News Column

Patent Issued for Automated Method and System for Predicting High Resolution Tidal Heights and Currents in Coastal Zones

July 15, 2014



By a News Reporter-Staff News Editor at Information Technology Newsweekly -- The United States of America, as represented by the Secretary of the Navy (Washington, DC) has been issued patent number 8768663, according to news reporting originating out of Alexandria, Virginia, by VerticalNews editors.

The patent's inventors are Chu, Yifei Philip (Slidell, LA); Blain, Cheryl Ann (Slidell, LA); Linzell, Robert S (Carriere, MS).

This patent was filed on September 23, 2011 and was published online on July 1, 2014.

From the background information supplied by the inventors, news correspondents obtained the following quote: "Methods and systems disclosed herein relate generally to automated forecasting, and specifically to automated forecasting of tidal heights and currents in coastal regions.

"Accurate prediction of water levels and currents in coastal areas is critical to the success of various oceanographic operations such as, for example, but not limited to, navigation, amphibious landing, mine warfare and Navy SEAL missions. Some existing coastal forecasting methods can be time-consuming and labor-intensive because model-related tasks and functions require human interactions. What is needed is an automated system to predict high resolution water level and currents at several geographic locations to support activities such as, for example, but not limited to, resource management, navigation safety, facility and structure planning, search and rescue, decision making, and recreational activities, as well as the earlier mentioned U.S. Navy-related operations."

Supplementing the background information on this patent, VerticalNews reporters also obtained the inventors' summary information for this patent: "The system and method of the present embodiment can automatically and regularly predict water level and currents in coastal areas, without operator intervention. The system and method can enable, but are not limited to enabling, automated operational forecasts at regular time intervals without operator intervention by using a computer forecast model that allows accurate prediction of tidal heights and currents in complex shoreline and bathymetry regions, single or parallel processing capability, optimal available processor assignment based on the size of the computing domain, standard and other tidal database forcing for water surface elevation boundary conditions, missing data gap-filling, and river discharge data, wind, bathymetry, and model-derived boundary condition model integration.

"The method of the present embodiment for predicting tidal heights and currents using an automated forecast model can include, but is not limited to including, the steps of receiving processing options, automatically creating necessary directories and preparing/updating input files based on the processing options. Databases can include, but are not limited to including, grid database, global bathymetry database, global shoreline database, and global tidal database. The method can generate a wind field and then interpolated wind fields, and thus, fort.22 data, from, for example, but not limited to, the U.S. Navy's Coupled Ocean Atmospheric Mesoscale Prediction System (COAMPS.RTM.) model or the U.S. Navy Operational Global Atmospheric Prediction System (NOGAPS) model. The method can generate grid data from a global bathymetry database and a global shoreline database. The method can receive a global tidal database and process tidal potential, specify harmonic constituents and tide boundary conditions to be included in fort.15 data. The method can create a grid for the model domain, and thus, fort.14 data, based on either a software-generated grid or a grid database. The method can create, prepare, and process such data files as, for example, but not limited to, fort.15, fort.14, fort.20, and fort.22 data for parallel computation, and can execute a two-dimensional (2D) or three-dimensional (3D) barotropic hydrodynamic model such as, for example, but not limited to, the Advanced Circulation Model for Shelves, Coastal Seas, and Estuaries (ADCIRC) model to produce, for example, but not limited to fort.61, fort.62, fort.63, and fort.64 displayed, plotted, and archived data.

"The system of the present embodiment for predicting tidal heights and currents using an automated forecast model can include, but is not limited to including, a forecast model input creation processor using a generic file and input parameters to produce a grid having data required for the forecast model, a tidal heights and currents prediction processor using a forecast domain to produce water cells and river discharge data, an execution time optimization processor using a forecast model identification and a forecast period to produce optimized input files for the forecast model, a reliability/stability processor using the forecast model ID, an execution ID, and the optimized input files to calculate storage space and access and include interpolated and resulting data from previous model executions, and a forecast model processor providing the grid, the water cells, the river discharge data the optimized input files, the storage space and the resulting data from previous model executions, to the forecast model which produces a forecast of tidal heights and currents, the forecast being stored on a computer-readable medium. The forecast model input creation processor can include, but is not limited to including, a generic file processor creating at least one generic electronic file having information related to the forecast, the generic file processor accepting input parameters related to the forecast, the generic file processor updating the at least one electronic generic file based on the input parameters, a required data processor collecting required data related to the forecast model based on the at least one updated generic file, and a grid processor accessing a grid related to the forecast, the grid processor mapping the required data into the grid, the grid processor providing the grid to the forecast model processor. The required data processor generates a wind field and interpolating the wind field to create fort.22 data, generates grid data from a global bathymetry database and a global shoreline database, prepares tide boundary conditions and tidal potential, including fort.15 data, based on a tidal database, and creates a grid and fort.14 data based on either the grid data or a grid database. The tidal heights and currents prediction processor can include, but is not limited to including, a data structure finder determining a data structure associated with a forecast domain, a river proximity processor automatically locating at least one water cell in the data structure, the data structure being coincident with a river, if a river is located within the forecast domain, or automatically locating the water cell in the data structure having a predetermined water depth and being near the river; a flow rate processor determining river discharge flow rate of the water cell, the flow rate processor converting the flow rate into river discharge data; and a forecast model processor incorporating the water cell and the river discharge data into the forecast model. The execution time optimization processor can include, but is not limited to including, a CPU locator automatically determining an available number of computer processors available for executing the forecasting model, an execution time processor automatically estimating the execution time required to execute the forecasting model on the computer processors based on the available number and the forecast period, an alternatives processor automatically executing an alternative procedure if the execution time is larger than the forecast period, a domain processor automatically partitioning a domain of the forecasting model based on the available number, an input file processor automatically preparing input files for the forecasting model based on the available number, and a forecast model processor automatically initiating the forecasting model on the computer processors based on the input files, the forecast period, and the domain, the forecast model processor automatically receiving a forecast over the forecast period from the forecasting model, the forecast model processor automatically providing the forecast to a computer-readable medium. The reliability/stability processor can include, but is not limited to including, a storage space processor estimating required storage space of a pre-selected execution of the forecast model, the storage space processor determining available storage space for a future execution of the forecast model by comparing the estimated required storage space to available space in the computer system, the storage space processor accessing additional storage space and providing the additional storage space to the forecasting model if the available storage space does not accommodate the forecast model, an interpolator providing needed data to the forecast model processor based on spatial and temporal interpolation of current data if current spatial and temporal data are available, and a previous model execution data processor providing the needed data to the forecast model processor based on resulting data from previous model executions for a maximum of two iterations of the forecast model if current spatial and temporal data are not available. Accessing additional storage space can be accomplished by, for example, but not limited to, compressing information, eliminating information, and awaiting the freeing of storage space.

"The computer readable medium of the present embodiment for predicting tidal heights and currents using an automated forecast model can include, but is not limited to including, computer code executing the steps of receiving processing options, automatically creating directories and preparing/updating input files based on the processing options, automatically calculating water cells and river discharge data based on the input files, automatically optimizing the input files for forecast model execution, automatically preparing reliability/stability information based on the forecast model, automatically preparing the water cells, river discharge data, optimized input files, and reliability/stability information as prepared input to the forecast model, automatically providing the prepared input to the forecast model, automatically receiving a forecast from the forecast model, the forecast based on the prepared data, and automatically providing the forecast to a computer readable medium. The computer code executing the step of automatically creating directories can include, but is not limited to including, the steps of creating at least one generic electronic file having information related to the forecast, accepting input parameters related to the forecast, updating the at least one electronic generic file based on the input parameters, collecting required data related to the forecast model based on the at least one updated generic file, accessing a grid related to the forecast, mapping the required data into the grid, and providing the grid to the forecast model. The computer code executing the step of calculating water cells and river discharge data can include, but is not limited to including, the steps of determining a data structure associated with a domain of the forecast, if a river is located within the domain, automatically locating the water cells in the data structure coincident with the river, if possible, or automatically locating the water cells in the data structure, the water cells having predetermined water depths and being near the river, determining river discharge flow rates of the water cells, and converting the flow rates into river discharge data. The computer code executing the step of preparing optimized input files can include, but is not limited to including, the steps of automatically determining an available number of computer processors available for executing the forecast model, the forecast model having a forecast period, automatically estimating the execution time required to execute the forecast model on the computer processors based on the available number and the forecast period, automatically executing an alternative procedure if the execution time is larger than the forecast period, automatically partitioning a domain of the forecasting model based on the available number, and automatically optimizing the input files based on the available number. The computer code executing the step of automatically preparing reliability/stability information further can include, but is not limited to including, the steps of estimating required storage space of a pre-selected execution of the forecast model, determining available storage space for a future execution of the forecast model by comparing the estimated required storage space to available space in the computer system, accessing additional storage space and providing the additional storage space to the forecasting model if the available storage space does not accommodate the forecast model, if current spatial and temporal data are available, providing needed data to the forecast model based on spatial and temporal interpolation of current data, and if current spatial and temporal data are not available, providing the needed data to the forecast model based on resulting data from previous model executions for a maximum of two iterations of the forecast model."

For the URL and additional information on this patent, see: Chu, Yifei Philip; Blain, Cheryl Ann; Linzell, Robert S. Automated Method and System for Predicting High Resolution Tidal Heights and Currents in Coastal Zones. U.S. Patent Number 8768663, filed September 23, 2011, and published online on July 1, 2014. Patent URL: http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PALL&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.htm&r=1&f=G&l=50&s1=8768663.PN.&OS=PN/8768663RS=PN/8768663

Keywords for this news article include: Information Technology, Information and Data Architecture, The United States of America as represented by the Secretary of the Navy.

Our reports deliver fact-based news of research and discoveries from around the world. Copyright 2014, NewsRx LLC


For more stories covering the world of technology, please see HispanicBusiness' Tech Channel



Source: Information Technology Newsweekly


Story Tools






HispanicBusiness.com Facebook Linkedin Twitter RSS Feed Email Alerts & Newsletters