Browsing by Subject "modeling"

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Advanced Modeling and Simulation of Turbulent Sprays
(2012-06-13) Liu, Wanjiao; Garrick, Sean C.
Spray and atomization have been extensively studied in the past due to their broad applications in areas such as agricultural spraying, chemical coatings, pharmaceutical synthesis, inhalation aerosols, fuel spray in engines, and so on. Droplet size distribution and breakup pattern are the most important characteristics of spray since it determines the performance, efficiency, or safety. For example, in agricultural spray the goal is to control the number of fine droplets with diameter of 100 micron or less, since they will drift in air and causing contamination and damage to non-target crops, animals, and human.
Biopolymer Simulations: From Next-Generation Genomics to Consumer Products
(2018-04) Li, Xiaolan
Biopolymers have many unique properties which play an essential and pervasive role in everyday life, thus making them attractive for engineering applications. Understand- ing how the particular properties of biopolymers give rise to important applications in technology remains a long-standing challenge. Although biopolymers can have different chemistries, they share some common physical properties: high molecular weights, stiff backbones, and complex internal structures. Computer simulation, therefore, plays quite an important role since it provides a way to study a generic model that, by changing the parameters appearing in the model, permits studying a wide variety of biopolymers. Specifically, we focus on two such biopolymers: DNA and methylcellulose. This thesis focuses on studying the universal properties of the two aforementioned biopolymers using novel molecular simulation techniques. DNA attracts particularly strong interest not only because of its fascinating double- helix structure but also because DNA carries biological information. Genomic mapping is emerging as a new technology to provide information about large-scale genomic structural variations. In this context, the conformation and properties of the linearized DNA are only beginning to be understood. With a Monte Carlo chain growth method known as pruned-enriched Rosenbluth method, we explore the force-extension relationship of stretched DNA. In this scenario, external forces and confinement are two fundamental and complementary aspects. We begin by stretching a single DNA in free solution. This allows separation of restrictions imposed by forces from that by walls. This work shows that the thickness of DNA plays an important role in the force-extension behavior. The key outcome is a new expression that approximates the force-extension behavior with about 5% relative error for all range of forces. We then analyze slit-confined DNA stretched by an external force. This work predicted a new regime in the force-extension behavior that features a mixed effect of both sensible DNA volume and sensible wall effects. We anticipate such a complete description of the force-extension of DNA will prove useful for the design of new genomic mapping technologies. The dissertation also involves another biopolymer, methylcellulose, which has an extremely wide range of commercial uses. Methylcellulose is thermoresponsive polymer that undergoes a morphological transition at elevated temperature, forming uniform diameter fibrils. However, mechanisms behind the solution-gel transition are poorly understood. Following the computational studies by Huang et al. [1], we apply Langevin dynamics simulations to a coarse-grained model that produces collapsed ring-like structures in dilute solution with a radius close to the fibrils observed in experiments. We show that the competition between the dihedral potential and self-attraction causes these collapsed states to undergo a rapid conformational change, which helps the chain to avoid kinetic traps by permitting a transition between collapsed states. We expect our findings from computational studies of biopolymers will not only provide a deep understanding of semiflexible polymer physics but also inspire novel engineering applications relying on the properties of biopolymers.
Compilation Geologic Model for Cannon River Watershed: A Pilot Project
(Minnesota Geological Survey, 2022-07) Steenberg, Julia R; Retzler, Andrew J; Hamilton, Jacqueline D; Francis, Sarah W
This report is a summary of year one of a two-year pilot project conducted by the Minnesota Geological Survey for the Minnesota Department of Health Groundwater Restoration and Protection Strategies (GRAPS) program designed to support watershed planning efforts in the Cannon River Watershed. Our goal was to provide a compilation of both surface and subsurface geologic data within selected Board of Water and Soil Resources One Watershed One Plan boundaries in a format suitable for both modelers and the general public. Seamless geologic products provided within the watershed are based on a compilation of previously published MGS maps along with new mapping where necessary. Compilation methods and limitations associated with the subsurface modeling processes are described in the report. These products were transferred into web-based 3D models so they could be readily visualized and used outside of a GIS environment by water planners, other state agencies involved in the GRAPS process, and the public. The 3D model is available online at https://arcg.is/09OS1L0.
Compilation Geologic Model for Missouri River Watershed: A Pilot Project
(Minnesota Geological Survey, 2022-07) Steenberg, Julia R; Retzler, Andrew J; Hamilton, Jacqueline D; Francis, Sarah W
This report is a summary of year one of a two-year pilot project conducted by the Minnesota Geological Survey for the Minnesota Department of Health Groundwater Restoration and Protection Strategies (GRAPS) program designed to support watershed planning efforts in the Missouri River Watershed. Our goal was to provide a compilation of both surface and subsurface geologic data within selected Board of Water and Soil Resources One Watershed One Plan boundaries in a format suitable for both modelers and the general public. Seamless geologic products provided within the watershed are based on a compilation of previously published MGS maps along with new mapping where necessary. Compilation methods and limitations associated with the subsurface modeling processes are described in the report. These products were transferred into web-based 3D models so they could be readily visualized and used outside of a GIS environment by water planners, other state agencies involved in the GRAPS process, and the public. The 3D model is available online at https://arcg.is/1iimH50.
Compilation Geologic Model for Redeye River Watershed: A Pilot Project
(Minnesota Geological Survey, 2022-07) Steenberg, Julia R; Retzler, Andrew J; Hamilton, Jacqueline D; Francis, Sarah W
This report is a summary of year one of a two-year pilot project conducted by the Minnesota Geological Survey for the Minnesota Department of Health Groundwater Restoration and Protection Strategies (GRAPS) program designed to support watershed planning efforts in the Redeye River Watershed. Our goal was to provide a compilation of both surface and subsurface geologic data within selected Board of Water and Soil Resources One Watershed One Plan boundaries in a format suitable for both modelers and the general public. Seamless geologic products provided within the watershed are based on a compilation of previously published MGS maps along with new mapping where necessary. Compilation methods and limitations associated with the subsurface modeling processes are described in the report. These products were transferred into web-based 3D models so they could be readily visualized and used outside of a GIS environment by water planners, other state agencies involved in the GRAPS process, and the public. The 3D model is available online at https://arcg.is/15Gnz02.
Computational and Experimental Comparison on the Effects of Flow-Induced Compression on the Permeability of Collagen Gels
(2020-08) Vidmar, Chris
Collagen is a fibrous material and is ubiquitous throughout the human body. It is a biphasic material, consisting of a solid fibrous matrix and interstitial fluid. Collagen is one of the primary components within the extracellular matrix, which plays a vital role in the physiological, mechanical, and transport functions of various systems and processes of the body. Understanding the mechanical and transport properties of collagen can help us understand the roles and processes of the extracellular matrix. Additionally, understanding these properties may lead to more rational design choices in tissue engineering, where the permeability of the biomaterial in tissue engineering is critical for the transport of nutrients. The underlying goal of this study is to experimentally determine and to develop a finite element model showing the effect of concentration and compression of collagen gels on permeability. In this study, two methods to determine the permeability of collagen gels was developed. With both methods, the interstitial fluid of collagen gels was expelled under a pressure load, resulting in compressed collagen gels that were denser than the starting gels. The permeability of collagen gels was determined using Darcy’s Law. In the vertical apparatus, a changing height of fluid pushed water through and compressed a collagen sample. In the horizontal apparatus, a syringe pump delivered water through three collagen concentrations (1.98 mg/mL, 3.5 mg/mL, 5 mg/mL) at a constant volumetric flow rate of 0.85 ml/min. Instantaneous permeability values were obtained at various points of compression and fitted to the α and M values of the strain-dependent Holmes-Mow permeability model where α and M are defined as intrinsic permeability parameters. A finite element model was developed to model the biphasic compression of the collagen gels using FEBio. A neo-Hookean material was used to model the solid matrix and Young’s modulus was changed to match the degree of compression. The vertical apparatus found a higher permeability compared to the horizontal apparatus. The vertical apparatus showed a permeability of 2.37 x 10-11 ± 2.4 x 10-11 m2. The initial permeability doubled as the collagen went from a starting concentration of 5 mg/mL to a starting concentration of 1.98 mg/mL. Each concentration compressed to a final concentration of about 12 mg/mL, resulting in no dependence on starting concentration for the permeability of compressed samples. The M values of the Holmes-Mow model increased from 2.4 to 5 with increasing concentration, while the α value decreased from 1.3 to 0.5 with increasing concentration. The Young’s modulus found by the finite element model increased from 200 to 3700 Pa with increasing initial collagen concentration. The Young’s modulus determined in the current study was similar to the short-time modulus of other published works.
Data-Driven Framework for Energy Management in Extended Range Electric Vehicles Used in Package Delivery Applications
(2020-08) Wang, Pengyue
Plug-in Hybrid Electric Vehicles (PHEVs) have potential to achieve high fuel efficiency and reduce on-road emissions compared to engine-powered vehicles when using well-designed Energy Management Strategies (EMSs). The EMS of PHEVs has been a research focus for many years and optimal or near optimal performance has been achieved using control-oriented approaches like Dynamic Programming (DP) and Model Predictive Control (MPC). These approaches either require accurate predictive models for the trip information during driving cycles or detailed velocity profiles in advance. However, such detailed information is not feasible to obtain in some real-world applications like the delivery vehicle application studied in this work. Here, data-driven approaches were developed and tested over real-world trips with the help of two-way Vehicle-to-Cloud (V2C) connectivity. First, the EMS problem was formulated as a probability density estimation problem and solved by Bayesian inference. The Bayesian algorithm deals with the condition where only small amounts of data are available and sequential parameter estimation problem elegantly, which matches the characteristics of the data generated by delivery vehicles. The predicted value of the parameter for the next trip is determined by the carefully designed prior information and all the available data of the vehicle so far. The parameter is updated before the delivery tasks using the latest trip information and stays static during the trip. This method was demonstrated on 13 vehicles with 155 real-world delivery trips in total and achieved an average of 8.9% energy efficiency improvement with respect to MPGe (miles per gallon equivalent). For vehicles with sufficient data that can represent the characteristics of future delivery trips, the EMS problem was formulated as a sequential decision-making problem under uncertainty and solved by deep reinforcement learning (DRL) algorithms. An intelligent agent was trained by interacting with the simulated environment built based on the vehicle model and historical trips. After training and validation, optimized parameter in the EMS was updated by the trained intelligent agent during the trip. This method was demonstrated on 3 vehicles with 36 real-world delivery trips in total and achieved an average of 20.8% energy efficiency improvement in MPGe. Finally, I investigated three problems that could be encountered when the developed DRL algorithms are deployed in real-world applications: model uncertainty, environment uncertainty and adversarial attacks. For model uncertainty, an uncertainty-aware DRL agent was developed, enabled by the technique of Bayesian ensemble. Given a state, the agent quantifies the uncertainty about the output action, which means although actions will be calculated for all input states, the high uncertainty associated with unfamiliar or novel states is captured. For environment uncertainty, a risk-aware DRL agent was built based on distributional RL algorithms. Instead of making decisions based on expected returns as standard RL algorithms, actions were chosen with respect to conditional value at risk, which gives more flexibility to the user and can be adapted according to different application scenarios. Lastly, the influence of adversarial attacks on the developed neural network based DRL agents was quantified. My work shows that to apply DRL agents on real-world transportation systems, adversarial examples in the form of cyber-attack should be considered carefully.
An E. coli cell-free transcription- translation system: modeling gene expression and characterizing CRISPR elements and gene circuits
(2019-09) Marshall, Ryan
Cell-free transcription-translation systems are versatile tools for rapid prototyping and characterization of biological systems and processes. Proteins can be expressed and measured in a matter of hours, whereas in vivo experiments often take days to weeks because they require protein purification or live cell transformations and cultures. TXTL systems, however, are still lacking in simple models that quantitatively describe the behavior of reactions. Here, we present an model of the all E. coli TXTL system using ordinary differential equations, encompassing the limited concentrations of transcription and translation machineries, capturing the linear and saturated regime of gene expression. Many biochemical constants are determined through experimental assays. We then show how this TXTL system was used to characterize CRISPR technologies. CRISPR-Cas systems have huge potential to be used as tools for genome engineering, as well as gene silencing and regulation. We characterize a set of sgRNAs, CRISPR nucleases, anti- CRISPR proteins, and determine protospacer-adjacent motifs. Finally, we use the TXTL system to execute gene circuits, including an IFFL and an integral controller.
Genetic Variants Associated with Tacrolimus Metabolism in Kidney Transplant Recipients
(2023-08) Dorr, Casey
This master’s thesis focuses on the work completed during my K01 award Genetic Variants Associated with Tacrolimus (TAC) metabolism in Kidney Transplant Recipients. In Chapter 1, I discuss the significance and innovations of this project. In Chapter 2, I present reformatted manuscript published in the Pharmacogenomics Journal titled: Identification of genetic variants associated with tacrolimus metabolism in kidney transplant recipients by extreme phenotype sampling and next generation sequencing. In Chapter 3, I present a reformatted manuscript published in Drug Metabolism and Disposition titled: CRISPR/Cas9 genetic modification of CYP3A5 *3 in human hepatocytes leads to cell lines with increased midazolam and tacrolimus metabolism. Chapter 4 is the general conclusions, future directions and take away messages.
High-rate Resource Recovery from Wastewater with Encapsulated Biomass
(2020-01) ZHU, KUANG
This dissertation describes the recovery of a high-value resource during anaerobic wastewater treatment using encapsulated biomass with specialized functions. The encapsulant was formed into a bead and consisted of a customizable alginate gel matrix. Biomass was encapsulated within the bead, enabling the retention of high concentrations of specific communities of biomass in reactors even when operating reactors with a low hydraulic retention time (HRT). The effects of encapsulant customization, including that of cross-linking agents (Ca2+, Sr2+, and Ba2+) and a composite coating on the beads (alternating layers of polyethylenimine (PEI) and silica hydrogel), on the biomass retention ability and mass transport performance was quantified. The diffusion of the organic carbon in brewery wastewater through the alginate encapsulation matrix was not affected by the cross-linking agent and was comparable to that of glucose in water. As a result, the biomass encapsulated in uncoated beads was not substrate limited and high rates of hydrogen production from brewery wastewater were observed, even at an HRT of 45 min. Suspended biomass controls were not able to maintain hydrogen production at this low HRT because the biomass was washed out. Although the coating reduced the biomass escape rate from the encapsulant, it created a mass transport barrier to substrates, reducing both the diffusivity and the partition coefficient of organic carbon. This resulted in lower hydrogen production rates from brewery wastewater compared to the uncoated encapsulation system. A diffusion-reaction model describing the encapsulation system was also developed to predict, and therefore optimize, the hydrogen production rate under various encapsulant customization schemes and operating conditions. Experimental data collected from flow-through reactors with encapsulated biomass fed brewery wastewater were used to calibrate and validate the model. The model was capable of successfully predicting the general hydrogen production trends as a function of HRT, bead size, and wastewater strength. A sensitivity test conducted with the model revealed that the hydrogen production process with encapsulated biomass from brewery wastewater was growth limited and was sensitive to the substrate partition coefficient into the encapsulation matrix, initial encapsulated biomass concentration, and the total volume of beads in the reactor. The effect of encapsulation on hydrogen and methane production when encapsulated biomass was incubated in the presence of several known inhibitors was also investigated to determine whether and how the encapsulating matrix mitigated or exacerbated inhibition by different types of chemicals. The charge of the inhibitors appeared to play a dominant role in how they partitioned into the encapsulation matrix. Dichromate (negatively charged) appeared to be repelled by the alginate matrix while ammonium (positively charged) concentrated into the matrix. Chloroform (uncharged) was unaffected by the matrix and was neither repelled by nor concentrated into it. This was thought to be a result of electrostatic interactions with alginate. As a result, the matrix mitigated dichromate inhibition, increased ammonium inhibition, and had no impact on chloroform inhibition of the encapsulated biomass. Copper, on the other hand, chelated with alginate and the PEI coating, even though it partitioned into the matrix, appeared to be non-bioavailable, completely eliminating inhibition of the hydrogen-producing biomass. These results were also confirmed with an encapsulated methane-producing anaerobic community, demonstrating that the ability of the encapsulant to mitigate or exacerbate inhibition was applicable beyond hydrogen-producing biomass. Finally, a pilot-scale system was built and deployed at a brewery. The system consisted of a single hydrogen-producing reactor containing encapsulated biomass in series with parallel methane-producing reactors, one containing encapsulated biomass and a second containing suspended biomass in a membrane bioreactor configuration. Performance during intermittent operation and perturbations was monitored along with shifts in the microbial community in the two parallel methane-producing reactors. A more rapid recovery after perturbation was observed in the membrane bioreactor. In addition, its microbial community was similar to that sampled from the bulk solution of the reactor containing encapsulated biomass. The encapsulated biomass had a distinct microbial community structure, even though both reactors were inoculated with the same culture. This demonstrated that the community in the membrane bioreactor was able to adapt and change with time, apparently enabling faster recovery from perturbations. This appears to be a potential problem with encapsulated biomass, particularly if highly variable wastewater is being fed to the reactors or the system is expected to experience upsets and operational perturbations. This multi-faceted investigation of a customizable alginate encapsulation system for high-rate recovery of resources during anaerobic wastewater treatment provided insights regarding how to design the system for good performance. It also provided further information regarding potential problems that could be encountered when using encapsulated biomass for treatment. Overall this system offers the potential for low-maintenance decentralized anaerobic wastewater treatment. More work is needed, however, to facilitate robust and reliable treatment and to provide guidance for system optimization and further life cycle assessment.
Induced nest failure as a mechanism for controlling invasive smallmouth (Micropterus dolomieu) and largemouth bass (Micropterus salmoides)
(2017-02) Loppnow, Grace
Mathematical modeling for assorted problems in crystal growth
(2019-12) Wang, Kerry
Crystal growth is a field that is ripe with opportunities for mathematical modeling to elucidate interesting phenomena. Important process parameters such as solute concentration, interface shape and location, and temperature field are uniquely difficult to observe \textit{in-situ} for many high temperature melt crystal growth systems. Additionally, the slow process of growing large, industrially-relevant single crystals can be prohibitive in time, material cost, and labor for tedious repeated experimental studies that are likely to be destructive. Modeling provides an efficient way for researchers to quickly gain an understanding of the physics underlying a crystal growth system. In this thesis, we examine three different cases where mathematical modeling can be utilized to interrogate crystal growth systems. First, we investigate the transport of oxygen in Czochralkski-grown silicon by posing a simple lumped-parameter model. The lumped-parameter model tracks transport of oxygen into and out of the melt without specifying its spatial distribution, relying only on estimated fluxes from various surfaces. The lumped-parameter model offers a near-instantaneous way to obtain a coarse estimate of oxygen given process parameters such as crystal/crucible rotation scheme, melt height, and melt overheating. Second, we examine a past experiment involving Europium-doped BaBrCl monitored \textit{in-situ} via Energy-Resolved Neutron Imaging. Europium acts as a strong neutron attentuator, allowing visualization of its migration in both the solid and melt phases. A prior experiment was conducted to perform \textit{in-situ} imaging of a melt crystal growth system, and we realized this presented an opportunity to use modeling to extract additional data from this past experiment. A 1D model of europium migration in both phases was formulated and solve via Finite Fourier Transforms and Finite Difference Method. The Finite Difference Method, being more flexible, allowed us to deduce the apparent solid and liquid diffusion coefficients of Eu as well as its segregation coefficient. This coupling of \textit{in-situ} imaging and modeling presents an exciting new way to measure physical properties and extract additional value from past experiments. Last, we analyze the curious phenomenon of Temperature Gradient Zone Melting (TGZM), whereby a solute-rich liquid particle migrates through a solid crystal under a thermal gradient. While this phenomenon has been studied in the past, prior models failed to give practical predictions in the time-evolution behavior of such migrating particles. We pose analytical and numerical models of 1-dimensional TGZM, which agree well with each other. The numerical model, solved via Finite Element Method, shows reasonable agreement with experimental data on Te-rich second-phase particles migrating in CdTe. It additionally shows excellent agreement with another physical system, NaCl brine particles in water ice, providing a far more accurate description of the particle's migration than previous theoretical models. Considerations are made for extending the model to higher dimensions in order to understand changes in particle morphology during migration. Different types of modeling using various analytical and numerical techniques are employed for each of these case studies. These three example cases show different scenarios in which mathematical modeling can be utilized to help researchers gain insight in crystal growth systems.
Modeling and Analysis of Small-Scale Hydraulic Systems
(2015-05) Xia, Jicheng
OBJECTIVE To determine the scaling law and design guidelines of small-scale hydraulic systems whose output power is in the range of 10 to 100 Watts. METHODS Fundamental fluid mechanics equations were employed to model the friction and leakage losses in the hydraulic components including cylinders, hoses, and pumps. Basic structural design equations were deployed to predict their weight. Customized test stands were built to validate the efficiency models, and catalog data of o-the-shelf components was compiled to validate the weight models. The electro-mechanical components including electric motors, gear heads and batteries were modeled using their catalog data. RESULTS The efficiency and the weight of both hydraulic and electro-mechanical components were modeled in analytical forms. These models were validated against either experimental data or existing catalog data. CONCLUSION The analytical models suggested the following design guidelines: first, high operating pressure is needed for hydraulic actuation systems to weigh lighter than equivalent electro-mechanical systems; second, critical dimension thresholds exist for hydraulic and electro-mechanical components, which should not be exceeded to achieve reasonable system efficiency; third, component efficiency plays a more important role than component weight to gain higher system power density; lastly, for applications where the actuator system weight matters the most, high pressure small scale hydraulic systems are preferred over electro-mechanical systems, but for applications where the overall system weight matters the most, electro-mechanical systems work better.
Modeling of the signaling networks in patterning and growth control of the Drosophila wing disc
(2016-01) Lin, Lin
A major challenge in understanding patterning and growth control is how the signaling pathways are balanced to produce normal pattern and growth and how they interact to respond to aberrant signals. In the dissertation, we aim to develop a mathematical model which incorporates the Hippo pathway locating at the center of different regulatory pathways in the wing disc of Drosophila so as to be able to understand existing experimental results, to make experimentally-testable predictions, and to provide a platform for integrating and testing new results and incorporating other signaling pathways. The model we developed addresses the limitation of previous models due to lack of mechanistic details, and predicts all the primary characteristic phenotypes associated with the pathway. Moreover, the model supports two hypotheses, one of which have been confirmed by experiments. As using a mathematical model to facilitate the development of biology is contingent on parameters, the other specific aim of our work is to propose a new way to improve parameter estimation from experimental data. We identify the source for poor estimation in Fluorescence recovery after photobleaching (FRAP), a widely-used technique for quantitative measurement of molecular dynamics, and propose three feasible ways to improve parameter estimation. In addition, we also introduce sensitivity analysis to improve model identification in FRAP.
Modeling of Transport Phenomena in Two-Dimensional Semiconductors
(2016-12) Liu, Yue
Recently, transition metal dichalcogenides and black phosphorus (BP) emerged as new 2D semiconductors due to the advantages of moderate energy band gap, high carrier mobility, ultra thin film and high anisotropy. Together with graphene, 2D materials have been utilized in the development of biomedical devices, touch screen and display technologies, and flexible applications such as wearable electronics and IoT devices. They also open up new opportunities in research fields including spintronics, optoelectronics and next generation post-silicon transistor. In this dissertation, we present theoretical modeling for several topics related to 2D materials. Starting with the fundamental tight-binding theory of graphene, we review electronic properties for graphene including massless 2x2 Dirac Hamiltonian and pseudo-spin wave function. Followed by discussion of ballistic transport, a detailed analysis on graphene diffusive transport is provided. Ionized impurity scattering and carrier screening effect is considered in the model. The momentum relaxation time and mobility for graphene is modeled. A non-linear Thomas Fermi screening is introduced to improve the simulation accuracy. Taking the real spin into account, the new Hamiltonian is a 4x4 matrix. An external field perpendicular to the graphene breaks the reflection symmetry and introduces a Rashba spin-orbit interaction, which couples pseudo-spin and real spin. The relevant charge carrier states are no longer spin eigenstates. Rashba interaction is found to be quite small compared to Coulomb impurity scattering. To characterize the spin-polarized electrons tunneling from electrodes and transport in graphene, a spin valve device modeling and magnetoresistance calculation is developed. Black phosphorus possesses excellent properties like other 2D materials for high performance nanoelectronic applications. Moreover, there is a uniquely high in-plane anisotropy in BP due to its puckered crystal structure. To model the anisotropic transport, a model based on the BTE is developed, considering the full anisotropic electronic structure. For zero temperature calculation with ionized impurity limited scattering, anisotropy ratio 3-4 can be obtained from the model. Due to the dominating effect of screening, mobility is found to decrease weakly with increasing temperature. For , a smaller anisotropy ratio of 1.8-3.5 matching experimental measurements indicates that impurity scattering is an important mechanism for black phosphorus.
Modeling the commute mode share of transit using continuous accessibility to jobs
(2013-09) Owen, Andrew
This research develops an accessibility-based model of aggregate commute mode share, focusing on the share of transit relative to auto. It demonstrates the use of continuous accessibility -- calculated continuously in time, rather than at a single or a few departure times -- for the evaluation of transit systems. These accessibility calculations are accomplished using only publicly-available data sources. Multiple time thresholds for a cumulative opportunities measure of accessibility are evaluated for their usefulness in modeling transit mode share. A binomial logit model is estimated which predicts the likelihood that a commuter will choose transit rather than auto for a commute trip based on aggregate characteristics of the surrounding area. Variables in this model include demographic factors as well as detailed accessibility calculations for both transit and auto. The model achieves a pseudo-R-sqaure value of 0.597, and analysis of the results suggests that continuous accessibility of transit systems may be a valuable tool for use in modeling and forecasting. It may be possible to apply these techniques to existing models of transit ridership and mode share to improve their performance and cost-effectiveness.
A Newtonian Development of the Mean-Axis Dynamics with Example and Simulation
(2017-05) Keyes, Sally
Mean-axis models of flight dynamics for flexible aircraft are being utilized more frequently in dynamics and controls research. The mean-axis equations of motion are traditionally developed with Lagrangian mechanics and are typically simplified using assumptions regarding the effects of elastic deformation. Although widely accepted in literature, the formulation and assumptions may be confusing to a user outside of the flight dynamics field. In this thesis, the equations of motion are derived from first principles utilizing Newtonian mechanics. Using this framework, the formulation offers new insight into the equations of motion and explanations for the assumptions. A three-lumped-mass idealization of a rolling flexible aircraft is presented as an example of the mean-axis equations of motion. The example is used to investigate the effects of common simplifying assumptions. The equations of motion are developed without any such assumptions, and simulation results allow for a comparison of the exact and simplified dynamics.
OFR21-02, Pilot Multi-county Modeling Synthesis For Bonanza Valley Groundwater Management Area
(Minnesota Geological Survey, 2019) Tipping, Robert G
This report reviews current subsurface unconsolidated sediment modeling methods at MGS to address how model application to regional investigations can be improved in several fundamental ways: 1.) reduce errors and redundancy in final subsurface models that are artifacts of the modeling process itself, including linearity along cross-section lines in both elevation and map unit extent, unintended gaps in map units between cross sections, and lithostratigraphic formation subdivision to accommodate sand bodies within formations ; 2.) quantify uncertainty in modeling subsurface sand and gravel; and 3.) provide a work plan and method for subsurface models to remain current within shorter time frames as new data become available.
OFR21-03, Compilation Geologic Model for Zumbro River Watershed: A Pilot Project
(Minnesota Geological Survey, 2021-06) Steenberg, Julia; McDonald, Jennifer; Retzler, Andrew; Hamilton, Jacqueline
This report is a summary of year one of a two-year pilot project between the Minnesota Geological Survey and the Minnesota Department of Health Groundwater Restoration and Protection Strategies (GRAPS) program designed to support watershed planning efforts in the Zumbro River Watershed. Our goal was to provide a compilation of both surface and subsurface geologic data within selected Board of Water and Soil Resources One Watershed One Plan boundaries in a format suitable for both modelers and the general public. Seamless geologic products provided within the watershed are based on a compilation of previously published MGS maps along with new mapping where necessary. Compilation methods and limitations associated with the subsurface modeling processes are described in the report. These products were transferred into web-based 3D models so they could be readily visualized and used outside of a GIS environment by water planners, other state agencies involved in the GRAPS process, and the public. The 3D model is available online at https://arcg.is/fevGS.
OFR21-08, Compilation Geologic Model for St. Louis River Watershed: A Pilot Project
(Minnesota Geological Survey, 2021-08) Steenberg, Julia R; Retzler, Andrew J; Wagner, Kaleb G; Hamilton, Jacqueline D
This report is a summary of year one of a two-year pilot project conducted by the Minnesota Geological Survey for the Minnesota Department of Health Groundwater Restoration and Protection Strategies (GRAPS) program designed to support watershed planning efforts in the St. Louis River Watershed. Our goal was to provide a compilation of both surface and subsurface geologic data within selected Board of Water and Soil Resources One Watershed One Plan boundaries in a format suitable for both modelers and the general public. Seamless geologic products provided within the watershed are based on a compilation of previously published MGS maps along with new mapping where necessary. Compilation methods and limitations associated with the subsurface modeling processes are described in the report. These products were transferred into web-based 3D models so they could be readily visualized and used outside of a GIS environment by water planners, other state agencies involved in the GRAPS process, and the public. The 3D model is available online at https://arcg.is/1mbDPC.

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