Matching Items (3)
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- All Subjects: stereolithography
- Creators: Peet, Yulia
- Creators: Nian, Qiong
- Status: Published
A level set approach for denoising and adaptively smoothing complex geometry stereolithography files
Description
Stereolithography files (STL) are widely used in diverse fields as a means of describing complex geometries through surface triangulations. The resulting stereolithography output is a result of either experimental measurements, or computer-aided design. Often times stereolithography outputs from experimental means are prone to noise, surface irregularities and holes in an otherwise closed surface.
A general method for denoising and adaptively smoothing these dirty stereolithography files is proposed. Unlike existing means, this approach aims to smoothen the dirty surface representation by utilizing the well established levelset method. The level of smoothing and denoising can be set depending on a per-requirement basis by means of input parameters. Once the surface representation is smoothened as desired, it can be extracted as a standard levelset scalar isosurface.
The approach presented in this thesis is also coupled to a fully unstructured Cartesian mesh generation library with built-in localized adaptive mesh refinement (AMR) capabilities, thereby ensuring lower computational cost while also providing sufficient resolution. Future work will focus on implementing tetrahedral cuts to the base hexahedral mesh structure in order to extract a fully unstructured hexahedra-dominant mesh describing the STL geometry, which can be used for fluid flow simulations.
A general method for denoising and adaptively smoothing these dirty stereolithography files is proposed. Unlike existing means, this approach aims to smoothen the dirty surface representation by utilizing the well established levelset method. The level of smoothing and denoising can be set depending on a per-requirement basis by means of input parameters. Once the surface representation is smoothened as desired, it can be extracted as a standard levelset scalar isosurface.
The approach presented in this thesis is also coupled to a fully unstructured Cartesian mesh generation library with built-in localized adaptive mesh refinement (AMR) capabilities, thereby ensuring lower computational cost while also providing sufficient resolution. Future work will focus on implementing tetrahedral cuts to the base hexahedral mesh structure in order to extract a fully unstructured hexahedra-dominant mesh describing the STL geometry, which can be used for fluid flow simulations.
ContributorsKannan, Karthik (Author) / Herrmann, Marcus (Thesis advisor) / Peet, Yulia (Committee member) / Frakes, David (Committee member) / Arizona State University (Publisher)
Created2014
Description
With a ground-based Doppler lidar on the upwind side of a wind farm in the Tehachapi Pass of California, radial wind velocity measurements were collected for repeating sector sweeps, scanning up to 10 kilometers away. This region consisted of complex terrain, with the scans made between mountains. The dataset was utilized for techniques being studied for short-term forecasting of wind power by correlating changes in energy content and of turbulence intensity by tracking spatial variance, in the wind ahead of a wind farm. A ramp event was also captured and its propagation was tracked.
Orthogonal horizontal wind vectors were retrieved from the radial velocity using a sector Velocity Azimuth Display method. Streamlines were plotted to determine the potential sites for a correlation of upstream wind speed with wind speed at downstream locations near the wind farm. A "virtual wind turbine" was "placed" in locations along the streamline by using the time-series velocity data at the location as the input to a modeled wind turbine, to determine the extractable energy content at that location. The relationship between this time-dependent energy content upstream and near the wind farm was studied. By correlating the energy content with each upstream location based on a time shift estimated according to advection at the mean wind speed, several fits were evaluated. A prediction of the downstream energy content was produced by shifting the power output in time and applying the best-fit function. This method made predictions of the power near the wind farm several minutes in advance. Predictions were also made up to an hour in advance for a large ramp event. The Magnitude Absolute Error and Standard Deviation are presented for the predictions based on each selected upstream location.
Orthogonal horizontal wind vectors were retrieved from the radial velocity using a sector Velocity Azimuth Display method. Streamlines were plotted to determine the potential sites for a correlation of upstream wind speed with wind speed at downstream locations near the wind farm. A "virtual wind turbine" was "placed" in locations along the streamline by using the time-series velocity data at the location as the input to a modeled wind turbine, to determine the extractable energy content at that location. The relationship between this time-dependent energy content upstream and near the wind farm was studied. By correlating the energy content with each upstream location based on a time shift estimated according to advection at the mean wind speed, several fits were evaluated. A prediction of the downstream energy content was produced by shifting the power output in time and applying the best-fit function. This method made predictions of the power near the wind farm several minutes in advance. Predictions were also made up to an hour in advance for a large ramp event. The Magnitude Absolute Error and Standard Deviation are presented for the predictions based on each selected upstream location.
ContributorsMagerman, Beth (Author) / Calhoun, Ronald (Thesis advisor) / Peet, Yulia (Committee member) / Huang, Huei-Ping (Committee member) / Krishnamurthy, Raghavendra (Committee member) / Arizona State University (Publisher)
Created2014
Description
Traditionally, for applications that require heat transfer (e.g. heat exchangers),metals have been the go-to material for manufacturers because of their high thermal as
well as structural properties. However, metals have some notable drawbacks. They are
not corrosion-resistant, offer no freedom of design, have a high cost of production, and
sourcing the material itself. Even though polymers on their own don’t show great
prospects in the field of thermal applications, their composites perform better than their
counterparts. Nanofillers, when added to a polymer matrix not only increase their
structural strength but also their thermal performance. This work aims to tackle two of
those problems by using the additive manufacturing method, stereolithography to solve
the problem of design freedom, and the use of polymer nanocomposite material for
corrosion-resistance and increase their overall thermal performance. In this work, three
different concentrations of polymer composite materials were studied: 0.25 wt%, 0.5
wt%, and 1wt% for their thermal conductivity. The samples were prepared by
magnetically stirring them for a period of 10 to 24 hours depending on their
concentrations and then sonicating in an ice bath further for a period of 2 to 3 hours.
These samples were then tested for their thermal conductivities using a Hot Disk TPS
2500S. Scanning Electron Microscope (SEM) to study the dispersion of the nanoparticles
in the matrix. Different theoretical models were studied and used to compare
experimental data to the predicted values of effective thermal conductivity. An increase
of 7.9 % in thermal conductivity of the composite material was recorded for just 1 wt%
addition of multiwalled carbon nanotubes (MWCNTs).
well as structural properties. However, metals have some notable drawbacks. They are
not corrosion-resistant, offer no freedom of design, have a high cost of production, and
sourcing the material itself. Even though polymers on their own don’t show great
prospects in the field of thermal applications, their composites perform better than their
counterparts. Nanofillers, when added to a polymer matrix not only increase their
structural strength but also their thermal performance. This work aims to tackle two of
those problems by using the additive manufacturing method, stereolithography to solve
the problem of design freedom, and the use of polymer nanocomposite material for
corrosion-resistance and increase their overall thermal performance. In this work, three
different concentrations of polymer composite materials were studied: 0.25 wt%, 0.5
wt%, and 1wt% for their thermal conductivity. The samples were prepared by
magnetically stirring them for a period of 10 to 24 hours depending on their
concentrations and then sonicating in an ice bath further for a period of 2 to 3 hours.
These samples were then tested for their thermal conductivities using a Hot Disk TPS
2500S. Scanning Electron Microscope (SEM) to study the dispersion of the nanoparticles
in the matrix. Different theoretical models were studied and used to compare
experimental data to the predicted values of effective thermal conductivity. An increase
of 7.9 % in thermal conductivity of the composite material was recorded for just 1 wt%
addition of multiwalled carbon nanotubes (MWCNTs).
ContributorsGide, Kunal Manoj (Author) / Nian, Qiong (Thesis advisor) / Kwon, Beomjin (Committee member) / Li, Xiangjia (Committee member) / Arizona State University (Publisher)
Created2020