東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

An Analysis of Scientific Data Quali...

Barrie, A. C.

FindBook

Google Book

Amazon

博客來

An Analysis of Scientific Data Quality for the Fast Plasma Investigation of the MMS Mission.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	An Analysis of Scientific Data Quality for the Fast Plasma Investigation of the MMS Mission./
作者:	Barrie, A. C.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
面頁冊數:	128 p.
附註:	Source: Dissertations Abstracts International, Volume: 80-07, Section: B.
Contained By:	Dissertations Abstracts International80-07B.
標題:	Aerospace engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10934761
ISBN:	9780438766747

An Analysis of Scientific Data Quality for the Fast Plasma Investigation of the MMS Mission.
Barrie, A. C.

An Analysis of Scientific Data Quality for the Fast Plasma Investigation of the MMS Mission. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 128 p.

Source: Dissertations Abstracts International, Volume: 80-07, Section: B.

Thesis (Ph.D.)--University of Colorado at Boulder, 2018.

This item must not be sold to any third party vendors.

This work describes technical innovations to improve the data quality and volume for the Fast Plasma Investigation (FPI) on board the Magnetospheric Multiscale mission (MMS). A parametric study of wavelet compression has shown that plasma count data can be compressed to high compression ratios with a minimal effect on the integrated plasma moments. Different regions of the magnetosphere are analyzed for both electron and ion count data. The FPI trigger data, intended as a data ranking metric, has been adapted and corrected to a point where scientifically accurate pseudo moments can be generated and released to the research community, drastically increasing the availability of high time resolution data. This is possible due to a scaling system that tunes the dynamic range of the system per region, and the method of using a neural network to correct for exterior contamination effects, such as spacecraft potential. Finally, a map of detection angle bias has been generated that can be used to correct raw count for errors in look direction of incoming particles. This map was generated by statistically sampling particle flight paths through a charged spacecraft environment, validating against flight data. All three of these efforts lead toward the overarching goal of improving data quality and volume for the FPI suite, and future missions to come.

ISBN: 9780438766747Subjects--Topical Terms:

1002622
Aerospace engineering.

An Analysis of Scientific Data Quality for the Fast Plasma Investigation of the MMS Mission.
LDR:02484nmm a2200337 4500 001 2210567
005 20191121124240.5
008 201008s2018 ||||||||||||||||| ||eng d
020 $a 9780438766747
035 $a (MiAaPQ)AAI10934761
035 $a (MiAaPQ)colorado:15717
035 $a AAI10934761
040 $a MiAaPQ $c MiAaPQ
100 1 $a Barrie, A. C. $3 3437705
245 1 3 $a An Analysis of Scientific Data Quality for the Fast Plasma Investigation of the MMS Mission.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2018
300 $a 128 p.
500 $a Source: Dissertations Abstracts International, Volume: 80-07, Section: B.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Advisor: Sternovsky, Zoltan.
502 $a Thesis (Ph.D.)--University of Colorado at Boulder, 2018.
506 $a This item must not be sold to any third party vendors.
520 $a This work describes technical innovations to improve the data quality and volume for the Fast Plasma Investigation (FPI) on board the Magnetospheric Multiscale mission (MMS). A parametric study of wavelet compression has shown that plasma count data can be compressed to high compression ratios with a minimal effect on the integrated plasma moments. Different regions of the magnetosphere are analyzed for both electron and ion count data. The FPI trigger data, intended as a data ranking metric, has been adapted and corrected to a point where scientifically accurate pseudo moments can be generated and released to the research community, drastically increasing the availability of high time resolution data. This is possible due to a scaling system that tunes the dynamic range of the system per region, and the method of using a neural network to correct for exterior contamination effects, such as spacecraft potential. Finally, a map of detection angle bias has been generated that can be used to correct raw count for errors in look direction of incoming particles. This map was generated by statistically sampling particle flight paths through a charged spacecraft environment, validating against flight data. All three of these efforts lead toward the overarching goal of improving data quality and volume for the FPI suite, and future missions to come.
590 $a School code: 0051.
650 4 $a Aerospace engineering. $3 1002622
650 4 $a Physics. $3 516296
650 4 $a Remote sensing. $3 535394
690 $a 0538
690 $a 0605
690 $a 0799
710 2 $a University of Colorado at Boulder. $b Aerospace Engineering. $3 1030473
773 0 $t Dissertations Abstracts International $g 80-07B.
790 $a 0051
791 $a Ph.D.
792 $a 2018
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10934761