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You searched for subject:(velocity time history). Showing records 1 – 2 of 2 total matches.

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Brigham Young University

1. Olsen, Peter A. Shear Modulus Degradation of Liquefying Sand: Quantification and Modeling.

Degree: MS, 2007, Brigham Young University

A major concern for geotechnical engineers is the ability to predict how a soil will react to large ground motions produced by earthquakes. Of all the different types of soil, liquefiable soils present some of the greatest challenges. The ability to quantify the degradation of a soil's shear modulus as it undergoes liquefaction would help engineers design more reliably and economically. This thesis uses ground motions recorded by an array of downhole accelerometers on Port Island, Japan, during the 1995 Kobe Earthquake, to quantify the shear modulus of sand as it liquefies. It has been shown that the shear modulus of sand decreases significantly as it liquefies, apparently decreasing in proportion to the increasing excess pore water pressure ratio (Ru). When completely liquefied, the shear modulus of sand (Ru = 1.0) for a relative density of 40 to 50% is approximately 15% of the high-strain modulus of the sand in its non-liquefied state, or 1% of its initial low-strain value. Presented in this thesis is an approach to modeling the shear modulus degradation of sand as it liquefies. This approach, called the "degrading shear modulus backbone curve method" reasonably predicts the hysteretic shear stress behavior of the liquefied sand. The shear stresses and ground accelerations computed using this method reasonably matches those recorded at the Port Island Downhole Array (PIDA) site. The degrading shear modulus backbone method is recommended as a possible method for conducting ground response analyses at sites with potentially liquefiable soils.

Subjects/Keywords: geotechnical engineering; geotechnical; earthquake; earthquake engineering; liquefaction; liquefying sand; shear modulus; modeling; earthquake modeling; shear modulus degradation; acceleration time history; velocity time history; displacement time history; ground motions; liquefiable soils; backbone curve; Port Island Downhole Array; 1995 Kobe earthquake; excess pore pressure ratio; response spectrum; equivalent linear method; nonlinear method; stress-strain loop; hysteretic loop; NERA; Civil and Environmental Engineering

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

APA (6th Edition):

Olsen, P. A. (2007). Shear Modulus Degradation of Liquefying Sand: Quantification and Modeling. (Masters Thesis). Brigham Young University. Retrieved from https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=2213&context=etd

Chicago Manual of Style (16th Edition):

Olsen, Peter A. “Shear Modulus Degradation of Liquefying Sand: Quantification and Modeling.” 2007. Masters Thesis, Brigham Young University. Accessed December 09, 2019. https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=2213&context=etd.

MLA Handbook (7th Edition):

Olsen, Peter A. “Shear Modulus Degradation of Liquefying Sand: Quantification and Modeling.” 2007. Web. 09 Dec 2019.

Vancouver:

Olsen PA. Shear Modulus Degradation of Liquefying Sand: Quantification and Modeling. [Internet] [Masters thesis]. Brigham Young University; 2007. [cited 2019 Dec 09]. Available from: https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=2213&context=etd.

Council of Science Editors:

Olsen PA. Shear Modulus Degradation of Liquefying Sand: Quantification and Modeling. [Masters Thesis]. Brigham Young University; 2007. Available from: https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=2213&context=etd


Linköping University

2. Vestin, Albin. Evaluation of Target Tracking Using Multiple Sensors and Non-Causal Algorithms.

Degree: Automatic Control, 2019, Linköping University

Today, the main research field for the automotive industry is to find solutions for active safety. In order to perceive the surrounding environment, tracking nearby traffic objects plays an important role. Validation of the tracking performance is often done in staged traffic scenarios, where additional sensors, mounted on the vehicles, are used to obtain their true positions and velocities. The difficulty of evaluating the tracking performance complicates its development. An alternative approach studied in this thesis, is to record sequences and use non-causal algorithms, such as smoothing, instead of filtering to estimate the true target states. With this method, validation data for online, causal, target tracking algorithms can be obtained for all traffic scenarios without the need of extra sensors. We investigate how non-causal algorithms affects the target tracking performance using multiple sensors and dynamic models of different complexity. This is done to evaluate real-time methods against estimates obtained from non-causal filtering. Two different measurement units, a monocular camera and a LIDAR sensor, and two dynamic models are evaluated and compared using both causal and non-causal methods. The system is tested in two single object scenarios where ground truth is available and in three multi object scenarios without ground truth. Results from the two single object scenarios shows that tracking using only a monocular camera performs poorly since it is unable to measure the distance to objects. Here, a complementary LIDAR sensor improves the tracking performance significantly. The dynamic models are shown to have a small impact on the tracking performance, while the non-causal application gives a distinct improvement when tracking objects at large distances. Since the sequence can be reversed, the non-causal estimates are propagated from more certain states when the target is closer to the ego vehicle. For multiple object tracking, we find that correct associations between measurements and tracks are crucial for improving the tracking performance with non-causal algorithms.

Subjects/Keywords: evaluation; target tracking; multiple sensors; non-causal; smoother; smoothing; tracking; vehicle tracking; camera; lidar; estimate; estimation; prediction; vehicle dynamics; sensor fusion; real-time tracking; extended kalman filter; filter validation; validation; position estimation; velocity estimation; dynamic model; model complexity; multi object tracking; multiple object; tracking; single object tracking; data association; tracking fundamentals; iterated kalman filter; track management; gnn; global nearest neighbour; mahalanobis; mahalanobis distance; performance evaluation; differential gps; dgps; roi; ego; several sensors; sensors; rmse; root mean square error; invertible motion; anti-causal motion; anti-causal tracking; constant velocity; gnn; imu; tfs; two filter smoother; ekf; rts; radar; inertial measurement unit; nonlinear; nonlinear systems; mono camera; monocular camera; noise model; tracking performance; fixed interval smoothing; m/n logic; centralized fusion; non-causal object tracker; car tracking; car dynamics; automotive; active safety; object tracking; automotive industry; thesis; master; reverse dynamics; reverse tracking; reverse sequence; sequence tracking; data propagation; ground truth; estimating ground truth; additional sensors; mounted sensors; true estimates; environment; comparison; algorithm; independent targets; overlapping; measurements; occluded; track switch; improve; lower; uncertainty; more; certain; state; process; noise; covariance; sampling; image; sprt; adas; cnn; cv; pdf; track; target; ego; tracker; tentative track; observatiom; online tracking; offline tracking; online; offline; recorded; sequences; robust; self driving; self-driving; car; traffic; trajectory; true state; scenario; scenarios; future; accurate; output; advanced; driver; assistance; systems; non-linear; complex noise; pedestrian; truck; bus; maneuvering; vehicles; processed; measurement; frame; state; correction; probability; density; function; tuning; likelihood; transition; measurement; motion; model; recursion; gaussian; approximation; distribution; linear; jacobian; multiplicative; noise; ratio; ad; hoc; ad hoc; state; space; approach; backward; auction; euclidean; distance; statistical; threshold; gating; association; margin; normalize; covariance; matrix; fusion; confirmed; rejected; tentative; history; absolute; error; modular; ego motion; parameters; variables; logg; hardware; specification; fused; causal; factorization; independent; uncorrelated; transform; moving; rotation; translation; oncoming; overtaking; Control Engineering; Reglerteknik

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

APA (6th Edition):

Vestin, A. (2019). Evaluation of Target Tracking Using Multiple Sensors and Non-Causal Algorithms. (Thesis). Linköping University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-160020

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):

Vestin, Albin. “Evaluation of Target Tracking Using Multiple Sensors and Non-Causal Algorithms.” 2019. Thesis, Linköping University. Accessed December 09, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-160020.

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

MLA Handbook (7th Edition):

Vestin, Albin. “Evaluation of Target Tracking Using Multiple Sensors and Non-Causal Algorithms.” 2019. Web. 09 Dec 2019.

Vancouver:

Vestin A. Evaluation of Target Tracking Using Multiple Sensors and Non-Causal Algorithms. [Internet] [Thesis]. Linköping University; 2019. [cited 2019 Dec 09]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-160020.

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

Council of Science Editors:

Vestin A. Evaluation of Target Tracking Using Multiple Sensors and Non-Causal Algorithms. [Thesis]. Linköping University; 2019. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-160020

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

.