The desire to gather acoustic data of a propeller in simulated hover without environmental effects is met with the challenge of recirculating flow in a closed anechoic chamber. Flow recirculation in an anechoic chamber is not ideal because the effects of it being ingested by the rotor cause unsteady loadings on the propeller. This unsteady loading causes vortex noise from the turbulence introduced by the recirculation of the flow. The aim is to study the acoustic signature of a propeller separate from external factors and engine noise. Two different propellers with three different screen combinations were tested in a closed anechoic chamber. The results of these tests showed that the screens are able to reduce the vortex and broadband noise levels, with the reduction being more pronounced when the dual screen was installed.

This dissertation comprises three papers introducing strategies, models, and frameworks to guide pandemic response. The first paper uses a novel mathematical model to analyze the coordination between government and humanitarian non-governmental organizations (NGOs) in response to pandemics. This is a vital form of public-private partnership between governments as the primary source for the humanitarian supplies required during a crisis and aid organizations. This coordination involves the equitable distribution of personal protective equipment, including face masks and face shields among health workers, patients, and the public in hospitals. Considering social costs such as deprivation and equity costs in the model, in addition to the other important classic cost terms, enables managers to organize the best possible response when such outbreaks happen. The second paper introduces a decision support framework designed to assist healthcare managers, and clinical informatics specialists in analyzing and selecting the most appropriate consensus algorithm for their organization's blockchain-based health platforms, with a specific focus on managing pandemic-related information. Blockchain technology holds great potential in addressing pandemics by enhancing security and transparency in various aspects of pandemic tracking and mitigation while promoting public engagements by facilitating real-time exchange of electronic health information. By improving information sharing and coordination among healthcare organizations, it offers more effective response efforts and helps reduce the spread of viruses. However, the performance of consensus algorithms, which are a crucial component of blockchain architecture, can vary, posing a challenge in selecting the appropriate algorithm. To address this, the framework incorporates two techniques: data envelopment analysis (DEA) and the ranking distribution technique. DEA enables the analysis of efficiency without relying solely on expert judgment, providing a more objective assessment. The ranking distribution technique enhances differentiation among algorithms, providing decision-makers with a robust basis for selecting the most suitable blockchain architecture and its associated properties. The third paper focuses on the challenges of disseminating guidance-related information to the public during a pandemic, specifically the role of opinion leaders as reliable sources of information. The study determines the practical characteristics of pandemic opinion leaders on public attitudes using surveys and identifies domain-sensitive pandemic opinion leaders on Twitter based on the discovered characteristics using social network analysis and text mining. The framework's results show that pandemic opinion leaders are active in eight different domains on the Twitter platform. Results also demonstrate that trust is the most influential characteristic of pandemic opinion leaders, while expertise, uniqueness, innovation, and reputation also play important roles. / Doctor of Philosophy / This dissertation presents a collection of three research papers that offer insights and practical techniques and strategies to effectively tackle the challenges posed by pandemics through enhanced information sharing, public engagement, and robust public-private partnerships. The first paper introduces a novel mathematical model that thoroughly examines the collaboration between governments and humanitarian non-governmental organizations (NGOs) during crises such as the Covid-19 pandemic. The model's primary focus is on the equitable distribution of vital supplies, including face masks and shields, to healthcare workers as well as the public. By incorporating considerations of social costs, fairness, and other critical factors, this model aids managers in organizing the most efficient response to initial impacts of outbreaks within a short-term planning horizon. Our primary objective is to ensure the prompt and equitable delivery of essential supplies to individuals in need, achieved primarily through establishing strong public-private partnerships. The second paper proposes a decision support framework for healthcare managers, IT analysts, and clinical informatics specialists to help them effectively analyze consensus algorithms, as the most important layer of blockchain architecture. The framework further helps them select the most suitable algorithm for their organization's blockchain-based health platforms, aligning with specific policies, needs, requirements, and goals in managing pandemic-related information. Blockchain technology offers potential in tracking medical supplies, identifying virus hotspots, and verifying protective equipment authenticity to manage pandemics. By enhancing information sharing and coordination among healthcare organizations, blockchain can minimize virus spread and improve overall response efforts. The proposed framework reduces reliance on expert judgment and addresses data uncertainty when selecting proper algorithms for blockchain-based information management systems in mitigating the effects of pandemics. The third paper delves into the intricate challenges associated with effectively disseminating guidance-related information to the public during a pandemic, placing particular emphasis on the pivotal role played by opinion leaders (OLs) as reliable sources. This study thoroughly examines the distinctive characteristics of pandemic OLs and their profound influence on public attitudes. By employing surveys, social network analysis, and text mining techniques on Twitter data, the research successfully identifies OLs within distinct pandemic-related domains. The study's significant findings provide insights into the dynamic role assumed by pandemic OLs on Twitter and their consequential impact on public perception and behavior across various domains. Ultimately, the dissertation findings strive to support decision-makers and public health officials in their efforts to effectively manage pandemics and protect public health. The research emphasizes facilitation of seamless, rapid, and dependable information sharing across various planning horizons.

A worldwide shift from fossil fuels to zero carbon energy sources is imperative to limit global warming to 1.5°C. While integrating high penetrations of VRE into the grid may introduce the need for upgrading an aging electrical system, renewable energy represents a new opportunity to decarbonize multiple sectors. Otherwise curtailed solar and wind energy can accelerate deep decarbonization in hard-to-reach sectors - transportation, industrial, residential, and commercial buildings, all of which must be decarbonized to limit global warming. With renewable energy as its input, electrolytic H₂ represents a solution to the supply-demand mismatch created by the proliferation of VREs on a grid designed for on-demand power. Electrolytic H₂ can stabilize the grid since the H2 created can be stored and transferred. Thus, Chapter 1 introduces the opportunity of green H2 in the context of low-cost VREs as a means of deep decarbonization through sector coupling, and an overview of the techno-economics, key technologies, and life cycle assessment versus the incumbent steam methane reformation. The growing imbalances between electricity demand and supply from VREs create increasingly large swings in electricity prices. Capable of operating with variable input power and high current densities without prohibitively large ohmic losses, polymer electrolyte membrane (PEM) electrolyzers are well suited to VREs. In Chapter 2, polymer electrolyte membrane (PEM) electrolyzers are shown to help buffer against these supply demand imbalances, while simultaneously minimizing the levelized cost of hydrogen (LCOH) by ramping up production of H2 through high-current-density operation when low-cost electricity is abundant, and ramping down current density to operate efficiently when electricity prices are high. A techno-economic model is introduced that optimizes current density profiles for dynamically operated electrolyzers, while accounting for the potential of increased degradation rates, to minimize LCOH for any given time-of-use (TOU) electricity pricing. This model is used to predict LCOH from different methods of operating a PEM electrolyzer for historical and projected electricity prices in California and Texas, which were chosen due to their high penetration of VREs. Results reveal that dynamic operation could enable reductions in LCOH ranging from 2% to 63% for historical 2020 pricing and 1% to 53% for projected 2030 pricing. Moreover, high-current-density operation above 2.5 A cm−2 is shown to be increasingly justified at electricity prices below $0.03 kWh−1. These findings suggest an actionable means of lowering LCOH and guide PEM electrolyzer development toward devices that can operate efficiently at a range of current densities. Chapter 3 uses techno-economic modeling to analyze the benefits of producing green (zero carbon) hydrogen through dynamically operated PEM electrolyzers connected to off-grid VREs. Dynamic electrolyzer operation is considered for current densities between 0 to 6 A cm-2 and compared to operating a PEM electrolyzer at a constant current density of 2 A cm-2. The analysis was carried out for different combinations of VRE to electrolysis (VRE:E) capacity ratios and compositions of wind and solar electricity in 4 locations – Ludlow, California, Dalhart, Texas, Calvin, North Dakota, and Maple Falls, Washington. For optimal VRE:E and wind:PV capacity ratios, dynamic operation of the PEM electrolyzer was found to reduce the LCOH by 5% to 9%, while increasing H₂ production by 134% to 173%, and decreasing excess (i.e. curtailed) electrical power by 82% to 95% compared to constant current density operation. Under dynamic electrolyzer operation, the minimum LCOH is achieved at higher VRE:E capacity ratios than constant current density operation and a VRE mix that was more skewed to whichever VRE source with the higher capacity factor at a given location. In addition, dynamically operated electrolyzers are found to achieve LCOH values within 10% of the minimum LCOH over a significantly wider range of VRE:E capacity ratios and VRE mixes than constant electrolyzers. As demonstrated, the techno-economic framework described herein may be used to determine the optimal VRE:E capacity and VRE mix for dynamically-operated green hydrogen systems that minimize cost and maximize the amount of H2 produced. Chapter 4 focuses on the production of high-purity water and H₂ from seawater. Current electrolyzers require deionized water so they need to be coupled with desalination units. This study shows that such coupling is cost-effective in H₂ generation, and offers benefits to thermal desalination, which can utilize waste heat from electrolysis. Furthermore, it is shown that such coupling can be optimized when electrolyzers operate at high current density, using low-cost solar and/or wind electricity, as such operation increases both H₂ production and heat generation. Results of techno-economic modeling of PEM electrolyzers define thresholds of electricity pricing, current density, and operating temperature that make clean electrolytic hydrogen cost-competitive with H₂ from steam methane reforming. By using 2020 hourly electricity pricing in California and Texas, H₂ is shown to be produced from seawater in coupled desalination-electrolyzer systems at prices near $2, reaching cost parity with SMR-produced H₂. Chapter 5 concludes the dissertation with an overview of the challenges and research needs for PEM electrolyzers at scale, including projected iridium needs, iridium thrifting, recycling methods, key degradation mechanisms, a failure modes and effects analysis, and LCOH projections.

Ransomware has been a growing threat to today's organizations, with irreparable damages and billions of dollars lost, it is crucial for organizations to implement mitigation strategies that can counter these attacks. With phishing attempts being the primary attack vector, it is evident that organizations need to implement the best practices in order to avoid the consequences. Thus, this study addresses the question “How do the actual ransomware mitigation strategies implemented by Swedish organizations compare to the best practices suggested in literature, with a focus on phishing emails as a common means of ransomware transmission?” The study was conducted by utilizing semi-structured interviews and interviewing five participants that work or have worked as IT-security consultants which are then summarized and analyzed with a thematic analysis approach. Seven relevant themes and fifteen sub-themes were introduced and analyzed in order to answer the proposed research question: attack vector, security awareness training, technical solutions, challenges of solutions, frameworks, evolution and keeping yourself updated. All participants were contacted via Linkedin and the interviews were done virtually via Zoom. The findings of this study shows that Swedish organizations utilize a minimal amount of ransomware mitigation strategies due to the lack of resources, care and overall awareness regarding the topic. According to the interviewed participants, basic forms of technical solutions and administrative solutions are mostly implemented, however they are a lacking form of medium and can generally be bypassed easily. The primary factors that were brought up and introduced was security awareness training and technical solutions. Essentially, it all boils down to employee’s incompetence and lack of security awareness. No matter how many technical solutions that are implemented within an organization, if an employee is not aware that they shouldn’t click on malicious links, an infection might spread.

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The implementation of Nationally Determined Contributions (NDC) in 2020 has coincided with the outbreak of COVID-19. Recovery paths taken to deal with the economic consequences of the pandemic can be either an opportunity to foster a sustainable growth or a return to business-as-usual model. Assuming that national budgets define the economic strategy of governments, this thesis addresses the relationship between mitigation pledges outlined in NDCs and mitigation-related expenditure in Chile, Peru and Colombia pre- and during the COVID-19 pandemic. A deductive thematic analysis of NDCs is used to identify the prioritized mitigation sectors and to allow for a refined focus in the analysis of the relevant mitigation-related expenses for each case country. Budgets of 2020 and 2021 are compared and discussed in the light of previous research. Results show different levels of climate ambition but common prioritised sectors (energy, land-use, and industry). Regarding Peru, the budgets indicate a higher mitigation ambition than their NDC by including expenditure in areas that are not mentioned in the NDC. Contrary, Colombia and Chile have detailed NDCs that cover more aspects than indicated through their government expenditure. Generally, energy and industry expenditure misalign with the NDC pledges, due to the increase of expenses on national fossil fuels resources in 2021. Land-use mitigation expenditure, linked to forestry and agriculture, have increased in Chile and Peru but are hardly represented in Colombia. Thus, the thesis outlines early misalignments of mitigation targets with government expenditure and differences in accountability and transparency that could challenge the monitoring of progress towards the achievement of the pledges.

In 1852, a five-minute long earthquake hit the Banda Arc region that was felt over most of Indonesia. It caused uplift of new islands and sent a tsunami across the Banda Sea that reached a height of 8 meters at Banda Neira and was also registered at Ambon, Saparua and other islands. Records of the 1852 earthquake at multiple locations provide the constraints needed to reconstruct the disastrous event through earthquake intensity analysis and numerical modeling of the tsunami. Using tsunami heights and arrival times as the major constraints, best fit numerical models of the tsunami were constructed using Clawpack. These models indicate that the earthquake was most likely a mega-thrust event along the Tanimbar Trough with a Mw of around 8.4. At least 10-15 meters of elastic strain energy has accumulated along the Tanimbar Through since the 1852 event, and the population in the region has increased exponentially. When another event occurs ≥ that in 1852, there will be many more people and treasure in harms way.

Radio astronomy synthesis imaging arrays are composed of many parabolic reflector antennas. These antennas are designed to be extremely sensitive to detect faint emissions from astronomical sources. Unfortunately, this also makes them susceptible to radio frequency interference (RFI) from man made sources such as orbiting satellites. The radio astronomy research group at Brigham Young University (BYU) is investigating methods to mitigate the effects of RFI in radio astronomy synthesis imaging. Though real-time RFI mitigation has been demonstrated for a large single dish telescope, for synthesis imaging arrays our prior work has consisted solely of algorithm development and computer simulations. To test our algorithms on experimental data we need an image synthesis array at BYU. The primary contribution of this Master's thesis is the design and construction of a working image synthesis array on the roof of the Clyde Building at BYU. This thesis describes the design of the antenna placement for the synthesis array. Antenna placement is the primary factor for determining image quality since the placement dictates the shape of the synthesized beam. Simulations were performed, prior to the array's construction, to predict the quality of images from the array. Another contribution of this thesis is signal processing code to generate correlations of the signals from the antennas. Code was written to calibrate measured data and generate an image from the correlations. Code was also written to steer the antennas and track astronomical phenomena. The performance of the array is evaluated in this thesis. The culmination of this thesis is a radio image of the supernova remnant Cassiopeia A. This thesis concludes with simulations of an RFI mitigation experiment that can be performed with the new array (pending certain improvements to the array).

Radio frequency interference (RFI) is a growing problem for radio astronomers. One potential solution utilizes spatial filtering by placing an array of electrically small antennas at the focal plane of a parabolic reflector. This thesis documents the design and characterization of a prototype array feed and RF receiver that were used to demonstrate the spatial filtering principle. The array consists of a 7-element hexagonal arrangement of thickened dipole antennas tuned to a center frequency of 1600 MHz. The receiver is a two-stage, low-noise frequency mixer that is tunable over the entire L-band. This thesis also documents a new receiver design that is part of an upgrade to the outdoor antenna test range for the National Radio Astronomy Observatory in Green Bank, West Virginia. The array feed was demonstrated on a three-meter parabolic reflector by recovering a weak signal of interest that was obscured by a strong, broadband interferer. Similar results were also obtained when the interferer moved with an angular velocity of 0.1 degree per second, but only when the power in the interferer dominated the signal. The aperture efficiency was measured at 64%, but adaptive beamformers can slightly perturb this value through distortions in the beam pattern. This phenomenon, called pattern rumble, effectively reduced the sensitivity of the radio telescope, and was measured by comparing the SNRs of adaptive beamformers to the SNR of a fixed-weight beamformer. It was found that pattern rumble can reduce the useful integration time by roughly one order of magnitude. It was also found that mechanical instability of the primary reflector introduces a great deal of pattern rumble, even when the interferer is fixed in direction.

Radio astronomy is the discipline dedicated to the study of celestial emissions in the radio band from a few MHz to 300 GHz. In recent years, spurious emissions from man-made devices that operate at these frequencies have made detection of astronomical signals difficult. These harmful RF transmissions are called radio frequency interference (RFI). One strategy to remove RFI is to apply spatial filtering using an array antenna. This thesis documents the development of a high-speed data acquisition system used to record data from 7- and 19-element phased array feeds. The system supports synchronous sampling over all channels and streams data to disk allowing spatial filtering to be applied in post-processing. The development of a time blanking RFI mitigation system was also developed as part of this thesis. Time blanking is a strategy to remove radar interference by blanking the time intervals corrupted by radar transmissions. The two blanking strategies are time window blanking and detected pulse blanking. This thesis documents the design and implementation of a detected pulse blanking system built using FPGAs. The system employs complex signal processing techniques to detect and excise radar transmissions in real time. This FPGA RFI mitigation system is the first to use a matched filter in pulse detection. Successful radio frequency interference mitigation is demonstrated by removing simulated radar interference from a sinusoidal tone.