Investigation of spatial patterns of ground-water exchange with lakes, using a three-dimensional numerical model

Hydrogeologic variables controlling groundwater exchange with inflow and flow-through lakes were simulated using a three-dimensional numerical model (MODFLOW) to investigate and quantify spatial patterns of lake bed seepage and hydraulic head distributions in the porous medium surrounding the lakes. Also, the total annual inflow and outflow were calculated as a percentage of lake volume for flow-through lake simulations. The general exponential decline of seepage rates with distance offshore was best demonstrated at lower anisotropy ratio (i.e., Kh/Kv = 1, 10), with increasing deviation from the exponential pattern as anisotropy was increased to 100 and 1000. 2-D vertical section models constructed for comparison with 3-D models showed that groundwater heads and seepages were higher in 3-D simulations. Addition of low conductivity lake sediments decreased seepage rates nearshore and increased seepage rates offshore in inflow lakes, and increased the area of groundwater inseepage on the beds of flow-through lakes. Introduction of heterogeneity into the medium decreased the water table and seepage ratesnearshore, and increased seepage rates offshore in inflow lakes. A laterally restricted aquifer located at the downgradient side of the flow-through lake increased the area of outseepage. Recharge rate, lake depth and lake bed slope had relatively little effect on the spatial patterns of seepage rates and groundwater exchange with lakes.

Computational modeling of intermediate temperature proton exchange membrane (PEM) fuel cells

A two-phase three-dimensional computational model of an intermediate temperature (120--190°C) proton exchange membrane (PEM) fuel cell is presented. This represents the first attempt to model PEM fuel cells employing intermediate temperature membranes, in this case, phosphoric acid doped polybenzimidazole (PBI). To date, mathematical modeling of PEM fuel cells has been restricted to low temperature operation, especially to those employing Nafion ® membranes; while research on PBI as an intermediate temperature membrane has been solely at the experimental level. This work is an advancement in the state of the art of both these fields of research. With a growing trend toward higher temperature operation of PEM fuel cells, mathematical modeling of such systems is necessary to help hasten the development of the technology and highlight areas where research should be focused.^ This mathematical model accounted for all the major transport and polarization processes occurring inside the fuel cell, including the two phase phenomenon of gas dissolution in the polymer electrolyte. Results were presented for polarization performance, flux distributions, concentration variations in both the gaseous and aqueous phases, and temperature variations for various heat management strategies. The model predictions matched well with published experimental data, and were self-consistent.^ The major finding of this research was that, due to the transport limitations imposed by the use of phosphoric acid as a doping agent, namely low solubility and diffusivity of dissolved gases and anion adsorption onto catalyst sites, the catalyst utilization is very low (∼1--2%). Significant cost savings were predicted with the use of advanced catalyst deposition techniques that would greatly reduce the eventual thickness of the catalyst layer, and subsequently improve catalyst utilization. The model also predicted that an increase in power output in the order of 50% is expected if alternative doping agents to phosphoric acid can be found, which afford better transport properties of dissolved gases, reduced anion adsorption onto catalyst sites, and which maintain stability and conductive properties at elevated temperatures.^

Eulerian-Lagrangian two phase debris flow model

The main objective of this work is to develop a quasi three-dimensional numerical model to simulate stony debris flows, considering a continuum fluid phase, composed by water and fine sediments, and a non-continuum phase including large particles, such as pebbles and boulders. Large particles are treated in a Lagrangian frame of reference using the Discrete Element Method, the fluid phase is based on the Eulerian approach, using the Finite Element Method to solve the depth-averaged Navier-Stokes equations in two horizontal dimensions. The particle’s equations of motion are in three dimensions. The model simulates particle-particle collisions and wall-particle collisions, taking into account that particles are immersed in a fluid. Bingham and Cross rheological models are used for the continuum phase. Both formulations provide very stable results, even in the range of very low shear rates. Bingham formulation is better able to simulate the stopping stage of the fluid when applied shear stresses are low. Results of numerical simulations have been compared with data from laboratory experiments on a flume-fan prototype. Results show that the model is capable of simulating the motion of big particles moving in the fluid flow, handling dense particulate flows and avoiding overlap among particles. An application to simulate debris flow events that occurred in Northern Venezuela in 1999 shows that the model could replicate the main boulder accumulation areas that were surveyed by the USGS. Uniqueness of this research is the integration of mud flow and stony debris movement in a single modeling tool that can be used for planning and management of debris flow prone areas.

Eulerian-Lagrangian Two Phase Debris Flow Model

The main objective of this work is to develop a quasi three-dimensional numerical model to simulate stony debris flows, considering a continuum fluid phase, composed by water and fine sediments, and a non-continuum phase including large particles, such as pebbles and boulders. Large particles are treated in a Lagrangian frame of reference using the Discrete Element Method, the fluid phase is based on the Eulerian approach, using the Finite Element Method to solve the depth-averaged Navier–Stokes equations in two horizontal dimensions. The particle’s equations of motion are in three dimensions. The model simulates particle-particle collisions and wall-particle collisions, taking into account that particles are immersed in a fluid. Bingham and Cross rheological models are used for the continuum phase. Both formulations provide very stable results, even in the range of very low shear rates. Bingham formulation is better able to simulate the stopping stage of the fluid when applied shear stresses are low. Results of numerical simulations have been compared with data from laboratory experiments on a flume-fan prototype. Results show that the model is capable of simulating the motion of big particles moving in the fluid flow, handling dense particulate flows and avoiding overlap among particles. An application to simulate debris flow events that occurred in Northern Venezuela in 1999 shows that the model could replicate the main boulder accumulation areas that were surveyed by the USGS. Uniqueness of this research is the integration of mud flow and stony debris movement in a single modeling tool that can be used for planning and management of debris flow prone areas.

A systems approach to describing the process of individual adoption of IT innovations

Research on the adoption of innovations by individuals has been criticized for focusing on various factors that lead to the adoption or rejection of an innovation while ignoring important aspects of the dynamic process that takes place. Theoretical process-based models hypothesize that individuals go through consecutive stages of information gathering and decision making but do not clearly explain the mechanisms that cause an individual to leave one stage and enter the next one. Research on the dynamics of the adoption process have lacked a structurally formal and quantitative description of the process. ^ This dissertation addresses the adoption process of technological innovations from a Systems Theory perspective and assumes that individuals roam through different, not necessarily consecutive, states, determined by the levels of quantifiable state variables. It is proposed that different levels of these state variables determine the state in which potential adopters are. Various events that alter the levels of these variables can cause individuals to migrate into different states. ^ It was believed that Systems Theory could provide the required infrastructure to model the innovation adoption process, particularly applied to information technologies, in a formal, structured fashion. This dissertation assumed that an individual progressing through an adoption process could be considered a system, where the occurrence of different events affect the system's overall behavior and ultimately the adoption outcome. The research effort aimed at identifying the various states of such system and the significant events that could lead the system from one state to another. By mapping these attributes onto an “innovation adoption state space” the adoption process could be fully modeled and used to assess the status, history, and possible outcomes of a specific adoption process. ^ A group of Executive MBA students were observed as they adopted Internet-based technological innovations. The data collected were used to identify clusters in the values of the state variables and consequently define significant system states. Additionally, events were identified across the student sample that systematically moved the system from one state to another. The compilation of identified states and change-related events enabled the definition of an innovation adoption state-space model. ^

Seagrass sediments as a global carbon sink: Isotopic constraints

Seagrass meadows are highly productive habitats found along many of the world's coastline, providing important services that support the overall functioning of the coastal zone. The organic carbon that accumulates in seagrass meadows is derived not only from seagrass production but from the trapping of other particles, as the seagrass canopies facilitate sedimentation and reduce resuspension. Here we provide a comprehensive synthesis of the available data to obtain a better understanding of the relative contribution of seagrass and other possible sources of organic matter that accumulate in the sediments of seagrass meadows. The data set includes 219 paired analyses of the carbon isotopic composition of seagrass leaves and sediments from 207 seagrass sites at 88 locations worldwide. Using a three source mixing model and literature values for putative sources, we calculate that the average proportional contribution of seagrass to the surface sediment organic carbon pool is ∼50%. When using the best available estimates of carbon burial rates in seagrass meadows, our data indicate that between 41 and 66 gC m−2 yr−1 originates from seagrass production. Using our global average for allochthonous carbon trapped in seagrass sediments together with a recent estimate of global average net community production, we estimate that carbon burial in seagrass meadows is between 48 and 112 Tg yr−1, showing that seagrass meadows are natural hot spots for carbon sequestration.

Forecasting future prevalence of type 2 diabetes mellitus in Syria

Background Type 2 diabetes mellitus (T2DM) is increasingly becoming a major public health problem worldwide. Estimating the future burden of diabetes is instrumental to guide the public health response to the epidemic. This study aims to project the prevalence of T2DM among adults in Syria over the period 2003–2022 by applying a modelling approach to the country’s own data. Methods Future prevalence of T2DM in Syria was estimated among adults aged 25 years and older for the period 2003–2022 using the IMPACT Diabetes Model (a discrete-state Markov model). Results According to our model, the prevalence of T2DM in Syria is projected to double in the period between 2003 and 2022 (from 10% to 21%). The projected increase in T2DM prevalence is higher in men (148%) than in women (93%). The increase in prevalence of T2DM is expected to be most marked in people younger than 55 years especially the 25–34 years age group. Conclusions The future projections of T2DM in Syria put it amongst countries with the highest levels of T2DM worldwide. It is estimated that by 2022 approximately a fifth of the Syrian population aged 25 years and older will have T2DM.