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Bistable DVR meta-structure: A reinforcement learning approach to vibration control
No full textThis research introduces a data-driven approach to vibration control, utilizing programmable bandgap metastructures tailored for applications such as cargo protection. Central to this design are bistable dynamic vibration absorbers (DVRs), which leverage a dual-state mechanism to enhance energy dissipation and improve vibration isolation under varying dynamic loads. The study employs a finite element approach to model the dynamic behavior of these metastructures, simulating their response to different forcing conditions. We then utilize artificial neural networks (ANNs) for predictive modeling of the metastructures’ characteristics to various DVR configurations, thereby enhancing their real-time adaptability. Additionally, we integrate reinforcement learning (RL) algorithms to dynamically adjust the bandgap behavior of the metastructures, allowing for on-the-fly tuning of their vibrational characteristics. This approach proves highly effective in scenarios with diverse vibration profiles. Experimental results demonstrate the efficacy of this comprehensive strategy, showcasing significant resonance frequency shifts and improved vibration absorption characteristics. This approach offers a robust solution for dynamic adaptation in various vibrational environments
ThermalTrack Dataset- Training Images- Fused RGB LWIR- sequence 2
Get PDFWe present a wheel track detection system that leverages RGB- Thermal (RGB-T) imaging, where thermal channels reveal critical temperature differentials between compacted tracks and loose snow- tracks exhibit higher thermal inertia and lower reflectivity, emitting stronger radiation signatures even in visually homogeneous conditions. By fusing these distinctive thermal patterns with RGB spatial information, our method reliably identifies navigable tracks, enabling robust path-following in complete white-out conditions where snow textures and terrain features become indistinguishable
INVESTIGATING DIMENSIONS OF SOCIAL VULNERABILITY TO WILDFIRE: A CASE STUDY OF WESTERN MONTANA
Get PDFCommunities across the US are facing increased wildfire risks due in part to historic fire suppression efforts, a warming climate, and an influx of people residing in wildland urban interface (WUI) landscapes. Because of these increasing risks, there have been growing concerns about the social factors that can increase individual and community vulnerability to wildfires. This research adds to the discussion of social vulnerability by examining how people living in a geographic area with heightened wildfire risk think about the ways in which people can be more or less vulnerable to wildfires. Using semi-structured interviews, round table discussions, and field notes, our research team found that various social dimensions contribute to vulnerability, including: living stress (how much time, money, and support a person might have in meeting daily needs), housing type, physical residential location and related infrastructure, age, community-level planning and resources, social norms, insurance, and ways in which wildfires threaten people’s ability to meet livelihoods
LAND REMATRIATION: UTILIZING THE NATIONAL REGISTER OF HISTORIC PLACES AND DEVELOPING TRIBAL HOMELAND TERRITORIES FOR THE RESTORATION OF HISTORIC LANDSCAPES AND SOVEREIGNTY
Get PDFLand rematriation and cultural revitalization are crucial to addressing the ongoing impacts of settler colonialism on Indigenous communities, particularly for the Lac Vieux Desert Band of Lake Superior Chippewa. The National Register of Historic Places and federal recognition processes have traditionally marginalized Indigenous practices and land claims, yet, as I argue in this thesis, they hold potential for reappropriation in support of sovereignty and heritage. This thesis argues that integrating Indigenous methodologies, geospatial research, and archival analyses can forge a path toward effective land rematriation efforts. My findings reveal culturally significant sites connected to the historic village of Getegitigaaning, helping to create a comprehensive homelands territory map that emphasizes Indigenous stewardship and resource gathering beyond colonial boundaries. By highlighting the importance of these sites, this research underscores the necessity of acknowledging and protecting Indigenous landscapes. This thesis provides a model for other tribes to reclaim their heritage and rights in the face of colonial legacies. Ultimately, this study contributes to broader discussions on Indigenous sovereignty and cultural revitalization and provides a framework to reclaim ancestral lands in the context of contemporary challenges faced by Indigenous Peoples
PROXIMAL SEISMIC TRACKING OF PYROCLASTIC DENSITY CURRENTS AT VOLCÁN DE FUEGO, GUATEMALA
Get PDFPyroclastic Density Currents (PDCs) are deadly flows of ash, tephra, gas, and solidified magma which predominantly occur when an ash plume collapses during a volcanic eruption. PDCs are also able to form when large deposits of ash at the summit of a volcano are displaced during an eruption and flow downslope. This is typically the mechanism behind PDCs that occur at Volcán de Fuego such as one that occurred in 2018 killing at least 430 people. The purpose of this paper is to track the propagation of PDCs that occurred at Fuego seismologically in order to better understand how they behave and, ultimately, better protect people in the future. The PDCs studied here occurred during eruptions on July 4 and December 11, 2022, and were recorded with four to seven seismic stations depending on the event. Three of these stations are within 100 m of the channels down which the PDCs flowed, much closer than is typical for an attempt to track PDCs.
Three methods were used to track the PDCs while one other was used to determine their velocities. The methods for tracking are referred to as the Envelope, RMS, and Linearized Decay methods while the method used to find velocity is referred to as the Cross Correlation method. The Cross Correlation method relies on calculating the cross correlation of seismic envelopes between two seismometers located close to the PDC’s path. This returns a time delay which, when divided by the distance between the seismometers, results in a velocity measurement for each event. While this method failed to produce results for the July 4 event due to anthropogenic interference, velocities for the December event are found to be between 9.9 and 13.5 m/s.
The Envelope, RMS, and Linearized Decay methods all rely on equations for amplitude decay. The first two methods used an equation that was dependent on anelastic attenuation factors. These methods are nearly identical, the only difference being that one analyzes the envelope of the seismogram, while the other uses the seismogram as is. Both methods produced similar results which displayed the location of the PDC far from the stations that recorded the highest amplitudes. This is unexpected as the point behind using equations for amplitude decay is to find the location where the amplitude is highest at any given point in time. This location is then presumed to be the source as amplitude decreases with distance from the source. The reason this failed is likely a result of the equation requiring attenuation values that are not well understood when close to the source location. The third tracking method, referred to as the Linearized Decay method, worked well as the equation did not require these values. This method placed the PDC at the expected locations, in expected times, and estimated the velocity of the PDC to be around 7 m/s for the December event. Both this velocity, and the velocities found by the cross correlation are slow compared to the average PDC but that is likely due to a low topographic slope and the fact that these PDCs are relatively small
FROM PLASMONICS TO SUPERFLUORESCENCE: ENGINEERING LIGHT- MATTER INTERACTIONS FOR QUANTUM OPTICAL PHENOMENA
Get PDFThis work presents different ways to engineer light-matter interactions by using nanostructures to exploit quantum-optical phenomena. First, sodium (Na) is predicted to be an ideal plasmonic material due to its ultra-low optical losses from the visible to the near-infrared (NIR). However, Na has practical limitations due to its high chemical reactivity. Using a scalable fabrication method for Na plasmonic nanostructures by combining phase-shift photolithography and a thermo-assisted spin-coating process, we produced nano-pit arrays of varying periodicities (300-600 nm), supporting tunable surface plasmon polariton (SPP) modes spanning visible to NIR. These structures demonstrated SPP resonances as narrow as 9.3 nm, with linewidth narrowing towards the NIR, highlighting their potential for low-loss NIR plasmonic applications. An encapsulation strategy was employed successfully, stabilizing the Na structures in ambient conditions for over two months. Continuing to explore the alkali metal library, we extended this approach to potassium (K) and sodium-potassium (NaK) liquid alloys, introducing a thermo-assisted nanoscale embossing (TANE) fabrication technique. This enabled the fabrication of high-quality plasmonic nanostructures with resonances as narrow as 15 nm in the NIR. Exploiting the Na-K eutectic phase diagram, we further expanded possibilities in liquid NaK plasmonics, enabling new platforms for active metamaterials and advanced photonic devices. Finally, quasi-two-dimensional (2D) perovskites with superlattice structures were investigated as platforms for room-temperature superfluorescence. Using steady-state and time-resolved spectroscopy, we identified characteristic signatures of superfluorescence– narrow emission linewidth, quadratic emission dependence on excitation power, and a delayed emission burst. These properties were unique to quasi-2D perovskites and absent in its 3D bulk form. Scanning transmission electron microscopy (STEM) confirmed superlattice formation, suggesting its presence is essential for superfluorescence. These results indicate that the search for new superfluorescent materials should prioritize exploring analogous materials with well-defined superlattice structures
Michigan\u27s EV Policies and Energy Justice
No full textThis research examines the alignment of Michigan’s electric vehicle (EV) policies with energy justice principles, focusing on affordability and equitable access to EV infrastructure for low-income households. As Michigan state policy encourages transitions toward more sustainable transportation through increased EV adoption, it is crucial to ensure that the benefits of this transition are accessible to all residents, including those in economically disadvantaged communities. The study adopts a qualitative research approach, utilizing content analysis of Michigan’s EV Laws and Incentives as provided by the U.S. Department of Energy Efficiency and Renewable Energy (EERE), and relevant demographic data to assess how these policies impact different socio-economic groups. By employing an energy justice informed approach, particularly focused on the need for affordable energy, this report aims to identify potential strengths and/or gaps in Michigan’s EV policies that could promote or hinder a just transition to EVs. The findings provide useful insights for policymakers, researchers, and community members, highlighting areas where current policies succeed or fall short in promoting energy justice. Ultimately, the study contributes to a more inclusive and socially equitable transition to EVs in Michigan
MOLECULAR MODELING METHODS AND APPLICATIONS FOR ACCELERATING POLYMERIZATION AND PYROLYSIS STUDIES
No full textPolymer matrix composites and carbon-carbon composites play critical roles in the aerospace, automotive, and construction industries. Different matrix materials and processing conditions can lead to a large variety of composite materials and composite properties. Integrated computational materials engineering has been used to tailor PMC matrix materials and processing conditions to specific properties and manufacturing techniques. The integrated computational materials engineering process modeling framework uses molecular dynamics at the nanometer length scale to characterize the evolving thermo-mechanical properties of the polymer as it cures. Then finite element analysis is used at the micrometer length scale to adjust cure cycles to tailor the composite material properties.
The goal of this work is to extend the integrated computational materials engineering based processing modeling from polymer matrix composites to carbon-carbon composites. This requires the ability to accurately model the polymerization and pyrosis process in molecular dynamics. As such a molecular dynamic workflow was generated to quickly and accurately model the polymerization and pyrolysis process, that allows for the prediction of the evolution of thermo-mechanical properties. The initial polymerization and pyrolysis process was modeled on a furan resin material using the ReaxFF force field.
Advancements of molecular force field parameterization was generated to allow simple and easy parameterization of different molecular system in a tool called LUNAR. LUNAR supports many force fields, allows for conversion between all supported force fields, allows for easy modeling of chemical reactions in the LAMMPS software, and provides simple analysis of molecular dynamics outputs. Finally, a reformulation of ClassII force fields was performed to allow for bond dissociation to occur. The reformulated functional form was derived to be able to allow for automatic parameterization of the parameters from the existing parameters. The new functional form of the force field is termed ClassII-xe
ThermalTrack Dataset - Validation Images
Get PDFWe present a wheel track detection system that leverages RGB-Thermal (RGB-T) imaging, where thermal channels reveal critical temperature differentials between compacted tracks and loose snow - tracks exhibit higher thermal inertia and lower reflectivity, emitting stronger radiation signatures even in visually homogeneous conditions. By fusing these distinctive thermal patterns with RGB spatial information, our method reliably identifies navigable tracks, enabling robust path-following in complete white-out conditions where snow textures and terrain features become indistinguishable
Continuous purification of a parvovirus using two aqueous two-phase extraction steps
Get PDFAqueous two-phase systems (ATPS) are a liquid–liquid extraction method that offers low-cost, continuous-adaptable virus purification. A two-step ATPS using polyethylene glycol (PEG) and sodium citrate that recovered 66% of infectious porcine parvovirus with 2.0 logs of protein removal and 1.0 logs of DNA removal in batch has now been run continuously. The continuous system output of \u3c 10 ng/mL DNA regardless of starting DNA titer agreed with batch studies. However, the continuous system had a five-fold higher contaminating protein titer than batch studies, likely because of incomplete mixing or settling. Turbidity was tested as a measure of mixing and settling efficiency. Monitoring in-line absorbance at 880 nm directly after mixing and before collection in the settling reservoir could track both mixing and settling during operation. Settling time was reduced by changing the settling line material from PVC to PTFE, which is more hydrophobic. A flow-through AEX filter tested to make impurity removal more robust recovered 90% of PPV and removed an additional 87% of host cell DNA. The filter did not add any additional protein removal. In the future, in-line absorbance sensors could be implemented along with conductivity sensors to measure salt concentration, refractive index sensors to track the PEG-citrate interface, and scales to track mixer and reservoir volumes to enable automated, continuous ATPS. Our vision is to integrate continuous ATPS into a fully continuous end-to-end production for viral vectors