Simulation of rock salt dissolution and its impact on land subsidence

Extensive land subsidence can occur due to subsurface dissolution of evaporites such as halite and gypsum. This paper explores techniques to simulate the salt dissolution forming an intrastratal karst, which is embedded in a sequence of carbonates, marls, anhydrite and gypsum. A numerical model is developed to simulate laminar flow in a subhorizontal void, which corresponds to an opening intrastratal karst. The numerical model is based on the laminar steady-state Stokes flow equation, and the advection dispersion transport equation coupled with the dissolution equation. The flow equation is solved using the nonconforming Crouzeix-Raviart (CR) finite element approximation for the Stokes equation. For the transport equation, a combination between discontinuous Galerkin method and multipoint flux approximation method is proposed. The numerical effect of the dissolution is considered by using a dynamic mesh variation that increases the size of the mesh based on the amount of dissolved salt. The numerical method is applied to a 2D geological cross section representing a Horst and Graben structure in the Tabular Jura of northwestern Switzerland. The model simulates salt dissolution within the geological section and predicts the amount of vertical dissolution as an indicator of potential subsidence that could occur. Simulation results showed that the highest dissolution amount is observed near the normal fault zones, and, therefore, the highest subsidence rates are expected above normal fault zones

Interaction-tuned Anderson versus Mott localization

Disorder or sufficiently strong interactions can render a metallic state unstable causing it to turn into an insulating one. Despite the fact that the interplay of these two routes to a vanishing conductivity has been a central research topic, a unifying picture has not emerged so far. Here, we establish that the two-dimensional Falicov-Kimball model, one of the simplest lattice models of strong electron correlation does allow for the study of this interplay. In particular, we show that this model at particle-hole symmetry possesses three distinct thermodynamic insulating phases and exhibits Anderson localization. The previously reported metallic phase is identified as a finite-size feature due to the presence of weak localization. We characterize these phases by their electronic density of states, staggered occupation, conductivity, and the generalized inverse participation ratio. The implications of our findings for other strongly correlated systems are discussed.Comment: 5 pages, 4 figure

All models of satellite-derived phenology are wrong, but some are useful: a case study from northern Australia

Satellite-derived phenology (or apparent phenology) is frequently used to illustrate changes in plant phenology (i.e. true phenology) and the effects of climate forcing. However, each study uses a different method to detect phenology. Plant phenology refers to the relationship between the life cycle of plants and weather and climate events. Phenology is often studied in the field, but recently studies have transitioned towards using satellite images to monitor phenology at the plot, country, and continental scales. The problem with this approach is that there is an ever-increasing variety of earth observation satellites collecting data with different spatial, spectral, and temporal characteristics. In this paper we ask if studies that detect phenology using different sensors over the same site produce comparable results. Mangrove forests are one example where different methods have been used to examine their apparent phenology. In general, plant phenology, including mangroves, is described using few individual plants, but continental-scale descriptions of phenological events are scarce or inexistent. Few attempts have been made to describe the phenology of mangroves using satellite imagery, and each study presents a different method. We hypothesize that apparent phenology changes with: 1) areal extent; 2) site location; 3) frequency of observation; 4) spatial resolution; 5) temporal coverage; and 6) the number of cloud contaminated observations. Intuitively, one would assume that these hypotheses hold true, yet few studies have investigated this. For example, one would expect that clouds change the observed phenology of vegetation, that the number of species captured at spatial resolution will impact the apparent phenology, or that mangroves in different places display different phenologies, but how are these changes represented in the apparent phenology? We use the Enhanced Vegetation Index (EVI) to examine the changes in the start of season and peak growing season dates, as well as the shape and amplitude of the apparent phenology in each hypothesis. We use Landsat and Sentinel 2 imagery over the mangrove forests in Darwin Harbour (Northern Territory, Australia) as a case study, and found that apparent phenology does change with the sensor, site, and cloud contamination. Importantly, the apparent phenology is comparable between Landsat and Sentinel 2 sensors, but it is not comparable to phenology derived from MODIS. This is due to differences in the spatial resolution of the sensors. Cloud contamination also significantly changes the apparent phenology of vegetation. In this paper we expose the complexity of modelling phenology with remote sensing and help guide future phenology investigations

Monitoring mangrove forests: are we taking full advantage of technology?

Mangrove forests grow in the estuaries of 124 tropical countries around the world. Because in-situ monitoring of mangroves is difficult and time-consuming, remote sensing technologies are commonly used to monitor these ecosystems. Landsat satellites have provided regular and systematic images of mangrove ecosystems for over 30 years, yet researchers often cite budget and infrastructure constraints to justify the underuse this resource. Since 2001, over 50 studies have used Landsat or ASTER imagery for mangrove monitoring, and most focus on the spatial extent of mangroves, rarely using more than five images. Even after the Landsat archive was made free for public use, few studies used more than five images, despite the clear advantages of using more images (e.g. lower signal-to-noise ratios). The main argument of this paper is that, with freely available imagery and high performance computing facilities around the world, it is up to researchers to acquire the necessary programming skills to use these resources. Programming skills allow researchers to automate repetitive and time-consuming tasks, such as image acquisition and processing, consequently reducing up to 60% of the time dedicated to these activities. These skills also help scientists to review and re-use algorithms, hence making mangrove research more agile. This paper contributes to the debate on why scientists need to learn to program, not only to challenge prevailing approaches to mangrove research, but also to expand the temporal and spatial extents that are commonly used for mangrove research

Automating drone image processing to map coral reef substrates using Google Earth Engine

While coral reef ecosystems hold immense biological, ecological, and economic value, frequent anthropogenic and environmental disturbances have caused these ecosystems to decline globally. Current coral reef monitoring methods include in situ surveys and analyzing remotely sensed data from satellites. However, in situ methods are often expensive and inconsistent in terms of time and space. High-resolution satellite imagery can also be expensive to acquire and subject to environmental conditions that conceal target features. High-resolution imagery gathered from remotely piloted aircraft systems (RPAS or drones) is an inexpensive alternative; however, processing drone imagery for analysis is time-consuming and complex. This study presents the first semi-automatic workflow for drone image processing with Google Earth Engine (GEE) and free and open source software (FOSS). With this workflow, we processed 230 drone images of Heron Reef, Australia and classified coral, sand, and rock/dead coral substrates with the Random Forest classifier. Our classification achieved an overall accuracy of 86% and mapped live coral cover with 92% accuracy. The presented methods enable efficient processing of drone imagery of any environment and can be useful when processing drone imagery for calibrating and validating satellite imagery

Efficient blood flow simulations for the design of stented valve reducer in enlarged ventricular outflow tracts

Tetralogy of Fallot is a congenital heart disease characterized over time, after the initial repair, by the absence of a functioning pulmonary valve, which causes regurgitation, and by progressive enlargement of the right ventricle and pulmonary arteries. Due to this pathological anatomy, available transcatheter valves are usually too small to be deployed in the enlarged right ventricular outflow tracts (RVOT). To avoid surgical valve replacement, an alternative consists in implanting a reducer prior to or in combination with a transcatheter valve. We describe a computational model to study the effect of a stented valve RVOT reducer on the hemodynamics in enlarged ventricular outflow tracts. To this aim, blood flow in the right ventricular outflow tract is modeled via the incompressible Navier--Stokes equations coupled to a simplified valve model, numerically solved with a standard finite element method and with a reduced order model based on Proper Orthogonal Decomposition (POD). Numerical simulations are based on a patient geometry obtained from medical imaging and boundary conditions tuned according to measurements of inlet flow rates and pressures. Different geometrical models of the reducer are built, varying its length and/or diameter, and compared with the initial device-free state. Simulations thus investigate multiple device configurations and describe the effect of geometry on hemodynamics. Forces exerted on the valve and on the reducer are monitored, varying with geometrical parameters. Results support the thesis that the reducer does not introduce significant pressure gradients, as was found in animal experiments. Finally, we demonstrate how computational complexity can be reduced with POD

Un-reduction

This paper provides a full geometric development of a new technique called un-reduction, for dealing with dynamics and optimal control problems posed on spaces that are unwieldy for numerical implementation. The technique, which was originally concieved for an application to image dynamics, uses Lagrangian reduction by symmetry in reverse. A deeper understanding of un-reduction leads to new developments in image matching which serve to illustrate the mathematical power of the technique.Comment: 25 pages, revised versio

Isocyanurate transformation induced healing of isocyanurate–oxazolidone polymers

Isocyanurate–oxazolidone (ISOX) polymers have been reported as a novel, intrinsically self‐healable thermoset, and their healing mechanism under the effect of nucleophiles, such as tertiary amines and pyridines during polymerization, is thoroughly investigated in this study. This work provides evidence that the healing behavior of the polymers results part from the transformation of isocyanurate to oxazolidone on the fracture surfaces of the ISOX polymers at elevated temperatures. The isocyanurate transformation is characterized by chemical composition of the ISOX polymers before and after a predetermined healing procedure, through a combination characterization of Fourier transform infrared spectroscopy and carbon nuclear magnetic resonance spectroscopy. From the chemical composition of the ISOX polymers, an increased oxazolidone fraction is observed after the healing event, which verifies the hypothesized healing mechanism. By correlating the change in oxazolidone fraction in the polymers during the healing event, with the corresponding healing performance of the polymers, healing efficiencies of the polymers are shown to be inversely proportional to the ratio of oxazolidone to isocyanurate in the polymers. The transformation to oxazolidone is also shown to be dependent on two variables, nucleophilicity of the polymerization catalyst and duration of the postcure. The isocyanate and epoxide polymerization mechanism in the presence of nucleophiles is also investigated to explain the effect of the catalyst nucleophilicity on the chemical composition as well as the healing performance of the ISOX polymers. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019, 137, 48698.Isocyanurate‐to‐oxazolidone transformation within the polymers for healing.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154270/1/app48695-sup-0001-FigureS1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154270/2/app48698_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154270/3/app48698.pd

The association between living conditions and health among Syrian refugee children in informal tented settlements in Lebanon

BACKGROUND: This cross-sectional study explores the relationship between housing, social wellbeing, access to services and health among a population of Syrian refugee children in Lebanon. METHODS: We surveyed 1902 Syrian refugee households living in informal tented settlements in Lebanon in 2017. Logistic regressions assessed relationships between housing problems, socioeconomic deprivation, social environment and health. RESULTS: Of the 8284 children in the study, 33.0% had at least one health problem. A considerable number of households (43.1%) had > 8 housing problems. Children in these households had higher odds to have three or more health problems compared to children in households with < 6 housing problems (adjusted odds ratio [AOR], 2.39; confidence interval [CI], 1.50-3.81). Nearly three-quarters (74.3%) of households were severely food insecure. Children in these households had higher odds to have one health problem than those in food secure households (AOR, 1.75; CI, 1.11-2.76). There was a significant positive association between households that reported being unhappy with their neighbourhood and the number of children with health problems in those households. CONCLUSIONS: This study highlights the association between the physical and social living conditions and refugee children's health. Without multidimensional interventions that consider improvements to living conditions, the health of young Syrian refugees will continue to worsen

Incorporating coarse and fine recycled aggregates into concrete mixes: mechanical characterization and environmental impact

Concrete waste (CW) recycling stands as a promising strategy to promote sustainable construction practices. This research aims to assess the feasibility of using recycled concrete aggregates (RCA) as a surrogate for natural aggregates (NA) in concrete applications and reduce the environmental impact associated with the depletion of natural resources and landfill space. To achieve these objectives, CW was segregated from debris mixes of construction and demolition waste (CDW), collected, crushed, and graded to generate RCA. Thirty-two concrete samples were prepared and categorized into four distinct groups with 0% (reference), 50%, 75%, and 100% substitution levels for both coarse RCA (CRCA) and fine RCA (FRCA), all utilized simultaneously. Concurrently, the environmental impacts of producing 1 m3 of concrete were evaluated using a life cycle assessment (LCA) approach, (cradle-to-gate) covering three phases, the raw material supply (A1), transportation (A2) and concrete production (A3). At the 50% replacement level, the mechanical properties of recycled aggregate concrete (RAC) demonstrated a 20.0% increase in splitting tensile strength, accompanied by marginal decrease in workability (15.0%) and compressive strength (6.0%). In addition, at that percentage, the average environmental effects were reduced by 31.3%, with specific reductions of 34.7% for A1, 40.3% for A2, and no change in A3