Automatic Detection and Control of Hazardous Plumes in Wall-Bounded Flow Systems.

Recent advances in technology and computational power have made the once theoretical concept of a real-time detection and control system, for the purpose of reducing risk from the deliberate or unintentional release of a hazardous plume, a practical reality. Such a system utilizes strategically placed sensor arrays and actuators in order to first detect the release of a hazardous chemical, and subsequently to determine the actions required by the actuators to effectively and expediently mitigate the plume. This basic framework is applicable to a number of real-world scenarios that can be described as wall-bounded, fluid-based systems, such as airport terminals, aqueducts, tall buildings and passenger tunnels. The present research develops the theoretical and numerical framework for the automatic detection and control algorithm, which requires two main steps: a source inversion phase in order to trace the history of the plume and determine its original properties, followed by a boundary control phase in which the recovered source information is used to predict the propagation of the plume in time and space and thereby determine a control strategy to be performed in order to effectively mitigate it. Both the source inversion and boundary control phases can be formulated in terms of numerical optimization, and hence in this work a coupled CFD-optimization model has been developed using open source software. The CFD model implemented in this research is a RANS (Reynolds-Averaged Navier-Stokes) based finite-volume model developed using the OpenFOAM CFD library. The CFD model has been linked to an external optimization software suite (DAKOTA). The resulting model is used to simulate the source inversion and boundary control components of the automatic detection and control algorithm and to investigate the effect of various parameters on their accuracy, reliability and expediency. The results indicate that gradient-based optimization methods are successful for the boundary control phase; however the source inversion problem is complicated by issues arising from the discretization of the optimization parameters and ill-posedness. Hybrid optimization approaches offer some benefits with regards to the former problem, yet ill-posedness remains a significant challenge with respect to the source inversion process.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/102288/1/awarnoc_1.pd

The NASA CYGNSS SmallSat Constellation

The NASA Cyclone Global Navigation Satellite System (CYGNSS) is a constellation of eight microsatellites in low earth orbit at ~525 km altitude and 35 deg inclination. CYGNSS was launched in December 2016 for a planned 2 year mission and 7 of the 8 spacecraft continue to operatue nominally as of May 2023. Each microsatellites carries a bistatic radar receiver to measure reflected GPS signals from the Earth surface. The measurements can be converted to surface wind speed and latent and sensible heat flux over the ocean, and to surface soil moisture and wetland extent over land. Measurements penetrate through all levels of precipitation as well as moderate to heavy vegetation due to the low microwave frequency used by GPS. The number of satellites in the constellation results in sub-daily refresh rates which supports imaging of short time scale weather events such as hurricane rapid intensification, flood inundation dynamics, and sudden soil saturation after major rain events. CYGNSS satellites uses a single string design architecture to reduce the complexity and recurring cost of each unit. Mission redundancy is obtained at the constellation level. Data products are produced by combining measurements from all satellites in such a way that the sampling requirements can be met using only a subset of the satellites. Constellation-level redundancy also permits individual satellites to be switched from their nominal science data taking mode to various engineering test and calibration modes while the overall mission is still able to meet its science requirements

The NASA Cyclone Global Navigation Satellite System SmallSat Constellation

The NASA Cyclone Global Navigation Satellite System (CYGNSS) mission consists of a constellation of eight microsatellites launched on 15 December 2016 into a common circular orbit at ~525 km altitude and 35 deg inclination. Each observatory carries a four channel bistatic radar receiver to measure GPS signals scattered by the Earth surface. Over ocean, near-surface wind speed, air-sea latent and sensible heat flux, and ocean microplastic concentration are derived from the measurements. Over land, near-surface soil moisture and inland water bodies extent are derived. The measurements penetrate through all levels of precipitation and most vegetation due to the 19 cm wavelength of GPS L1 signals. The sampling produced by the constellation makes possible the reliable detection of short time scale weather events such as flood inundation dynamics immediately after a tropical cyclone landfall and rapid soil moisture dry down immediately after major precipitation events. The sun-asynchronous nature of the CYGNSS orbit also supports full sampling of the diurnal cycle of hydrological dynamics within a short period of time. Summaries are presented of engineering and science highlights of the CYGNSS mission, with particular emphasis on those aspects most directly enabled by the use of a constellation of SmallSats

Marine Tar Residues: a Review

Abstract Marine tar residues originate from natural and anthropogenic oil releases into the ocean environment and are formed after liquid petroleum is transformed by weathering, sedimentation, and other processes. Tar balls, tar mats, and tar patties are common examples of marine tar residues and can range in size from millimeters in diameter (tar balls) to several meters in length and width (tar mats). These residues can remain in the ocean envi-ronment indefinitely, decomposing or becoming buried in the sea floor. However, in many cases, they are transported ashore via currents and waves where they pose a concern to coastal recreation activities, the seafood industry and may have negative effects on wildlife. This review summarizes the current state of knowledge on marine tar residue formation, transport, degradation, and distribution. Methods of detection and removal of marine tar residues and their possible ecological effects are discussed, in addition to topics of marine tar research that warrant further investigation. Emphasis is placed on ben-thic tar residues, with a focus on the remnants of the Deepwater Horizon oil spill in particular, which are still affecting the northern Gulf of Mexico shores years after the leaking submarine well was capped

Response to Variations in River Flowrate by a Spaceborne GNSS-R River Width Estimator

In recent years, the use of Global Navigation Satellite System-Reflectometry (GNSS-R) for remote sensing of the Earth’s surface has gained momentum as a means to exploit existing spaceborne microwave navigation systems for science-related applications. Here, we explore the potential for using measurements made by a spaceborne GNSS-R bistatic radar system (CYGNSS) during river overpasses to estimate its width, and to use that width as a proxy for river flowrate. We present a case study utilizing CYGNSS data collected in the spring of 2019 during multiple overpasses of the Pascagoula River in southern Mississippi over a range of flowrates. Our results demonstrate that a measure of river width derived from CYGNSS is highly correlated with the observed flowrates. We show that an approximately monotonic relationship exists between river flowrate and a measure of river width which we define as the associated GNSS-R width (AGW). These results suggest the potential for GNSS-R systems to be utilized as a means to estimate river flowrates and widths from space

Initial Findings On The Feasibility Of Real-Time Feedback Control Of A Hazardous Contaminant Released Into Channel Flow By Means Of A Laboratory-Scale Physical Prototype

The threat of accidental or deliberate toxic chemicals released into public spaces is a significant concern to public safety. The real-time detection and mitigation of such hazardous contaminants has the potential to minimize harm and save lives. We develop a computational fluid dynamics (CFD) flow control model with the capability of detecting and mitigating such contaminants. Furthermore, we develop a physical prototype to then test the computer model. The physical prototype is in its final stages of construction. Its current state, along with preliminary examples of the flow control model are presented throughout this paper

Marine Tar Residues: A Review

Marine tar residues originate from natural and anthropogenic oil releases into the ocean environment and are formed after liquid petroleum is transformed by weathering, sedimentation, and other processes. Tar balls, tar mats, and tar patties are common examples of marine tar residues and can range in size from millimeters in diameter (tar balls) to several meters in length and width (tar mats). These residues can remain in the ocean environment indefinitely, decomposing or becoming buried in the sea floor. However, in many cases, they are transported ashore via currents and waves where they pose a concern to coastal recreation activities, the seafood industry and may have negative effects on wildlife. This review summarizes the current state of knowledge on marine tar residue formation, transport, degradation, and distribution. Methods of detection and removal of marine tar residues and their possible ecological effects are discussed, in addition to topics of marine tar research that warrant further investigation. Emphasis is placed on benthic tar residues, with a focus on the remnants of the Deepwater Horizon oil spill in particular, which are still affecting the northern Gulf of Mexico shores years after the leaking submarine well was capped

Initial Findings on the Feasibility of Real-Time Feedback Control of a Hazardous Contaminant Released Into Channel Flow by Means of a Laboratory-Scale Physical Prototype

The threat of accidental or deliberate toxic chemicals released into public spaces is a significant concern to public safety. The real-time detection and mitigation of such hazardous contaminants has the potential to minimize harm and save lives. We develop a computational fluid dynamics (CFD) flow control model with the capability of detecting and mitigating such contaminants. Furthermore, we develop a physical prototype to then test the computer model. The physical prototype is in its final stages of construction. Its current state, along with preliminary examples of the flow control model are presented throughout this paper

Practical guidelines for Bayesian phylogenetic inference using Markov Chain Monte Carlo (MCMC) [version 1; peer review: 2 approved, 1 approved with reservations]

Phylogenetic estimation is, and has always been, a complex endeavor. Estimating a phylogenetic tree involves evaluating many possible solutions and possible evolutionary histories that could explain a set of observed data, typically by using a model of evolution. Modern statistical methods involve not just the estimation of a tree, but also solutions to more complex models involving fossil record information and other data sources. Markov Chain Monte Carlo (MCMC) is a leading method for approximating the posterior distribution of parameters in a mathematical model. It is deployed in all Bayesian phylogenetic tree estimation software. While many researchers use MCMC in phylogenetic analyses, interpreting results and diagnosing problems with MCMC remain vexing issues to many biologists. In this manuscript, we will offer an overview of how MCMC is used in Bayesian phylogenetic inference, with a particular emphasis on complex hierarchical models, such as the fossilized birth-death (FBD) model. We will discuss strategies to diagnose common MCMC problems and troubleshoot difficult analyses, in particular convergence issues. We will show how the study design, the choice of models and priors, but also technical features of the inference tools themselves can all be adjusted to obtain the best results. Finally, we will also discuss the unique challenges created by the incorporation of fossil information in phylogenetic inference, and present tips to address them

The CYGNSS Mission: On-Going Science Team Investigations

In 2012, the National Aeronautics and Space Administration (NASA) selected the CYclone Global Navigation Satellite System (CYGNSS) mission coordinated by the University of Michigan (UM) as a low-cost and high-science Earth Venture Mission. The CYGNSS mission was originally proposed for ocean surface wind speed estimation over Tropical Cyclones (TCs) using Earth-reflected Global Positioning System (GPS) signals, as signals of opportunity. The orbital configuration of each CYGNSS satellite is a circular Low Earth Orbit (LEO) with an altitude ~520 km and an inclination angle of ~35°. Each single Delay Doppler Mapping Instrument (DDMI) aboard the eight CYGNSS microsatellites collects forward scattered signals along four specular directions (incidence angle of the incident wave equals incidence angle of the reflected wave) corresponding to four different transmitting GPS spacecrafts, simultaneously. As such, CYGNSS allows one to sample the Earth’s surface along 32 tracks simultaneously, within a wide range of the satellites’ elevation angles over tropical latitudes. Following the Earth Science Division 2020 Senior Review, NASA announced recently it is extending the CYGNSS mission through 30 September 2023. The extended CYGNSS mission phase is focused on both ocean and land surface scientific investigations. In addition to ocean surface wind speed estimation, CYGNSS has also shown a significant ability to retrieve several geophysical parameters over land surfaces, such as Soil Moisture Content (SMC), Above Ground Biomass (AGB), and surface water extent. The on-going science team investigations are presented in this article