Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-3, 8-10, and 15-17 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by “A variational framework for high-order mesh generation” by Michael Turner, et al. (hereinafter Turner).
Regarding claim 1, the limitations “A method comprising: by a computing system: accessing a linear mesh and a target geometry, wherein the linear mesh is comprises of mesh elements with linear edges; constructing, from the linear mesh, a curved mesh for the target geometry by: projecting the linear mesh on to the target geometry to form a projected mesh” are taught by Turner (Turner, e.g. abstract, sections 1-6, describes a system for generating curvilinear meshes for CAD models by deforming a linear high-order mesh. Turner, e.g. section 2, paragraphs 1-2, section 3.1, figures 1, 2, 4a, teaches that the starting point is a straight-sided high-order mesh
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composed of Nel elements, i.e. the claimed linear mesh comprised of mesh elements with linear edges, which is equipped with geometry conforming displacements at the boundary of the domain as shown in figure 4a, i.e. the geometry conforming displacements are the result of projecting the straight-sided mesh onto the target geometry, corresponding to the claimed projected mesh. It is additionally noted with respect to corresponding independent claims 8 and 15, Turner, section 5, paragraph 1, indicates that the system was implemented using a consumer computing system, i.e. a computing system that would require program instructions stored in a non-transitory memory to be executed by the programmable processors of the computing system.)
The limitations “determining deformation patches included in the projected mesh comprised of deformed mesh elements of the projected mesh that fail deformation criteria; selecting a cost function to apply to the deformation patches from a set of available cost functions; iteratively adapting the deformation patches based on the selected cost function to obtain adjusted mesh elements” are taught by Turner (Turner, e.g. section 2, paragraphs 1-2, section 3.1, figures 1, 2, teaches that the meshes comprise elements/nodes i which are deformed using a mapping XM to determine the curvilinear mesh representation
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which minimizes the energy functional measuring the displacement between the straight-sided high-order mesh
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and the deformed/curvilinear mesh
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, i.e. the elements/nodes i correspond to the claimed deformation patches included in the projected mesh, and the energy functional corresponds to the claimed cost function. Turner, e.g. sections 3-3.4, describes the optimization procedure, a gradient descent algorithm which minimizes the energy associated with each node by iteratively calculating an adjusted node spatial coordinate for every non-boundary node using the gradient vector G and Hessian matrix H representing the energy derivative with respect to the node, until a convergence criteria is met by all of the nodes, i.e. as claimed the iteration continues while it is determined that at least one deformation patch in the projected mesh fails the deformation criteria, and the deformation patches are iteratively adapted based on the cost function, i.e. the energy function. Finally, Turner, e.g. abstract, section 2, paragraph 3, sections 2.2-2.2.4, teaches that the implemented system allows selection from four different energy functionals, as part of the purpose of the system is provide a route to investigate the question of which energy functional is the most robust, fastest, and produces the “best” matches, i.e. as claimed, a cost function is selected for applying to the deformation patches from a set of available cost functions.)
The limitations “forming the curved mesh as a combination of the adjusted mesh elements and portions of the projected mesh not determined as part of the deformation patches” are taught by Turner (As noted above, Turner, e.g. section 2, paragraph 1, indicates that the projected mesh comprises boundary elements which are geometry conforming prior to the optimization procedure, where the optimization procedure induces a deformation to the interior elements, i.e. the resulting curvilinear mesh will include both the deformed interior elements and the originally displaced boundary elements, corresponding to the claimed curved mesh which is a combination of the adjusted mesh elements and portions of the projected mesh not determined as part of the deformation patches.)
Regarding claim 2, the limitations “wherein determining the deformation patches comprises determining curve displacement values for edges of the deformed mesh elements resultant from projecting the linear mesh onto the target geometry; and wherein iteratively adapting the deformation patches comprises applying the curve displacement values as constraints for iterations performed to obtain the adjusted mesh elements” are taught by Turner (Turner, e.g. section 2, paragraph 2, sections 3.1, 3.3 teaches that the optimization problem being solved is finding u as a function of the elements/nodes i which minimizes the energy functional, where u represents the displacements between a point in the mesh and the corresponding point in the deformed domain, which are used by the energy functional to measure the energy of a current iteration of deformation, i.e. the claimed determining curve displacement values for edges of the deformed mesh. Further, Turner, e.g. section 2, paragraph 3, indicates that in addition to the energy functional, the optimization problem is closed by setting a boundary condition of zero displacement at the boundary once the deformation has been imposed, i.e. as claimed the iterative adaptation of the deformation patches applies the curve displacement values as constraints).
Regarding claim 3, the limitations “determining the deformation patches to include: the deformed mesh elements; and surrounding mesh elements of the projected mesh that are direct neighbors of the deformed mesh elements” are taught by Turner (Turner, e.g. section 3.1, indicates that each element/node i subject to deformation is evaluated along with a set of neighboring nodes e which are influenced by a change in the position of the node i, i.e. as claimed, the each deformation patch i includes the deformed mesh element i and may additionally include surrounding/direct neighbor elements e of the mesh element i.)
Regarding claims 8 and 15, the limitations are similar to those treated in the above rejection(s) and are met by the references as discussed in claim 1 above.
Regarding claims 9 and 16, the limitations are similar to those treated in the above rejection(s) and are met by the references as discussed in claim 2 above.
Regarding claims 10 and 17, the limitations are similar to those treated in the above rejection(s) and are met by the references as discussed in claim 3 above.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 4-6, 11-13, 18 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over “A variational framework for high-order mesh generation” by Michael Turner, et al. (hereinafter Turner) as applied to claims 1, 8, and 15 above.
Regarding claim 4, the limitations “wherein selecting the cost function from the set of available cost functions comprises: identifying an ordering of the available cost functions; sequentially evaluating the available cost functions according to the ordering” are taught by Turner (As noted in the claim 1 rejection above, Turner, e.g. abstract, section 2, paragraph 3, sections 2.2-2.2.4, teaches that the implemented system allows selection from four different energy functionals, as part of the purpose of the system is provide a route to investigate the question of which energy functional is the most robust, fastest, and produces the “best” matches, i.e. as claimed, a cost function is selected for applying to the deformation patches from a set of available cost functions. Further, Turner, e.g. section 5, teaches that the same machine is used to evaluate all of the energy functionals on each mesh, i.e. the same machine optimizes one mesh using one energy functional at a time, sequentially, producing the results of sections 5.2 and 5.3, such that by extension Turner’s evaluating all four energy functionals on the same mesh corresponds to the claimed sequential evaluation according to an identified ordering of the cost function/energy functionals.)
The limitation “determining the given cost function satisfies the cost function stringency criteria as the selected cost function to apply to the deformation patches” is taught by Turner (Turner, e.g. sections 5, 5.2, 5.3, figures 4c, 4d, 5d, 5e, teaches that the overall quality of the mesh can be measured using the minimum scaled Jacobian metric, and the energy functional which results in the highest quality curvilinear mesh differs for different input meshes/target geometries, i.e. in the two-dimensional example in section 5.2, the linear elastic energy functional achieves the highest quality, whereas in the three-dimensional example of section 5.3, the hyper elastic energy functional achieves the highest quality, i.e. the selected energy functional may be the energy functional which is determined to achieve the highest quality result for the mesh. Turner, e.g. section 6, paragraph 2, further indicates that one of ordinary skill in the art would understand that what constitutes high-quality varies from application to application, e.g. as in section 5.2, paragraph 3, Turner suggests other criteria may be the rate of convergence, having implications for computational cost. That is, Turner teaches that for each application, different cost function/energy functional stringency criteria may be used to select the cost function/energy functional based on the results of evaluation of the cost functions/energy functional, i.e. the linear elastic energy functional would be selected for the example of section 5.2 when the stringency criteria are satisfied by producing the highest quality mesh, whereas the hyper elastic energy functional would be selected for the example of section 5.3 using the same stringency criteria.)
The limitations “wherein selecting the cost function from the set of available cost functions comprises: identifying an ordering of the available cost functions; sequentially evaluating the available cost functions according to the ordering until a given cost function of the available cost functions satisfies cost function stringency criteria; and determining the given cost function satisfies the cost function stringency criteria as the selected cost function to apply to the deformation patches” are implicitly taught by Turner (As discussed above, Turner, e.g. sections 5.2, 5.3, teaches evaluating all four energy functionals on the same mesh corresponding to the claimed sequential evaluation according to an ordering of the cost function/energy functionals, and further Turner teaches that for each application, different cost function/energy functional stringency criteria may be used to select the cost function/energy functional based on the results of evaluation of the cost functions/energy functional. Further, the energy functional producing the highest quality mesh could not be determined until all of the energy functionals have been evaluated, i.e. as claimed the cost functions/energy functionals would be evaluated sequentially until all of the cost functions/energy functionals have been evaluated, allowing determination of whether a given cost function/energy functional satisfies the cost function/energy functional stringency criteria by having the highest quality result. In the interest of compact prosecution, because Turner’s system enables a user to manually control the system to evaluate each energy functional for a mesh, and then optimize the mesh again using the selected energy functional, but Turner does not address having the computing system, per se, perform these steps automatically, Official Notice is taken of the fact that it is old and well-known in the art of computer programming that an automated evaluation function can be used to test and identify the element of a set of elements having a largest or smallest value compared to the rest of the set of elements, i.e. by sequentially comparing each element’s value to the current minimum/maximum element value and updating the current minimum/maximum element value to the compared element’s value if a compared element’s value is smaller/larger. It is additionally noted that one of ordinary skill in the art would recognize the advantage of automating Turner’s manual activity of selecting the cost function/energy functional producing the highest quality result for a given mesh, i.e. rather than require a user to manually evaluate each energy functional and then select the energy functional producing the highest quality result for producing a final mesh, the selection could be automated using well-known programming techniques as noted above, allowing the user to avoid having to perform manual steps, analogous to MPEP 2144.04 III, wherein automating a manual activity using known automating means is not sufficient to distinguish over the prior art.)
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Turner’s high-order mesh generation system to automatically evaluate the energy functionals in order to select the energy functional producing the highest quality result for a given input mesh because one of ordinary skill in the art would generally be motivated to automate manual activity where feasible, analogous to the example of MPEP 2144.04 III, and one of ordinary skill in the art of computer programming would know that an automated evaluation function can be used to test and identify the element of a set of elements having a largest or smallest value compared to the rest of the set of elements, i.e. automating Turner’s manual evaluation using a program. In Turner’s modified system, the automated cost function/energy functional evaluation function would sequentially test each of the energy functionals for the input mesh to identify the energy functional producing the highest quality result as measured using the minimum scaled Jacobian as in Turner, section 5, paragraph 1.
Regarding claim 5, the limitations “wherein sequentially evaluating the available cost functions comprises: for a particular cost function in the ordering: performing an iteration of adapting the deformation patches based on the particular cost function; and determining whether the particular cost function satisfies the cost function stringency criteria based on one or more Jacobian values computed for adapted mesh elements generated from the iteration, a step size value computed for the iteration, or a combination of both” are taught by Turner (As discussed in the claim 4 rejection above, in Turner’s modified system, the automated cost function/energy functional evaluation function would sequentially test each of the energy functionals for the input mesh to identify the energy functional producing the highest quality result as measured using the minimum scaled Jacobian as in Turner, section 5, paragraph 1. That is, the sequential evaluation for a particular cost function comprises performing iteration(s) of adapting the deformation patches as discussed in the claim 1 rejection, and the determining of whether the particular cost function satisfies the cost function stringency criteria are based on one or more Jacobian values computed for adapted mesh elements generated from the iteration(s), corresponding to the additional limitations of claim 5.)
Regarding claim 6, the limitation “wherein the cost function stringency criteria are satisfied when the one or more Jacobian values from the iteration do not exceed a threshold Jacobian value, when the step size value for the iteration is not less than a threshold step size value, or a combination of both” is implicitly taught by Turner (As discussed in the claim 4 rejection above, in Turner’s modified system, the automated cost function/energy functional evaluation function would sequentially test each of the energy functionals for the input mesh to identify the energy functional producing the highest quality result as measured using the minimum scaled Jacobian as in Turner, section 5, paragraph 1. Turner, section 5, paragraph 1, further indicates that any element having a minimum scaled Jacobian value which is less than 0 is invalid. That is, while it is implicit that selecting the cost function/energy functional producing the highest quality result, i.e. having the largest minimum scaled Jacobian value, would exclude selection of any cost function/energy functional which includes invalid elements, one of ordinary skill in the art would have found it implicit that a cost function/energy functional which produces an invalid mesh should not be selected, i.e. should be excluded from further consideration by the automated cost function/energy functional evaluation function.)
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Turner’s high-order mesh generation system having the automated cost function/energy functional evaluation function to exclude cost functions/energy functionals producing invalid meshes from further consideration/selection, i.e. one of ordinary skill in the art would have found it implicit that cost functions/energy functionals producing invalid meshes should not be used for high-order mesh generation.
Regarding claims 11 and 18, the limitations are similar to those treated in the above rejection(s) and are met by the references as discussed in claim 4 above.
Regarding claim 12, the limitations are similar to those treated in the above rejection(s) and are met by the references as discussed in claim 5 above.
Regarding claim 13, the limitations are similar to those treated in the above rejection(s) and are met by the references as discussed in claim 6 above.
Regarding claim 19, the limitations are similar to those treated in the above rejection(s) and are met by the references as discussed in claims 5 and 6 above.
Claims 7, 14, and 20 are rejected under 35 U.S.C. 102(a)(1) as anticipated by or, in the alternative, under 35 U.S.C. 103 as obvious over “A variational framework for high-order mesh generation” by Michael Turner, et al. (hereinafter Turner) as applied to claims 1, 8, and 15 above.
Regarding claim 7, the limitations “wherein iteratively adapting the deformation patches to obtain adjusted mesh elements comprises: determining adjusted surface mesh elements of the adjusted mesh elements based on the cost function; and determining adjusted volume mesh elements of the adjusted mesh elements using the adjusted surface mesh elements as fixed geometric elements for determination of the adjusted volume mesh elements” are taught by Turner (Turner, e.g. section 6, paragraph 2, teaches that as an alternative to using fixed boundary nodes, a bottom-up approach could be used where the energy is first applied to curves, followed by surfaces, then volumes. That is, although Turner does not implement the additionally claimed limitations of first determining adjusted surface mesh elements and then determining adjusted volume mesh elements using the adjusted surface mesh elements as fixed geometric elements for determining the adjusted volume mesh elements, Turner does anticipate the additionally claimed limitations, i.e. Turner’s bottom-up approach modification would initially determine deformed curves using a first set of fixed boundary elements/nodes, i.e. point elements/nodes, followed by determining deformed surface elements/nodes using the deformed curves as fixed boundary elements/nodes, followed by determining deformed volume elements/nodes using the deformed surfaces as fixed boundary elements/nodes. In the interest of compact prosecution, although Turner does anticipate this modification, Turner also suggests the modification, and therefore it is noted that one of ordinary skill in the art would also have found it obvious to modify Turner’s system to use the bottom-up approach because Turner suggests doing so.)
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Turner’s high-order mesh generation system to use Turner’s bottom-up approach as an alternative to the fixed boundary approach because Turner suggests doing so. It is noted that one of ordinary skill in the art would have found it obvious to modify Turner’s system either by simply substituting the bottom-up approach for the described fixed boundary approach, or alternatively to allow a user to select between them, analogous to Turner’s discussion in the Abstract of providing a system for investigating which of several known techniques work best.
Regarding claims 14 and 20, the limitations are similar to those treated in the above rejection(s) and are met by the references as discussed in claim 7 above.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ROBERT BADER whose telephone number is (571)270-3335. The examiner can normally be reached 11-7 m-f.
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/ROBERT BADER/Primary Examiner, Art Unit 2611