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Colorado School of Mines
1.
Andrade de Almeida, Lucas José.
Seismic data interpolation using sparsity constrained inversion.
Degree: MS(M.S.), Geophysics, 2017, Colorado School of Mines
URL: http://hdl.handle.net/11124/171138 
► Missing data reconstruction is an ongoing challenge in seismic processing for incomplete and irregular acquisition. The problem of missing data negatively affects several important processing…
(more)
▼ Missing data reconstruction is an ongoing challenge in seismic processing for incomplete and irregular acquisition. The problem of missing data negatively affects several important processing steps such as migration. While many methods have been developed to address this problem, most of the recent research on the subject focuses on transform domain approaches due to their low computational cost and independence of medium property estimation, such as velocity and density. Because of the underdetermined nature of the interpolation problem, transform domain techniques use sparsity constraints in order to obtain better solutions than the conventional least squares approach. Motivated by the compressive sensing framework, which proves that sparse signals can be recovered from a highly incomplete set of measurements, two approaches for sparsity constrained inversion are commonly used: the synthesis and analysis approaches. Although similarly posed, they present differences when the transform domain used in the inversion is redundant. Due to the high dimensionality and aliasing that occurs in the interpolation problem, such approaches are not able to handle large gaps between traces and display artifacts in the reconstruction. Weighted L1 minimization algorithms have been proposed as a way to mitigate such problems. In this paper, we show the problems associated with the synthesis and analysis approaches when applied to seismic interpolation and propose an approach based on a reweighted L1 algorithm that estimates weights recursively, i.e., from previous weighted steps. Experiments, carried out on 2D and 3D data using different undersampling schemes, show that the proposed approach is able to improve estimation inside large gaps, decrease artifacts and obtain better SNR when compared with conventional analysis and synthesis sparsity constrained inversion.
Advisors/Committee Members: Sava, Paul C. (advisor), Wakin, Michael B. (committee member), Constantine, Paul G. (committee member).
Subjects/Keywords: interpolation; sparsity; analysis; synthesis; seismic processing
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APA (6th Edition):
Andrade de Almeida, L. J. (2017). Seismic data interpolation using sparsity constrained inversion. (Masters Thesis). Colorado School of Mines. Retrieved from http://hdl.handle.net/11124/171138
Chicago Manual of Style (16th Edition):
Andrade de Almeida, Lucas José. “Seismic data interpolation using sparsity constrained inversion.” 2017. Masters Thesis, Colorado School of Mines. Accessed March 06, 2021.
http://hdl.handle.net/11124/171138.
MLA Handbook (7th Edition):
Andrade de Almeida, Lucas José. “Seismic data interpolation using sparsity constrained inversion.” 2017. Web. 06 Mar 2021.
Vancouver:
Andrade de Almeida LJ. Seismic data interpolation using sparsity constrained inversion. [Internet] [Masters thesis]. Colorado School of Mines; 2017. [cited 2021 Mar 06].
Available from: http://hdl.handle.net/11124/171138.
Council of Science Editors:
Andrade de Almeida LJ. Seismic data interpolation using sparsity constrained inversion. [Masters Thesis]. Colorado School of Mines; 2017. Available from: http://hdl.handle.net/11124/171138
Colorado School of Mines
2.
Loudon, Tyson S.
Analysis and dynamic active subspaces for a long term model of HIV.
Degree: MS(M.S.), Applied Mathematics and Statistics, 2015, Colorado School of Mines
URL: http://hdl.handle.net/11124/20117
► The Human Immunodeficiency Virus (HIV) disables many components of the body's immune system and, without antiretroviral treatment, leads to the onset of Acquired Immune Deficiency…
(more)
▼ The Human Immunodeficiency Virus (HIV) disables many components of the body's immune system and, without antiretroviral treatment, leads to the onset of Acquired Immune Deficiency Syndrome (AIDS) and subsequently death. The infection progresses through three stages: initial or acute infection, an asymptomatic or latent period, and finally AIDS. Modeling the entire time course of HIV within the body can be difficult as many models have oversimplified its biological dynamics in the effort to gain mathematical insight but fail to capture the three stages of infection. Only one HIV model has been able to describe the entire time course of the infection, but this model is large and is expensive to simulate. In this paper, we'll show there are two viral free steady states and conduct a stability analysis of one of the steady states. Then, we'll present a reduced order model for the T-cell count 1700 days after initial infection using active subspace methods. Building on the previous results, we'll create a global in time approximation of the T-cell count at any time using dynamic active subspaces.
Advisors/Committee Members: Pankavich, Stephen (advisor), Collis, Jon M. (committee member), Constantine, Paul G. (committee member).
Subjects/Keywords: HIV; sensitivity analysis; math modeling; active subspaces
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APA (6th Edition):
Loudon, T. S. (2015). Analysis and dynamic active subspaces for a long term model of HIV. (Masters Thesis). Colorado School of Mines. Retrieved from http://hdl.handle.net/11124/20117
Chicago Manual of Style (16th Edition):
Loudon, Tyson S. “Analysis and dynamic active subspaces for a long term model of HIV.” 2015. Masters Thesis, Colorado School of Mines. Accessed March 06, 2021.
http://hdl.handle.net/11124/20117.
MLA Handbook (7th Edition):
Loudon, Tyson S. “Analysis and dynamic active subspaces for a long term model of HIV.” 2015. Web. 06 Mar 2021.
Vancouver:
Loudon TS. Analysis and dynamic active subspaces for a long term model of HIV. [Internet] [Masters thesis]. Colorado School of Mines; 2015. [cited 2021 Mar 06].
Available from: http://hdl.handle.net/11124/20117.
Council of Science Editors:
Loudon TS. Analysis and dynamic active subspaces for a long term model of HIV. [Masters Thesis]. Colorado School of Mines; 2015. Available from: http://hdl.handle.net/11124/20117
Colorado School of Mines
3.
Simens, Jacqueline.
Mathematical modeling of hepatic and adipose insulin resistance in girls with polycystic ovarian syndrome.
Degree: MS(M.S.), Applied Mathematics and Statistics, 2015, Colorado School of Mines
URL: http://hdl.handle.net/11124/20154
► Polycystic Ovarian Syndrome (PCOS) affects 6-10% of women in the United States and is one of the leading causes of infertility. The metabolic phenotype for…
(more)
▼ Polycystic Ovarian Syndrome (PCOS) affects 6-10% of women in the United States and is one of the leading causes of infertility. The metabolic phenotype for PCOS includes insulin resistance (IR), and IR may vary with tissue type. The goal of this project is to determine the contributions of hepatic (liver) tissue and adipose (fat) tissue to increased IR in a cohort of adolescent females. For hepatic IR, we use the Labeled Oral Minimal Model (OMM*), originally developed by Dalla Man and colleagues. This differential equations based mathematical model describes the dynamics of glucose and insulin during an oral glucose tolerance test (OGTT) with stable isotope tracers for glucose and glycerol. Parameters for OMM* are used to quantify hepatic IR. We investigate the identifiability of this system and estimate model parameters in 6 subjects. For adipose IR, we propose a novel approach to modeling glycerol dynamics during an OGTT. We investigate the identifiability of this system and develop a numerical approach for estimating model parameters in the same cohort of 6 subjects. We propose the use of model parameters and metrics involving the numerical solution to quantify adipose IR. This work contributes to an improved understanding of tissue-specific IR, which may lead to targeted therapeutics.
Advisors/Committee Members: Diniz Behn, Cecilia (advisor), Pankavich, Stephen (committee member), Constantine, Paul G. (committee member).
Subjects/Keywords: mathematical modeling; model identifiability; PCOS; metabolism; glucose-insulin dynamics; parameter estimation
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APA (6th Edition):
Simens, J. (2015). Mathematical modeling of hepatic and adipose insulin resistance in girls with polycystic ovarian syndrome. (Masters Thesis). Colorado School of Mines. Retrieved from http://hdl.handle.net/11124/20154
Chicago Manual of Style (16th Edition):
Simens, Jacqueline. “Mathematical modeling of hepatic and adipose insulin resistance in girls with polycystic ovarian syndrome.” 2015. Masters Thesis, Colorado School of Mines. Accessed March 06, 2021.
http://hdl.handle.net/11124/20154.
MLA Handbook (7th Edition):
Simens, Jacqueline. “Mathematical modeling of hepatic and adipose insulin resistance in girls with polycystic ovarian syndrome.” 2015. Web. 06 Mar 2021.
Vancouver:
Simens J. Mathematical modeling of hepatic and adipose insulin resistance in girls with polycystic ovarian syndrome. [Internet] [Masters thesis]. Colorado School of Mines; 2015. [cited 2021 Mar 06].
Available from: http://hdl.handle.net/11124/20154.
Council of Science Editors:
Simens J. Mathematical modeling of hepatic and adipose insulin resistance in girls with polycystic ovarian syndrome. [Masters Thesis]. Colorado School of Mines; 2015. Available from: http://hdl.handle.net/11124/20154
Colorado School of Mines
4.
Collins, Caitlin M.
Using an integrated hydrology model to elucidate plant water use in a headwaters research catchment.
Degree: MS(M.S.), Geology and Geological Engineering, 2018, Colorado School of Mines
URL: http://hdl.handle.net/11124/172353
► Mountain headwaters are vulnerable to change. Increases in annual average temperature, changes in seasonal precipitation and drought stress will continue to alter the dynamics of…
(more)
▼ Mountain headwaters are vulnerable to change. Increases in annual average temperature, changes in seasonal precipitation and drought stress will continue to alter the dynamics of these delicate ecosystems. Despite its significance in the water budget, both the quantity and partitioning of evapotranspiration (ET) is poorly resolved. Restricted by discrete point observations, physical observations in mountain headwaters are challenging, limited by uncertainties and difficult to scale. Integrated, physically-based models are tools for dissecting the mechanisms driving evaporation and transpiration. Understanding mountain vegetation water use is an essential component for predicting the vegetative response to stress. This study is motivated by evidence of drought-induced tree mortality in some Sierran catchments, a high degree of uncertainty in mountain regolith groundwater storage, and the impacts of subsurface characterization on mountain ecohydrology (Holbrook et al. 2014; Jepsen et al. 2016). Using a physically-based integrated modeling approach, this study explores the role of lateral groundwater flow on the drought-tolerance of montane vegetation. Despite a 68.8% decrease in precipitation during the drought period, evapotranspiration only decreased by 26.5%. From the pre-drought period to the drought period the total change in groundwater storage decreased by 470%. Incorporating lateral groundwater flow increased transpiration partitioning (T/ET) from 44.9% to 59.0% in the pre-drought period and from 52.8% to 63.5% in the drought period. These results suggest that plant stress is mitigated under drought conditions because lateral flow of groundwater storage sustains transpiration.
Advisors/Committee Members: Maxwell, Reed M. (advisor), Singha, Kamini (committee member), Constantine, Paul G. (committee member).
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APA (6th Edition):
Collins, C. M. (2018). Using an integrated hydrology model to elucidate plant water use in a headwaters research catchment. (Masters Thesis). Colorado School of Mines. Retrieved from http://hdl.handle.net/11124/172353
Chicago Manual of Style (16th Edition):
Collins, Caitlin M. “Using an integrated hydrology model to elucidate plant water use in a headwaters research catchment.” 2018. Masters Thesis, Colorado School of Mines. Accessed March 06, 2021.
http://hdl.handle.net/11124/172353.
MLA Handbook (7th Edition):
Collins, Caitlin M. “Using an integrated hydrology model to elucidate plant water use in a headwaters research catchment.” 2018. Web. 06 Mar 2021.
Vancouver:
Collins CM. Using an integrated hydrology model to elucidate plant water use in a headwaters research catchment. [Internet] [Masters thesis]. Colorado School of Mines; 2018. [cited 2021 Mar 06].
Available from: http://hdl.handle.net/11124/172353.
Council of Science Editors:
Collins CM. Using an integrated hydrology model to elucidate plant water use in a headwaters research catchment. [Masters Thesis]. Colorado School of Mines; 2018. Available from: http://hdl.handle.net/11124/172353
Colorado School of Mines
5.
Sattelberg, Ben.
Global sensitivity analysis for a collisionless plasma using a particle-in-cell method, A.
Degree: MS(M.S.), Applied Mathematics and Statistics, 2016, Colorado School of Mines
URL: http://hdl.handle.net/11124/170652
► Knowing the effects of physical parameters underlying the behavior of plasmas is useful when designing or investigating associated high velocity systems. We use a kinetic…
(more)
▼ Knowing the effects of physical parameters underlying the behavior of plasmas is useful when designing or investigating associated high velocity systems. We use a kinetic model given by the Vlasov-Poisson equations to consider global linear and gradient-based active subspace models that calculate sensitivity metrics related to the phenomena of Landau damping and the two-stream instability. Since analytic results are difficult or impossible to obtain for this system, we use a particle-in-cell method to numerically compute quantities of interest for which the sensitivity metrics can be calculated. In particular, we consider three equilibrium distributions that include Maxwellian and Lorentzian velocity distributions to demonstrate the usefulness of this method in understanding and quantifying parameter effects.
Advisors/Committee Members: Pankavich, Stephen (advisor), Constantine, Paul G. (committee member), Bialecki, Bernard (committee member).
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APA (6th Edition):
Sattelberg, B. (2016). Global sensitivity analysis for a collisionless plasma using a particle-in-cell method, A. (Masters Thesis). Colorado School of Mines. Retrieved from http://hdl.handle.net/11124/170652
Chicago Manual of Style (16th Edition):
Sattelberg, Ben. “Global sensitivity analysis for a collisionless plasma using a particle-in-cell method, A.” 2016. Masters Thesis, Colorado School of Mines. Accessed March 06, 2021.
http://hdl.handle.net/11124/170652.
MLA Handbook (7th Edition):
Sattelberg, Ben. “Global sensitivity analysis for a collisionless plasma using a particle-in-cell method, A.” 2016. Web. 06 Mar 2021.
Vancouver:
Sattelberg B. Global sensitivity analysis for a collisionless plasma using a particle-in-cell method, A. [Internet] [Masters thesis]. Colorado School of Mines; 2016. [cited 2021 Mar 06].
Available from: http://hdl.handle.net/11124/170652.
Council of Science Editors:
Sattelberg B. Global sensitivity analysis for a collisionless plasma using a particle-in-cell method, A. [Masters Thesis]. Colorado School of Mines; 2016. Available from: http://hdl.handle.net/11124/170652
Colorado School of Mines
6.
Hickman, David A.
Particle swarm optimization for energy minimization of molecular systems.
Degree: MS(M.S.), Applied Mathematics and Statistics, 2014, Colorado School of Mines
URL: http://hdl.handle.net/11124/10612
► The minimization of a potential energy function can be used to provide insight into the ground state configuration of a wide range of molecular systems.…
(more)
▼ The minimization of a potential energy function can be used to provide insight into the ground state configuration of a wide range of molecular systems. Optimization problems of this type can be challenging for deterministic (e.
g. line search) optimization algorithms due to the size of the search space and the large number of local minima that are inherent within molecular configuration problems. We describe how Particle Swarm Optimization, a stochastic optimization algorithm inspired by flocking behavior, can be used to accurately and efficiently solve energy minimization problems associated with molecular systems.
Advisors/Committee Members: Pankavich, Stephen (advisor), Constantine, Paul G. (committee member), Collis, Jon M. (committee member).
Subjects/Keywords: Mathematical optimization; Molecular structure; Algorithms; Swarm intelligence; Potential theory (Mathematics)
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APA (6th Edition):
Hickman, D. A. (2014). Particle swarm optimization for energy minimization of molecular systems. (Masters Thesis). Colorado School of Mines. Retrieved from http://hdl.handle.net/11124/10612
Chicago Manual of Style (16th Edition):
Hickman, David A. “Particle swarm optimization for energy minimization of molecular systems.” 2014. Masters Thesis, Colorado School of Mines. Accessed March 06, 2021.
http://hdl.handle.net/11124/10612.
MLA Handbook (7th Edition):
Hickman, David A. “Particle swarm optimization for energy minimization of molecular systems.” 2014. Web. 06 Mar 2021.
Vancouver:
Hickman DA. Particle swarm optimization for energy minimization of molecular systems. [Internet] [Masters thesis]. Colorado School of Mines; 2014. [cited 2021 Mar 06].
Available from: http://hdl.handle.net/11124/10612.
Council of Science Editors:
Hickman DA. Particle swarm optimization for energy minimization of molecular systems. [Masters Thesis]. Colorado School of Mines; 2014. Available from: http://hdl.handle.net/11124/10612
Colorado School of Mines
7.
Teter, Michael D.
Modeling uncertainty of expert-elicited data for use in risk-based, capital budgeting and underground mine production scheduling optimization models.
Degree: PhD, Mechanical Engineering, 2016, Colorado School of Mines
URL: http://hdl.handle.net/11124/170433
► This dissertation consists of three papers in various stages of publication. The first paper, "Consistent Notation for Presenting Complex Optimization Models in Technical Writing,'' is…
(more)
▼ This dissertation consists of three papers in various stages of publication. The first paper, "Consistent Notation for Presenting Complex Optimization Models in Technical Writing,'' is published in Surveys in Operations Research and Management Science. The topics we discuss are: (i) conventions for defining sets, parameters, and variables, (ii) ways of presenting the objective and constraints, and (iii) means by which to organize formulations as they pertain to mathematical programming. A second paper, "Modeling uncertainty of expert elicitation for use in risk-based optimization,'' is under review, at the time of this submission, in Annals of Operation Research. We derive, for the first time, a three-dimensional density estimate with epi-splines from which we generate scenarios to implement in a superquantile risk-based, capital budgeting optimization model. The last paper, "Optimizing underground mine scheduling under production rate uncertainty,'' is awaiting the company's letter of endorsement necessary for submission to Interfaces. We employ a risk-based optimization model, with uncertain ground conditions, to demonstrate the effects geotechnical risk has on an underground mine production schedule.
Advisors/Committee Members: Newman, Alexandra M. (advisor), Royset, Johannes O. (advisor), Gorman, Brian P. (committee member), Constantine, Paul G. (committee member), Hering, Amanda S. (committee member).
Subjects/Keywords: epi-spline estimation; nonparametric density estimation; technical writing of optimization; mine production scheduling optimization; capital budgeting optimization; stochastic optimization
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APA (6th Edition):
Teter, M. D. (2016). Modeling uncertainty of expert-elicited data for use in risk-based, capital budgeting and underground mine production scheduling optimization models. (Doctoral Dissertation). Colorado School of Mines. Retrieved from http://hdl.handle.net/11124/170433
Chicago Manual of Style (16th Edition):
Teter, Michael D. “Modeling uncertainty of expert-elicited data for use in risk-based, capital budgeting and underground mine production scheduling optimization models.” 2016. Doctoral Dissertation, Colorado School of Mines. Accessed March 06, 2021.
http://hdl.handle.net/11124/170433.
MLA Handbook (7th Edition):
Teter, Michael D. “Modeling uncertainty of expert-elicited data for use in risk-based, capital budgeting and underground mine production scheduling optimization models.” 2016. Web. 06 Mar 2021.
Vancouver:
Teter MD. Modeling uncertainty of expert-elicited data for use in risk-based, capital budgeting and underground mine production scheduling optimization models. [Internet] [Doctoral dissertation]. Colorado School of Mines; 2016. [cited 2021 Mar 06].
Available from: http://hdl.handle.net/11124/170433.
Council of Science Editors:
Teter MD. Modeling uncertainty of expert-elicited data for use in risk-based, capital budgeting and underground mine production scheduling optimization models. [Doctoral Dissertation]. Colorado School of Mines; 2016. Available from: http://hdl.handle.net/11124/170433
Colorado School of Mines
8.
Hein, Annette.
Drought on the North American high plains: modeling effects of vegetation, temperature and rainfall perturbations on regional hydrology.
Degree: MS(M.S.), Geology and Geological Engineering, 2018, Colorado School of Mines
URL: http://hdl.handle.net/11124/172337
► Drought is a natural disaster that may become more common in the future under climate change. It involves changes to temperature, precipitation, land cover or…
(more)
▼ Drought is a natural disaster that may become more common in the future under climate change. It involves changes to temperature, precipitation, land cover or all three variables. A high-resolution integrated hydrologic model of the High Plains explores the individual importance of each of these factors and the feedbacks between them. The model was constructed using ParFlow-CLM, which represents surface and subsurface processes in detail with physically based equations. Numerical experiments were run to perturb vegetation, precipitation and temperature separately, as well as a baseline scenario with no changes and two multi-factor scenarios. Less precipitation caused larger anomalies in evapotranspiration, soil moisture, stream flow and water table levels than did increased temperature or disturbed land cover. However, many mechanisms including lateral flow, antecedent soil moisture and scaling affected the details of model response, thus making the behavior of multi-factor runs complex.
Advisors/Committee Members: Maxwell, Reed M. (advisor), Constantine, Paul G. (committee member), Kroepsch, Adrianne (committee member), Benson, David A. (committee member).
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APA (6th Edition):
Hein, A. (2018). Drought on the North American high plains: modeling effects of vegetation, temperature and rainfall perturbations on regional hydrology. (Masters Thesis). Colorado School of Mines. Retrieved from http://hdl.handle.net/11124/172337
Chicago Manual of Style (16th Edition):
Hein, Annette. “Drought on the North American high plains: modeling effects of vegetation, temperature and rainfall perturbations on regional hydrology.” 2018. Masters Thesis, Colorado School of Mines. Accessed March 06, 2021.
http://hdl.handle.net/11124/172337.
MLA Handbook (7th Edition):
Hein, Annette. “Drought on the North American high plains: modeling effects of vegetation, temperature and rainfall perturbations on regional hydrology.” 2018. Web. 06 Mar 2021.
Vancouver:
Hein A. Drought on the North American high plains: modeling effects of vegetation, temperature and rainfall perturbations on regional hydrology. [Internet] [Masters thesis]. Colorado School of Mines; 2018. [cited 2021 Mar 06].
Available from: http://hdl.handle.net/11124/172337.
Council of Science Editors:
Hein A. Drought on the North American high plains: modeling effects of vegetation, temperature and rainfall perturbations on regional hydrology. [Masters Thesis]. Colorado School of Mines; 2018. Available from: http://hdl.handle.net/11124/172337
Colorado School of Mines
9.
Nealy, Jennifer L.
Study of normal mode solutions for seismo-acoustic propagation scenarios, A: a generalized range-independent case, earthquake modeling using seismic moment tensors, and an improved moment tensor inversion method.
Degree: PhD, Applied Mathematics and Statistics, 2015, Colorado School of Mines
URL: http://hdl.handle.net/11124/17111
► This work presents improvements to the study of tsunamigenic offshore earthquakes and complex earthquakes, i.e., earthquakes that are better represented as multiple events, through the…
(more)
▼ This work presents improvements to the study of tsunamigenic offshore earthquakes and complex earthquakes, i.e., earthquakes that are better represented as multiple events, through the use of underwater acoustic normal mode solutions and updated inversion techniques. When considering offshore earthquakes, normal mode solutions, i.e., analytic solutions that can be expressed as an infinite sum of residues, are used to model the acoustic field generated by an event. The environment under consideration, an ocean environment where water is overlying the seafloor, is approximated as a fluid layer overlying an elastic bottom. A source, such as an explosion or earthquake, is represented as a point source that is located in either the water column or the sediment layer. Using a generalized Green's function formulation for normal mode solutions, accurate solutions are obtained for various source cases and are benchmarked against elastic parabolic equation solutions that have been previously benchmarked against wavenumber integration solutions. Normal mode solutions for seismo-acoustic propagation problems using generalized Green's functions can then be used to study tsunamigenic earthquakes. Moment tensor representations of earthquake sources are used to find forcing terms that represent earthquakes of varying shear-to-compressional composition. The extension of this technique to a range-dependent environment where a coupling integral technique is used to ensure mode coupling across range segments is then explored. When considering complex events that do not necessarily occur offshore, the environment being considered is now the earth rather than the ocean. In this case it is beneficial to find characteristics of the earthquake instead of studying pressure fields generated by events. Using normal mode solutions of this new system, a matrix-vector equation may be found which, through least-squares inversion techniques, can characterize a complex earthquake as two near-simultaneous events rather than a single event. This allows for a more accurate characterization of the earthquake being modeled. A statistical test is used to compare results from a single source inversion to results obtained with a double source inversion and select the most appropriate number of sources for any given earthquake.
Advisors/Committee Members: Collis, Jon M. (advisor), Callan, Kristine E. (committee member), Carney, Debra (committee member), Constantine, Paul G. (committee member), Pankavich, Stephen (committee member).
Subjects/Keywords: Earthquakes; Tsunamis; Seismology – Statistical methods; Matrix inversion; Wave guides; Underwater acoustics
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APA ·
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APA (6th Edition):
Nealy, J. L. (2015). Study of normal mode solutions for seismo-acoustic propagation scenarios, A: a generalized range-independent case, earthquake modeling using seismic moment tensors, and an improved moment tensor inversion method. (Doctoral Dissertation). Colorado School of Mines. Retrieved from http://hdl.handle.net/11124/17111
Chicago Manual of Style (16th Edition):
Nealy, Jennifer L. “Study of normal mode solutions for seismo-acoustic propagation scenarios, A: a generalized range-independent case, earthquake modeling using seismic moment tensors, and an improved moment tensor inversion method.” 2015. Doctoral Dissertation, Colorado School of Mines. Accessed March 06, 2021.
http://hdl.handle.net/11124/17111.
MLA Handbook (7th Edition):
Nealy, Jennifer L. “Study of normal mode solutions for seismo-acoustic propagation scenarios, A: a generalized range-independent case, earthquake modeling using seismic moment tensors, and an improved moment tensor inversion method.” 2015. Web. 06 Mar 2021.
Vancouver:
Nealy JL. Study of normal mode solutions for seismo-acoustic propagation scenarios, A: a generalized range-independent case, earthquake modeling using seismic moment tensors, and an improved moment tensor inversion method. [Internet] [Doctoral dissertation]. Colorado School of Mines; 2015. [cited 2021 Mar 06].
Available from: http://hdl.handle.net/11124/17111.
Council of Science Editors:
Nealy JL. Study of normal mode solutions for seismo-acoustic propagation scenarios, A: a generalized range-independent case, earthquake modeling using seismic moment tensors, and an improved moment tensor inversion method. [Doctoral Dissertation]. Colorado School of Mines; 2015. Available from: http://hdl.handle.net/11124/17111
Colorado School of Mines
10.
Zhu, Zhihui.
Subspace approximation on the continuum.
Degree: PhD, Electrical Engineering and Computer Science, 2017, Colorado School of Mines
URL: http://hdl.handle.net/11124/172031
► Many signal processing problems – such as analysis, compression, reconstruction, and denoising – can be facilitated by exploiting the underlying models the signals and data sets obey.…
(more)
▼ Many signal processing problems – such as analysis, compression, reconstruction, and denoising – can be facilitated by exploiting the underlying models the signals and data sets obey. A model often deals with the notion of conciseness and suggests a signal has few degrees of freedom relative to its ambient dimensionality. For instance, the Shannon-Nyquist sampling theorem works on bandlimited signals obeying{\em subspace model}. As an another example, the power of sparse signal processing often relies on the assumption that the signals live in some union of subspaces. In many cases, signals have concise representations which are often obtained by (i) constructing a{\em dictionary} of elements drawn from the signal space, and then (ii) expressing the signal of interest as a linear combination of a small number of atoms drawn from the dictionary. Such representations serve as an efficient way to describe the conciseness of the signals and enable effective signal processing methods. For example, the sparse representation forms the core of compressive sensing (CS), an emerging research area that aims to break through the Shannon-Nyquist limit for sampling analog signals. However, despite its recent success, there are many important applications in signal processing that do not naturally fall into the subspace models and sparse recovery framework. As a classical example, a finite-length vector obtained by sampling a bandlimited signal is not sparse using the discrete Fourier transform (DFT), the natural tool for frequency analysis on finite-dimensional space. In other words, the DFT cannot excavate the concise structure within the sampled bandlimited signals. These signals obey a so-called{\em parameterized subspace model} in which the signals of interest are inherently low-dimensional and live in a union of subspaces, but the choice of subspace is controlled by a small number of continuous-valued parameters (the parameter controlling sampled bandlimited signals is the frequency). This continuous-valued parameterized subspace model appears in many problems including spectral estimation, mitigation of narrowband interference, feature extraction, and steerable filters for rotation-invariant image recognition. The purpose of this thesis is to 1) construct a subspace – whose dimension matches the effective number of local degrees of freedom – for approximating (almost) all the signals controlled by a small number of continuous-valued parameters ranging within some certain intervals; 2) develop rigorous, theoretically-backed techniques for computing projections onto and orthogonal to these subspaces. By developing an appropriate basis to economically represent the signals of interest, one can apply effective tools developed for the subspace model and sparse recovery framework for signal processing. In the process of building local subspace fits, we will also obtain the effective dimensionality of such signals. Our key contributions include (i) new non-asymptotic results on the eigenvalue distribution of (periodic) discrete…
Advisors/Committee Members: Wakin, Michael B. (advisor), Constantine, Paul G. (committee member), Davenport, Mark A. (committee member), Tang, Gongguo (committee member), Vincent, Tyrone (committee member).
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APA (6th Edition):
Zhu, Z. (2017). Subspace approximation on the continuum. (Doctoral Dissertation). Colorado School of Mines. Retrieved from http://hdl.handle.net/11124/172031
Chicago Manual of Style (16th Edition):
Zhu, Zhihui. “Subspace approximation on the continuum.” 2017. Doctoral Dissertation, Colorado School of Mines. Accessed March 06, 2021.
http://hdl.handle.net/11124/172031.
MLA Handbook (7th Edition):
Zhu, Zhihui. “Subspace approximation on the continuum.” 2017. Web. 06 Mar 2021.
Vancouver:
Zhu Z. Subspace approximation on the continuum. [Internet] [Doctoral dissertation]. Colorado School of Mines; 2017. [cited 2021 Mar 06].
Available from: http://hdl.handle.net/11124/172031.
Council of Science Editors:
Zhu Z. Subspace approximation on the continuum. [Doctoral Dissertation]. Colorado School of Mines; 2017. Available from: http://hdl.handle.net/11124/172031
Colorado School of Mines
11.
Jefferson, Jennifer L.
Exploring sensitivities of latent heat parameterizations using a coupled, integrated hydrologic model.
Degree: PhD, Geology and Geological Engineering, 2016, Colorado School of Mines
URL: http://hdl.handle.net/11124/170080
► Evapotranspiration and its energy counterpart latent heat flux are critical components of the terrestrial water and energy balances. Precipitation, runoff, condensation and groundwater flow are…
(more)
▼ Evapotranspiration and its energy counterpart latent heat flux are critical components of the terrestrial water and energy balances. Precipitation, runoff, condensation and groundwater flow are also significant members of the hydrologic cycle, but it is evapotranspiration that links water in the subsurface to water on the land surface or in the atmosphere. Hydrologic models use parameterizations to represent the physical and physiological processes of evaporation and transpiration, respectively. These parameterizations assume some mathematical structure and require that values of certain parameters be assigned; however, questions remain regarding how changes in each of these two aspects translate to output quantities of interest. Quantifying the sensitivity of model outputs to structure and input value decisions is important to understand a model’s behavior and response to changes. This dissertation explores sensitivities associated with evaporation and transpiration parameterizations within the ParFlow-Common Land Model through systematic comparisons and the application of a new sensitivity analysis method called active subspaces. Results indicate that model sensitivities vary throughout the year. For bare ground evaporation, parameterization structure affects both the magnitude and behavior of annual estimates. Including complexities associated with atmospheric stability influences evaporation behavior the most under water-limited conditions. For a vegetated surface, important input parameters used to compute the rate of transpiration vary seasonally and diurnally. Further analysis uncovers unique relationships between input and output quantities associated with evaporation and transpiration. For example, ground temperature and bare ground evaporation exhibit a parabolic relationship where similar points group together based on seasonal values of subsurface pressure, specific humidity and air temperature. The input-output relationship discovered using the active subspace method changes in time and suggests that transpiration estimates are more sensitive to changes in important parameter values during midday summer time hours.
Advisors/Committee Members: Maxwell, Reed M. (advisor), Singha, Kamini (committee member), McCray, John E. (committee member), Wood, Brian (committee member), Constantine, Paul G. (committee member).
Subjects/Keywords: hydrology; latent heat; model; PF-CLM; sensitivity
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APA (6th Edition):
Jefferson, J. L. (2016). Exploring sensitivities of latent heat parameterizations using a coupled, integrated hydrologic model. (Doctoral Dissertation). Colorado School of Mines. Retrieved from http://hdl.handle.net/11124/170080
Chicago Manual of Style (16th Edition):
Jefferson, Jennifer L. “Exploring sensitivities of latent heat parameterizations using a coupled, integrated hydrologic model.” 2016. Doctoral Dissertation, Colorado School of Mines. Accessed March 06, 2021.
http://hdl.handle.net/11124/170080.
MLA Handbook (7th Edition):
Jefferson, Jennifer L. “Exploring sensitivities of latent heat parameterizations using a coupled, integrated hydrologic model.” 2016. Web. 06 Mar 2021.
Vancouver:
Jefferson JL. Exploring sensitivities of latent heat parameterizations using a coupled, integrated hydrologic model. [Internet] [Doctoral dissertation]. Colorado School of Mines; 2016. [cited 2021 Mar 06].
Available from: http://hdl.handle.net/11124/170080.
Council of Science Editors:
Jefferson JL. Exploring sensitivities of latent heat parameterizations using a coupled, integrated hydrologic model. [Doctoral Dissertation]. Colorado School of Mines; 2016. Available from: http://hdl.handle.net/11124/170080
Colorado School of Mines
12.
Eftekhari, Armin.
Model-based signal recovery: a geometric perspective.
Degree: PhD, Electrical Engineering and Computer Sciences, 2015, Colorado School of Mines
URL: http://hdl.handle.net/11124/166679
► Model-based signal processing is concerned with measuring, understanding, and communicating data under the assumption that the (potentially high-dimensional) data in hand has in fact few…
(more)
▼ Model-based signal processing is concerned with measuring, understanding, and communicating data under the assumption that the (potentially high-dimensional) data in hand has in fact few degrees of freedom and can be accurately represented with a concise signal model. For instance, when the signal model is the class of sparse signals (i.e., signals with a concise representation in some basis), compressive sensing has proved effective in combining the sensing and compression stages, thereby allowing for more efficient sensors and powerful signal processing algorithms. A canonical result in compressive sensing states that sparse signals can be accurately recovered from a small number of generic linear measurements by solving a tractable convex optimization problem. More generally, however, manifold-based signal processing focuses on (possibly high-dimensional) data which lives on (or near) low-dimensional surfaces (or manifolds, to use the precise term). Typically, this is a stronger notion of conciseness compared to sparsity and results in a more efficient representation of data, one that often leads to better signal processing algorithms for manifold-modeled data. With this introduction, the central question in this dissertation can be phrased as follows: What can we learn about data that lives on (or near) a manifold from limited (or compressive) measurements? In adding to the collective knowledge of this question, we study the quality of signal reconstruction from compressive measurements. Moreover, we make strides in answering the question above for certain specific manifolds that often arise in applications. For instance, we estimate (from limited measurements) the unknown parameters of signals that live on the shift-manifold (which is formed from translated copies of a template signal). Lastly, we focus on a framework for time-series analysis that relies heavily on manifold models.
Advisors/Committee Members: Wakin, Michael B. (advisor), Constantine, Paul G. (committee member), Rebennack, Steffen (committee member), Romberg, Justin (committee member), Tenorio, Luis (committee member), Vincent, Tyrone (committee member).
Subjects/Keywords: compressive sensing; manifold models; signal processing
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APA (6th Edition):
Eftekhari, A. (2015). Model-based signal recovery: a geometric perspective. (Doctoral Dissertation). Colorado School of Mines. Retrieved from http://hdl.handle.net/11124/166679
Chicago Manual of Style (16th Edition):
Eftekhari, Armin. “Model-based signal recovery: a geometric perspective.” 2015. Doctoral Dissertation, Colorado School of Mines. Accessed March 06, 2021.
http://hdl.handle.net/11124/166679.
MLA Handbook (7th Edition):
Eftekhari, Armin. “Model-based signal recovery: a geometric perspective.” 2015. Web. 06 Mar 2021.
Vancouver:
Eftekhari A. Model-based signal recovery: a geometric perspective. [Internet] [Doctoral dissertation]. Colorado School of Mines; 2015. [cited 2021 Mar 06].
Available from: http://hdl.handle.net/11124/166679.
Council of Science Editors:
Eftekhari A. Model-based signal recovery: a geometric perspective. [Doctoral Dissertation]. Colorado School of Mines; 2015. Available from: http://hdl.handle.net/11124/166679
Colorado School of Mines
13.
Beisman, James Joseph.
Hydrogeochemical model development and advanced numerical simulation of alpine hillslope geochemical response to temperature-induced hydrologic changes.
Degree: PhD, Geology and Geological Engineering, 2018, Colorado School of Mines
URL: http://hdl.handle.net/11124/172221
► Subsurface hydrogeochemical systems are complex components of the terrestrial environment, playing host to a multitude of interacting processes. Reactive transport modeling provides a method to…
(more)
▼ Subsurface hydrogeochemical systems are complex components of the terrestrial environment, playing host to a multitude of interacting processes. Reactive transport modeling provides a method to numerically integrate our mechanistic, process-based understanding of the phenomena that dictate terrestrial hydrogeochemistry, and can help to further refine and test our understanding of these systems. Here, the development of a new hydrogeochemical reactive transport model, ParCrunchFlow, is detailed. This model provides a continuum-scale approximation of subsurface geochemical reactions in porous media under transient, surface-subsurface flow conditions. An integrated land-surface model allows the representation of snow accumulation/melt and evapotranspiration, driven by realistic meteorological forcing data. A novel representation of atmosphere-subsurface diffusion is described, and is used to simulate atmospheric oxygen diffusion into the vadose zone. The code runs in parallel, and is highly scalable, allowing the representation of field-scale systems at high resolutions. Several higher-order positivity-preserving advection schemes are described, and the effects of scheme accuracy on mixing-induced kinetic and equilibrium reactions are explored. The response of an alpine hillslope containing pyrite to a two degree Celsius temperature increase is examined. The temperature increase causes hillslope discharge to decrease and water table elevation to decline, exposing more of the reactive subsurface to atmospheric oxygen and increasing pyrite oxidation rates. Concentration-discharge plots, commonly used in field studies to analyze geochemical controls, are generated from model outputs and are a useful tool with which to interpret model behavior. The results suggest that recently observed increasing concentrations of pyrite oxidation proxies in alpine catchments, thought to be caused by increasing temperatures, may be more attributable to the effects of reduced dilution than to increasing reaction rates, though both appear to play a role.
Advisors/Committee Members: Maxwell, Reed M. (advisor), Navarre-Sitchler, Alexis K. (advisor), Singha, Kamini (committee member), Smits, Kathleen M. (committee member), Constantine, Paul G. (committee member), Steefel, Carl (committee member).
Subjects/Keywords: reactive transport
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APA (6th Edition):
Beisman, J. J. (2018). Hydrogeochemical model development and advanced numerical simulation of alpine hillslope geochemical response to temperature-induced hydrologic changes. (Doctoral Dissertation). Colorado School of Mines. Retrieved from http://hdl.handle.net/11124/172221
Chicago Manual of Style (16th Edition):
Beisman, James Joseph. “Hydrogeochemical model development and advanced numerical simulation of alpine hillslope geochemical response to temperature-induced hydrologic changes.” 2018. Doctoral Dissertation, Colorado School of Mines. Accessed March 06, 2021.
http://hdl.handle.net/11124/172221.
MLA Handbook (7th Edition):
Beisman, James Joseph. “Hydrogeochemical model development and advanced numerical simulation of alpine hillslope geochemical response to temperature-induced hydrologic changes.” 2018. Web. 06 Mar 2021.
Vancouver:
Beisman JJ. Hydrogeochemical model development and advanced numerical simulation of alpine hillslope geochemical response to temperature-induced hydrologic changes. [Internet] [Doctoral dissertation]. Colorado School of Mines; 2018. [cited 2021 Mar 06].
Available from: http://hdl.handle.net/11124/172221.
Council of Science Editors:
Beisman JJ. Hydrogeochemical model development and advanced numerical simulation of alpine hillslope geochemical response to temperature-induced hydrologic changes. [Doctoral Dissertation]. Colorado School of Mines; 2018. Available from: http://hdl.handle.net/11124/172221
Colorado School of Mines
14.
Zaharatos, Brian.
Statistical modeling of photovoltaic device performance.
Degree: PhD, Applied Mathematics and Statistics, 2015, Colorado School of Mines
URL: http://hdl.handle.net/11124/17121
► Accurate performance modeling of photovoltaic (PV) devices is important for increasing the usage, reliability, and bankability of solar energy. For example, performance modeling of PV…
(more)
▼ Accurate performance modeling of photovoltaic (PV) devices is important for increasing the usage, reliability, and bankability of solar energy. For example, performance modeling of PV devices can help reduce costs and spur deployment by giving confidence to system engineers, customers, lenders, and investors. The performance of a PV device is typically determined by measuring its current-voltage (I-V) characteristics. These measurements, along with a performance model such as the single-diode model, are used to estimate important device performance parameters such as the maximum power output under a range of operating conditions. Many possible approaches to estimating these parameters have been explored in the PV literature. However, to the best of our knowledge, a statistical approach to PV performance modeling using measured I-V characteristics and the single-diode model has not yet been studied. In this thesis, we study several aspects of parameter estimation for the single-diode model, often within a statistical framework, in order to provide more reliable estimates of PV performance parameters.
Advisors/Committee Members: Tenorio, Luis (advisor), Constantine, Paul G. (advisor), Navidi, William Cyrus (committee member), Campanelli, Mark (committee member), Mitcham, Carl (committee member), Porter, Aaron T. (committee member).
Subjects/Keywords: active subspaces; statistics; photovoltaics; Photovoltaic power generation – Statistical methods; Photovoltaic power generation – Measurement; Photovoltaic cells; Mathematical models; Statistics
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APA (6th Edition):
Zaharatos, B. (2015). Statistical modeling of photovoltaic device performance. (Doctoral Dissertation). Colorado School of Mines. Retrieved from http://hdl.handle.net/11124/17121
Chicago Manual of Style (16th Edition):
Zaharatos, Brian. “Statistical modeling of photovoltaic device performance.” 2015. Doctoral Dissertation, Colorado School of Mines. Accessed March 06, 2021.
http://hdl.handle.net/11124/17121.
MLA Handbook (7th Edition):
Zaharatos, Brian. “Statistical modeling of photovoltaic device performance.” 2015. Web. 06 Mar 2021.
Vancouver:
Zaharatos B. Statistical modeling of photovoltaic device performance. [Internet] [Doctoral dissertation]. Colorado School of Mines; 2015. [cited 2021 Mar 06].
Available from: http://hdl.handle.net/11124/17121.
Council of Science Editors:
Zaharatos B. Statistical modeling of photovoltaic device performance. [Doctoral Dissertation]. Colorado School of Mines; 2015. Available from: http://hdl.handle.net/11124/17121
Colorado School of Mines
15.
Li, Shuang.
Optimization for high-dimensional analysis and estimation in signal processing and machine learning.
Degree: PhD, Electrical Engineering, 2020, Colorado School of Mines
URL: http://hdl.handle.net/11124/174160
► High-dimensional signal analysis and estimation appears in many signal processing and machine learning applications, including modal analysis, airborne radar system demixing, parameter estimation in spectrally…
(more)
▼ High-dimensional signal analysis and estimation appears in many signal processing and machine learning applications, including modal analysis, airborne radar system demixing, parameter estimation in spectrally sparse signals, and simultaneous blind deconvolution and phase retrieval. The underlying low-dimensional structure in these high-dimensional signals inspires us to develop optimality guarantees as well as some optimization-based techniques for the fundamental problems in signal processing and machine learning.In many applications, high-dimensional signals often have a certain concise representation, which is a linear combination of a small number of atoms in a dictionary with elements drawn from the signal space. In compressive sensing,L1-minimization is a widely used framework to find the sparse representations of a signal. It has recently been shown that atomic norm minimization (ANM), which is a generalization of L1-minimization, is an efficient and powerful way for exactly recovering unobserved time-domain samples and identifying unknown frequencies in signals having sparse frequency spectra, namely, finding a concise representation for spectrally sparse signals. This new technique works on a continuous dictionary and can completely avoid the effects of basis mismatch, which can plague conventional grid-based compressive sensing techniques.Almost every problem in the fields of signal processing and machine learning can be formulated as either a convex or non-convex optimization problem. With convex formulations, we can get guaranteed global optimality but we often encounter problems with large size. Though non-convex optimization often lacks global optimality, it can have much lower computational and storage complexity. The objective of this dissertation is to (i) analyze and estimate high-dimensional signals or parameters with convex optimization-based techniques; (ii) analyze and estimate high-dimensional signals or parameters with non-convex optimization-based techniques; (iii) generalize the ideas and techniques used in optimization to differentiable games, which are games with continuous decision variables and differentiable cost functions, and have been gradually adapted to model many signal processing, communication, and networking problems in the last two decades.Our main contributions include a new (i) method to estimate the modal parameters in modal analysis, non-asymptotic bound on the sample complexity of modal analysis with random temporal compression, and non-asymptotic bound on the recovery error of an atomic norm denoising problem in the multiple measurement vector setting; (ii) analysis for the airborne radar system demixing problem, where the received signal consists of contributions from targets, jammers, and clutter; (iii) optimization-based perspective on the classical MUSIC algorithm that could lead to future developments and understanding, and non-asymptotic theoretical guarantees for the proposed algorithms; (iv) non-asymptotic theoretical bound on the mean square error of atomic…
Advisors/Committee Members: Wakin, Michael B. (advisor), Tang, Gongguo (advisor), Zhang, Hao (committee member), Tenorio, Luis (committee member), Vincent, Tyrone (committee member), Nayeri, Payam (committee member), Constantine, Paul G. (committee member).
Subjects/Keywords: signal processing; machine learning
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APA ·
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APA (6th Edition):
Li, S. (2020). Optimization for high-dimensional analysis and estimation in signal processing and machine learning. (Doctoral Dissertation). Colorado School of Mines. Retrieved from http://hdl.handle.net/11124/174160
Chicago Manual of Style (16th Edition):
Li, Shuang. “Optimization for high-dimensional analysis and estimation in signal processing and machine learning.” 2020. Doctoral Dissertation, Colorado School of Mines. Accessed March 06, 2021.
http://hdl.handle.net/11124/174160.
MLA Handbook (7th Edition):
Li, Shuang. “Optimization for high-dimensional analysis and estimation in signal processing and machine learning.” 2020. Web. 06 Mar 2021.
Vancouver:
Li S. Optimization for high-dimensional analysis and estimation in signal processing and machine learning. [Internet] [Doctoral dissertation]. Colorado School of Mines; 2020. [cited 2021 Mar 06].
Available from: http://hdl.handle.net/11124/174160.
Council of Science Editors:
Li S. Optimization for high-dimensional analysis and estimation in signal processing and machine learning. [Doctoral Dissertation]. Colorado School of Mines; 2020. Available from: http://hdl.handle.net/11124/174160
16.
Diaz, Paul Marcus.
Global sensitivity metrics from active subspaces with applications.
Degree: MS(M.S.), Applied Mathematics and Statistics, 2016, Colorado School of Mines
URL: http://hdl.handle.net/11124/170244
► Predictions from science and engineering models depend on input parameters. Global sensitivity metrics quantify the importance of input parameters, which can lead to model insight…
(more)
▼ Predictions from science and engineering models depend on input parameters. Global sensitivity metrics quantify the importance of input parameters, which can lead to model insight and reduced computational cost. Active subspaces are an emerging set of tools for identifying important directions in a model's input parameter space; these directions can be exploited to reduce the model's dimension enabling otherwise infeasible parameter studies. We develop global sensitivity metrics called activity scores from the estimated active subspace and analytically compare the active subspace-based metrics to established sensitivity metrics. These commonly used metrics include Sobol' indices derived from a variance-based decomposition and derivative-based metrics. Additionally, we outline practical computational methods to estimate the activity scores. We then consider three numerical examples with algebraic scalar valued functions from engineering and biological models. In each case, the models admit reduced dimensional active subspaces. For each of the models, a variety of sensitivity metrics are compared to the activity scores.
Advisors/Committee Members: Constantine, Paul G. (advisor), Pankavich, Stephen (committee member), Doostan, Alireza (committee member).
Subjects/Keywords: active subspaces; activity scores; Ebola; global sensitivity metrics; sensitivity analysis; Sobol
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APA (6th Edition):
Diaz, P. M. (2016). Global sensitivity metrics from active subspaces with applications. (Masters Thesis). Colorado School of Mines. Retrieved from http://hdl.handle.net/11124/170244
Chicago Manual of Style (16th Edition):
Diaz, Paul Marcus. “Global sensitivity metrics from active subspaces with applications.” 2016. Masters Thesis, Colorado School of Mines. Accessed March 06, 2021.
http://hdl.handle.net/11124/170244.
MLA Handbook (7th Edition):
Diaz, Paul Marcus. “Global sensitivity metrics from active subspaces with applications.” 2016. Web. 06 Mar 2021.
Vancouver:
Diaz PM. Global sensitivity metrics from active subspaces with applications. [Internet] [Masters thesis]. Colorado School of Mines; 2016. [cited 2021 Mar 06].
Available from: http://hdl.handle.net/11124/170244.
Council of Science Editors:
Diaz PM. Global sensitivity metrics from active subspaces with applications. [Masters Thesis]. Colorado School of Mines; 2016. Available from: http://hdl.handle.net/11124/170244
17.
Gilbert, James M.
Exploring catchment connections with integrated hydrologic models: system interactions and responses to groundwater extraction and climate change in the San Joaquin River basin.
Degree: PhD, Geology and Geological Engineering, 2016, Colorado School of Mines
URL: http://hdl.handle.net/11124/170449
► The water that we rely on exists as the result of complex interacting processes that occur over a range of temporal and spatial scales. Historically…
(more)
▼ The water that we rely on exists as the result of complex interacting processes that occur over a range of temporal and spatial scales. Historically hydrologic research has been directed at the study of individual processes or components of the larger hydrologic or water resource system, but the advent of sophisticated integrated hydrologic simulation tools in recent decades has enabled a more comprehensive approach to studying the factors that control the quantity, timing, and location of water in the environment. Specifically, such tools provide a platform through which to quantify fluxes and stores in a physically consistent way across large spatial and temporal extents and to test and isolate the impact of specific anthropogenic changes within and among connected hydrologic domains like the subsurface, land surface, and the atmosphere. This dissertation makes use of the integrated hydrologic modeling platform built around ParFlow (i.e. ParFlow-CLM and ParFlow-WRF) to explore the nature of hydrologic connections and the propagation of change across the regional-scale San Joaquin River basin system. Simulations of the integrated land surface and subsurface system expose the dependence of the Central Valley aquifer on the adjacent mountain blocks while highlighting the dynamic interaction of surface processes in supporting streamflow and groundwater-surface water interactions. Analysis of atmospheric response over a region of declining groundwater levels shows that boundary layer height is directly tied to water table depth, although local increases in boundary layer height depend on the regional configuration of the water table. Atmospheric perturbations translate to changes in terrestrial hydrology as well. Simulations of uniform warming across the basin shows that increasing temperatures initiate a cascade of effects that starts with a shift from snow to rainfall and declining snowpack and propagates through an elevation-dependent shift in runoff, evapotranspiration, and saturated groundwater recharge. These local scale effects produce an aggregate response characterized by precipitation-dependent decreases in streamflow and increases in evapotranspiration.
Advisors/Committee Members: Maxwell, Reed M. (advisor), Constantine, Paul G. (committee member), Fogg, Graham E. (committee member), Singha, Kamini (committee member).
Subjects/Keywords: climate warming; integrated hydrology; simulation; groundwater; California; San Joaquin River
…privilege during my time at
the Colorado School of Mines. Second, I offer many thanks to my PhD… …administered between the
University of California, Davis and the Colorado School of Mines. NCAR’s… …resources were
provided by the Golden Energy Computing Organization at the Colorado School of… …School of Mines, Golden, Colorado, USA
2
Climate Change, Water, and Society (CCWAS)… …Mines using
resources acquired with financial assistance from the National Science Foundation…
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APA (6th Edition):
Gilbert, J. M. (2016). Exploring catchment connections with integrated hydrologic models: system interactions and responses to groundwater extraction and climate change in the San Joaquin River basin. (Doctoral Dissertation). Colorado School of Mines. Retrieved from http://hdl.handle.net/11124/170449
Chicago Manual of Style (16th Edition):
Gilbert, James M. “Exploring catchment connections with integrated hydrologic models: system interactions and responses to groundwater extraction and climate change in the San Joaquin River basin.” 2016. Doctoral Dissertation, Colorado School of Mines. Accessed March 06, 2021.
http://hdl.handle.net/11124/170449.
MLA Handbook (7th Edition):
Gilbert, James M. “Exploring catchment connections with integrated hydrologic models: system interactions and responses to groundwater extraction and climate change in the San Joaquin River basin.” 2016. Web. 06 Mar 2021.
Vancouver:
Gilbert JM. Exploring catchment connections with integrated hydrologic models: system interactions and responses to groundwater extraction and climate change in the San Joaquin River basin. [Internet] [Doctoral dissertation]. Colorado School of Mines; 2016. [cited 2021 Mar 06].
Available from: http://hdl.handle.net/11124/170449.
Council of Science Editors:
Gilbert JM. Exploring catchment connections with integrated hydrologic models: system interactions and responses to groundwater extraction and climate change in the San Joaquin River basin. [Doctoral Dissertation]. Colorado School of Mines; 2016. Available from: http://hdl.handle.net/11124/170449
. 
Open Access Theses and Dissertations
