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 .
DETAILED ACTION
Status
This instant application No. 18/227587 has claims 1-20 pending.
Priority /Filing Date
Applicant claimed Foreign Priority from Korean Application No. KR10-2022-0103481. The priority filing date of this application is August 18, 2022.
Information Disclosure Statement
As required by M.P.E.P. 609(C), the Applicant’s submissions of the Information Disclosure Statements dated July 28, 2023 is acknowledged by the Examiner and the cited references have been considered in the examination of the claims now pending. As required by M.P.E.P. 609 C(2), a copy of each of the PTOL-1449s initialed and dated by the Examiner is attached to the instant Office action.
Drawings
4. The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because Figure 13 mentions nomenclature such as ‘3st’, which should be mentioned as ‘3rd” for maintaining clarity with the specification. See MPEP § 608.02(g). Corrected drawings in compliance with 37 CFR 1.121 (d) are required in reply to the Office action to avoid abandonment of the application. The replacement sheet(s) should be labeled "Replacement Sheet" in the page header (as per 37 CFR 1.84(c)) so as not to obstruct any portion of the drawing figures. If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
5. Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Step 2A Prong One:
Independent claim 1 recite:
generating a first simulation model by performing a first simulation based on pipe information and fluid information comprising a flow rate and pressure of a fluid in a pipe;
generating a second simulation model by performing a second simulation that is different from the first simulation, based on the pipe information and the fluid information;
generating a third simulation model, based on the first simulation model and the second simulation model;
predicting pipe blockage for each of a plurality of sections of the pipe based on the third
simulation model.
Independent claim 12 recite:
generating a first pressure value for each of a plurality of pipes using a three dimensional
computational fluid dynamics (CFD) analysis method based on pipe information and fluid information;
generating a section pressure for each section of the plurality of pipes based on the pipe information and the fluid information;
generating a second pressure value of each of the plurality of pipes based on the section pressure;
generating a section diameter for each section of the plurality of pipes based on the first pressure value and the second pressure value;
setting the section diameter and the second pressure value as parameters, and generating a pipe prediction model
generating a fluid analysis map in a three-dimensional drawing based on the pipe prediction model.
Independent claim 18 recite:
generating a first simulation model by performing a first simulation based on pipe information and fluid information comprising flow rate information;
obtaining a second simulation model by performing a second simulation that is different from the first simulation on the pipe information and the fluid information;
generating a third simulation model using a machine learning model based on the first simulation model and the second simulation model;
generating a fluid analysis map displaying a pipe diameter and a pipe pressure for each section of the plurality of pipes in a three-dimensional drawing using the third simulation model;
and
predicting pipe blockage for each section of the plurality of pipes based on the fluid analysis map,
wherein the first simulation model predicts a first pressure value corresponding to pipe pressure in an end portion of each of the plurality of pipes,
wherein the second simulation model predicts a second pressure value corresponding to a section pressure for each section of the plurality of pipes and a pressure of the end portion of each of the plurality of pipes,
wherein, when a difference between the first pressure value and the second pressure value is less than or equal to a preset threshold, the third simulation model is generated.
All of the above limitations, as drafted, are steps that, under it’s broadest reasonable interpretation, cover mathematical concepts including mathematical relationships, formulas or equations as well as calculations, that could be performed using simple pen or paper. Said limitations in claims 1, 12 and 18 are a process that under its broadest reasonable interpretation, covers performance of the limitations considered as mathematical concept but for the recitation of generic computer components such as “machine learning model”, “simulation model” -which by themselves are mathematical algorithm/entity. Other than reciting “machine learning model” and “simulation model” in the claims nothing in the claim elements precludes the steps from practically being perceived as mathematical relationships/calculation. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation that are considered mathematical relationships/calculation/formulae, but for the recitation of generic computer components, then it falls within the “mathematical concept” grouping of abstract ideas. As such claims 1, 12, and 18 recite an abstract idea.
Step 2A Prong Two:
This judicial exception is not integrated into a practical application. The claims recite the additional element of “machine learning model”, “simulation model” to perform the claimed method steps at a high level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component. These additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Step 2B:
Claims 1, 12 and 18 only recite “machine learning model”, “simulation model” to perform the claimed method steps and therefore only recite general purpose computer rather than a specific machine under MPEP 2106.05(b), and are directed to mere instructions to apply the exception under MPEP 2106.05(f), and do not result in anything significantly more than the judicial exception. The additional elements have been considered both individually and as an ordered combination in the significantly more consideration. The inclusion of generic computing/simulation entity to perform the generating, setting, obtaining and predicting steps amount to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Claims 1, 12, and 18 are not patent eligible.
The dependent claims 2-5, 7, 9-12, 15-18, and 20 recite additional steps of determining the source of the difference using a lookup table and by using the lookup table making specific determinations of individual sources of the difference. The lookup table identify cause and effect relationships between specific conditions and specific sources of those conditions and therefore using said lookup table is a mental process. Because the dependent claims recite additional steps which are all directed to judicial exceptions, claims 2-5, 7, 9-12, 15-18, and 20 are also not patent eligible.
The dependent claims include the same abstract ideas recited in the independent claims, and merely incorporate additional details that narrow the abstract ideas and fail to add significantly more to the claims.
Dependent claim 2 is directed to further generating first pressure value of the fluid in the pipe using a three-dimensional computational fluid dynamics (CFD) analysis- a mathematical entity, which further narrows the abstract idea identified in the independent claim, which is directed to “Mathematical concepts”.
Dependent claim 3 is directed to further generating a second pressure value based on a Darcy-Weisbach equation, which further narrows the abstract idea identified in the independent claim, which is directed to “Mathematical concepts”.
Dependent claim 4 is directed to further
calculating a plurality of section pressures for each section of the pipe;
generating a second pressure value for an end portion of the pipe based on the plurality of section pressures; and
generating a second simulation model for predicting the plurality of section pressures and the second pressure value - all of which involve mathematical calculations/relationships - which further narrows the abstract idea identified in the independent claim, which is directed to “Mathematical concepts”.
Dependent claim 6 is directed to further generating of the third simulation model comprises predicting a diameter for each of the plurality of sections of the pipe using an optimizer based on the first simulation model and the second simulation model using mathematical analysis, which further narrows the abstract idea identified in the independent claim, which is directed to “Mathematical concepts”.
Dependent claim 7 is directed to further reciting wherein generating of the third simulation model comprises generating a third preliminary simulation model that minimizes a difference between a first pressure value of the first simulation model and a second pressure value of the second simulation model using mathematical analysis, which further narrows the abstract idea identified in the independent claim, which is directed to “Mathematical concepts”.
Dependent claim 8 is directed to further reciting wherein the generating of the third simulation model comprises obtaining a difference and a variance of the first simulation model and the second simulation model, and excluding the third preliminary simulation model exceeding a preset threshold based on at least one of the difference and the variance using mathematical analysis, which further narrows the abstract idea identified in the independent claim, which is directed to “Mathematical concepts”.
Dependent claim 9 is directed to further reciting wherein the generating of the
third simulation model further comprises determining whether the third preliminary simulation model satisfies a set condition, and
wherein, when the set condition is satisfied, the third preliminary simulation model is selected as the third simulation model. Both of these limitations covers mental processes including an observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper, which is directed to “Mental Process”.
Dependent claim 10 is directed to further reciting the types of machine language used, which further narrows the abstract idea identified in the independent claim, which is directed to “Mathematical concepts”.
Dependent claim 11 is directed to further reciting wherein the third simulation model predicts a diameter, a model pressure, and a mass of a slurry for each of the plurality of sections using mathematical analysis, which further narrows the abstract idea identified in the independent claim, which is directed to “Mathematical concepts”.
Dependent claim 13 is directed to further generating of the section diameter comprises generating the section diameter by a stochastic gradient descent (SGD) algorithm-a mathematical entity, which further narrows the abstract idea identified in the independent claim, which is directed to “Mathematical concepts”.
Dependent claim 14 is directed to further reciting wherein the generating of the pipe prediction model comprises repeatedly generating a first diameter based on the section diameter, changing a second pressure value based on the first diameter to create a changed second pressure value, and generating a second diameter based on the changed second pressure value using mathematical analysis, which further narrows the abstract idea identified in the independent claim, which is directed to “Mathematical concepts”.
Dependent claim 15 is directed to further reciting wherein the generating of the pipe prediction model comprises generating the pipe prediction model when a difference between the first pressure value and the changed second pressure value is less than or equal to a preset threshold value using mathematical analysis, which further narrows the abstract idea identified in the independent claim, which is directed to “Mathematical concepts”.
Dependent claim 16 is directed to further reciting wherein the fluid analysis map comprises a pipe diameter and a pipe pressure for each section of each of the plurality of pipes using mathematical analysis, which further narrows the abstract idea identified in the independent claim, which is directed to “Mathematical concepts”.
Dependent claim 17 is directed to further reciting wherein the first pressure value is based on a measurement by pressure sensors disposed at each end of the plurality of pipes, which represents data acquisition/gathering and simply an extra-solution activity.
Dependent claim 19 is directed to further reciting wherein the predicting of the pipe blockage for each section of the plurality of pipes comprises determining a pipe blockage for a particular section of the each section, if the pipe diameter for the particular section is 70 percent or less of an unblocked diameter of the pipe where a slurry is not formed using mathematical analysis, which further narrows the abstract idea identified in the independent claim, which is directed to “Mathematical concepts”.
Dependent claim 20 is directed to further reciting wherein the first simulation
generates the first simulation model including the first pressure value using a three-dimensional computational fluid dynamics analysis method, wherein the second simulation generates the second simulation model including the second pressure value based on a Darcy-Weisbach equation, and wherein a third simulation generates the third simulation model by calculating the pipe diameter for each section of the plurality of pipes based on the first pressure value and the second pressure value using mathematical analysis, which further narrows the abstract idea identified in the independent claim, which is directed to “Mathematical concepts”.
Allowable Subject Matter
6. Claims 1-20 are allowable pending resolving all intervening issues such as drawing objection, USC 101 rejections above. Reasons for allowance will be held in abeyance pending final recitation of the claims.
Conclusion
7. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Yasuda et al. (Pub. No.: US 20130092257A1) relates to a flow rate control device and the like having a configuration for diagnosing an abnormality of a measurement flow rate value indicated by a flow rate measuring mechanism for measuring a flow rate of fluid flowing through a flow channel.
Golinveaux et al. (Pub. No.: US 2010/0299122 A1) teaches a method of and a computer program for analyzing models of dry pipe systems that provide modeling a referential dry pipe system as a plurality of interconnected nodes, the nodes corresponding to a pipe connector, the interconnection between the nodes corresponding to a pipe device.
Hussain Abbas (Pub. No.: US 2018/0300639 A1) is directed towards pipe leak prediction systems configured to predict whether a pipe is likely to leak based on one or more machine learning techniques, and a predictive model can be trained using data for the characteristics of various pipes in order to determine the patterns associated with pipes without leaks and the patterns associated with pipes with leaks.
Zhu et al. (Intelligent Prediction of Stuck Pipe Using Combined Data-Driven and Knowledge-Driven Model,2022, MDPI, pp 1-16) conceptually presents three models for the prediction of stuck pipe. The first method targets the detection of friction coefficient which can represent the trend of stuck pipe. The second method targets the prediction of probability for stuck pipe using ANN (artificial neural network). The last model establishes a comprehensive indicator based on the first and the second method using fuzzy mathematics which can give more accurate probability for stuck pipe.
Wu et al. (Research on Method for Detecting Pipeline Blockages Based on Fluid Oscillation Theory, 2022, MDPI, pp 1-13) proposes a governing equation of the water hammer of fluid motion in a pipeline with a blockage point, and The Dirac function is introduced for dimension lessness and linearization. The blocking position can be determined by the ratio of the two-component harmonics, and the blocking magnitude can be determined by the blocking attenuation parameters of each component’s harmonics.
Correspondence Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to IFTEKHAR A KHAN whose telephone number is (571)272-5699. The examiner can normally be reached on M-F from 9:00AM-6:00PM (CST). If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Emerson Puente can be reached on (571)272-3652. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/IFTEKHAR A KHAN/Primary Examiner, Art Unit 2187
