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Doppler Lidar Vector Retrievals and Atmospheric Data Visualization in Mixed/Augmented Reality.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Doppler Lidar Vector Retrievals and Atmospheric Data Visualization in Mixed/Augmented Reality./
Author:	Cherukuru, Nihanth Wagmi.
Description:	1 online resource (146 pages)
Notes:	Source: Dissertation Abstracts International, Volume: 78-09(E), Section: B.
Contained By:	Dissertation Abstracts International78-09B(E).
Subject:	Mechanical engineering. -
Online resource:	click for full text (PQDT)
ISBN:	9781369735710

Doppler Lidar Vector Retrievals and Atmospheric Data Visualization in Mixed/Augmented Reality.
Cherukuru, Nihanth Wagmi.

Doppler Lidar Vector Retrievals and Atmospheric Data Visualization in Mixed/Augmented Reality. - 1 online resource (146 pages)

Source: Dissertation Abstracts International, Volume: 78-09(E), Section: B.

Thesis (Ph.D.)

Includes bibliographical references

Environmental remote sensing has seen rapid growth in the recent years and Doppler wind lidars have gained popularity primarily due to their non-intrusive, high spatial and temporal measurement capabilities. While lidar applications early on, relied on the radial velocity measurements alone, most of the practical applications in wind farm control and short term wind prediction require knowledge of the vector wind field. Over the past couple of years, multiple works on lidars have explored three primary methods of retrieving wind vectors viz., using homogeneous windfield assumption, computationally extensive variational methods and the use of multiple Doppler lidars.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9781369735710Subjects--Topical Terms:

557493
Mechanical engineering.
Index Terms--Genre/Form:

554714
Electronic books.

Doppler Lidar Vector Retrievals and Atmospheric Data Visualization in Mixed/Augmented Reality.
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100 1 $a Cherukuru, Nihanth Wagmi. $3 1179391
245 1 0 $a Doppler Lidar Vector Retrievals and Atmospheric Data Visualization in Mixed/Augmented Reality.
264 0 $c 2017
300 $a 1 online resource (146 pages)
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500 $a Source: Dissertation Abstracts International, Volume: 78-09(E), Section: B.
500 $a Adviser: Ronald Calhoun.
502 $a Thesis (Ph.D.) $c Arizona State University $d 2017.
504 $a Includes bibliographical references
520 $a Environmental remote sensing has seen rapid growth in the recent years and Doppler wind lidars have gained popularity primarily due to their non-intrusive, high spatial and temporal measurement capabilities. While lidar applications early on, relied on the radial velocity measurements alone, most of the practical applications in wind farm control and short term wind prediction require knowledge of the vector wind field. Over the past couple of years, multiple works on lidars have explored three primary methods of retrieving wind vectors viz., using homogeneous windfield assumption, computationally extensive variational methods and the use of multiple Doppler lidars.
520 $a Building on prior research, the current three-part study, first demonstrates the capabilities of single and dual Doppler lidar retrievals in capturing downslope windstorm-type flows occurring at Arizona's Barringer Meteor Crater as a part of the METCRAX II field experiment. Next, to address the need for a reliable and computationally efficient vector retrieval for adaptive wind farm control applications, a novel 2D vector retrieval based on a variational formulation was developed and applied on lidar scans from an offshore wind farm and validated with data from a cup and vane anemometer installed on a nearby research platform. Finally, a novel data visualization technique using Mixed Reality (MR)/ Augmented Reality (AR) technology is presented to visualize data from atmospheric sensors. MR is an environment in which the user's visual perception of the real world is enhanced with live, interactive, computer generated sensory input (in this case, data from atmospheric sensors like Doppler lidars). A methodology using modern game development platforms is presented and demonstrated with lidar retrieved wind fields. In the current study, the possibility of using this technology to visualize data from atmospheric sensors in mixed reality is explored and demonstrated with lidar retrieved wind fields as well as a few earth science datasets for education and outreach activities.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
650 4 $a Mechanical engineering. $3 557493
650 4 $a Atmospheric sciences. $3 1179392
650 4 $a Computer science. $3 573171
655 7 $a Electronic books. $2 local $3 554714
690 $a 0548
690 $a 0725
690 $a 0984
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a Arizona State University. $b Mechanical Engineering. $3 845641
773 0 $t Dissertation Abstracts International $g 78-09B(E).
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10272198 $z click for full text (PQDT)