Advanced search options

Advanced Search Options 🞨

Browse by author name (“Author name starts with…”).

Find ETDs with:

in
/  
in
/  
in
/  
in

Written in Published in Earliest date Latest date

Sorted by

Results per page:

Sorted by: relevance · author · university · dateNew search

You searched for subject:(FM based). Showing records 1 – 3 of 3 total matches.

Search Limiters

Last 2 Years | English Only

No search limiters apply to these results.

▼ Search Limiters


Delft University of Technology

1. Caichac Avilés, Daniel (author). Beach representation in morphodynamic predictions: Coupling models to improve beach behavior applied to Anmok beach.

Degree: 2017, Delft University of Technology

Numerical process-based morphodynamic models are widespread in coastal engineering practice and have become the new standard when it comes to assessing the impact of natural or man-made structures on coastal environments. The most common practice among engineers is to focus on a single spatial and time scale, which means either neglecting certain processes under the assumption that they will average out, or performing detailed simulations for short time-spans in order to optimize the normally limited computational resources. Despite the efforts from several authors, at the moment there is a lack of a clear methodology which would allow incorporating the relevant physical phenomena only when required, hence optimizing the computational effort. The above leads to the main research objective of this thesis: to gain insight in what is the added value of coupling process based morphodynamic models, regarding the morphological impacts near the beach. For this purpose two models that were originally conceived to resolve different timescales are selected; XBeach as a storm model, and the new suite from Deltares, Delft3D-Flexible Mesh (D3D-FM) as a long-term morphodynamic model. The area selected as study site is Anmok beach, located at the east coast of South Korea. The coastal erosion at this location is not yet well understood (mainly due to human interventions and storms) plus the micro-tidal wave-dominated environment makes this location ideal for this study. Recent researches on this site have found that there is a delicate balance between the stormy and calm periods, where the high energy wave events are the main drivers of local morphology. One of the main findings in this thesis is that the coupling of independently calibrated models does not necessarily provide better morphodynamic results than the results obtained by running each model separately. Including different processes such as infragravity waves or Eulerian mass transport (which enhances the offshore sediment transport in the surf zone) during highly energetic events tend to generate large supratidal beach erosion. However, the post-storm recovery mechanisms present in long-term morphodynamic models are not sufficient to bring the sediment back to the beach. Therefore, it is recommended to include all the relevant physical processes (storm erosion and post storm recovery mechanisms) when following a coupling approach in order to have a coherent morphodynamic balance. Furthermore, the coupling of models can play an important role in identifying which processes are missing or are not fully represented by the different modelling packages. The erosive effect of cumulative storms was shown to be relevant in the short to medium term and might become a key parameter when defining, for instance, the worst case scenario regarding shoreline retreat. Despite the fact that uncoupled long-term morphodynamic models produce better average results in the case of Anmok beach, the implementation of a coupled scheme was proven to be important when… Advisors/Committee Members: Aarninkhof, Stefan (mentor), Luijendijk, Arjen (graduation committee), McCall, Robert (graduation committee), de Boer, Wiebe (graduation committee), Reyns, J (graduation committee), Delft University of Technology (degree granting institution).

Subjects/Keywords: Delft3D-FM; XBeach; Sediment transport; Morphodynamics; Process-based modelling; BMI; Coupled models; surfbeat; micro tidal

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Caichac Avilés, D. (. (2017). Beach representation in morphodynamic predictions: Coupling models to improve beach behavior applied to Anmok beach. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:8452f24d-afb7-4d08-b9d9-7ad384821f4e

Chicago Manual of Style (16th Edition):

Caichac Avilés, Daniel (author). “Beach representation in morphodynamic predictions: Coupling models to improve beach behavior applied to Anmok beach.” 2017. Masters Thesis, Delft University of Technology. Accessed October 21, 2020. http://resolver.tudelft.nl/uuid:8452f24d-afb7-4d08-b9d9-7ad384821f4e.

MLA Handbook (7th Edition):

Caichac Avilés, Daniel (author). “Beach representation in morphodynamic predictions: Coupling models to improve beach behavior applied to Anmok beach.” 2017. Web. 21 Oct 2020.

Vancouver:

Caichac Avilés D(. Beach representation in morphodynamic predictions: Coupling models to improve beach behavior applied to Anmok beach. [Internet] [Masters thesis]. Delft University of Technology; 2017. [cited 2020 Oct 21]. Available from: http://resolver.tudelft.nl/uuid:8452f24d-afb7-4d08-b9d9-7ad384821f4e.

Council of Science Editors:

Caichac Avilés D(. Beach representation in morphodynamic predictions: Coupling models to improve beach behavior applied to Anmok beach. [Masters Thesis]. Delft University of Technology; 2017. Available from: http://resolver.tudelft.nl/uuid:8452f24d-afb7-4d08-b9d9-7ad384821f4e


Iowa State University

2. Sangeetha, Venkata Krishna. Novel approach to FM-based device free passive indoor localization through neural networks.

Degree: 2015, Iowa State University

Indoor Localization has been one of the most extensively researched topics for the past couple of years with a recent surge in a specific area of Device-free localization in wireless environments. Particularly FM-radio based technologies are being been preferred over WiFi-based technologies due to better penetration indoors and free availability. The major challenges for obtaining a consistent and highly accurate indoor FM based system are susceptibility to human presence, multipath fading and environmental changes. Our research works around these limitations and utilizes the environment itself to establish stronger fingerprints and thus creating a robust localization system. This novel thesis also investigates the feasibility of using neural networks to solve the problem of accuracy degradation when using a single passive receiver across multiple ambient FM radio stations. The system achieves high fidelity and temporal stability to the tunes of 95% by utilizing pattern recognition techniques for the multiple channel spectra.

Subjects/Keywords: Computer Engineering; Device free; DFPL; FM-based; Indoor Localization; Neural Networks; Single Passive Receiver; Electrical and Electronics; Engineering

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Sangeetha, V. K. (2015). Novel approach to FM-based device free passive indoor localization through neural networks. (Thesis). Iowa State University. Retrieved from https://lib.dr.iastate.edu/etd/14619

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Sangeetha, Venkata Krishna. “Novel approach to FM-based device free passive indoor localization through neural networks.” 2015. Thesis, Iowa State University. Accessed October 21, 2020. https://lib.dr.iastate.edu/etd/14619.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Sangeetha, Venkata Krishna. “Novel approach to FM-based device free passive indoor localization through neural networks.” 2015. Web. 21 Oct 2020.

Vancouver:

Sangeetha VK. Novel approach to FM-based device free passive indoor localization through neural networks. [Internet] [Thesis]. Iowa State University; 2015. [cited 2020 Oct 21]. Available from: https://lib.dr.iastate.edu/etd/14619.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Sangeetha VK. Novel approach to FM-based device free passive indoor localization through neural networks. [Thesis]. Iowa State University; 2015. Available from: https://lib.dr.iastate.edu/etd/14619

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

3. Duan, Xiao. The Fractional Fourier Transform and Its Application to Fault Signal Analysis.

Degree: MS, Mechanical Engineering, 2012, Texas A&M University

To a large extent mathematical transforms are applied on a signal to uncover information that is concealed, and the capability of such transforms is valuable for signal processing. One such transforms widely used in this area, is the conventional Fourier Transform (FT), which decomposes a stationary signal into different frequency components. However, a major drawback of the conventional transform is that it does not easily render itself to the analysis of non-stationary signals such as a frequency modulated (FM) or amplitude modulated (AM) signal. The different frequency components of complex signals cannot be easily distinguished and separated from one another using the conventional FT. So in this thesis an innovative mathematical transform, Fractional Fourier Transform (FRFT), has been considered, which is more suitable to process non-stationary signals such as FM signals and has the capability not only of distinguishing different frequency components of a multi-component signal but also separating them in a proper domain, different than the traditional time or frequency domain. The discrete-time FRFT (DFRFT) developed along with its derivatives, such as Multi-angle-DFRFT (MA-DFRFT), Slanted Spectrum and Spectrogram Based on Slanted Spectrum (SBSS) are tools belonging to the same FRFT family, and they could provide an effective approach to identify unknown signals and distinguish the different frequency components contained therein. Both artificial stationary and FM signals have been researched using the DFRFT and some derivative tools from the same family. Moreover, to accomplish a contrast with the traditional tools such as FFT and STFT, performance comparisons are shown to support the DFRFT as an effective tool in multi-component chirp signal analysis. The DFRFT taken at the optimum transform order on a single-component FM signal has provided higher degree of signal energy concentration compared to FFT results; and the Slanted Spectrum taken along the slant line obtained from the MA-DFRFT demonstration has shown much better discrimination between different frequency components of a multi-component FM signal. As a practical application of these tools, the motor current signal has been analyzed using the DFRFT and other tools from FRFT family to detect the presence of a motor bearing fault and obtain the fault signature frequency. The conclusion drawn about the applicability of DFRFT and other derivative tools on AM signals with very slowly varying FM phenomena was not encouraging. Tools from the FRFT family appear more effective on FM signals, whereas AM signals are more effectively analyzed using traditional methods like spectrogram or its derivatives. Such methods are able to identify the signature frequency of faults while using less computational time and memory. Advisors/Committee Members: Parlos, Alexander G. (advisor), Ji, Jim (committee member), Kim, Won-jong (committee member).

Subjects/Keywords: Fractional Fourier Transform(FRFT); Discrete Fractional Fourier Transform(DFRFT); MA-DFRFT; Slanted Spectrum; Spectrogram Based on Slanted Spectrum(SBSS); Fault Signature Frequency; FM; AM

…64 III MULTI-COMPONENT FM SIGNAL PROCESSING WITH MA-DFRFT, MA-CDFRFT, SLANTED SPECTRUM AND… …66 A. Introduction to the FM signals................................................. 66 B… …97 F. Spectrogram Based on Slanted Spectrum................................ 103 1… …Comparison between Traditional Spectrogram and Spectrogram Based on Slanted Spectrum… …CDFRFT of a multi-component chirp signal based on [9]. ....................... 82 34… 

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Duan, X. (2012). The Fractional Fourier Transform and Its Application to Fault Signal Analysis. (Masters Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11207

Chicago Manual of Style (16th Edition):

Duan, Xiao. “The Fractional Fourier Transform and Its Application to Fault Signal Analysis.” 2012. Masters Thesis, Texas A&M University. Accessed October 21, 2020. http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11207.

MLA Handbook (7th Edition):

Duan, Xiao. “The Fractional Fourier Transform and Its Application to Fault Signal Analysis.” 2012. Web. 21 Oct 2020.

Vancouver:

Duan X. The Fractional Fourier Transform and Its Application to Fault Signal Analysis. [Internet] [Masters thesis]. Texas A&M University; 2012. [cited 2020 Oct 21]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11207.

Council of Science Editors:

Duan X. The Fractional Fourier Transform and Its Application to Fault Signal Analysis. [Masters Thesis]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11207

.