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Virginia Tech

1. D'Augustine, Anthony Frank. MATLODE: A MATLAB ODE Solver and Sensitivity Analysis Toolbox.

Degree: MS, Computer Science and Applications, 2018, Virginia Tech

URL: http://hdl.handle.net/10919/83081

► Sensitivity analysis quantifies the effect that of perturbations of the model inputs have on the model's outputs. Some of the key insights gained using sensitivity…
(more)

Subjects/Keywords: ODE Solver; Tangent Linear Model; Adjoint Model; Sensitivity Analysis; Software

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APA (6^{th} Edition):

D'Augustine, A. F. (2018). MATLODE: A MATLAB ODE Solver and Sensitivity Analysis Toolbox. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/83081

Chicago Manual of Style (16^{th} Edition):

D'Augustine, Anthony Frank. “MATLODE: A MATLAB ODE Solver and Sensitivity Analysis Toolbox.” 2018. Masters Thesis, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/83081.

MLA Handbook (7^{th} Edition):

D'Augustine, Anthony Frank. “MATLODE: A MATLAB ODE Solver and Sensitivity Analysis Toolbox.” 2018. Web. 04 Mar 2021.

Vancouver:

D'Augustine AF. MATLODE: A MATLAB ODE Solver and Sensitivity Analysis Toolbox. [Internet] [Masters thesis]. Virginia Tech; 2018. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/83081.

Council of Science Editors:

D'Augustine AF. MATLODE: A MATLAB ODE Solver and Sensitivity Analysis Toolbox. [Masters Thesis]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/83081

Virginia Tech

2. Radcliffe, Nicholas Ryan. Adjusting Process Count on Demand for Petascale Global Optimization.

Degree: MS, Computer Science, 2011, Virginia Tech

URL: http://hdl.handle.net/10919/36349

► There are many challenges that need to be met before efficient and reliable computation at the petascale is possible. Many scientific and engineering codes running…
(more)

Subjects/Keywords: Petascale computing; Global optimization; Message Passing Interface (MPI); Dynamic process count

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APA (6^{th} Edition):

Radcliffe, N. R. (2011). Adjusting Process Count on Demand for Petascale Global Optimization. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/36349

Chicago Manual of Style (16^{th} Edition):

Radcliffe, Nicholas Ryan. “Adjusting Process Count on Demand for Petascale Global Optimization.” 2011. Masters Thesis, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/36349.

MLA Handbook (7^{th} Edition):

Radcliffe, Nicholas Ryan. “Adjusting Process Count on Demand for Petascale Global Optimization.” 2011. Web. 04 Mar 2021.

Vancouver:

Radcliffe NR. Adjusting Process Count on Demand for Petascale Global Optimization. [Internet] [Masters thesis]. Virginia Tech; 2011. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/36349.

Council of Science Editors:

Radcliffe NR. Adjusting Process Count on Demand for Petascale Global Optimization. [Masters Thesis]. Virginia Tech; 2011. Available from: http://hdl.handle.net/10919/36349

Virginia Tech

3. Martinez Arroyo, Gabriel Ernesto. Cu2cl: a Cuda-To-Opencl Translator for Multi- and Many-Core Architectures.

Degree: MS, Computer Science and Applications, 2011, Virginia Tech

URL: http://hdl.handle.net/10919/34233

► The use of graphics processing units (GPUs) in high-performance parallel computing continues to steadily become more prevalent, often as part of a heterogeneous system. For…
(more)

Subjects/Keywords: GPU; Compilers; CUDA; OpenCL; Source Translation; Clang

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APA (6^{th} Edition):

Martinez Arroyo, G. E. (2011). Cu2cl: a Cuda-To-Opencl Translator for Multi- and Many-Core Architectures. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/34233

Chicago Manual of Style (16^{th} Edition):

Martinez Arroyo, Gabriel Ernesto. “Cu2cl: a Cuda-To-Opencl Translator for Multi- and Many-Core Architectures.” 2011. Masters Thesis, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/34233.

MLA Handbook (7^{th} Edition):

Martinez Arroyo, Gabriel Ernesto. “Cu2cl: a Cuda-To-Opencl Translator for Multi- and Many-Core Architectures.” 2011. Web. 04 Mar 2021.

Vancouver:

Martinez Arroyo GE. Cu2cl: a Cuda-To-Opencl Translator for Multi- and Many-Core Architectures. [Internet] [Masters thesis]. Virginia Tech; 2011. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/34233.

Council of Science Editors:

Martinez Arroyo GE. Cu2cl: a Cuda-To-Opencl Translator for Multi- and Many-Core Architectures. [Masters Thesis]. Virginia Tech; 2011. Available from: http://hdl.handle.net/10919/34233

Virginia Tech

4. Gao, Guangyue. A Stochastic Model for The Transmission Dynamics of Toxoplasma Gondii.

Degree: MS, Computer Science, 2016, Virginia Tech

URL: http://hdl.handle.net/10919/78106

► Toxoplasma gondii (T. gondii) is an intracellular protozoan parasite. The parasite can infect all warm-blooded vertebrates. Up to 30% of the world's human population carry…
(more)

Subjects/Keywords: Gillespie Algorithm; Toxoplasma Gondii; Finite Difference Method; Transmission Dynamics; Compartment-Based Model; Stochastic Simulation

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APA (6^{th} Edition):

Gao, G. (2016). A Stochastic Model for The Transmission Dynamics of Toxoplasma Gondii. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/78106

Chicago Manual of Style (16^{th} Edition):

Gao, Guangyue. “A Stochastic Model for The Transmission Dynamics of Toxoplasma Gondii.” 2016. Masters Thesis, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/78106.

MLA Handbook (7^{th} Edition):

Gao, Guangyue. “A Stochastic Model for The Transmission Dynamics of Toxoplasma Gondii.” 2016. Web. 04 Mar 2021.

Vancouver:

Gao G. A Stochastic Model for The Transmission Dynamics of Toxoplasma Gondii. [Internet] [Masters thesis]. Virginia Tech; 2016. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/78106.

Council of Science Editors:

Gao G. A Stochastic Model for The Transmission Dynamics of Toxoplasma Gondii. [Masters Thesis]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/78106

Virginia Tech

5. Anandakrishnan, Ramamoorthi. Speeding up electrostatic computations for molecular dynamics.

Degree: PhD, Computer Science and Applications, 2011, Virginia Tech

URL: http://hdl.handle.net/10919/40262

► Molecular dynamics (MD) simulations are routinely used to study the structure and function of biological molecules. However the accuracy and duration of these simulations are…
(more)

Subjects/Keywords: statistical mechanics; biomolecular electrostatics; molecular dynamics

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APA (6^{th} Edition):

Anandakrishnan, R. (2011). Speeding up electrostatic computations for molecular dynamics. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/40262

Chicago Manual of Style (16^{th} Edition):

Anandakrishnan, Ramamoorthi. “Speeding up electrostatic computations for molecular dynamics.” 2011. Doctoral Dissertation, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/40262.

MLA Handbook (7^{th} Edition):

Anandakrishnan, Ramamoorthi. “Speeding up electrostatic computations for molecular dynamics.” 2011. Web. 04 Mar 2021.

Vancouver:

Anandakrishnan R. Speeding up electrostatic computations for molecular dynamics. [Internet] [Doctoral dissertation]. Virginia Tech; 2011. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/40262.

Council of Science Editors:

Anandakrishnan R. Speeding up electrostatic computations for molecular dynamics. [Doctoral Dissertation]. Virginia Tech; 2011. Available from: http://hdl.handle.net/10919/40262

Virginia Tech

6. Aguilar Huacan, Boris Abner. Improving of the accuracy and efficiency of implicit solvent models in Biomolecular Modeling.

Degree: PhD, Computer Science and Applications, 2014, Virginia Tech

URL: http://hdl.handle.net/10919/64409

► Biomolecular Modeling is playing an important role in many practical applications such as biotechnology and structure-based drug design. One of the essential requirements of Biomolecular…
(more)

Subjects/Keywords: Molecular Modeling; Implicit solvents; Generalized Born Model

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APA (6^{th} Edition):

Aguilar Huacan, B. A. (2014). Improving of the accuracy and efficiency of implicit solvent models in Biomolecular Modeling. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/64409

Chicago Manual of Style (16^{th} Edition):

Aguilar Huacan, Boris Abner. “Improving of the accuracy and efficiency of implicit solvent models in Biomolecular Modeling.” 2014. Doctoral Dissertation, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/64409.

MLA Handbook (7^{th} Edition):

Aguilar Huacan, Boris Abner. “Improving of the accuracy and efficiency of implicit solvent models in Biomolecular Modeling.” 2014. Web. 04 Mar 2021.

Vancouver:

Aguilar Huacan BA. Improving of the accuracy and efficiency of implicit solvent models in Biomolecular Modeling. [Internet] [Doctoral dissertation]. Virginia Tech; 2014. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/64409.

Council of Science Editors:

Aguilar Huacan BA. Improving of the accuracy and efficiency of implicit solvent models in Biomolecular Modeling. [Doctoral Dissertation]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/64409

Virginia Tech

7. Chen, Minghan. Stochastic Modeling and Simulation of Multiscale Biochemical Systems.

Degree: PhD, Computer Science and Applications, 2019, Virginia Tech

URL: http://hdl.handle.net/10919/90898

► Modeling and simulation of biochemical networks faces numerous challenges as biochemical networks are discovered with increased complexity and unknown mechanisms. With improvement in experimental techniques,…
(more)

Subjects/Keywords: Caulobacter cell cycle model; hybrid stochastic simulation algorithm; stochastic parameter optimization

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APA (6^{th} Edition):

Chen, M. (2019). Stochastic Modeling and Simulation of Multiscale Biochemical Systems. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/90898

Chicago Manual of Style (16^{th} Edition):

Chen, Minghan. “Stochastic Modeling and Simulation of Multiscale Biochemical Systems.” 2019. Doctoral Dissertation, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/90898.

MLA Handbook (7^{th} Edition):

Chen, Minghan. “Stochastic Modeling and Simulation of Multiscale Biochemical Systems.” 2019. Web. 04 Mar 2021.

Vancouver:

Chen M. Stochastic Modeling and Simulation of Multiscale Biochemical Systems. [Internet] [Doctoral dissertation]. Virginia Tech; 2019. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/90898.

Council of Science Editors:

Chen M. Stochastic Modeling and Simulation of Multiscale Biochemical Systems. [Doctoral Dissertation]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/90898

8. Attia, Ahmed Mohamed Mohamed. Advanced Sampling Methods for Solving Large-Scale Inverse Problems.

Degree: PhD, Computer Science and Applications, 2016, Virginia Tech

URL: http://hdl.handle.net/10919/73683

► Ensemble and variational techniques have gained wide popularity as the two main approaches for solving data assimilation and inverse problems. The majority of the methods…
(more)

Subjects/Keywords: Data Assimilation; Inverse Problems; Uncertainty Quantification; Hamiltonian Monte-Carlo; Cluster Sampling Filters; High Performance Computing.

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APA (6^{th} Edition):

Attia, A. M. M. (2016). Advanced Sampling Methods for Solving Large-Scale Inverse Problems. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/73683

Chicago Manual of Style (16^{th} Edition):

Attia, Ahmed Mohamed Mohamed. “Advanced Sampling Methods for Solving Large-Scale Inverse Problems.” 2016. Doctoral Dissertation, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/73683.

MLA Handbook (7^{th} Edition):

Attia, Ahmed Mohamed Mohamed. “Advanced Sampling Methods for Solving Large-Scale Inverse Problems.” 2016. Web. 04 Mar 2021.

Vancouver:

Attia AMM. Advanced Sampling Methods for Solving Large-Scale Inverse Problems. [Internet] [Doctoral dissertation]. Virginia Tech; 2016. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/73683.

Council of Science Editors:

Attia AMM. Advanced Sampling Methods for Solving Large-Scale Inverse Problems. [Doctoral Dissertation]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/73683

Virginia Tech

9. Cioaca, Alexandru George. A Computational Framework for Assessing and Optimizing the Performance of Observational Networks in 4D-Var Data Assimilation.

Degree: PhD, Computer Science and Applications, 2013, Virginia Tech

URL: http://hdl.handle.net/10919/51795

► A deep scientific understanding of complex physical systems, such as the atmosphere, can be achieved neither by direct measurements nor by numerical simulations alone. Data…
(more)

Subjects/Keywords: data assimilation; dynamic data-driven problem; second-order adjoints; adaptive observations; sensor placement; intelligent sensors; sensitivity analysis; uncertainty quantification; nonlinear optimization; inverse problems; parameter estimation; matrix-free linear solvers; truncated singular value decomposition

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APA (6^{th} Edition):

Cioaca, A. G. (2013). A Computational Framework for Assessing and Optimizing the Performance of Observational Networks in 4D-Var Data Assimilation. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/51795

Chicago Manual of Style (16^{th} Edition):

Cioaca, Alexandru George. “A Computational Framework for Assessing and Optimizing the Performance of Observational Networks in 4D-Var Data Assimilation.” 2013. Doctoral Dissertation, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/51795.

MLA Handbook (7^{th} Edition):

Cioaca, Alexandru George. “A Computational Framework for Assessing and Optimizing the Performance of Observational Networks in 4D-Var Data Assimilation.” 2013. Web. 04 Mar 2021.

Vancouver:

Cioaca AG. A Computational Framework for Assessing and Optimizing the Performance of Observational Networks in 4D-Var Data Assimilation. [Internet] [Doctoral dissertation]. Virginia Tech; 2013. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/51795.

Council of Science Editors:

Cioaca AG. A Computational Framework for Assessing and Optimizing the Performance of Observational Networks in 4D-Var Data Assimilation. [Doctoral Dissertation]. Virginia Tech; 2013. Available from: http://hdl.handle.net/10919/51795

Virginia Tech

10. Liu, Zhen. Stochastic Simulation Methods for Biochemical Systems with Multi-state and Multi-scale Features.

Degree: PhD, Computer Science and Applications, 2012, Virginia Tech

URL: http://hdl.handle.net/10919/19191

► In this thesis we study stochastic modeling and simulation methods for biochemical systems. The thesis is focused on systems with multi-state and multi-scale features and…
(more)

Subjects/Keywords: SSA; Stochsim; rule-based modeling; QSSA; hybrid method

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APA (6^{th} Edition):

Liu, Z. (2012). Stochastic Simulation Methods for Biochemical Systems with Multi-state and Multi-scale Features. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/19191

Chicago Manual of Style (16^{th} Edition):

Liu, Zhen. “Stochastic Simulation Methods for Biochemical Systems with Multi-state and Multi-scale Features.” 2012. Doctoral Dissertation, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/19191.

MLA Handbook (7^{th} Edition):

Liu, Zhen. “Stochastic Simulation Methods for Biochemical Systems with Multi-state and Multi-scale Features.” 2012. Web. 04 Mar 2021.

Vancouver:

Liu Z. Stochastic Simulation Methods for Biochemical Systems with Multi-state and Multi-scale Features. [Internet] [Doctoral dissertation]. Virginia Tech; 2012. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/19191.

Council of Science Editors:

Liu Z. Stochastic Simulation Methods for Biochemical Systems with Multi-state and Multi-scale Features. [Doctoral Dissertation]. Virginia Tech; 2012. Available from: http://hdl.handle.net/10919/19191

Virginia Tech

11. Glandon Jr, Steven Ross. Time Integration Methods for Large-scale Scientific Simulations.

Degree: PhD, Computer Science and Applications, 2020, Virginia Tech

URL: http://hdl.handle.net/10919/99160

► Differential equations are a fundamental building block of the mathematical description of many physical phenomena. Thus, solving problems involving complex differential equations is necessary for…
(more)

Subjects/Keywords: ODEs; PDEs; time integration

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APA (6^{th} Edition):

Glandon Jr, S. R. (2020). Time Integration Methods for Large-scale Scientific Simulations. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/99160

Chicago Manual of Style (16^{th} Edition):

Glandon Jr, Steven Ross. “Time Integration Methods for Large-scale Scientific Simulations.” 2020. Doctoral Dissertation, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/99160.

MLA Handbook (7^{th} Edition):

Glandon Jr, Steven Ross. “Time Integration Methods for Large-scale Scientific Simulations.” 2020. Web. 04 Mar 2021.

Vancouver:

Glandon Jr SR. Time Integration Methods for Large-scale Scientific Simulations. [Internet] [Doctoral dissertation]. Virginia Tech; 2020. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/99160.

Council of Science Editors:

Glandon Jr SR. Time Integration Methods for Large-scale Scientific Simulations. [Doctoral Dissertation]. Virginia Tech; 2020. Available from: http://hdl.handle.net/10919/99160

Virginia Tech

12. Tranquilli, Paul J. Lightly-Implicit Methods for the Time Integration of Large Applications.

Degree: PhD, Computer Science and Applications, 2016, Virginia Tech

URL: http://hdl.handle.net/10919/81974

► Many scientific and engineering applications require the solution of large systems of initial value problems arising from method of lines discretization of partial differential equations.…
(more)

Subjects/Keywords: Time Integration; Numerical PDEs; Numerical ODEs

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APA (6^{th} Edition):

Tranquilli, P. J. (2016). Lightly-Implicit Methods for the Time Integration of Large Applications. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/81974

Chicago Manual of Style (16^{th} Edition):

Tranquilli, Paul J. “Lightly-Implicit Methods for the Time Integration of Large Applications.” 2016. Doctoral Dissertation, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/81974.

MLA Handbook (7^{th} Edition):

Tranquilli, Paul J. “Lightly-Implicit Methods for the Time Integration of Large Applications.” 2016. Web. 04 Mar 2021.

Vancouver:

Tranquilli PJ. Lightly-Implicit Methods for the Time Integration of Large Applications. [Internet] [Doctoral dissertation]. Virginia Tech; 2016. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/81974.

Council of Science Editors:

Tranquilli PJ. Lightly-Implicit Methods for the Time Integration of Large Applications. [Doctoral Dissertation]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/81974

Virginia Tech

13. Ahn, Tae-Hyuk. Computational Techniques for the Analysis of Large Scale Biological Systems.

Degree: PhD, Computer Science, 2016, Virginia Tech

URL: http://hdl.handle.net/10919/77162

► An accelerated pace of discovery in biological sciences is made possible by a new generation of computational biology and bioinformatics tools. In this dissertation we…
(more)

Subjects/Keywords: Stochastic simulation algorithm (SSA); Parallel load balancing; Cell cycle; RNA-Sequencing; Stochastic differential equations (SDEs)

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APA (6^{th} Edition):

Ahn, T. (2016). Computational Techniques for the Analysis of Large Scale Biological Systems. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/77162

Chicago Manual of Style (16^{th} Edition):

Ahn, Tae-Hyuk. “Computational Techniques for the Analysis of Large Scale Biological Systems.” 2016. Doctoral Dissertation, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/77162.

MLA Handbook (7^{th} Edition):

Ahn, Tae-Hyuk. “Computational Techniques for the Analysis of Large Scale Biological Systems.” 2016. Web. 04 Mar 2021.

Vancouver:

Ahn T. Computational Techniques for the Analysis of Large Scale Biological Systems. [Internet] [Doctoral dissertation]. Virginia Tech; 2016. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/77162.

Council of Science Editors:

Ahn T. Computational Techniques for the Analysis of Large Scale Biological Systems. [Doctoral Dissertation]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/77162

Virginia Tech

14. Zhao, Junbo. A Robust Dynamic State and Parameter Estimation Framework for Smart Grid Monitoring and Control.

Degree: PhD, Electrical Engineering, 2018, Virginia Tech

URL: http://hdl.handle.net/10919/83423

► The enhancement of the reliability, security, and resiliency of electric power systems depends on the availability of fast, accurate, and robust dynamic state estimators. These…
(more)

Subjects/Keywords: Kalman filter; Robust statistics; Power system state estimation; Dynamic state estimation; Unscented transformation; Robust control theory; Estimation theory; Power system dynamics and control; Outliers; Cyber attacks; Phasor measurement units

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APA (6^{th} Edition):

Zhao, J. (2018). A Robust Dynamic State and Parameter Estimation Framework for Smart Grid Monitoring and Control. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/83423

Chicago Manual of Style (16^{th} Edition):

Zhao, Junbo. “A Robust Dynamic State and Parameter Estimation Framework for Smart Grid Monitoring and Control.” 2018. Doctoral Dissertation, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/83423.

MLA Handbook (7^{th} Edition):

Zhao, Junbo. “A Robust Dynamic State and Parameter Estimation Framework for Smart Grid Monitoring and Control.” 2018. Web. 04 Mar 2021.

Vancouver:

Zhao J. A Robust Dynamic State and Parameter Estimation Framework for Smart Grid Monitoring and Control. [Internet] [Doctoral dissertation]. Virginia Tech; 2018. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/83423.

Council of Science Editors:

Zhao J. A Robust Dynamic State and Parameter Estimation Framework for Smart Grid Monitoring and Control. [Doctoral Dissertation]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/83423

Virginia Tech

15. Hays, Joseph T. Parametric Optimal Design Of Uncertain Dynamical Systems.

Degree: PhD, Mechanical Engineering, 2011, Virginia Tech

URL: http://hdl.handle.net/10919/28850

► This research effort develops a comprehensive computational framework to support the parametric optimal design of uncertain dynamical systems. Uncertainty comes from various sources, such as:…
(more)

Subjects/Keywords: Ordinary Differential Equations (ODEs); Trajectory Planning; Motion Planning; Generalized Polynomial Chaos (gPC); Uncertainty Quantification; Multi-Objective Optimization (MOO); Nonlinear Programming (NLP); Dynamic Optimization; Optimal Control; Robust Design Optimization (RDO); Collocation; Uncertainty Apportionment; Tolerance Allocation; Multibody Dynamics; Differential Algebraic Equations (DAEs)

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APA (6^{th} Edition):

Hays, J. T. (2011). Parametric Optimal Design Of Uncertain Dynamical Systems. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/28850

Chicago Manual of Style (16^{th} Edition):

Hays, Joseph T. “Parametric Optimal Design Of Uncertain Dynamical Systems.” 2011. Doctoral Dissertation, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/28850.

MLA Handbook (7^{th} Edition):

Hays, Joseph T. “Parametric Optimal Design Of Uncertain Dynamical Systems.” 2011. Web. 04 Mar 2021.

Vancouver:

Hays JT. Parametric Optimal Design Of Uncertain Dynamical Systems. [Internet] [Doctoral dissertation]. Virginia Tech; 2011. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/28850.

Council of Science Editors:

Hays JT. Parametric Optimal Design Of Uncertain Dynamical Systems. [Doctoral Dissertation]. Virginia Tech; 2011. Available from: http://hdl.handle.net/10919/28850

Virginia Tech

16. Umsrithong, Anake. Deterministic and Stochastic Semi-Empirical Transient Tire Models.

Degree: PhD, Mechanical Engineering, 2012, Virginia Tech

URL: http://hdl.handle.net/10919/26270

► The tire is one of the most important components of the vehicle. It has many functions, such as supporting the load of the vehicle, transmitting…
(more)

Subjects/Keywords: tire model; uncertainties; vehicle dynamics

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APA (6^{th} Edition):

Umsrithong, A. (2012). Deterministic and Stochastic Semi-Empirical Transient Tire Models. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/26270

Chicago Manual of Style (16^{th} Edition):

Umsrithong, Anake. “Deterministic and Stochastic Semi-Empirical Transient Tire Models.” 2012. Doctoral Dissertation, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/26270.

MLA Handbook (7^{th} Edition):

Umsrithong, Anake. “Deterministic and Stochastic Semi-Empirical Transient Tire Models.” 2012. Web. 04 Mar 2021.

Vancouver:

Umsrithong A. Deterministic and Stochastic Semi-Empirical Transient Tire Models. [Internet] [Doctoral dissertation]. Virginia Tech; 2012. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/26270.

Council of Science Editors:

Umsrithong A. Deterministic and Stochastic Semi-Empirical Transient Tire Models. [Doctoral Dissertation]. Virginia Tech; 2012. Available from: http://hdl.handle.net/10919/26270

Virginia Tech

17. Nino Ruiz, Elias David. Efficient formulation and implementation of ensemble based methods in data assimilation.

Degree: PhD, Computer Science and Applications, 2016, Virginia Tech

URL: http://hdl.handle.net/10919/64438

► Ensemble-based methods have gained widespread popularity in the field of data assimilation. An ensemble of model realizations encapsulates information about the error correlations driven by…
(more)

Subjects/Keywords: Ensemble-based methods; ensemble Kalman filter; ensemble square root filter; hybrid data assimilation; background error covariance matrix estimation; parallel data assimilation

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APA (6^{th} Edition):

Nino Ruiz, E. D. (2016). Efficient formulation and implementation of ensemble based methods in data assimilation. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/64438

Chicago Manual of Style (16^{th} Edition):

Nino Ruiz, Elias David. “Efficient formulation and implementation of ensemble based methods in data assimilation.” 2016. Doctoral Dissertation, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/64438.

MLA Handbook (7^{th} Edition):

Nino Ruiz, Elias David. “Efficient formulation and implementation of ensemble based methods in data assimilation.” 2016. Web. 04 Mar 2021.

Vancouver:

Nino Ruiz ED. Efficient formulation and implementation of ensemble based methods in data assimilation. [Internet] [Doctoral dissertation]. Virginia Tech; 2016. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/64438.

Council of Science Editors:

Nino Ruiz ED. Efficient formulation and implementation of ensemble based methods in data assimilation. [Doctoral Dissertation]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/64438

Virginia Tech

18. Xu, Yijun. Uncertainty Quantification, State and Parameter Estimation in Power Systems Using Polynomial Chaos Based Methods.

Degree: PhD, Electrical Engineering, 2019, Virginia Tech

URL: http://hdl.handle.net/10919/97876

► It is a well-known fact that a power system contains many sources of uncertainties. These uncertainties coming from the loads, the renewables, the model and…
(more)

Subjects/Keywords: Uncertainty Quantification; Dynamic State Estimation; Generalized Polynomial Chaos; Multi-Element Polynomial Chaos; ANOVA; Polynomial-Chaos-Based Kalman Filter; Response Surface; Bayesian Inference; Markov Chain Monte Carlo.

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

APA (6^{th} Edition):

Xu, Y. (2019). Uncertainty Quantification, State and Parameter Estimation in Power Systems Using Polynomial Chaos Based Methods. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/97876

Chicago Manual of Style (16^{th} Edition):

Xu, Yijun. “Uncertainty Quantification, State and Parameter Estimation in Power Systems Using Polynomial Chaos Based Methods.” 2019. Doctoral Dissertation, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/97876.

MLA Handbook (7^{th} Edition):

Xu, Yijun. “Uncertainty Quantification, State and Parameter Estimation in Power Systems Using Polynomial Chaos Based Methods.” 2019. Web. 04 Mar 2021.

Vancouver:

Xu Y. Uncertainty Quantification, State and Parameter Estimation in Power Systems Using Polynomial Chaos Based Methods. [Internet] [Doctoral dissertation]. Virginia Tech; 2019. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/97876.

Council of Science Editors:

Xu Y. Uncertainty Quantification, State and Parameter Estimation in Power Systems Using Polynomial Chaos Based Methods. [Doctoral Dissertation]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/97876

Virginia Tech

19. Hebbur Venkata Subba Rao, Vishwas. Adjoint based solution and uncertainty quantification techniques for variational inverse problems.

Degree: PhD, Computer Science and Applications, 2015, Virginia Tech

URL: http://hdl.handle.net/10919/76665

► Variational inverse problems integrate computational simulations of physical phenomena with physical measurements in an informational feedback control system. Control parameters of the computational model are…
(more)

Subjects/Keywords: Data assimilation; Inverse problems; sensitivity analysis

Record Details Similar Records

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

APA (6^{th} Edition):

Hebbur Venkata Subba Rao, V. (2015). Adjoint based solution and uncertainty quantification techniques for variational inverse problems. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/76665

Chicago Manual of Style (16^{th} Edition):

Hebbur Venkata Subba Rao, Vishwas. “Adjoint based solution and uncertainty quantification techniques for variational inverse problems.” 2015. Doctoral Dissertation, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/76665.

MLA Handbook (7^{th} Edition):

Hebbur Venkata Subba Rao, Vishwas. “Adjoint based solution and uncertainty quantification techniques for variational inverse problems.” 2015. Web. 04 Mar 2021.

Vancouver:

Hebbur Venkata Subba Rao V. Adjoint based solution and uncertainty quantification techniques for variational inverse problems. [Internet] [Doctoral dissertation]. Virginia Tech; 2015. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/76665.

Council of Science Editors:

Hebbur Venkata Subba Rao V. Adjoint based solution and uncertainty quantification techniques for variational inverse problems. [Doctoral Dissertation]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/76665

Virginia Tech

20. Zavar Moosavi, Azam Sadat. Probabilistic and Statistical Learning Models for Error Modeling and Uncertainty Quantification.

Degree: PhD, Computer Science and Applications, 2018, Virginia Tech

URL: http://hdl.handle.net/10919/82491

► Simulations and modeling of large-scale systems are vital to understanding real world phenomena. However, even advanced numerical models can only approximate the true physics. The…
(more)

Subjects/Keywords: Uncertainty Quantification; Uncertainty Reduction; Stochastic Simulation of Chemical Reactions; Reduced-Order Models; Structural Uncertainty; Data Assimilation; Numerical Weather Prediction Models; Machine Learning

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

APA (6^{th} Edition):

Zavar Moosavi, A. S. (2018). Probabilistic and Statistical Learning Models for Error Modeling and Uncertainty Quantification. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/82491

Chicago Manual of Style (16^{th} Edition):

Zavar Moosavi, Azam Sadat. “Probabilistic and Statistical Learning Models for Error Modeling and Uncertainty Quantification.” 2018. Doctoral Dissertation, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/82491.

MLA Handbook (7^{th} Edition):

Zavar Moosavi, Azam Sadat. “Probabilistic and Statistical Learning Models for Error Modeling and Uncertainty Quantification.” 2018. Web. 04 Mar 2021.

Vancouver:

Zavar Moosavi AS. Probabilistic and Statistical Learning Models for Error Modeling and Uncertainty Quantification. [Internet] [Doctoral dissertation]. Virginia Tech; 2018. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/82491.

Council of Science Editors:

Zavar Moosavi AS. Probabilistic and Statistical Learning Models for Error Modeling and Uncertainty Quantification. [Doctoral Dissertation]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/82491

Virginia Tech

21. Lloyd, John William. Generalized Predictive Control Parameter Adaptation Using a Fuzzy Logic Approach.

Degree: PhD, Mechanical Engineering, 2011, Virginia Tech

URL: http://hdl.handle.net/10919/29306

► A method to adapt the Generalized Predictive Control parameters to improve broadband disturbance rejection was developed and tested. The effect of the parameters on disturbance…
(more)

Subjects/Keywords: GPC; generalized predictive control; active control; adaptive control; fuzzy logic; fuzzy logic adaptation; vibration control; disturbance rejection

Record Details Similar Records

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

APA (6^{th} Edition):

Lloyd, J. W. (2011). Generalized Predictive Control Parameter Adaptation Using a Fuzzy Logic Approach. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/29306

Chicago Manual of Style (16^{th} Edition):

Lloyd, John William. “Generalized Predictive Control Parameter Adaptation Using a Fuzzy Logic Approach.” 2011. Doctoral Dissertation, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/29306.

MLA Handbook (7^{th} Edition):

Lloyd, John William. “Generalized Predictive Control Parameter Adaptation Using a Fuzzy Logic Approach.” 2011. Web. 04 Mar 2021.

Vancouver:

Lloyd JW. Generalized Predictive Control Parameter Adaptation Using a Fuzzy Logic Approach. [Internet] [Doctoral dissertation]. Virginia Tech; 2011. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/29306.

Council of Science Editors:

Lloyd JW. Generalized Predictive Control Parameter Adaptation Using a Fuzzy Logic Approach. [Doctoral Dissertation]. Virginia Tech; 2011. Available from: http://hdl.handle.net/10919/29306

Virginia Tech

22. Zhu, Yitao. Sensitivity Analysis and Optimization of Multibody Systems.

Degree: PhD, Mechanical Engineering, 2015, Virginia Tech

URL: http://hdl.handle.net/10919/71649

► Multibody dynamics simulations are currently widely accepted as valuable means for dynamic performance analysis of mechanical systems. The evolution of theoretical and computational aspects of…
(more)

Subjects/Keywords: Sensitivity Analysis; Optimization; Multibody Dynamics; Vehicle Dynamics

Record Details Similar Records

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

APA (6^{th} Edition):

Zhu, Y. (2015). Sensitivity Analysis and Optimization of Multibody Systems. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/71649

Chicago Manual of Style (16^{th} Edition):

Zhu, Yitao. “Sensitivity Analysis and Optimization of Multibody Systems.” 2015. Doctoral Dissertation, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/71649.

MLA Handbook (7^{th} Edition):

Zhu, Yitao. “Sensitivity Analysis and Optimization of Multibody Systems.” 2015. Web. 04 Mar 2021.

Vancouver:

Zhu Y. Sensitivity Analysis and Optimization of Multibody Systems. [Internet] [Doctoral dissertation]. Virginia Tech; 2015. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/71649.

Council of Science Editors:

Zhu Y. Sensitivity Analysis and Optimization of Multibody Systems. [Doctoral Dissertation]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/71649

Virginia Tech

23. Alexe, Mihai. Adjoint-based space-time adaptive solution algorithms for sensitivity analysis and inverse problems.

Degree: PhD, Computer Science, 2011, Virginia Tech

URL: http://hdl.handle.net/10919/37515

► Adaptivity in both space and time has become the norm for solving problems modeled by partial differential equations. The size of the discretized problem makes…
(more)

Subjects/Keywords: Inverse problems; Adjoint Method; Adaptive Mesh Refinement; Automatic Differentiation

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

APA (6^{th} Edition):

Alexe, M. (2011). Adjoint-based space-time adaptive solution algorithms for sensitivity analysis and inverse problems. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/37515

Chicago Manual of Style (16^{th} Edition):

Alexe, Mihai. “Adjoint-based space-time adaptive solution algorithms for sensitivity analysis and inverse problems.” 2011. Doctoral Dissertation, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/37515.

MLA Handbook (7^{th} Edition):

Alexe, Mihai. “Adjoint-based space-time adaptive solution algorithms for sensitivity analysis and inverse problems.” 2011. Web. 04 Mar 2021.

Vancouver:

Alexe M. Adjoint-based space-time adaptive solution algorithms for sensitivity analysis and inverse problems. [Internet] [Doctoral dissertation]. Virginia Tech; 2011. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/37515.

Council of Science Editors:

Alexe M. Adjoint-based space-time adaptive solution algorithms for sensitivity analysis and inverse problems. [Doctoral Dissertation]. Virginia Tech; 2011. Available from: http://hdl.handle.net/10919/37515

24. Cui, Jing. Visualization of the Budding Yeast Cell Cycle.

Degree: MS, Computer Science and Applications, 2017, Virginia Tech

URL: http://hdl.handle.net/10919/78815

► The cell cycle of budding yeast is controlled by a complex chemically reacting network. Many mathematical models have been proposed to unravel its molecular mechanism.…
(more)

Subjects/Keywords: Budding yeast cell cycle; Deterministic model; MUTANTS; HYBRID MODEL; VISUALIZATION

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

APA (6^{th} Edition):

Cui, J. (2017). Visualization of the Budding Yeast Cell Cycle. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/78815

Chicago Manual of Style (16^{th} Edition):

Cui, Jing. “Visualization of the Budding Yeast Cell Cycle.” 2017. Masters Thesis, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/78815.

MLA Handbook (7^{th} Edition):

Cui, Jing. “Visualization of the Budding Yeast Cell Cycle.” 2017. Web. 04 Mar 2021.

Vancouver:

Cui J. Visualization of the Budding Yeast Cell Cycle. [Internet] [Masters thesis]. Virginia Tech; 2017. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/78815.

Council of Science Editors:

Cui J. Visualization of the Budding Yeast Cell Cycle. [Masters Thesis]. Virginia Tech; 2017. Available from: http://hdl.handle.net/10919/78815

Virginia Tech

25. Zhang, Hong. Efficient Time Stepping Methods and Sensitivity Analysis for Large Scale Systems of Differential Equations.

Degree: PhD, Computer Science and Applications, 2014, Virginia Tech

URL: http://hdl.handle.net/10919/50492

► Many fields in science and engineering require large-scale numerical simulations of complex systems described by differential equations. These systems are typically multi-physics (they are driven…
(more)

Subjects/Keywords: Time Stepping; General Linear Methods; Implicit-explicit; Sensitivity Analysis

Record Details Similar Records

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

APA (6^{th} Edition):

Zhang, H. (2014). Efficient Time Stepping Methods and Sensitivity Analysis for Large Scale Systems of Differential Equations. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/50492

Chicago Manual of Style (16^{th} Edition):

Zhang, Hong. “Efficient Time Stepping Methods and Sensitivity Analysis for Large Scale Systems of Differential Equations.” 2014. Doctoral Dissertation, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/50492.

MLA Handbook (7^{th} Edition):

Zhang, Hong. “Efficient Time Stepping Methods and Sensitivity Analysis for Large Scale Systems of Differential Equations.” 2014. Web. 04 Mar 2021.

Vancouver:

Zhang H. Efficient Time Stepping Methods and Sensitivity Analysis for Large Scale Systems of Differential Equations. [Internet] [Doctoral dissertation]. Virginia Tech; 2014. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/50492.

Council of Science Editors:

Zhang H. Efficient Time Stepping Methods and Sensitivity Analysis for Large Scale Systems of Differential Equations. [Doctoral Dissertation]. Virginia Tech; 2014. Available from: http://hdl.handle.net/10919/50492

Virginia Tech

26. Cui, Xuewen. Directive-Based Data Partitioning and Pipelining and Auto-Tuning for High-Performance GPU Computing.

Degree: PhD, Computer Science and Applications, 2020, Virginia Tech

URL: http://hdl.handle.net/10919/101497

► Over the past decade, parallel accelerators have become increasingly prominent in this emerging era of "big data, big compute, and artificial intelligence.'' In more recent…
(more)

Subjects/Keywords: OpenMP; GPU; Pipeline; Paritioning; Unified Memory; High-performance Computing; Machine Learning

Record Details Similar Records

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

APA (6^{th} Edition):

Cui, X. (2020). Directive-Based Data Partitioning and Pipelining and Auto-Tuning for High-Performance GPU Computing. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/101497

Chicago Manual of Style (16^{th} Edition):

Cui, Xuewen. “Directive-Based Data Partitioning and Pipelining and Auto-Tuning for High-Performance GPU Computing.” 2020. Doctoral Dissertation, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/101497.

MLA Handbook (7^{th} Edition):

Cui, Xuewen. “Directive-Based Data Partitioning and Pipelining and Auto-Tuning for High-Performance GPU Computing.” 2020. Web. 04 Mar 2021.

Vancouver:

Cui X. Directive-Based Data Partitioning and Pipelining and Auto-Tuning for High-Performance GPU Computing. [Internet] [Doctoral dissertation]. Virginia Tech; 2020. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/101497.

Council of Science Editors:

Cui X. Directive-Based Data Partitioning and Pipelining and Auto-Tuning for High-Performance GPU Computing. [Doctoral Dissertation]. Virginia Tech; 2020. Available from: http://hdl.handle.net/10919/101497

27. Corner, Sebastien Marc. Modeling, Sensitivity Analysis, and Optimization of Hybrid, Constrained Mechanical Systems.

Degree: PhD, Mechanical Engineering, 2018, Virginia Tech

URL: http://hdl.handle.net/10919/82713

► This dissertation provides a complete mathematical framework to compute the sensitivities with respect to system parameters for any second order hybrid Ordinary Differential Equation (ODE)…
(more)

Subjects/Keywords: Sensitivity analysis; Hybrid systems; Constrained systems

…Multibody Systems at *Virginia* *Tech*) capable of
modeling any complex multibody system by…

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

APA (6^{th} Edition):

Corner, S. M. (2018). Modeling, Sensitivity Analysis, and Optimization of Hybrid, Constrained Mechanical Systems. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/82713

Chicago Manual of Style (16^{th} Edition):

Corner, Sebastien Marc. “Modeling, Sensitivity Analysis, and Optimization of Hybrid, Constrained Mechanical Systems.” 2018. Doctoral Dissertation, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/82713.

MLA Handbook (7^{th} Edition):

Corner, Sebastien Marc. “Modeling, Sensitivity Analysis, and Optimization of Hybrid, Constrained Mechanical Systems.” 2018. Web. 04 Mar 2021.

Vancouver:

Corner SM. Modeling, Sensitivity Analysis, and Optimization of Hybrid, Constrained Mechanical Systems. [Internet] [Doctoral dissertation]. Virginia Tech; 2018. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/82713.

Council of Science Editors:

Corner SM. Modeling, Sensitivity Analysis, and Optimization of Hybrid, Constrained Mechanical Systems. [Doctoral Dissertation]. Virginia Tech; 2018. Available from: http://hdl.handle.net/10919/82713

28. Pu, Yang. The Art of Modeling and Simulation of Multiscale Biochemical Systems.

Degree: PhD, Computer Science and Applications, 2015, Virginia Tech

URL: http://hdl.handle.net/10919/52347

► In this thesis we study modeling and simulation approaches for multiscale biochemical systems. The thesis addresses both modeling methods and simulation strategies. In the first…
(more)

Subjects/Keywords: Insulin secretion pathway; Numerical model; Hybrid method; SSA; QSSA

Record Details Similar Records

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

APA (6^{th} Edition):

Pu, Y. (2015). The Art of Modeling and Simulation of Multiscale Biochemical Systems. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/52347

Chicago Manual of Style (16^{th} Edition):

Pu, Yang. “The Art of Modeling and Simulation of Multiscale Biochemical Systems.” 2015. Doctoral Dissertation, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/52347.

MLA Handbook (7^{th} Edition):

Pu, Yang. “The Art of Modeling and Simulation of Multiscale Biochemical Systems.” 2015. Web. 04 Mar 2021.

Vancouver:

Pu Y. The Art of Modeling and Simulation of Multiscale Biochemical Systems. [Internet] [Doctoral dissertation]. Virginia Tech; 2015. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/52347.

Council of Science Editors:

Pu Y. The Art of Modeling and Simulation of Multiscale Biochemical Systems. [Doctoral Dissertation]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/52347

29. Li, Fei. Stochastic Modeling and Simulation of Reaction-Diffusion Biochemical Systems.

Degree: PhD, Computer Science and Applications, 2016, Virginia Tech

URL: http://hdl.handle.net/10919/64913

► Reaction Diffusion Master Equation (RDME) framework, characterized by the discretization of the spatial domain, is one of the most widely used methods in the stochastic…
(more)

Subjects/Keywords: stochastic simulation; reaction-diffusion systems; Caulobacter crescentus

Record Details Similar Records

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

APA (6^{th} Edition):

Li, F. (2016). Stochastic Modeling and Simulation of Reaction-Diffusion Biochemical Systems. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/64913

Chicago Manual of Style (16^{th} Edition):

Li, Fei. “Stochastic Modeling and Simulation of Reaction-Diffusion Biochemical Systems.” 2016. Doctoral Dissertation, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/64913.

MLA Handbook (7^{th} Edition):

Li, Fei. “Stochastic Modeling and Simulation of Reaction-Diffusion Biochemical Systems.” 2016. Web. 04 Mar 2021.

Vancouver:

Li F. Stochastic Modeling and Simulation of Reaction-Diffusion Biochemical Systems. [Internet] [Doctoral dissertation]. Virginia Tech; 2016. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/64913.

Council of Science Editors:

Li F. Stochastic Modeling and Simulation of Reaction-Diffusion Biochemical Systems. [Doctoral Dissertation]. Virginia Tech; 2016. Available from: http://hdl.handle.net/10919/64913

Virginia Tech

30. Liu, Zhen. Stochastic Simulation Methods for Solving Systems with Multi-State Species.

Degree: MS, Computer Science, 2009, Virginia Tech

URL: http://hdl.handle.net/10919/32392

► Gillespie's stochastic simulation algorithm (SSA) has been a conventional method for stochastic modeling and simulation of biochemical systems. However, its population-based scheme faces the challenge…
(more)

Subjects/Keywords: StochSim; rule-based modeling; multi-state; SSA; hybrid method

Record Details Similar Records

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

APA (6^{th} Edition):

Liu, Z. (2009). Stochastic Simulation Methods for Solving Systems with Multi-State Species. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/32392

Chicago Manual of Style (16^{th} Edition):

Liu, Zhen. “Stochastic Simulation Methods for Solving Systems with Multi-State Species.” 2009. Masters Thesis, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/32392.

MLA Handbook (7^{th} Edition):

Liu, Zhen. “Stochastic Simulation Methods for Solving Systems with Multi-State Species.” 2009. Web. 04 Mar 2021.

Vancouver:

Liu Z. Stochastic Simulation Methods for Solving Systems with Multi-State Species. [Internet] [Masters thesis]. Virginia Tech; 2009. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/32392.

Council of Science Editors:

Liu Z. Stochastic Simulation Methods for Solving Systems with Multi-State Species. [Masters Thesis]. Virginia Tech; 2009. Available from: http://hdl.handle.net/10919/32392