ...
The porous medium is simplified to a side heated cavity filled with water as fluid (Pr = 7), 32 aluminum objects with a thermal conductivity ratio of λ* = λal/λf = 337.33 and 32 wooden objects at thermal conductivity ratio λ* = λw/λf = 0.29. 4 cases, each with the aluminum and wooden cubes differently configured are simulated at a Rayleigh number(Ra) of 105, 106 and 107. Conjugate heat transfer (the fluid fase and solid fase are modelled as separate regions) simulations are done with direct Navier-Stokes where Ra = 105 and 106 are run steady and Ra = 107 is run transient. There are two different geometries simulated. One when the objects are unattached (heat cannot directly conduct into the objects from the walls) to the wall and when they are attached (heat can directly conduct into the objects) to the wall. From these simulations the temperature profile, the velocity field and the Nu profile is obtained. Also the average Nu at the hot wall and the Urms are calculated and compared between the different cases. Lastly the thermal disequilibrium %|DT| between the solid temperature and fluid temperature is calculated and compared between place of the object in the cavity and between the cases. The simulations show that conductive objects increased heat transfer at Ra = 105 when they are close to the wall. This is because they decrease the thermal resistance heat travels in the thermal boundary layer. Insulating objects on the other hand show decreased heat transfer as they increase the thermal resistance in the thermal boundary layer. At Ra = 106 and at Ra = 107 the circulation is to strong and the thermal boundary layer is mostly in between the wall and the objects so there is little difference seen in the flow and heat transfer. When the objects are attached to the wall the simulations show very different results for the flow and heat transfer and is very dependent on the conductivity and position of the object. Conductive objects attached at the wall, especially at the bottom of the wall where the temperature-gradient is the biggest, greatly improve the flow and heat transfer. They improve the area heat is transported from the wall to the fluid and thus increase the buoyancy force significantly. Insulting objects attached to the wall on the other hand prevent heat from flowing through the object and also prevents flow from reaching the wall. A big decrease in velocity and heat transfer is seen for all Ra values. For a case where conductive objects are placed against the wall and there are insulating objects in the middle, heat transfer can be improved compared to a fluid-only cavity for Ra ≥106.
The analytical solution gave the same results as the collisionless DSMC method for both single and dual jets. Simulations with a strong interaction effect resulted in a shock. These behaved similar compared to three-dimensional jets, in the plane of the jets. The shock results in a secondary jet, which has a lower density in the middle. The interaction effect depends primarily on the inlet density. Multiple regimes are observed for different inlet density ranging from small change in properties to a shock wave, with a transitional regime inbetween. The influence of the distance between the jets is found to result in a higher density at the axis of the inlet behind the shock, for bigger distance between jets. However, for very small distances between jets compared to the inlet size the shock is weak. For the optimization, it resulted in the conclusion that the optimal coating in general is applied with the smallest distance between jets. This generally gives a better uniform coating and increased performance. However, this is not always the case when constraining the distance between the jets and sheet, as it only holds if the shock between the jets for this distance. Furthermore, an approximation is found for the optimization, which results in fewer simulations needed. ...
The analytical solution gave the same results as the collisionless DSMC method for both single and dual jets. Simulations with a strong interaction effect resulted in a shock. These behaved similar compared to three-dimensional jets, in the plane of the jets. The shock results in a secondary jet, which has a lower density in the middle. The interaction effect depends primarily on the inlet density. Multiple regimes are observed for different inlet density ranging from small change in properties to a shock wave, with a transitional regime inbetween. The influence of the distance between the jets is found to result in a higher density at the axis of the inlet behind the shock, for bigger distance between jets. However, for very small distances between jets compared to the inlet size the shock is weak. For the optimization, it resulted in the conclusion that the optimal coating in general is applied with the smallest distance between jets. This generally gives a better uniform coating and increased performance. However, this is not always the case when constraining the distance between the jets and sheet, as it only holds if the shock between the jets for this distance. Furthermore, an approximation is found for the optimization, which results in fewer simulations needed.
This study revealed that both coupled simulations caused a reduced value for the roughness length in wind- and wave wake conditions. Furthermore, a spatially averaged reduction in the sea state is observed due to the wake effect, where the magnitude of this wave deficit follows the line of a typical wind turbine thrust curve. The effect is however small compared to a realistic significant wave height. Besides, the two-way coupled simulations provided higher average roughness lengths in comparison to the one-way coupled simulations. This resulted in higher friction velocities and drag coefficients for the two-way coupled simulations, which subsequently reduced the time- and slab averaged wind profiles.
Moreover, the modelling performance of SWAN improves when it is forced by GRASP friction velocities instead of ERA5 wind fields. In addition, the established two-way coupled simulation is proven to be an enhancement for the spectral wave model in comparison to the one-way coupled configuration. The performance of the atmospheric large-eddy simulation could also benefit from the two-way coupled configuration. However, it is sensitive to the implemented roughness length parameterization. ...
This study revealed that both coupled simulations caused a reduced value for the roughness length in wind- and wave wake conditions. Furthermore, a spatially averaged reduction in the sea state is observed due to the wake effect, where the magnitude of this wave deficit follows the line of a typical wind turbine thrust curve. The effect is however small compared to a realistic significant wave height. Besides, the two-way coupled simulations provided higher average roughness lengths in comparison to the one-way coupled simulations. This resulted in higher friction velocities and drag coefficients for the two-way coupled simulations, which subsequently reduced the time- and slab averaged wind profiles.
Moreover, the modelling performance of SWAN improves when it is forced by GRASP friction velocities instead of ERA5 wind fields. In addition, the established two-way coupled simulation is proven to be an enhancement for the spectral wave model in comparison to the one-way coupled configuration. The performance of the atmospheric large-eddy simulation could also benefit from the two-way coupled configuration. However, it is sensitive to the implemented roughness length parameterization.
Convolution in Multiphase Flow Simulations
Improving Interface Curvature Estimations
It was proven analytically that, for these interfaces, the original curvature is retrieved from the convoluted field. Interfaces along which the curvature varies were also considered, and it was found that there is a critical convolution support that minimizes the error in the curvature, given that the choice of the support length can modify the curvature that is estimated.
An algorithm was implemented in OpenFOAM that calculates the convolution of the VOF colour field. The resulting smoothed field was then used to calculate the curvature, which is needed for the surface tension force of the system. The simulations of a two-dimensional rising bubble resulted in more accurate results for the circularity and the rising velocity, when compared to the original OpenFOAM implementation with no smoothing. With the convolution algorithm, the terminal velocity deviated only 0.01% from a well-accepted benchmark case, a great improvement when compared to the 4.2% difference when no smoothing was used. However, simulations of a static bubble in zero-gravity rapidly resulted in unphysical flow, manifested as a wavy interface, when a convolution support larger than 2 cells was chosen. An improvement of the estimation of the surface tension force direction may be needed for this behaviour to disappear. ...
It was proven analytically that, for these interfaces, the original curvature is retrieved from the convoluted field. Interfaces along which the curvature varies were also considered, and it was found that there is a critical convolution support that minimizes the error in the curvature, given that the choice of the support length can modify the curvature that is estimated.
An algorithm was implemented in OpenFOAM that calculates the convolution of the VOF colour field. The resulting smoothed field was then used to calculate the curvature, which is needed for the surface tension force of the system. The simulations of a two-dimensional rising bubble resulted in more accurate results for the circularity and the rising velocity, when compared to the original OpenFOAM implementation with no smoothing. With the convolution algorithm, the terminal velocity deviated only 0.01% from a well-accepted benchmark case, a great improvement when compared to the 4.2% difference when no smoothing was used. However, simulations of a static bubble in zero-gravity rapidly resulted in unphysical flow, manifested as a wavy interface, when a convolution support larger than 2 cells was chosen. An improvement of the estimation of the surface tension force direction may be needed for this behaviour to disappear.
In this study, the goal was to design, characterise, and construct a TEVG perfusion bioreactor that is foremost simpler to operate and extends the capabilities of particular currently available set-ups. A modular bioreactor design is presented that allows for the toolless mounting of the graft with a diameter up to 6 mm and features completely separated circuits for the intra- and extraluminal side of the scaffold wall. The culture chamber encloses a removable graft frame, mainly machined out of polyether ether ketone (PEEK). In silico simulations have been used to assess local fluid dynamics within the scaffold, to predict the reliability of the simulated culture conditions. The presented design allows the exertion of a broad range of physiologically relevant shear stresses on cultured TEVGs, including arterial shear stresses. A test for the in vitro cytotoxicity showed that the medium extracts of the constructed graft frame did not show any cytotoxic potential. Finally, an assessment method for the estimation of the radial compliance is proposed, which aims to adhere to the relevant international standards on the mechanical characterisation of vascular substitutes. ...
In this study, the goal was to design, characterise, and construct a TEVG perfusion bioreactor that is foremost simpler to operate and extends the capabilities of particular currently available set-ups. A modular bioreactor design is presented that allows for the toolless mounting of the graft with a diameter up to 6 mm and features completely separated circuits for the intra- and extraluminal side of the scaffold wall. The culture chamber encloses a removable graft frame, mainly machined out of polyether ether ketone (PEEK). In silico simulations have been used to assess local fluid dynamics within the scaffold, to predict the reliability of the simulated culture conditions. The presented design allows the exertion of a broad range of physiologically relevant shear stresses on cultured TEVGs, including arterial shear stresses. A test for the in vitro cytotoxicity showed that the medium extracts of the constructed graft frame did not show any cytotoxic potential. Finally, an assessment method for the estimation of the radial compliance is proposed, which aims to adhere to the relevant international standards on the mechanical characterisation of vascular substitutes.
Numerical study of solidifying molten metal droplet impingement on a cold solid surface
The effect of thermocapillary forces