Naval Postgraduate School
Dudley Knox Library
NPS Dudley Knox Library
View Item 
  •   Calhoun Home
  • Departments, Schools and Academic Groups Publications
  • Acquisition Research Program
  • Acquisition Research Symposium
  • View Item
  •   Calhoun Home
  • Departments, Schools and Academic Groups Publications
  • Acquisition Research Program
  • Acquisition Research Symposium
  • View Item
  • How to search in Calhoun
  • My Accounts
  • Ask a Librarian
JavaScript is disabled for your browser. Some features of this site may not work without it.

Browse

All of CalhounCollectionsThis Collection

My Account

LoginRegister

Statistics

Most Popular ItemsStatistics by CountryMost Popular Authors

Determining New System Design Requirements to Optimize Fleet Level Metrics under Uncertainty

Thumbnail
Download
IconPUR-AM-17-208.pdf (1.539Mb)
Download Record
Download to EndNote/RefMan (RIS)
Download to BibTex
Author
Crossley, William
Date
2017-07
Metadata
Show full item record
Abstract
Traditional approaches to design and optimize a new system often do not consider how the operator will use this new system alongside the other existing systems. This モhand-offヤ between the designs of the new system and how this new system operates with the group of systems, leads to the sub-optimal performance of the new system when measured with respect to system-level objective. In the case of aircraft design, choices made to meet a set of requirements dictate the performance of the aircraft, and this aircraft performance in turn influences how the operator might use the aircraft. Further, the presence of uncertainties in predictions of the new aircraft performance and costs and uncertainties in the amount of payload / passenger to transport further exacerbate the problem of determining these requirements. Recent efforts have posed approaches to address this problem, but generally with a deterministic perspective. This research improves upon prior work by extending a prior developed subspace decomposition framework to enable capability that addresses multi-domain uncertainties. The framework addresses uncertainties arising in one domain and its propagation to the next connected domain. The framework employs a Reliability-Based Design Optimization (RBDO) approach to address the uncertainties arising from the aircraft design optimization subspace and employs an Interval Robust Counterpart (IRC) formulation to address the uncertainty propagation from the design subspace to the allocation subspace. The research adopts a previously developed subspace decomposition approach and integrates features from robust / reliability based optimization to address the uncertainties and solves two application problems ヨ a military and a commercial airline application. The military application involves an Air Mobility Command (AMC) fleet problem, and, the commercial airline applications reflects typical operations of a US based carrier. The framework demonstrates its ability to acceptably handle uncertainties arising from various domains. Results of application also demonstrates the ability of the framework to identify the design requirements for the new aircraft, and a posterior analysis indicates that the framework acceptably handles the uncertainties.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
URI
http://hdl.handle.net/10945/58911
NPS Report Number
PUR-AM-17-208
Collections
  • Acquisition Research Symposium

Related items

Showing items related by title, author, creator and subject.

  • Thumbnail

    Determining New System Design Requirements to Optimize Fleet Level Metrics Under Uncertainty 

    Roy, Satadru; Davendralingam, Navindran; Crossley, William A.; Govindaraju, Parithi (Monterey, California. Naval Postgraduate School, 2017-03); SYM-AM-17-090
    Traditional approaches to design and optimize a new system often do not consider how the operator will use this new system alongside the other existing systems. This モhandoffヤ between the designs of the new system and how ...
  • Thumbnail

    On integrated plant, control and guidance design 

    Hallberg, Eric N (Monterey, California. Naval Postgraduate School, 1997-09);
    Two theoretical methods and the development of a guidance, navigation and control rapid protoyping system address the issue of considering the integral participation of feedback early in the design process. The first method ...
  • Thumbnail

    Learning Robust and Discriminative Subspace With Low-Rank Constraints 

    Sheng Li; Yun Fu (2016);
    In this paper, we aim at learning robust and discriminative subspaces from noisy data. Subspace learning is widely used in extracting discriminative features for classifica- tion. However, when data are contaminated with ...
NPS Dudley Knox LibraryDUDLEY KNOX LIBRARY
Feedback

411 Dyer Rd. Bldg. 339
Monterey, CA 93943
circdesk@nps.edu
(831) 656-2947
DSN 756-2947

    Federal Depository Library      


Start Your Research

Research Guides
Academic Writing
Ask a Librarian
Copyright at NPS
Graduate Writing Center
How to Cite
Library Liaisons
Research Tools
Thesis Processing Office

Find & Download

Databases List
Articles, Books & More
NPS Theses
NPS Faculty Publications: Calhoun
Journal Titles
Course Reserves

Use the Library

My Accounts
Request Article or Book
Borrow, Renew, Return
Tech Help
Remote Access
Workshops & Tours

For Faculty & Researchers
For International Students
For Alumni

Print, Copy, Scan, Fax
Rooms & Study Spaces
Floor Map
Computers & Software
Adapters, Lockers & More

Collections

NPS Archive: Calhoun
Restricted Resources
Special Collections & Archives
Federal Depository
Homeland Security Digital Library

About

Hours
Library Staff
About Us
Special Exhibits
Policies
Our Affiliates
Visit Us

NPS-Licensed Resources—Terms & Conditions
Copyright Notice

Naval Postgraduate School

Naval Postgraduate School
1 University Circle, Monterey, CA 93943
Driving Directions | Campus Map

This is an official U.S. Navy Website |  Please read our Privacy Policy Notice  |  FOIA |  Section 508 |  No FEAR Act |  Whistleblower Protection |  Copyright and Accessibility |  Contact Webmaster

Export search results

The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

A logged-in user can export up to 15000 items. If you're not logged in, you can export no more than 500 items.

To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.