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Publication Safeguarding user privacy in the IoT era(Colorado School of Mines. Arthur Lakes Library, 2024)The Internet of Things (IoT) has been erupting the world widely over the decade. Smart home and smart building owners are increasingly deploying IoT devices to monitor and control their environments due to the rapid decline in the price of IoT devices. However, serious privacy threat was revealed by recent research and media reports. First, the Internet traffic data generated by IoT devices are collected by Internet Service Providers (ISPs) and IoT device manufacturers, and often shared with third-parties to maintain and enhance user services. Extensive recent research has shown that on-path adversaries can infer and fingerprint user's sensitive privacy information such as occupancy and user in-home activities by analyzing IoT network traffic rates alone. Most recent approaches that aim at defending against these malicious IoT traffic analytics can not sufficiently protect user privacy with reasonable Internet traffic and hardware resource overhead. In particular, many approaches did not consider practical limitations, e.g., network bandwidth, maximum package injection rate or actual user in-home behavior in their design. Second, such privacy threats also shows in some specific types of IoT devices, like smart cameras. Significant recent research has uncovered potential user privacy threats associated with popular commercial camera systems. The manufacture design of these commercial camera systems usually requires smart camera users to relinquish their control of camera recorded data. For instance, these cameras often upload camera recordings to their cloud servers or data centers to enable advanced data analysis for camera app services. To facilitate enhanced camera services, the data may also be shared with on-path vendors, third parties of manufacturers, and cloud providers, potentially allowing them to access video footage or image captures without users' awareness or obtaining meaningful consent. To address these problems, my research aims at building and implementing computer systems in different scales of implementation, to allow Cyber-Physical System (CPS) and IoT users to regain the comprehensive control over their privacy, and the following contributions were made: \underline{\textit{SmartAttack}} and \underline{\textit{TrafficSpy}} aim at disaggregating individual IoT devices from both raw and VPN-encrypted IoT network traffic data. I designed and implemented two Machine Learning (ML) and Deep Learning (DL)-based adversarial attack model frameworks to mimic the malicious external adversaries carrying on user activity inference attacks. In addition to proving the severeness of smart home user privacy threat, these two works can also be leveraged by researchers and industrial users from IoT security community, to better evaluate their privacy preserving works. \underline{\textit{PrivacyGuard}}, as the first prototype, successfully provided an open-sourced, low-cost, user-tunable defense system, that enable users to significantly reduce the private information leaked through IoT device network traffic data, while still permitting sophisticated data analytics or control that is necessary in smart home management. I evaluated PrivacyGuard using IoT network traffic traces of 31 IoT devices from 5 smart homes and deploying a Raspberry Pi 4-based prototype. And the result shows that PrivacyGuard can effectively prevent a wide range of state-of-the-art machine learning-based occupancy and other 9 user-in-home activity detection attacks. \underline{\textit{PAROS}} - Privacy As a Router Operating system Service, made significant improvement from PrivacyGuard, to lift the requirement for installation of additional hub hardware, and still maintain comparable privacy preserving performance and system overhead. By leveraging Hidden Markov Model (HMM)-based artificial traffic signature injection, and Support Vector Machines (SVM)-based memory replacement scheme, the performance of PAROS was significantly optimized. \underline{\textit{SecCam}}, designed to solve the second half of the privacy threat, has provided a new open-sourced, adaptive and distributed privacy-preserving camera system. By harnessing the technique of on-device learning, SecCam provided several tiny intelligent camera services that offer the same features found in the commercially available cameras. SecCam enables user to regain the control of their data while still retaining access to regular camera services. The SecCam was evaluated using multiple camera video footage traces and on multiple real camera prototypes. In the future, I plan to dive deeper on safeguarding the IoT user privacy by improving my current systems, developing new attacking approaches, and doing ethical related work in the field of CPS and IoT.Publication Narrow-channel fluidized-bed heat exchangers for particle-based thermal energy storage in concentrating solar power applications(Colorado School of Mines. Arthur Lakes Library, 2024)Concentrating solar power (CSP) with thermal energy storage (TES) promises clean dispatchable electricity at high solar conversion efficiencies when coupled with emerging recompression closed Brayton (RCBC) supercritical carbon dioxide (sCO$_2$) power cycles. Inert-oxide particles provide a cost-effective storage and heat transfer media at adequate firing temperatures ($>$~700~\(^\circ\)C) for RCBC sCO$_2$ power cycles with thermal efficiencies $\geq~50\%$. To achieve cost-effective power at high conversion efficiencies, primary particle-sCO$_2$ heat exchangers (HXs) need high overall heat transfer coefficients to reduce HX area and costs of manufacturing with high-temperature alloys. In this study, mild bubbling fluidization with downward-falling particles and upward-flowing gas in narrow channels is shown to enhance the limiting bed-wall heat transfer and offer a pathway to meet HX cost targets of $\leq~150$ per kW\textsubscript{th}). Extensive laboratory-scale heat transfer tests characterized narrow-channel fluidization and demonstrated bed-wall heat transfer coefficients $\geq~800$ W~m$^{-2}$~K$^{-1}$ at bed temperatures $\approx~500~\,^\circ$C. Correlations derived from experiments indicate the potential for bed-wall heat transfer coefficients $> 1000$ W m$^{-2}$ K$^{-1}$ at expected HX operating conditions for $\leq~300~\,\mu$m particles. Incorporating correlations into reduced-order models of particle-sCO$_2$ HXs identifies preferred HX geometry and operating conditions for a 40-kW\textsubscript{th} prototype HX. The resulting particle-sCO$_2$ HX design is fabricated and assembled with a unique particle feed system with 12 $\approx~0.5$ m-high parallel fluidized bed channels and counter-flowing sCO$_2$ microchannels embedded in the HX walls. Prototype HX tests at Sandia National Laboratories yield lower-than-expected overall heat transfer coefficients with values reaching only 200 W~m$^{-2}$~K$^{-1}$ at mild fluidization velocities. High axial dispersion of particles due to fluidizing bubbles limits local driving bed-wall temperature differences and overall HX performance. Nonetheless, stable fluidized bed HX operation achieved 34~kW\textsubscript{th} of heat transfer to the sCO$_2$. Insights from these tests and lab-scale measurements inform updated models, incorporating axial dispersion correlations to identify necessary improvements for meeting performance targets. A system-level analysis reveals minimal balance-of-plant penalties associated with the power required and heat lost in the fluidization gas flows. Furthermore, models indicate that reducing dispersion can significantly improve fluidized bed HX performance by providing adequately high overall heat transfer coefficients that support cost-effective, particle-based TES subsystems for CSP plants.Publication Potential implementation of geologic carbon sequestration in southern Colorado(Colorado School of Mines. Arthur Lakes Library, 2024)Deep saline aquifers provide isolated reservoirs for geologic carbon sequestration. It is necessary to minimize the risk of CO2 injection within these deep saline aquifers. This is done through reservoir characterization, static modeling and injection modeling of CO2 within the saline aquifer. Modeling the time-lapse seismic response from this injection allows for better monitoring of the CO2 plume when injection commences. Utilizing available data, a static model of the Lyons saline aquifer is built. Post stack seismic inversionis used within a 3D seismic volume to determine the acoustic impedance of the saline aquifer and calculate subsequent properties including porosity and permeability. With this model, injection of CO2 is simulated for 30 years with 70 years of shut-in simulated afterwards. The resulting pressure and saturation plumes are used to model the change in P-impedance (IP) and S-impedance (IS) to create synthetic seismic and study the change due to CO2 injection. Changes in IP and IS are modeled using pressure dependent velocity testing of the Lyons sandstone to find the elastic moduli of the dry rock as effective pressure changes and the pressure dependence of the pore fluids. Variations in porosity in the reservoir rock are accounted for by calculating the pore space stiffness and rigidity and integrating that into the rock physics model. Resulting IP and IS within the aquifer are used to calculate synthetic angle stacks to simulate the change in Amplitude Versus Offset as a function of the change in IP and IS. From the simulation of CO2 injection into the static model a decrease in IP and IS is calculated. CO2 replaces brine in the pore space lowering fluid bulk modulus (Kfluid). Increased pore pressure reduces the effective pressure, softening the rock matrix and lowering dry rock bulk modulus (Kdry) and dry rock shear modulus (µdry). Additionally, density (ρ) decreases as the density of the pore fluid drops. The Lyons sandstone is not sensitive to pressure changes at the initial effective pressure or after injection. The changes in the elastic moduli from effective pressure decrease does not contribute significantly to the decrease in IP and IS. IP and IS within the CO2 plume decrease as pore pressure increases and CO2 replaces the brine in the pore space, with a maximum decrease of 4.31% and 1.13% respectively. This change creates a decrease in intercept and gradient from the simulated amplitude versus offset. Evaluation of the reservoir properties, geologic structure, simulation results and synthetic AVO data allows us to conclude that the Lyons saline aquifer would be suitable for geologic sequestration of CO2. Utilizing the limited data a reliable static model is able to be constructed. The aquifer is strongly sealed by alternating anhydrites and shales. Synthetic angle stacks allow for modeling of the extent of the simulated CO2 plume as CO2 saturation and pore pressure change the elastic moduli of the saturated rock.Publication Understanding deformation and cyclic behavior of shape memory ceramics: a quantitative phase-field study(Colorado School of Mines. Arthur Lakes Library, 2024)Zirconia-based shape memory ceramics (SMCs) are a class of intelligent materials that can be utilized in industries such as aerospace and biomedical engineering for their remarkable superelasticity (SE) and shape memory effect (SME). These ceramics are brittle and unable to fully accommodate the large shape change due to martensitic phase transformation (MPT) and this leads to their low fracture toughness and short cyclic life. In this Ph.D. research, we aimed to develop a reliable computational framework to study the complex interactions between phase transformation, microstructural features, fracture, and plasticity in order to design SMCs with a higher fatigue life. For this purpose, first, we proposed a modified phase-field (PF) fracture model to study cracking in brittle materials at microscopic domains. Unlike traditional models, this modified model incorporates the influence of both fracture strength and cleavage plane effects simultaneously. As a result, it accurately reproduces the mechanical response and crack propagation path and reveals that intergranular fracture is the dominant type of cracking in ceramics. Additionally, to investigate the interaction between cracking and MPT in SE SMCs, an advanced PF-based model was developed. Unlike previous PF-MPT models, this model successfully predicts the correct elastic response in the stress-strain curve. This improvement is attributed to the proposed modified chemical free energy formulation. This is the first PF model used for simulating cracking in SE regime and accurately predicts reverse MPT behind the crack tip, a phenomenon attributed to SE regime. In addition, the model captures the effects of grain orientation and predicts a final stress drop in the stress-strain curve. Furthermore, to explore the influence of different microstructural features on the cyclic life of SMCs prior to fatigue crack initiation, the modified chemical free energy model was integrated with a viscoplasticity model. The plastic strain accumulation (PSA) was used as a cyclic life indicator, and we aimed to lower PSA by microstructure tailoring. Simulations revealed that by controlling grain orientations, lowering the GB density, or locating pores at GBs, the PSA decreases significantly. Finally, a new predictive numerical framework was developed incorporating the PF fracture, PF-MPT, and crystal viscoplasticity to study crystal-orientation dependent SE and SME behaviors of 3D micropillars. Through validation against experimental data, the proposed framework demonstrated the ability to accurately predict the intricate interplay between MPT, cracking, and plasticity. Our investigation revealed a broad spectrum of crystal orientations in which these ceramics undergo a complete MPT cycle without experiencing fracturing or slipping. However, we also identified certain orientations where either fracturing or slipping emerges as the dominant mechanism, with little to no observable MPT. The findings of this Ph.D. research provided valuable insights into the crystal-orientation dependent mechanical properties of SMCs and strategies for enhancing their cyclic life, thus possibly enabling their practical applications.Publication Insights into the synthesis and applications of earth-abundant metal-oxide nanoparticles(Colorado School of Mines. Arthur Lakes Library, 2024)Earth-abundant materials serve as a key source for potential wide-scale solutions toward current environmental challenges. Via the modification of surface morphology and particle size, the overall chemical activity can be tuned towards higher activity for environmental pollutant capture and degradation. CaO material was synthesized via a modified wet-chemical synthesis route for MgO (111). The addition of 4-methoxybenzyl alcohol as a structure directing agent was shown to alter the resulting precursor material via XRD, and evidence of the (111) facet was determined via HRTEM. Via CO2 TPD studies, some early insights were gleaned for this material and its ability to adsorb high quantities of CO2, as well as its increased binding strength. A review of light-driven technologies for PFAS degradation and detection was done in order to summarize the potential applications of UV-Vis driven technologies, with a discussion on the potential usage (and misusage) of TiO2 P25 and anatase phase as a baseline material for many photocatalytic PFAS destruction technologies. As a whole, this work aims to show the potential of earth-abundant metal-oxide materials. Via the alteration of surface chemistry new key applications can be discovered for old materials, and that one-day Earth-abundant materials can be implemented on a large scale as key solutions to global issues in an economically viable manner.