Preliminary results of accelerated exposure testing of solar cell system components

Plastic samples and solar cell sub modules were exposed to an accelerated outdoor environment in Arizona and an accelerated simulated environment in a cyclic ultraviolet exposure tester which included humidity exposure. These tests were for preliminary screening of materials suitable for use in the manufacture of solar cell modules which are to have a 20-year lifetime. The samples were exposed for various times up to six months, equivalent to a real time exposure of four years. Suitable materials were found to be FEP-A, FEP-C, PFA, acrylic, silicone compounds and adhesives and possibly parylene. The method of packaging the sub modules was also found to be important to their performance

Method of making encapsulated solar cell modules

Electrical connections to solar cells in a module are made at the same time the cells are encapsulated for protection. The encapsulating material is embossed to facilitate the positioning of the cells during assembly

Improved cover for cadmium sulfide solar cells

Solar cell performance and radiation resistance is improved by application of 1-mil thickness of Teflon FEP protective material. Cells produce 30 percent more power than similar cells with conventional Kapton covers

Characterization of the precipitation in southwestern part of Greece with X-band Doppler radar, 2-D video disdrometer and rain gauges

International audienceWe document precipitation in the southwestern part of Greece with the National Observatory of Athens (NOA) X-band radar, NOA 2D video disdrometer and a network of rain gauges. The observations were collected between February and April 2004. Time evolution of the drop size distribution (DSD) is presented for the 9 March 2004 case where rain rate (computed on 1-min period) was measured up to 80 mm/h and reflectivity at the location of the disdrometer exceeded 40 dBZ. We then present the differences of DSD as function of the rain rate for the studied case as well as for the entire observations of the field experiment. It shows that higher the rain rate is, larger the range of the DSD and higher the concentration of the raindrops are

Real time outdoor exposure testing of solar cell modules and component materials

Plastic samples, solar cell modules, and sub-modules were exposed at test sites in Florida, Arizona, Puerto Rico, and Cleveland, Ohio, in order to determine materials suitable for use in solar cell modules with a proposed 20-year lifetime. Various environments were encountered including subtropical, subtropical with a sea air atmosphere, desert, rain forest, normal urban, and urban-polluted. The samples were exposed for periods up to six months. Materials found not suitable were polyurethane, polyester, Kapton, Mylar, and UV-stabilized Lexan. Suitable materials were acrylic, FEP-A, and glass. The results of exposure of polyvinylidene fluoride were dependent on the specific formulation, but several types appear suitable. RTV silicone rubber (clear) appears to pick up and hold dirt both as a free film and as a potting medium for modules. The results indicate that dirt accumulation and cleanability are important factors in the selection of solar cell module covers and encapsulants

The Random Bit Complexity of Mobile Robots Scattering

We consider the problem of scattering $n$ robots in a two dimensional continuous space. As this problem is impossible to solve in a deterministic manner, all solutions must be probabilistic. We investigate the amount of randomness (that is, the number of random bits used by the robots) that is required to achieve scattering. We first prove that $n \log n$ random bits are necessary to scatter $n$ robots in any setting. Also, we give a sufficient condition for a scattering algorithm to be random bit optimal. As it turns out that previous solutions for scattering satisfy our condition, they are hence proved random bit optimal for the scattering problem. Then, we investigate the time complexity of scattering when strong multiplicity detection is not available. We prove that such algorithms cannot converge in constant time in the general case and in $o(\log \log n)$ rounds for random bits optimal scattering algorithms. However, we present a family of scattering algorithms that converge as fast as needed without using multiplicity detection. Also, we put forward a specific protocol of this family that is random bit optimal ($n \log n$ random bits are used) and time optimal ($\log \log n$ rounds are used). This improves the time complexity of previous results in the same setting by a $\log n$ factor. Aside from characterizing the random bit complexity of mobile robot scattering, our study also closes its time complexity gap with and without strong multiplicity detection (that is, $O(1)$ time complexity is only achievable when strong multiplicity detection is available, and it is possible to approach it as needed otherwise)

The effect of sub-grid rainfall variability on the water balance and flux exchange processes resolved at climate scale: the European region contrasted to Central Africa and Amazon rainforests

International audienceThis paper investigates the effect of sub-grid rainfall variability on the simulation of land surface hydrologic processes of three regions (Europe, Africa and Amazon) with contrasting precipitation and vegetation characteristics. The sub-grid rainfall variability is defined in terms of the rainfall coverage fraction at the model's grid cells, and the statistical distribution of rain rates within the rain-covered areas. A statistical-dynamic approach is devised to incorporate the above variability properties into the canopy interception process of a land surface model. Our results reveal that incorporation of sub-grid rainfall variability significantly impacts the land-atmosphere water vapor exchanges. Specifically, it alters the partitioning between runoff and total evapotranspiration as well as the partitioning among the three components of evapotranspiration (canopy interception loss, ground evaporation and plant transpiration). This further influences the soil water, and to a lesser effect surface/vegetation temperatures and surface heat fluxes. It is shown that, overall, rainfall variability exerts less of an impact on the land-atmosphere flux exchanges over Europe compared to Africa and Amazon

A non-linear and stochastic response surface method for Bayesian estimation of uncertainty in soil moisture simulation from a land surface model

International audienceThis study presents a simple and efficient scheme for Bayesian estimation of uncertainty in soil moisture simulation by a Land Surface Model (LSM). The scheme is assessed within a Monte Carlo (MC) simulation framework based on the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. A primary limitation of using the GLUE method is the prohibitive computational burden imposed by uniform random sampling of the model's parameter distributions. Sampling is improved in the proposed scheme by stochastic modeling of the parameters' response surface that recognizes the non-linear deterministic behavior between soil moisture and land surface parameters. Uncertainty in soil moisture simulation (model output) is approximated through a Hermite polynomial chaos expansion of normal random variables that represent the model's parameter (model input) uncertainty. The unknown coefficients of the polynomial are calculated using limited number of model simulation runs. The calibrated polynomial is then used as a fast-running proxy to the slower-running LSM to predict the degree of representativeness of a randomly sampled model parameter set. An evaluation of the scheme's efficiency in sampling is made through comparison with the fully random MC sampling (the norm for GLUE) and the nearest-neighborhood sampling technique. The scheme was able to reduce computational burden of random MC sampling for GLUE in the ranges of 10%-70%. The scheme was also found to be about 10% more efficient than the nearest-neighborhood sampling method in predicting a sampled parameter set's degree of representativeness. The GLUE based on the proposed sampling scheme did not alter the essential features of the uncertainty structure in soil moisture simulation. The scheme can potentially make GLUE uncertainty estimation for any LSM more efficient as it does not impose any additional structural or distributional assumptions

Multiregional Satellite Precipitation Products Evaluation over Complex Terrain

An extensive evaluation of nine global-scale high-resolution satellite-based rainfall (SBR) products is performed using a minimum of 6 years (within the period of 2000-13) of reference rainfall data derived from rain gauge networks in nine mountainous regions across the globe. The SBR products are compared to a recently released global reanalysis dataset from the European Centre for Medium-Range Weather Forecasts (ECMWF). The study areas include the eastern Italian Alps, the Swiss Alps, the western Black Sea of Turkey, the French Cévennes, the Peruvian Andes, the Colombian Andes, the Himalayas over Nepal, the Blue Nile in East Africa, Taiwan, and the U.S. Rocky Mountains. Evaluation is performed at annual, monthly, and daily time scales and 0.25° spatial resolution. The SBR datasets are based on the following retrieval algorithms: Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis (TMPA), the NOAA/Climate Prediction Center morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN), and Global Satellite Mapping of Precipitation (GSMaP). SBR products are categorized into those that include gauge adjustment versus unadjusted. Results show that performance of SBR is highly dependent on the rainfall variability. Many SBR products usually underestimate wet season and overestimate dry season precipitation. The performance of gauge adjustment to the SBR products varies by region and depends greatly on the representativeness of the rain gauge network