CNF:CNF - Revision history

Spyridon97: /* References */

2021-05-27T19:44:19Z

References

← Older revision		Revision as of 14:44, 27 May 2021
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	## [https://www.techscience.com/CMES/v94n4/26992/pdf Quadratic Interpolation with Tetrahedra for 3D Scalar Fields]		## [https://www.techscience.com/CMES/v94n4/26992/pdf Quadratic Interpolation with Tetrahedra for 3D Scalar Fields]
	## [https://www.researchgate.net/publication/326950468_A_look-up_table_method_based_on_unstructured_grids_and_its_application_to_non-ideal_compressible_fluid_dynamic_simulations A look-up table method based on unstructured grids and its application to non-ideal compressible fluid dynamic simulations]		## [https://www.researchgate.net/publication/326950468_A_look-up_table_method_based_on_unstructured_grids_and_its_application_to_non-ideal_compressible_fluid_dynamic_simulations A look-up table method based on unstructured grids and its application to non-ideal compressible fluid dynamic simulations]
			## [https://arxiv.org/pdf/physics/0203033.pdf Foam: A General-Purpose Cellular Monte Carlo Event Generator]

	= Restricted Access (available to CNF Imaging Project i.e., CRTC/JLAB only) =		= Restricted Access (available to CNF Imaging Project i.e., CRTC/JLAB only) =

Spyridon97: /* References */

2021-05-21T22:59:21Z

References

← Older revision		Revision as of 17:59, 21 May 2021
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	## [https://www.hpl.hp.com/techreports/2002/HPL-2002-320.pdf n-Simplex Interpolation]		## [https://www.hpl.hp.com/techreports/2002/HPL-2002-320.pdf n-Simplex Interpolation]
	## [https://www.techscience.com/CMES/v94n4/26992/pdf Quadratic Interpolation with Tetrahedra for 3D Scalar Fields]		## [https://www.techscience.com/CMES/v94n4/26992/pdf Quadratic Interpolation with Tetrahedra for 3D Scalar Fields]
			## [https://www.researchgate.net/publication/326950468_A_look-up_table_method_based_on_unstructured_grids_and_its_application_to_non-ideal_compressible_fluid_dynamic_simulations A look-up table method based on unstructured grids and its application to non-ideal compressible fluid dynamic simulations]

	= Restricted Access (available to CNF Imaging Project i.e., CRTC/JLAB only) =		= Restricted Access (available to CNF Imaging Project i.e., CRTC/JLAB only) =

Spyridon97: /* References */

2021-05-21T15:58:11Z

References

← Older revision		Revision as of 10:58, 21 May 2021
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	## [https://link.springer.com/chapter/10.1007%2F978-3-319-76201-2_3 Interpolation on Unstructured Tetrahedral Grids]		## [https://link.springer.com/chapter/10.1007%2F978-3-319-76201-2_3 Interpolation on Unstructured Tetrahedral Grids]
	## [https://www.hpl.hp.com/techreports/2002/HPL-2002-320.pdf n-Simplex Interpolation]		## [https://www.hpl.hp.com/techreports/2002/HPL-2002-320.pdf n-Simplex Interpolation]
			## [https://www.techscience.com/CMES/v94n4/26992/pdf Quadratic Interpolation with Tetrahedra for 3D Scalar Fields]

	= Restricted Access (available to CNF Imaging Project i.e., CRTC/JLAB only) =		= Restricted Access (available to CNF Imaging Project i.e., CRTC/JLAB only) =

Spyridon97: /* References */

2021-05-21T02:19:42Z

References

← Older revision		Revision as of 21:19, 20 May 2021
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	## [https://www.researchgate.net/publication/275348534_Picking_a_Uniformly_Random_Point_from_an_Arbitrary_Simplex Picking a Uniformly Random Point from an Arbitrary Simplex]		## [https://www.researchgate.net/publication/275348534_Picking_a_Uniformly_Random_Point_from_an_Arbitrary_Simplex Picking a Uniformly Random Point from an Arbitrary Simplex]
	## [https://link.springer.com/chapter/10.1007%2F978-3-319-76201-2_3 Interpolation on Unstructured Tetrahedral Grids]		## [https://link.springer.com/chapter/10.1007%2F978-3-319-76201-2_3 Interpolation on Unstructured Tetrahedral Grids]
			## [https://www.hpl.hp.com/techreports/2002/HPL-2002-320.pdf n-Simplex Interpolation]

	= Restricted Access (available to CNF Imaging Project i.e., CRTC/JLAB only) =		= Restricted Access (available to CNF Imaging Project i.e., CRTC/JLAB only) =

Spyridon97: /* Week April 26 - May 2 */

2021-04-28T21:42:36Z

Week April 26 - May 2

← Older revision		Revision as of 16:42, 28 April 2021
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	=== Week April 26 - May 2 ===		=== Week April 26 - May 2 ===
	# Using the interpolation error as the sizing function is the way to go to close the "loop" for the following reasons:		# Using the interpolation error as the sizing function is the way to go to close the "loop" for the following reasons:
	## ~~Performs exactly~~ the amount of partons calculations ~~(NO MORE)~~ to guarantee that the interpolation error within every cell is below <= error-threshold		## Minimizes the amount of partons calculations needed to guarantee that the interpolation error within every cell is below <= error-threshold
	## Minimizes the number of points/cells of the mesh. The benefits of this are:		## Minimizes the number of points/cells of the mesh. The benefits of this are:
	### Fewer points/cells -> faster Monte Carlo Event Generation		### Fewer points/cells -> faster Monte Carlo Event Generation
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	## Create a mesh using the linear interpolation error as the sizing function		## Create a mesh using the linear interpolation error as the sizing function
	### Pros:		### Pros:
	#### Everything that was ~~originally~~ mentioned		#### Everything that was mentioned
	### Cons:		### Cons:
	#### Maybe caching issues		#### Maybe caching issues, but they are possibly insignificant since PODM is already really fast.

	= References =		= References =

Spyridon97: /* Week April 26 - May 2 */

2021-04-28T21:32:13Z

Week April 26 - May 2

← Older revision		Revision as of 16:32, 28 April 2021
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	## Enables the saving of all the CFFs into one mesh rather than creating a mesh for each CFF. The benefits of this are:		## Enables the saving of all the CFFs into one mesh rather than creating a mesh for each CFF. The benefits of this are:
	### Simpler model storage for the future database of CNF models		### Simpler model storage for the future database of CNF models
	~~### By splitting a cell if a CFF requires that while another CFF does not, we create a Mesh with a better error distribution than the one that would have if we did not split that cell.~~
	### Let's say that we create a mesh for each CFF and every mesh has 100k cells. So the total number of cells needed are: number of CFFs * 100k. <br> Creating the common denominator mesh of all these meshes will reduce the total PARTONS calculations by almost (!) as much as the number of CFFs.		### Let's say that we create a mesh for each CFF and every mesh has 100k cells. So the total number of cells needed are: number of CFFs * 100k. <br> Creating the common denominator mesh of all these meshes will reduce the total PARTONS calculations by almost (!) as much as the number of CFFs.
			### By splitting a cell that one CFF requires while another CFF does not, we create a mesh with a better error distribution than the one that would have if we did not split that cell.
	### Additionally, for the Monte Carlo event generation step. If we were to create a random point within a domain, we would have to locate the cell in which this point lies into for every CFFs mesh (complexity = O (log (number of cells) * number of CFFs)). <br> While we could just randomly create a point based on the volume of every cell, as we do it currently just for one CFF (complexity O(1)).		### Additionally, for the Monte Carlo event generation step. If we were to create a random point within a domain, we would have to locate the cell in which this point lies into for every CFFs mesh (complexity = O (log (number of cells) * number of CFFs)). <br> While we could just randomly create a point based on the volume of every cell, as we do it currently just for one CFF (complexity O(1)).
	# The steps that we will describe in the paper that we tried to achieve the desired result (sufficient interpolation accuracy throughout every cell of a cell, with the minimum partons calculations) are:		# The steps that we will describe in the paper that we tried to achieve the desired result (sufficient interpolation accuracy throughout every cell of a cell, with the minimum partons calculations) are:

Spyridon97: /* Week April 26 - May 2 */

2021-04-28T21:27:43Z

Week April 26 - May 2

@@ Line 369: / Line 369: @@
 ### Let's say that we create a mesh for each CFF and every mesh has 100k cells. So the total number of cells needed are: number of CFFs * 100k. <br> Creating the common denominator mesh of all these meshes will reduce the total PARTONS calculations by almost (!) as much as the number of CFFs.
 ### Additionally, for the Monte Carlo event generation step. If we were to create a random point within a domain, we would have to locate the cell in which this point lies into for every CFFs mesh (complexity = O (log (number of cells) * number of CFFs)). <br> While we could just randomly create a point based on the volume of every cell, as we do it currently just for one CFF (complexity O(1)).
-# The steps that we will describe in the paper that we tried to achieve the desired result (sufficient interpolation error throughout every cell of a cell, with the minimum partons calculations) are:
+# The steps that we will describe in the paper that we tried to achieve the desired result (sufficient interpolation accuracy throughout every cell of a cell, with the minimum partons calculations) are:
-## Gagik's approach: he proposed to decimate a huge image (1,000,000 partons calculation) and then generate a tessellation that would capture the important features of the CFF described
+## (Optional) Gagik's approach: he proposed to decimate a huge image (1,000,000 partons calculation) and then generate a tessellation that would capture the important features of the CFF described
 ### Pros:
 #### Predefined number of partons calculations
@@ Line 377: / Line 377: @@
 #### Many Partons calculations
 #### No interpolation error guarantee
-## Create a dense enough
+#### Only for one CFF
 = References =

Spyridon97: /* Week April 26 - May 2 */

2021-04-28T21:21:47Z

Week April 26 - May 2

← Older revision		Revision as of 16:21, 28 April 2021
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	### Let's say that we create a mesh for each CFF and every mesh has 100k cells. So the total number of cells needed are: number of CFFs * 100k. <br> Creating the common denominator mesh of all these meshes will reduce the total PARTONS calculations by almost (!) as much as the number of CFFs.		### Let's say that we create a mesh for each CFF and every mesh has 100k cells. So the total number of cells needed are: number of CFFs * 100k. <br> Creating the common denominator mesh of all these meshes will reduce the total PARTONS calculations by almost (!) as much as the number of CFFs.
	### Additionally, for the Monte Carlo event generation step. If we were to create a random point within a domain, we would have to locate the cell in which this point lies into for every CFFs mesh (complexity = O (log (number of cells) * number of CFFs)). <br> While we could just randomly create a point based on the volume of every cell, as we do it currently just for one CFF (complexity O(1)).		### Additionally, for the Monte Carlo event generation step. If we were to create a random point within a domain, we would have to locate the cell in which this point lies into for every CFFs mesh (complexity = O (log (number of cells) * number of CFFs)). <br> While we could just randomly create a point based on the volume of every cell, as we do it currently just for one CFF (complexity O(1)).
	# The steps that we will describe in the paper that we tried to achieve the desired result (sufficient interpolation error throughout every cell of a cell) are:		# The steps that we will describe in the paper that we tried to achieve the desired result (sufficient interpolation error throughout every cell of a cell, with the minimum partons calculations) are:
	## Gagik's approach: he proposed to decimate a huge image (1,000,000 partons calculation) and then generate a tessellation that would capture the important features of the CFF described		## Gagik's approach: he proposed to decimate a huge image (1,000,000 partons calculation) and then generate a tessellation that would capture the important features of the CFF described
	### Pros:		### Pros:

Spyridon97: /* Week April 26 - May 2 */

2021-04-28T21:21:20Z

Week April 26 - May 2

← Older revision		Revision as of 16:21, 28 April 2021
Line 369:		Line 369:
	### Let's say that we create a mesh for each CFF and every mesh has 100k cells. So the total number of cells needed are: number of CFFs * 100k. <br> Creating the common denominator mesh of all these meshes will reduce the total PARTONS calculations by almost (!) as much as the number of CFFs.		### Let's say that we create a mesh for each CFF and every mesh has 100k cells. So the total number of cells needed are: number of CFFs * 100k. <br> Creating the common denominator mesh of all these meshes will reduce the total PARTONS calculations by almost (!) as much as the number of CFFs.
	### Additionally, for the Monte Carlo event generation step. If we were to create a random point within a domain, we would have to locate the cell in which this point lies into for every CFFs mesh (complexity = O (log (number of cells) * number of CFFs)). <br> While we could just randomly create a point based on the volume of every cell, as we do it currently just for one CFF (complexity O(1)).		### Additionally, for the Monte Carlo event generation step. If we were to create a random point within a domain, we would have to locate the cell in which this point lies into for every CFFs mesh (complexity = O (log (number of cells) * number of CFFs)). <br> While we could just randomly create a point based on the volume of every cell, as we do it currently just for one CFF (complexity O(1)).
			# The steps that we will describe in the paper that we tried to achieve the desired result (sufficient interpolation error throughout every cell of a cell) are:
			## Gagik's approach: he proposed to decimate a huge image (1,000,000 partons calculation) and then generate a tessellation that would capture the important features of the CFF described
			### Pros:
			#### Predefined number of partons calculations
			#### Small mesh size
			### Cons:
			#### Many Partons calculations
			#### No interpolation error guarantee
			## Create a dense enough

	= References =		= References =

Spyridon97: /* Week April 26 - May 2 */

2021-04-28T21:15:13Z

Week April 26 - May 2

← Older revision		Revision as of 16:15, 28 April 2021
Line 365:		Line 365:
	### Fewer points/cells -> faster IO		### Fewer points/cells -> faster IO
	## Enables the saving of all the CFFs into one mesh rather than creating a mesh for each CFF. The benefits of this are:		## Enables the saving of all the CFFs into one mesh rather than creating a mesh for each CFF. The benefits of this are:
	### Simpler model storage for the future database of ~~every CFF~~		### Simpler model storage for the future database of CNF models
	### By splitting a cell if a CFF requires that while another CFF does not, we create a Mesh with a better error distribution than the one that would have if we did not split that cell.		### By splitting a cell if a CFF requires that while another CFF does not, we create a Mesh with a better error distribution than the one that would have if we did not split that cell.
	### Let's say that we create a mesh for each CFF and every mesh has 100k cells. So the total number of cells needed are: number of CFFs * 100k. <br> Creating the common denominator mesh of all these meshes will reduce the total PARTONS calculations by almost (!) as much as the number of CFFs.		### Let's say that we create a mesh for each CFF and every mesh has 100k cells. So the total number of cells needed are: number of CFFs * 100k. <br> Creating the common denominator mesh of all these meshes will reduce the total PARTONS calculations by almost (!) as much as the number of CFFs.