A two-dimensional finite element model of front surface current flow in cells under non-uniform, concentrated illumination

A two-dimensional finite element model of current flow in the front surface of a PV cell is presented. In order to validate this model we perform an experimental test. Later, particular attention is paid to the effects of non-uniform illumination in the finger direction which is typical in a linear concentrator system. Fill factor, open circuit voltage and efficiency are shown to decrease with increasing degree of non-uniform illumination. It is shown that these detrimental effects can be mitigated significantly by reoptimization of the number of front surface metallization fingers to suit the degree of non-uniformity. The behavior of current flow in the front surface of a cell operating at open circuit voltage under non-uniform illumination is discussed in detail.

Desing of an Airport Surface Routing Evaluation Tool

There are many studies related with airport surface routing algorithms, based on different approaches and with different evaluation methods and metrics. So, the need of performing a balanced analysis and comparison using a common framework is evident. This paper presents an implementation of an evaluation tool for airport surface routing algorithms. The routing evaluation tool presented here is based in three basic pillars composed by the airport model, the model and generation of traffic and a comprehensive figure of merit function. The paper includes some example evaluations performed over Barajas Airport with representative traffic samples using several simple routing methods.

Topological invariance and spatial scaling of surface roughness in two highly eroded zones of Mexico: a comparative study

The Fractal Image Informatics toolbox (Oleschko et al., 2008 a; Torres-Argüelles et al., 2010) was applied to extract, classify and model the topological structure and dynamics of surface roughness in two highly eroded catchments of Mexico. Both areas are affected by gully erosion (Sidorchuk, 2005) and characterized by avalanche-like matter transport. Five contrasting morphological patterns were distinguished across the slope of the bare eroded surface of Faeozem (Queretaro State) while only one (apparently independent on the slope) roughness pattern was documented for Andosol (Michoacan State). We called these patterns ?the roughness clusters? and compared them in terms of metrizability, continuity, compactness, topological connectedness (global and local) and invariance, separability, and degree of ramification (Weyl, 1937). All mentioned topological measurands were correlated with the variance, skewness and kurtosis of the gray-level distribution of digital images. The morphology0 spatial dynamics of roughness clusters was measured and mapped with high precision in terms of fractal descriptors. The Hurst exponent was especially suitable to distinguish between the structure of ?turtle shell? and ?ramification? patterns (sediment producing zone A of the slope); as well as ?honeycomb? (sediment transport zone B) and ?dinosaur steps? and ?corals? (sediment deposition zone C) roughness clusters. Some other structural attributes of studied patterns were also statistically different and correlated with the variance, skewness and kurtosis of gray distribution of multiscale digital images. The scale invariance of classified roughness patterns was documented inside the range of five image resolutions. We conjectured that the geometrization of erosion patterns in terms of roughness clustering might benefit the most semi-quantitative models developed for erosion and sediment yield assessments (de Vente and Poesen, 2005).

Estimation of the solubility parameters of model plant surfaces and agrochemicals: a valuable tool for understanding plant surface interactions

Background Most aerial plant parts are covered with a hydrophobic lipid-rich cuticle, which is the interface between the plant organs and the surrounding environment. Plant surfaces may have a high degree of hydrophobicity because of the combined effects of surface chemistry and roughness. The physical and chemical complexity of the plant cuticle limits the development of models that explain its internal structure and interactions with surface-applied agrochemicals. In this article we introduce a thermodynamic method for estimating the solubilities of model plant surface constituents and relating them to the effects of agrochemicals. Results Following the van Krevelen and Hoftyzer method, we calculated the solubility parameters of three model plant species and eight compounds that differ in hydrophobicity and polarity. In addition, intact tissues were examined by scanning electron microscopy and the surface free energy, polarity, solubility parameter and work of adhesion of each were calculated from contact angle measurements of three liquids with different polarities. By comparing the affinities between plant surface constituents and agrochemicals derived from (a) theoretical calculations and (b) contact angle measurements we were able to distinguish the physical effect of surface roughness from the effect of the chemical nature of the epicuticular waxes. A solubility parameter model for plant surfaces is proposed on the basis of an increasing gradient from the cuticular surface towards the underlying cell wall. Conclusions The procedure enabled us to predict the interactions among agrochemicals, plant surfaces, and cuticular and cell wall components, and promises to be a useful tool for improving our understanding of biological surface interactions.

Sensitivity of a distributed temperature-radiation index melt model based on AWS observations and surface energy balance fluxes, Hurd Peninsula glaciers, Livingston Island, Antarctica

We use an automatic weather station and surface mass balance dataset spanning four melt seasons collected on Hurd Peninsula Glaciers, South Shetland Islands, to investigate the point surface energy balance, to determine the absolute and relative contribution of the various energy fluxes acting on the glacier surface and to estimate the sensitivity of melt to ambient temperature changes. Long-wave incoming radiation is the main energy source for melt, while short-wave radiation is the most important flux controlling the variation of both seasonal and daily mean surface energy balance. Short-wave and long-wave radiation fluxes do, in general, balance each other, resulting in a high correspondence between daily mean net radiation flux and available melt energy flux. We calibrate a distributed melt model driven by air temperature and an expression for the incoming short-wave radiation. The model is calibrated with the data from one of the melt seasons and validated with the data of the three remaining seasons. The model results deviate at most 140 mm w.e. from the corresponding observations using the glaciological method. The model is very sensitive to changes in ambient temperature: a 0.5 ◦ C increase results in 56 % higher melt rates.

Estimation of the solubility parameters of model plant surfaces and agrochemicals: a valuable tool for understanding plant surface interactions

Background Most aerial plant parts are covered with a hydrophobic lipid-rich cuticle, which is the interface between the plant organs and the surrounding environment. Plant surfaces may have a high degree of hydrophobicity because of the combined effects of surface chemistry and roughness. The physical and chemical complexity of the plant cuticle limits the development of models that explain its internal structure and interactions with surface-applied agrochemicals. In this article we introduce a thermodynamic method for estimating the solubilities of model plant surface constituents and relating them to the effects of agrochemicals. Results Following the van Krevelen and Hoftyzer method, we calculated the solubility parameters of three model plant species and eight compounds that differ in hydrophobicity and polarity. In addition, intact tissues were examined by scanning electron microscopy and the surface free energy, polarity, solubility parameter and work of adhesion of each were calculated from contact angle measurements of three liquids with different polarities. By comparing the affinities between plant surface constituents and agrochemicals derived from (a) theoretical calculations and (b) contact angle measurements we were able to distinguish the physical effect of surface roughness from the effect of the chemical nature of the epicuticular waxes. A solubility parameter model for plant surfaces is proposed on the basis of an increasing gradient from the cuticular surface towards the underlying cell wall. Conclusions The procedure enabled us to predict the interactions among agrochemicals, plant surfaces, and cuticular and cell wall components, and promises to be a useful tool for improving our understanding of biological surface interactions.

A stochastic model updating method for parameter variability quantification based on response surface models and Monte Carlo simulation

Stochastic model updating must be considered for quantifying uncertainties inherently existing in real-world engineering structures. By this means the statistical properties,instead of deterministic values, of structural parameters can be sought indicating the parameter variability. However, the implementation of stochastic model updating is much more complicated than that of deterministic methods particularly in the aspects of theoretical complexity and low computational efficiency. This study attempts to propose a simple and cost-efficient method by decomposing a stochastic updating process into a series of deterministic ones with the aid of response surface models and Monte Carlo simulation. The response surface models are used as surrogates for original FE models in the interest of programming simplification, fast response computation and easy inverse optimization. Monte Carlo simulation is adopted for generating samples from the assumed or measured probability distributions of responses. Each sample corresponds to an individual deterministic inverse process predicting the deterministic values of parameters. Then the parameter means and variances can be statistically estimated based on all the parameter predictions by running all the samples. Meanwhile, the analysis of variance approach is employed for the evaluation of parameter variability significance. The proposed method has been demonstrated firstly on a numerical beam and then a set of nominally identical steel plates tested in the laboratory. It is found that compared with the existing stochastic model updating methods, the proposed method presents similar accuracy while its primary merits consist in its simple implementation and cost efficiency in response computation and inverse optimization.

Linking topography of its potential surface with the dynamics of folding of a protein model

The “3-color, 46-bead” model of a folding polypeptide is the vehicle for adapting to proteins a mode of analysis used heretofore for atomic clusters, to relate the topography of the potential surface to the dynamics that lead to formation of selected structures. The analysis is based on sequences of stationary points—successive minima, joined by saddles—that rise monotonically in energy from basin bottoms. Like structure-seeking clusters, the potential surface of the model studied here is staircase-like, rather than sawtooth-like, with highly collective motions required for passage from one minimum to the next. The surface has several deep basins whose minima correspond to very similar structures, but which are separated by high energy barriers.

DNA-mediated immunization in a transgenic mouse model of the hepatitis B surface antigen chronic carrier state.

Transgenic mice expressing the sequences coding for the envelope proteins of the hepatitis B virus (HBV) in the liver have been used as a model of the HBV chronic carrier state. We evaluated the possibility of inducing a specific immune response to the viral envelope antigens and thus potentially controlling chronic HBV infection. Using HBV-specific DNA-mediated immunization in this transgenic model, we show that the immune response induced after a single intramuscular injection of DNA resulted in the complete clearance of circulating hepatitis B surface antigen and in the long-term control of transgene expression in hepatocytes. This response does not involve a detectable cytopathic effect in the liver. Adoptive transfer of fractionated primed spleen cells from DNA-immunized mice shows that T cells are responsible for the down-regulation of HBV mRNA in the liver of transgenic mice. To our knowledge, this is the first demonstration of a potential immunotherapeutic application of DNA-mediated immunization against an infectious disease and raises the possibility of designing more effective ways of treating HBV chronic carriers.

A Hydrodynamic Method For Measuring Aqueous Nanoparticle Surface Interactions

The objectives of this research dissertation were to develop and present novel analytical methods for the quantification of surface binding interactions between aqueous nanoparticles and water-soluble organic solutes. Quantification of nanoparticle surface interactions are presented in this work as association constants where the solutes have interacted with the surface of the nanoparticles. By understanding these nanoparticle-solute interactions, in part through association constants, the scientific community will better understand how organic drugs and nanomaterials interact in the environment, as well as to understand their eventual environmental fate. The biological community, pharmaceutical, and consumer product industries also have vested interests in nanoparticle-drug interactions for nanoparticle toxicity research and in using nanomaterials as drug delivery vesicles. The presented novel analytical methods, applied to nanoparticle surface association chemistry, may prove to be useful in assisting the scientific community to understand the risks, benefits, and opportunities of nanoparticles. The development of the analytical methods presented uses a model nanoparticle, Laponite-RD (LRD). LRD was the proposed nanoparticle used to model the system and technique because of its size, 25 nm in diameter. The solutes selected to model for these studies were chosen because they are also environmentally important. Caffeine, oxytetracycline (OTC), and quinine were selected to use as models because of their environmental importance and chemical properties that can be exploited in the system. All of these chemicals are found in the environment; thus, how they interact with nanoparticles and are transported through the environment is important. The analytical methods developed utilize and a wide-bore hydrodynamic chromatography to induce a partial hydrodynamic separation between nanoparticles and dissolved solutes. Then, using deconvolution techniques, two separate elution profiles for the nanoparticle and organic solute can be obtained. Followed by a mass balance approach, association constants between LRD, our model nanoparticle, and organic solutes are calculated. These findings are the first of their kind for LRD and nanoclays in dilute dispersions.

Surface velocity fields, digital elevation models and ice front positions derived from multi-mission SAR remote sensing data at Sjögren Inlet glaciers, Antarctic Peninsula

Substantial retreat or disintegration of numerous ice shelves have been observed on the Antarctic Peninsula. The ice shelf in the Prince Gustav Channel retreated gradually since the late 1980's and broke-up in 1995. Tributary glaciers reacted with speed-up, surface lowering and increased ice discharge, consequently contributing to sea level rise. We present a detailed long-term study (1993-2014) on the dynamic response of Sjögren Inlet glaciers to the disintegration of Prince Gustav Ice Shelf. We analyzed various remote sensing datasets to observe the reactions of the glaciers to the loss of the buttressing ice shelf. A strong increase in ice surface velocities was observed with maximum flow speeds reaching 2.82±0.48 m/d in 2007 and 1.50±0.32 m/d in 2004 at Sjögren and Boydell glaciers respectively. Subsequently, the flow velocities decelerated, however in late 2014, we still measured about two times the values of our first measurements in 1996. The tributary glaciers retreated 61.7±3.1 km² behind the former grounding line of the ice shelf. In regions below 1000 m a.s.l., a mean surface lowering of -68±10 m (-3.1 m/a) was observed in the period 1993-2014. The lowering rate decreased to -2.2 m/a in recent years. Based on the surface lowering rates, geodetic mass balances of the glaciers were derived for different time steps. High mass loss rate of -1.21±0.36 Gt/a was found in the earliest period (1993-2001). Due to the dynamic adjustments of the glaciers to the new boundary conditions the ice mass loss reduced to -0.59±0.11 Gt/a in the period 2012-2014, resulting in an average mass loss rate of -0.89±0.16 Gt/a (1993-2014). Including the retreat of the ice front and grounding line, a total mass change of -38.5±7.7 Gt and a contribution to sea level rise of 0.061±0.013 mm were computed. Analysis of the ice flux revealed that available bedrock elevation estimates at Sjögren Inlet are too shallow and are the major uncertainty in ice flux computations. This temporally dense time series analysis of Sjögren Inlet glaciers shows that the adjustments of tributary glaciers to ice shelf disintegration are still going on and provides detailed information of the changes in glacier dynamics.

Development of a digital model of ground-water flow in deeply weathered crystalline rock, Chester County, Pennsylvania /

"August 1980."

Calculating the Uncertainty of a Structure from Motion (SfM) Model, Cadman Quarry, Monroe, Washington

Structure from Motion (SfM) is a new form of photogrammetry that automates the rendering of georeferenced 3D models of objects using digital photographs and independently surveyed Ground Control Points (GCPs). This project seeks to quantify the error found in Digital Elevation Models (DEMs) produced using SfM. I modeled a rockslide found at the Cadman Quarry (Monroe, Washington) because the surface is vegetation-free, which is ideal for SfM and Terrestrial LiDAR Scanner (TLS) surveys. By using SfM, TLS, and GPS positioning at the same time, I attempted to find the deviation in the SfM model from the TLS model and GPS points. Using the deviation, I found the Root-Mean-Square Error (RMSE) between the SfM DEM and GPS positions. The RMSE of the SfM model when compared to surveyed GPS points is 17cm. I propagated the uncertainty of the GPS points with the RMSE of the SfM model to find the uncertainty of the SfM model compared to the NAD 1984 datum. The uncertainty of the SfM model compared to the NAD 1984 is 27cm. This study did not produce a model from the TLS that had sufficient resolution on horizontal surfaces to compare to surveyed GPS points.