FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2334162815> ?p ?o ?g. }

• W2334162815 abstract "PreviousNext No AccessSymposium on the Application of Geophysics to Engineering and Environmental Problems 2013UXO LOCATION EFFICIENCY – COMPARATIVE NUMERICAL ESTIMATION RESULTS FROM VARIOUS MAGNETIC SENSOR CONFIGURATIONSAuthors: Mikhail TchernychevJeff JohnstonRoss JohnsonMikhail Tchernychev Geometrics Inc, San Jose, CASearch for more papers by this author, Jeff Johnston Geometrics Inc, San Jose, CASearch for more papers by this author, and Ross Johnson Geometrics Inc, San Jose, CASearch for more papers by this authorhttps://doi.org/10.4133/sageep2013-136.1 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract Magnetometer sensor arrays are commonly used in today's UXO remediation efforts. A typical interpretation approach is to move a magnetometer array over the earth and then use a dipole-model based inversion to estimate the position and magnetic moment which is proportional to the target mass. Varied sensor array configurations will produce various accuracies in terms of the computed source position and target moment. Other important factors are the spatial sampling rate and amount of the data selected for interpretation. All of these factors contribute to the quality of the solution obtained. In this paper we use numerical modeling to compare the efficiency of different sensor array configurations encountered in typical survey conditions. The efficiency is expressed in terms of standard deviations of position and magnetic moment estimates: the smaller the standard deviation, the better the estimate. A variety of array configurations are analyzed including transverse gradiometers of different sensor separations and 3-D sensor deployments. A target position for each configuration is assumed to be off to the side of the array and at various distances. Plots of standard deviations of position and magnetic moment estimates are presented as a function of the target distance. Numerical simulations consist of computing the magnetic field using a known source and then contaminating the model with different types of noise (random noise with normal distribution or noise due to a large unknown source in the proximity of the object of interest.) We then compare the inversion results with the known model conditions. The model analysis also addresses various sensor sample rates and the use of a sub-set selection of the anomaly profile rather than the whole anomaly curve. We conclude by ranking the various sensor configurations and spatial sampling rates in terms of target positional accuracy and offer general operational survey recommendations. Permalink: https://doi.org/10.4133/sageep2013-136.1FiguresReferencesRelatedDetails Symposium on the Application of Geophysics to Engineering and Environmental Problems 2013ISSN (online):1554-8015Copyright: 2013 Pages: 821 publication data© 2013 Published in electronic format with permission by the Environment and Engineering Geophysical SocietyPublisher:Environmental & Engineering Geophysical Society HistoryPublished: 28 May 2013 CITATION INFORMATION Mikhail Tchernychev, Jeff Johnston, and Ross Johnson, (2013), UXO LOCATION EFFICIENCY – COMPARATIVE NUMERICAL ESTIMATION RESULTS FROM VARIOUS MAGNETIC SENSOR CONFIGURATIONS, Symposium on the Application of Geophysics to Engineering and Environmental Problems Proceedings : 393-402. https://doi.org/10.4133/sageep2013-136.1 Plain-Language Summary PDF DownloadLoading ..." @default.
• W2334162815 created "2016-06-24" @default.
• W2334162815 creator A5003334453 @default.
• W2334162815 creator A5031137988 @default.
• W2334162815 creator A5032124622 @default.
• W2334162815 date "2013-03-17" @default.
• W2334162815 modified "2023-09-25" @default.
• W2334162815 title "UXO LOCATION EFFICIENCY – COMPARATIVE NUMERICAL ESTIMATION RESULTS FROM VARIOUS MAGNETIC SENSOR CONFIGURATIONS" @default.
• W2334162815 cites W1624012152 @default.
• W2334162815 cites W2036441941 @default.
• W2334162815 cites W2085432568 @default.
• W2334162815 doi "https://doi.org/10.4133/sageep2013-136.1" @default.
• W2334162815 hasPublicationYear "2013" @default.
• W2334162815 type Work @default.
• W2334162815 sameAs 2334162815 @default.
• W2334162815 citedByCount "0" @default.
• W2334162815 crossrefType "proceedings-article" @default.
• W2334162815 hasAuthorship W2334162815A5003334453 @default.
• W2334162815 hasAuthorship W2334162815A5031137988 @default.
• W2334162815 hasAuthorship W2334162815A5032124622 @default.
• W2334162815 hasConcept C10138342 @default.
• W2334162815 hasConcept C115260700 @default.
• W2334162815 hasConcept C121332964 @default.
• W2334162815 hasConcept C127313418 @default.
• W2334162815 hasConcept C13280743 @default.
• W2334162815 hasConcept C153946474 @default.
• W2334162815 hasConcept C162324750 @default.
• W2334162815 hasConcept C165205528 @default.
• W2334162815 hasConcept C169852918 @default.
• W2334162815 hasConcept C173523689 @default.
• W2334162815 hasConcept C179254644 @default.
• W2334162815 hasConcept C1893757 @default.
• W2334162815 hasConcept C198082294 @default.
• W2334162815 hasConcept C41008148 @default.
• W2334162815 hasConcept C62520636 @default.
• W2334162815 hasConcept C62649853 @default.
• W2334162815 hasConcept C74650414 @default.
• W2334162815 hasConcept C77928131 @default.
• W2334162815 hasConceptScore W2334162815C10138342 @default.
• W2334162815 hasConceptScore W2334162815C115260700 @default.
• W2334162815 hasConceptScore W2334162815C121332964 @default.
• W2334162815 hasConceptScore W2334162815C127313418 @default.
• W2334162815 hasConceptScore W2334162815C13280743 @default.
• W2334162815 hasConceptScore W2334162815C153946474 @default.
• W2334162815 hasConceptScore W2334162815C162324750 @default.
• W2334162815 hasConceptScore W2334162815C165205528 @default.
• W2334162815 hasConceptScore W2334162815C169852918 @default.
• W2334162815 hasConceptScore W2334162815C173523689 @default.
• W2334162815 hasConceptScore W2334162815C179254644 @default.
• W2334162815 hasConceptScore W2334162815C1893757 @default.
• W2334162815 hasConceptScore W2334162815C198082294 @default.
• W2334162815 hasConceptScore W2334162815C41008148 @default.
• W2334162815 hasConceptScore W2334162815C62520636 @default.
• W2334162815 hasConceptScore W2334162815C62649853 @default.
• W2334162815 hasConceptScore W2334162815C74650414 @default.
• W2334162815 hasConceptScore W2334162815C77928131 @default.
• W2334162815 hasLocation W23341628151 @default.
• W2334162815 hasOpenAccess W2334162815 @default.
• W2334162815 hasPrimaryLocation W23341628151 @default.
• W2334162815 hasRelatedWork W1612724426 @default.
• W2334162815 hasRelatedWork W2021202196 @default.
• W2334162815 hasRelatedWork W2106484078 @default.
• W2334162815 hasRelatedWork W2110200090 @default.
• W2334162815 hasRelatedWork W2319880389 @default.
• W2334162815 hasRelatedWork W2329949735 @default.
• W2334162815 hasRelatedWork W2332720159 @default.
• W2334162815 hasRelatedWork W2365436221 @default.
• W2334162815 hasRelatedWork W3178252510 @default.
• W2334162815 hasRelatedWork W4244024131 @default.
• W2334162815 isParatext "false" @default.
• W2334162815 isRetracted "false" @default.
• W2334162815 magId "2334162815" @default.
• W2334162815 workType "article" @default.