Patents by Inventor Harsh Chaudhary
Harsh Chaudhary has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20230155896Abstract: A system and method of managing a network that includes assets are described. The method includes modeling the network as a directed graph with each of the assets represented as a node and determining alternative paths to each node from each available corresponding source of the node. The method also includes computing upstream robustness of each node, computing upstream robustness of the network, and computing downstream criticality of each node. Managing the network and each asset of the network is based on the upstream robustness and the downstream criticality of each node.Type: ApplicationFiled: January 10, 2023Publication date: May 18, 2023Inventors: Aanchal Aggarwal, Harsh Chaudhary, Yakup Koç, Younghun Kim, Tarun Kumar, Abhishek Raman
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Patent number: 11552854Abstract: A system and method of managing a network that includes assets are described. The method includes modeling the network as a directed graph with each of the assets represented as a node and determining alternative paths to each node from each available corresponding source of the node. The method also includes computing upstream robustness of each node, computing upstream robustness of the network, and computing downstream criticality of each node. Managing the network and each asset of the network is based on the upstream robustness and the downstream criticality of each node.Type: GrantFiled: September 14, 2020Date of Patent: January 10, 2023Assignee: Utopus Insights, Inc.Inventors: Aanchal Aggarwal, Harsh Chaudhary, Yakup Koç, Younghun Kim, Tarun Kumar, Abhishek Raman
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Patent number: 11449013Abstract: Technical solutions are described for predicting linepack delays. An example method includes receiving temporal sensor measurements of a first fluid-delivery pipeline network and generating a causality graph of the first fluid-delivery pipeline network. The method also includes determining a topological network of the stations based on the causality graph, where the topological network identifies a temporal delay between a pair of stations. The method also includes generating a temporal delay prediction model based on the topological network and predicting the linepack delays of a second fluid-delivery pipeline network based on the temporal delay prediction model, where a compressor station of the second fluid-delivery pipeline network compresses fluid based on the predicted linepack delays to maintain a predetermined pressure.Type: GrantFiled: March 10, 2020Date of Patent: September 20, 2022Assignee: Utopus Insights, Inc.Inventors: Harsh Chaudhary, Younghun Kim, Tarun Kumar, Abhishek Raman, Rui Zhang
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Publication number: 20210006469Abstract: A system and method of managing a network that includes assets are described. The method includes modeling the network as a directed graph with each of the assets represented as a node and determining alternative paths to each node from each available corresponding source of the node. The method also includes computing upstream robustness of each node, computing upstream robustness of the network, and computing downstream criticality of each node. Managing the network and each asset of the network is based on the upstream robustness and the downstream criticality of each node.Type: ApplicationFiled: September 14, 2020Publication date: January 7, 2021Inventors: Aanchal Aggarwal, Harsh Chaudhary, Yakup Koç, Younghun Kim, Tarun Kumar, Abhishek Raman
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Publication number: 20200387119Abstract: Technical solutions are described for predicting linepack delays. An example method includes receiving temporal sensor measurements of a first fluid-delivery pipeline network and generating a causality graph of the first fluid-delivery pipeline network. The method also includes determining a topological network of the stations based on the causality graph, where the topological network identifies a temporal delay between a pair of stations. The method also includes generating a temporal delay prediction model based on the topological network and predicting the linepack delays of a second fluid-delivery pipeline network based on the temporal delay prediction model, where a compressor station of the second fluid-delivery pipeline network compresses fluid based on the predicted linepack delays to maintain a predetermined pressure.Type: ApplicationFiled: March 10, 2020Publication date: December 10, 2020Applicant: Utopus Insights, Inc.Inventors: Harsh Chaudhary, Younghun Kim, Tarun Kumar, Abhishek Raman, Rui Zhang
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Patent number: 10778529Abstract: A system and method of managing a network that includes assets are described. The method includes modeling the network as a directed graph with each of the assets represented as a node and determining alternative paths to each node from each available corresponding source of the node. The method also includes computing upstream robustness of each node, computing upstream robustness of the network, and computing downstream criticality of each node. Managing the network and each asset of the network is based on the upstream robustness and the downstream criticality of each node.Type: GrantFiled: June 5, 2018Date of Patent: September 15, 2020Assignee: Utopus Insights, Inc.Inventors: Aanchal Aggarwal, Harsh Chaudhary, Yakup Koç, Younghun Kim, Tarun Kumar, Abhishek Raman
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Patent number: 10585403Abstract: Technical solutions are described for predicting linepack delays. An example method includes receiving temporal sensor measurements of a first fluid-delivery pipeline network and generating a causality graph of the first fluid-delivery pipeline network. The method also includes determining a topological network of the stations based on the causality graph, where the topological network identifies a temporal delay between a pair of stations. The method also includes generating a temporal delay prediction model based on the topological network and predicting the linepack delays of a second fluid-delivery pipeline network based on the temporal delay prediction model, where a compressor station of the second fluid-delivery pipeline network compresses fluid based on the predicted linepack delays to maintain a predetermined pressure.Type: GrantFiled: February 17, 2017Date of Patent: March 10, 2020Assignee: Utopus Insights, Inc.Inventors: Harsh Chaudhary, Younghun Kim, Tarun Kumar, Abhishek Raman, Rui Zhang
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Patent number: 10401879Abstract: Technical solutions are described for determining topological connectivity between stations of a fluid-delivery pipeline network. An example method includes receiving temporal sensor measurements of the fluid-delivery pipeline network, that include a series of sensor measurements from each respective station of the fluid-delivery pipeline network. The method also includes generating a causality graph of the fluid-delivery pipeline network based on the temporal sensor measurements, where the causality graph includes a set of nodes and a set of links, where the nodes are representative of the stations, and a pair of nodes is connected by a link in response to the pair of stations being temporally dependent. The method also includes determining a topological network of the stations based on the causality graph, where the topological network identifies one or more destination stations for a supply station in the fluid-delivery pipeline network.Type: GrantFiled: February 9, 2017Date of Patent: September 3, 2019Assignee: Utopus Insights, Inc.Inventors: Harsh Chaudhary, Younghun Kim, Tarun Kumar, Abhishek Raman, Rui Zhang
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Patent number: 10386262Abstract: A method and system method to detect a leak within a pipeline network include measuring pressure at each of a plurality of sensors distributed along the pipeline network as a time-varying pressure signal. Tuning a model is based on gas mass conservation law in the absence of the leak, the tuning including obtaining the time-varying pressure signal from each of the plurality of sensors, and monitoring the time-varying pressure signals is done to detect the leak based on the model.Type: GrantFiled: January 28, 2016Date of Patent: August 20, 2019Assignee: Utopus Insights, Inc.Inventors: Harsh Chaudhary, Younghun Kim, Tarun Kumar, Abhishek Raman, Rui Zhang
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Patent number: 10354195Abstract: Technical solutions are described for forecasting leaks in a pipeline network. An example method includes identifying a subsystem in the pipeline network that includes a first station. The method also includes accessing historical temporal sensor measurements of the stations. The method also includes generating a prediction model for the first station that predicts a pressure measurement at the first station based on the historical temporal sensor measurements at each station in the subsystem. The method also includes predicting a series of pressure measurements at the first station based on the historical temporal sensor measurements. The method also includes determining a series of deviations between the series of pressure measurements and historical pressure measurements of the first station and identifying a threshold value from the series of deviations, where a pressure measurement at the first station above or below the threshold value is indicative of a leak in the subsystem.Type: GrantFiled: December 22, 2016Date of Patent: July 16, 2019Assignee: Utopus Insights, Inc.Inventors: Harsh Chaudhary, Younghun Kim, Tarun Kumar, Abhishek Raman, Rui Zhang
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Publication number: 20180351814Abstract: A system and method of managing a network that includes assets are described. The method includes modeling the network as a directed graph with each of the assets represented as a node and determining alternative paths to each node from each available corresponding source of the node. The method also includes computing upstream robustness of each node, computing upstream robustness of the network, and computing downstream criticality of each node. Managing the network and each asset of the network is based on the upstream robustness and the downstream criticality of each node.Type: ApplicationFiled: June 5, 2018Publication date: December 6, 2018Applicant: Utopus Insights, Inc.Inventors: Aanchal Aggarwal, Harsh Chaudhary, Yakup Koç, Younghun Kim, Tarun Kumar, Abhishek Raman
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Patent number: 9992069Abstract: A system and method of managing a network that includes assets are described. The method includes modeling the network as a directed graph with each of the assets represented as a node and determining alternative paths to each node from each available corresponding source of the node. The method also includes computing upstream robustness of each node, computing upstream robustness of the network, and computing downstream criticality of each node. Managing the network and each asset of the network is based on the upstream robustness and the downstream criticality of each node.Type: GrantFiled: June 22, 2015Date of Patent: June 5, 2018Assignee: Utopus Insights, Inc.Inventors: Aanchal Aggarwal, Harsh Chaudhary, Yakup Koç, Younghun Kim, Tarun Kumar, Abhishek Raman
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Patent number: 9923778Abstract: A system and method of managing a network that includes assets are described. The method includes modeling the network as a directed graph with each of the assets represented as a node and determining alternative paths to each node from each available corresponding source of the node. The method also includes computing upstream robustness of each node, computing upstream robustness of the network, and computing downstream criticality of each node. Managing the network and each asset of the network is based on the upstream robustness and the downstream criticality of each node.Type: GrantFiled: March 23, 2015Date of Patent: March 20, 2018Assignee: Utopus Insights, Inc.Inventors: Aanchal Aggarwal, Harsh Chaudhary, Yakup Koç, Younghun Kim, Tarun Kumar, Abhishek Raman
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Publication number: 20170219454Abstract: A method and system method to detect a leak within a pipeline network include measuring pressure at each of a plurality of sensors distributed along the pipeline network as a time-varying pressure signal. Tuning a model is based on gas mass conservation law in the absence of the leak, the tuning including obtaining the time-varying pressure signal from each of the plurality of sensors, and monitoring the time-varying pressure signals is done to detect the leak based on the model.Type: ApplicationFiled: January 28, 2016Publication date: August 3, 2017Inventors: Harsh Chaudhary, Younghun Kim, Tarun Kumar, Abhishek Raman, Rui Zhang
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Publication number: 20170219451Abstract: A method and system of calibrating uncalibrated sensors among sensors distributed along a pipeline network include designating a set of the sensors as upstream sensors based on their geopositions, and designating remaining ones of the sensors other than the set of the sensors as downstream sensors. The method also includes determining a temporal delay associated with each of the sensors. Calibrating the uncalibrated sensors is based on the corresponding temporal delay and on calibrated sensors among the sensors.Type: ApplicationFiled: January 28, 2016Publication date: August 3, 2017Inventors: Harsh Chaudhary, Younghun Kim, Tarun Kumar, Rui Zhang
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Publication number: 20170176957Abstract: Technical solutions are described for predicting linepack delays. An example method includes receiving temporal sensor measurements of a first fluid-delivery pipeline network and generating a causality graph of the first fluid-delivery pipeline network. The method also includes determining a topological network of the stations based on the causality graph, where the topological network identifies a temporal delay between a pair of stations. The method also includes generating a temporal delay prediction model based on the topological network and predicting the linepack delays of a second fluid-delivery pipeline network based on the temporal delay prediction model, where a compressor station of the second fluid-delivery pipeline network compresses fluid based on the predicted linepack delays to maintain a predetermined pressure.Type: ApplicationFiled: February 17, 2017Publication date: June 22, 2017Inventors: Harsh Chaudhary, Younghun Kim, Tarun Kumar, Abhishek Raman, Rui Zhang
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Publication number: 20170177008Abstract: Technical solutions are described for determining topological connectivity between stations of a fluid-delivery pipeline network. An example method includes receiving temporal sensor measurements of the fluid-delivery pipeline network, that include a series of sensor measurements from each respective station of the fluid-delivery pipeline network. The method also includes generating a causality graph of the fluid-delivery pipeline network based on the temporal sensor measurements, where the causality graph includes a set of nodes and a set of links, where the nodes are representative of the stations, and a pair of nodes is connected by a link in response to the pair of stations being temporally dependent. The method also includes determining a topological network of the stations based on the causality graph, where the topological network identifies one or more destination stations for a supply station in the fluid-delivery pipeline network.Type: ApplicationFiled: February 9, 2017Publication date: June 22, 2017Inventors: Harsh Chaudhary, Younghun Kim, Tarun Kumar, Abhishek Raman, Rui Zhang
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Publication number: 20170178016Abstract: Technical solutions are described for forecasting leaks in a pipeline network. An example method includes identifying a subsystem in the pipeline network that includes a first station. The method also includes accessing historical temporal sensor measurements of the stations. The method also includes generating a prediction model for the first station that predicts a pressure measurement at the first station based on the historical temporal sensor measurements at each station in the subsystem. The method also includes predicting a series of pressure measurements at the first station based on the historical temporal sensor measurements. The method also includes determining a series of deviations between the series of pressure measurements and historical pressure measurements of the first station and identifying a threshold value from the series of deviations, where a pressure measurement at the first station above or below the threshold value is indicative of a leak in the subsystem.Type: ApplicationFiled: December 22, 2016Publication date: June 22, 2017Inventors: Harsh Chaudhary, Younghun Kim, Tarun Kumar, Abhishek Raman, Rui Zhang
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Patent number: 9599499Abstract: Technical solutions are described for predicting linepack delays. An example method includes receiving temporal sensor measurements of a first fluid-delivery pipeline network and generating a causality graph of the first fluid-delivery pipeline network. The method also includes determining a topological network of the stations based on the causality graph, where the topological network identifies a temporal delay between a pair of stations. The method also includes generating a temporal delay prediction model based on the topological network and predicting the linepack delays of a second fluid-delivery pipeline network based on the temporal delay prediction model, where a compressor station of the second fluid-delivery pipeline network compresses fluid based on the predicted linepack delays to maintain a predetermined pressure.Type: GrantFiled: December 21, 2015Date of Patent: March 21, 2017Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Harsh Chaudhary, Younghun Kim, Tarun Kumar, Abhishek Raman, Rui Zhang
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Patent number: 9599531Abstract: Technical solutions are described for determining topological connectivity between stations of a fluid-delivery pipeline network. An example method includes receiving temporal sensor measurements of the fluid-delivery pipeline network, that include a series of sensor measurements from each respective station of the fluid-delivery pipeline network. The method also includes generating a causality graph of the fluid-delivery pipeline network based on the temporal sensor measurements, where the causality graph includes a set of nodes and a set of links, where the nodes are representative of the stations, and a pair of nodes is connected by a link in response to the pair of stations being temporally dependent. The method also includes determining a topological network of the stations based on the causality graph, where the topological network identifies one or more destination stations for a supply station in the fluid-delivery pipeline network.Type: GrantFiled: December 21, 2015Date of Patent: March 21, 2017Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Harsh Chaudhary, Younghun Kim, Tarun Kumar, Abhishek Raman, Rui Zhang