Aero-Optical Assessments of Hypersonic Flowfields

A potential future use of hypersonic platforms is for responsive Intelligence, Surveillance, and Reconnaissance (ISR). It is common for these types of missions to employ Electro-Optical/Infrared (EO/IR) sensors and Radio Frequency (RF) sensors to collect information. If an optical signal were to travel through a hypersonic flowfield, the type of high-speed flow analysis required to perform reliable assessments of sensor performance is unclear. In order to provide this information, the hypersonic flow phenomena of thermochemistry, high speed turbulence, and high enthalpy turbulence are studied. In a hypersonic environment, the high kinetic energy of the oncoming flow causes the molecules in the flow to be thermally excited, leading to dissociation. In such a flowfield, an aero-optical analysis that considers thermochemical nonequilibrium is necessary to assist in sensor design. In the present thesis, we assess the optical properties of a nonequilibrium flowfield. The optical distortions are quantified using optical path length (OPL) and optical path difference (OPD). Optical distortion is also assessed based on flowfield modeling performed using a perfect gas assumption, and these distortions are provided for comparison. The primary contributions of nonequilibrium flow properties on optical distortion are identified. For all Mach numbers, OPLs are higher when the effects of dissociation and vibrational relaxation are included. Oxygen dissociation is the dominant nonequilibrium flow phenomenon affecting the optical distortion. As Mach number increases, atomic nitrogen begins to have an additional influence on optical aberrations. Additional distortion can arise in the hypersonic regime from high speed turbulence within the boundary layer. An initial study is conducted on a Mach 6 flow over a flat plate. This simulation is performed using air as a calorically perfect gas with varying levels of turbulence modeling and resolution. The cases are run using a laminar flow assumption (no turbulence), the Menter SST closure model for the Reynolds Averaged Navier-Stokes equations (RANS), and Implicit Large Eddy Simulation (ILES). It was found that the OPDs produced by the highest fidelity ILES approach can be as much as two orders of magnitude larger than solutions produced by the Menter SST model and laminar flow. While RANS was able to predict the mean flow quantities, it is unable to correctly predict the optical distortion. The effects of thermochemical nonequilibrium on turbulent flow, and consequently optical distortion, are also presented in this dissertation. In the present study, numerical simulations are utilized to perform implicit large eddy simulations of flows over an adiabatic flat plate. The simulations are run with and without thermochemistry models to determine the effects of thermochemical nonequilibrium on optical distortion. Accounting for thermochemical nonequilibrium predicts less variation in OPD across the sensor aperture. The RMS average of OPD is significantly smaller for the real gas simulation when compared to a perfect gas. These differences in OPD occur because nonequilibrium energy exchanges act to damp out turbulent fluctuations, as illustrated with the Taylor-Green Vortex problem in this thesis. It is therefore necessary to include these physical flow effects in optical assessments to obtain an accurate description of the aero-optic distortions.PHDAerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/149887/1/lemackey_1.pd

An interdisciplinary assessment of climate engineering strategies

Author Posting. © Ecological Society of America, 2014. This article is posted here by permission of Ecological Society of America for personal use, not for redistribution. The definitive version was published in Frontiers in Ecology and the Environment 12 (2014): 280–287, doi:10.1890/130030.Mitigating further anthropogenic changes to the global climate will require reducing greenhouse-gas emissions (“abatement”), or else removing carbon dioxide from the atmosphere and/or diminishing solar input (“climate engineering”). Here, we develop and apply criteria to measure technical, economic, ecological, institutional, and ethical dimensions of, and public acceptance for, climate engineering strategies; provide a relative rating for each dimension; and offer a new interdisciplinary framework for comparing abatement and climate engineering options. While abatement remains the most desirable policy, certain climate engineering strategies, including forest and soil management for carbon sequestration, merit broad-scale application. Other proposed strategies, such as biochar production and geological carbon capture and storage, are rated somewhat lower, but deserve further research and development. Iron fertilization of the oceans and solar radiation management, although cost-effective, received the lowest ratings on most criteria. We conclude that although abatement should remain the central climate-change response, some low-risk, cost-effective climate engineering approaches should be applied as complements. The framework presented here aims to guide and prioritize further research and analysis, leading to improvements in climate engineering strategies.NSF grant #1103575 supported KRMM

Accounting for biomass carbon stock change due to wildfire in temperate forest landscapes in Australia

Carbon stock change due to forest management and disturbance must be accounted for in UNFCCC national inventory reports and for signatories to the Kyoto Protocol. Impacts of disturbance on greenhouse gas (GHG) inventories are important for many countries with large forest estates prone to wildfires. Our objective was to measure changes in carbon stocks due to short-term combustion and to simulate longer-term carbon stock dynamics resulting from redistribution among biomass components following wildfire. We studied the impacts of a wildfire in 2009 that burnt temperate forest of tall, wet eucalypts in south-eastern Australia. Biomass combusted ranged from 40 to 58 tC ha(-1), which represented 6-7% and 9-14% in low- and high-severity fire, respectively, of the pre-fire total biomass carbon stock. Pre-fire total stock ranged from 400 to 1040 tC ha(-1) depending on forest age and disturbance history. An estimated 3.9 TgC was emitted from the 2009 fire within the forest region, representing 8.5% of total biomass carbon stock across the landscape. Carbon losses from combustion were large over hours to days during the wildfire, but from an ecosystem dynamics perspective, the proportion of total carbon stock combusted was relatively small. Furthermore, more than half the stock losses from combustion were derived from biomass components with short lifetimes. Most biomass remained on-site, although redistributed from living to dead components. Decomposition of these components and new regeneration constituted the greatest changes in carbon stocks over ensuing decades. A critical issue for carbon accounting policy arises because the timeframes of ecological processes of carbon stock change are longer than the periods for reporting GHG inventories for national emissions reductions targets. Carbon accounts should be comprehensive of all stock changes, but reporting against targets should be based on human-induced changes in carbon stocks to incentivise mitigation activities.The funder provided support in the form of salaries for the authors [HK, SO], but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript

Seeing double with K2: Testing re-inflation with two remarkably similar planets around red giant branch stars

Despite more than 20 years since the discovery of the first gas giant planet with an anomalously large radius, the mechanism for planet inflation remains unknown. Here, we report the discovery of EPIC228754001.01, an inflated gas giant planet found with the NASA K2 Mission, and a revised mass for another inflated planet, K2-97b. These planets reside on ~9 day orbits around host stars which recently evolved into red giants. We constrain the irradiation history of these planets using models constrained by asteroseismology and Keck/HIRES spectroscopy and radial velocity measurements. We measure planet radii of 1.31 +\- 0.11 Rjup and and 1.30 +\- 0.07 Rjup, respectively. These radii are typical for planets receiving the current irradiation, but not the former, zero age main sequence irradiation of these planets. This suggests that the current sizes of these planets are directly correlated to their current irradiation. Our precise constraints of the masses and radii of the stars and planets in these systems allow us to constrain the planetary heating efficiency of both systems as 0.03% +0.03%/-0.02%. These results are consistent with a planet re-inflation scenario, but suggest the efficiency of planet re-inflation may be lower than previously theorized. Finally, we discuss the agreement within 10% of stellar masses and radii, and planet masses, radii, and orbital periods of both systems and speculate that this may be due to selection bias in searching for planets around evolved stars.Comment: 18 pages, 15 figures, accepted to AJ. Figures 11, 12, and 13 are the key figures of the pape

A Double Machine Learning Trend Model for Citizen Science Data

1. Citizen and community-science (CS) datasets have great potential for estimating interannual patterns of population change given the large volumes of data collected globally every year. Yet, the flexible protocols that enable many CS projects to collect large volumes of data typically lack the structure necessary to keep consistent sampling across years. This leads to interannual confounding, as changes to the observation process over time are confounded with changes in species population sizes. 2. Here we describe a novel modeling approach designed to estimate species population trends while controlling for the interannual confounding common in citizen science data. The approach is based on Double Machine Learning, a statistical framework that uses machine learning methods to estimate population change and the propensity scores used to adjust for confounding discovered in the data. Additionally, we develop a simulation method to identify and adjust for residual confounding missed by the propensity scores. Using this new method, we can produce spatially detailed trend estimates from citizen science data. 3. To illustrate the approach, we estimated species trends using data from the CS project eBird. We used a simulation study to assess the ability of the method to estimate spatially varying trends in the face of real-world confounding. Results showed that the trend estimates distinguished between spatially constant and spatially varying trends at a 27km resolution. There were low error rates on the estimated direction of population change (increasing/decreasing) and high correlations on the estimated magnitude. 4. The ability to estimate spatially explicit trends while accounting for confounding in citizen science data has the potential to fill important information gaps, helping to estimate population trends for species, regions, or seasons without rigorous monitoring data.Comment: 28 pages, 6 figure

Semantic network analysis of vaccine sentiment in online social media.

OBJECTIVE: To examine current vaccine sentiment on social media by constructing and analyzing semantic networks of vaccine information from highly shared websites of Twitter users in the United States; and to assist public health communication of vaccines. BACKGROUND: Vaccine hesitancy continues to contribute to suboptimal vaccination coverage in the United States, posing significant risk of disease outbreaks, yet remains poorly understood. METHODS: We constructed semantic networks of vaccine information from internet articles shared by Twitter users in the United States. We analyzed resulting network topology, compared semantic differences, and identified the most salient concepts within networks expressing positive, negative, and neutral vaccine sentiment. RESULTS: The semantic network of positive vaccine sentiment demonstrated greater cohesiveness in discourse compared to the larger, less-connected network of negative vaccine sentiment. The positive sentiment network centered around parents and focused on communicating health risks and benefits, highlighting medical concepts such as measles, autism, HPV vaccine, vaccine-autism link, meningococcal disease, and MMR vaccine. In contrast, the negative network centered around children and focused on organizational bodies such as CDC, vaccine industry, doctors, mainstream media, pharmaceutical companies, and United States. The prevalence of negative vaccine sentiment was demonstrated through diverse messaging, framed around skepticism and distrust of government organizations that communicate scientific evidence supporting positive vaccine benefits. CONCLUSION: Semantic network analysis of vaccine sentiment in online social media can enhance understanding of the scope and variability of current attitudes and beliefs toward vaccines. Our study synthesizes quantitative and qualitative evidence from an interdisciplinary approach to better understand complex drivers of vaccine hesitancy for public health communication, to improve vaccine confidence and vaccination coverage in the United States

Overfitting Affects the Reliability of Radial Velocity Mass Estimates of the V1298 Tau Planets

Mass, radius, and age measurements of young (<100 Myr) planets have the power to shape our understanding of planet formation. However, young stars tend to be extremely variable in both photometry and radial velocity, which makes constraining these properties challenging. The V1298 Tau system of four ~0.5 Rjup planets transiting a pre-main sequence star presents an important, if stress-inducing, opportunity to directly observe and measure the properties of infant planets. Su\'arez-Mascare\~no et al. (2021) published radial-velocity-derived masses for two of the V1298 Tau planets using a state-of-the-art Gaussian Process regression framework. The planetary densities computed from these masses were surprisingly high, implying extremely rapid contraction after formation in tension with most existing planet formation theories. In an effort to further constrain the masses of the V1298 Tau planets, we obtained 36 RVs using Keck/HIRES, and analyzed them in concert with published RVs and photometry. Through performing a suite of cross validation tests, we found evidence that the preferred model of SM21 suffers from overfitting, defined as the inability to predict unseen data, rendering the masses unreliable. We detail several potential causes of this overfitting, many of which may be important for other RV analyses of other active stars, and recommend that additional time and resources be allocated to understanding and mitigating activity in active young stars such as V1298 Tau.Comment: 26 pages, 12 figures; published in A

US SOLAS Science Report

The article of record may be found at https://doi.org/10.1575/1912/27821The Surface Ocean – Lower Atmosphere Study (SOLAS) (http://www.solas-int.org/) is an international research initiative focused on understanding the key biogeochemical-physical interactions and feedbacks between the ocean and atmosphere that are critical elements of climate and global biogeochemical cycles. Following the release of the SOLAS Decadal Science Plan (2015-2025) (Brévière et al., 2016), the Ocean-Atmosphere Interaction Committee (OAIC) was formed as a subcommittee of the Ocean Carbon and Biogeochemistry (OCB) Scientific Steering Committee to coordinate US SOLAS efforts and activities, facilitate interactions among atmospheric and ocean scientists, and strengthen US contributions to international SOLAS. In October 2019, with support from OCB, the OAIC convened an open community workshop, Ocean-Atmosphere Interactions: Scoping directions for new research with the goal of fostering new collaborations and identifying knowledge gaps and high-priority science questions to formulate a US SOLAS Science Plan. Based on presentations and discussions at the workshop, the OAIC and workshop participants have developed this US SOLAS Science Plan. The first part of the workshop and this Science Plan were purposefully designed around the five themes of the SOLAS Decadal Science Plan (2015-2025) (Brévière et al., 2016) to provide a common set of research priorities and ensure a more cohesive US contribution to international SOLAS.This report was developed with federal support of NSF (OCE-1558412) and NASA (NNX17AB17G).This report was developed with federal support of NSF (OCE-1558412) and NASA (NNX17AB17G)