Ice/frost detection using millimeter wave radiometry

A series of ice detection tests was performed on the shuttle external tank (ET) and on ET target samples using a 35/95 GHz instrumentation radiometer. Ice was formed using liquid nitrogen and water spray inside a test enclosure containing ET spray on foam insulation samples. During cryogenic fueling operations prior to the shuttle orbiter engine firing tests, ice was formed with freon and water over a one meter square section of the ET LOX tank. Data analysis was performed on the ice signatures, collected by the radiometer, using Georgia Tech computing facilities. Data analysis technique developed include: ice signature images of scanned ET target; pixel temperature contour plots; time correlation of target data with ice present versus no ice formation; and ice signature radiometric temperature statistical data, i.e., mean, variance, and standard deviation

A 94/183 GHz multichannel radiometer for Convair flights

A multichannel 94/183 GHz radiometer was designed, built, and installed on the NASA Convair 990 research aircraft to take data for hurricane penetration flights, SEASAT-A underflights for measuring rain and water vapor, and Nimbus-G underflights for new sea ice signatures and sea surface temperature data (94 GHz only). The radiometer utilized IF frequencies of 1, 5, and 8.75 GHz about the peak of the atmospheric water vapor absorption line, centered at 183.3 GHz, to gather data needed to determine the shape of the water molecule line. Another portion of the radiometer operated at 94 GHz and obtained data on the sea brightness temperature, sea ice signatures, and on areas of rain near the ocean surface. The radiometer used a multiple lens antenna/temperature calibration technique using 3 lenses and corrugated feed horns at 94 GHz and 183 GHz. Alignment of the feed beams at 94 GHz and 183 GHz was accomplished using a 45 deg oriented reflecting surface which permitted simultaneous viewing of the feeds on alternate cycles of the chopping intervals

A geographic information method for managing urban energy use

This paper presents a geographical information method to support urban-level energy policies. It proposes using a geographical information system to store, display, edit, share and analyse geographical information for territorial decision-making. The method was used to help develop a sustainable energy action plan for the municipality of Randazzo in Sicily, Italy, by providing an accurate representation of actual energy consumption. Based on this case study, the use of a geographical information system appears to be a suitable support tool for both developing and managing sustainable energy action plans, regardless of the geographical area or context. This method will help municipalities estimate and monitor the energy consumption of residential, commercial and industrial buildings and, by taking into account the approaches of different stakeholders, help develop more accurate models for reducing urban carbon dioxide emissions

Development of an Equilibrium-based Model of Gasification of Biomass by Aspen Plus

Abstract Agricultural and forestry residues are usually processed as wastes; otherwise, they can be recovered to produce electrical and thermal energy through processes of thermochemical conversion, such us torrefaction, pyrolysis and gasification. Currently, the gasification of residual biomass for producing neutral CO 2 fuel for energy production is in development stage. In this context, this study proposes anequilibrium-based model, developed by the commercial software Aspen Plus, of a co-current gasifier fueled with agriculture residual, which allows estimating the chemical composition and theheating value of the syngas produced. The prediction of such model includes the main gaseous species, the yields of char and tar and describes the gasification process through the mass and energy balances, the water-gas shift (WGS) and the methanation reaction. The model validation was carried out through the comparison with experimental data, concerning two biomass with different moisture content and different gasification conditions, for sixteen cases compared. Overall, the comparison between the results of the simulations and the experimental data have shown a good agreement

Optical Conductivity of the Two-Dimensional Hubbard Model

Charge dynamics of the two-dimensional Hubbard model is investigated. Lancz$\ddot{\rm o}$s-diagonalization results for the optical conductivity and the Drude weight of this model are presented. Near the Mott transition, large incoherence below the upper-Hubbard band is obtained together with a remarkably suppressed Drude weight in two dimensions while the clearly coherent character is shown in one dimension. The two-dimensional results are consistent with previous results from quantum Monte Carlo calculations indicating that the Mott transition in this two-dimensional model belongs to the universality class characterized by the dynamical exponent of $z=4$.Comment: 4 pages LaTeX including 2 PS figures, to appear in J. Phys. Soc. Jp

Informing disease modelling with brain-relevant functional genomic annotations

The past decade has seen a surge in the number of disease/trait-associated variants, largely because of the union of studies to share genetic data and the availability of electronic health records from large cohorts for research use. Variant discovery for neurological and neuropsychiatric genome-wide association studies, including schizophrenia, Parkinson's disease and Alzheimer's disease, has greatly benefitted; however, the translation of these genetic association results to interpretable biological mechanisms and models is lagging. Interpreting disease-associated variants requires knowledge of gene regulatory mechanisms and computational tools that permit integration of this knowledge with genome-wide association study results. Here, we summarize key conceptual advances in the generation of brain-relevant functional genomic annotations and amongst tools that allow integration of these annotations with association summary statistics, which together provide a new and exciting opportunity to identify disease-relevant genes, pathways and cell types in silico. We discuss the opportunities and challenges associated with these developments and conclude with our perspective on future advances in annotation generation, tool development and the union of the two