Soft X-ray detection with the Fairchild 100 by 100 CCD

The soft X-ray sensitivity of the Fairchild 100 x 100 element CCD is studied for possible use as a detector in plasma physics research. The experimental setup and laboratory results are reported including data on slow scan operation of the CCD and performance when cooled. Results from digital computer processing of the data to correct for element-to-element nonuniformities are also discussed

Investigation of friction hysteresis using a laboratory-scale tribometer

The current paper addresses the characterization of dynamic friction by using a laboratory-scale tribometer. A special post-processing script in MatLab has been developed in order to analyse the data from the experiments. A sine wave signal for the velocity is imposed, with three different frequencies and, consequently, acceleration and deceleration rates. A friction material from brakes, with nominal contact area of 254 mm², was subjected to sliding against a commercially available brake disc (gray cast iron, diameter of 256 mm). Some technical details and adjustments from the designed tribometer are showed and the results from the experiments are discussed. A friction hysteresis has been observed for all experimental curves, which exhibit loops in elliptical shape. A negative slope has been encountered for the curves when the imposed frequency is 1 Hz and 2 Hz, while for the highest frequency (4 Hz) the slope is positive. The laboratory-scale tribometer, associated to the post-processing stage, is capable to successfully be used to characterize friction hysteresis effect

Reconstruction of the refractive index from experimental backscattering data using a globally convergent inverse method

The problem to be studied in this work is within the context of coefficient identification problems for the wave equation. More precisely, we consider the problem of reconstruction of the refractive index (or equivalently, the dielectric constant) of an inhomogeneous medium using one backscattering boundary measurement. The goal of this paper is to analyze the performance of a globally convergent algorithm of Beilina and Klibanov on experimental data acquired in the Microwave Laboratory at University of North Carolina at Charlotte. The main challenge working with experimental data is the the huge misfit between these data and computationally simulated data. We present data pre-processing steps to make the former somehow look similar to the latter. Results of both non-blind and blind targets are shown indicating good reconstructions even for high contrasts between the targets and the background medium.Comment: 25 page

Advanced development: Fuels

The solar thermal fuels and chemicals program at Jet Propulsion Laboratory are described. High technology is developed and applied to displace fossil fuel (oil) use in the production/processing of valuable fuels and chemicals. The technical and economic feasibility is demonstrated to extent that enables the industry to participate and commercialize the product. A representative process, namely Furfural production with a bottoming of acetone, butanol and ethanol, is described. Experimental data from all solar production of furfural is discussed. Estimates are given to show the attractiveness of this process, considering its flexibility to be adaptable to dishes, troughs or central receivers. Peat, lignite and low rank coal processing, heavy oil stripping and innovative technologies for process diagnostics and control are mentioned as examples of current projects under intensive development

Experimental Test Plan DOE Tidal and River Reference Turbines

Our aim is to provide details of the experimental test plan for scaled model studies in St. Anthony Falls Laboratory (SAFL) Main Channel at the University of Minnesota, including a review of study objectives, descriptions of the turbine models, the experimental set-up, instrumentation details, instrument measurement uncertainty, anticipated experimental test cases, post-processing methods, and data archiving for model developers

Simulation basis for a techno-economic evaluation of chitin nanomaterials production process using Aspen Plus® software

Process simulation is a useful tool that has been widely used to analyze, design and optimize energy balances in chemical technologies including those related to biomass processing, biorefinery processes and chemical engineering. The presented data set serves as basis for the simulation of chitin purification, nanofibers and nanocrystals production processes, considering laboratory experimental procedures described in previous experimental articles.Peer ReviewedPostprint (published version

Lessons taught and learned from the operation of the solar energy e-learning laboratory

The solar energy e learning laboratory (solar e-lab) in Cyprus is a good example of a web-based, remote engineering laboratory. It comprises a pilot solar energy conversion plant which is equipped with all necessary instrumentation, data acquisition, and communication devices needed for remote access, control, data collection and processing. The impact that the solar e-lab had during its nearly 5 years of operation is indeed high. Throughout this period, the solar e-lab has been accessed by users from over 500 locations from 79 countries spread all over the world. In the period of November 2004 to October 2008, more than a million visits were recorded, out of which 25000 have registered on the site and surfed through studying the supplied material. Around 1000 hits concerned registered users that passed the pre-lab test and performed the experimentation part. The four years of operation of the solar e-lab demonstrated how the Internet can be used as a tool to make the laboratory facilities accessible to engineering students and technicians located outside the laboratory, including overseas. In this way, the solar energy e-learning lab, its equipment and experimental facilities were made available and shared by a number of interested people, thus widening educational experiences. Judging from the online evaluation reports that were received from the solar e-lab users during the last 2 years of operation, it can be concluded that there is nearly excellent satisfaction by the users

Randomization in Laboratory Procedure Is Key to Obtaining Reproducible Microarray Results

The quality of gene expression microarray data has improved dramatically since the first arrays were introduced in the late 1990s. However, the reproducibility of data generated at multiple laboratory sites remains a matter of concern, especially for scientists who are attempting to combine and analyze data from public repositories. We have carried out a study in which a common set of RNA samples was assayed five times in four different laboratories using Affymetrix GeneChip arrays. We observed dramatic differences in the results across laboratories and identified batch effects in array processing as one of the primary causes for these differences. When batch processing of samples is confounded with experimental factors of interest it is not possible to separate their effects, and lists of differentially expressed genes may include many artifacts. This study demonstrates the substantial impact of sample processing on microarray analysis results and underscores the need for randomization in the laboratory as a means to avoid confounding of biological factors with procedural effects

Randomization in Laboratory Procedure Is Key to Obtaining Reproducible Microarray Results

The quality of gene expression microarray data has improved dramatically since the first arrays were introduced in the late 1990s. However, the reproducibility of data generated at multiple laboratory sites remains a matter of concern, especially for scientists who are attempting to combine and analyze data from public repositories. We have carried out a study in which a common set of RNA samples was assayed five times in four different laboratories using Affymetrix GeneChip arrays. We observed dramatic differences in the results across laboratories and identified batch effects in array processing as one of the primary causes for these differences. When batch processing of samples is confounded with experimental factors of interest it is not possible to separate their effects, and lists of differentially expressed genes may include many artifacts. This study demonstrates the substantial impact of sample processing on microarray analysis results and underscores the need for randomization in the laboratory as a means to avoid confounding of biological factors with procedural effects