COSMO—Software for designing smoke control systems in high-rise buildings

A differential computer model specifically designed to quantify smoke movement during a fire in a high-rise structure is described. The basic conservation equations are transformed into a computer code which can be used to determine the paths that smoke will take during a fire. The program is a tool for fire protection engineers to design a smoke management plan with the ultimate goal of improving occupant safety in the event of a fire. The computer code is based on a modified and improved differential smoke control model for the conditions in the floor spaces, stairwells and elevator shafts and it considers a complete set of variables that influence the motion of smoke throughout the building. Program output suggests ways to alter the pressure distribution within the building by using air handling equipment, so that occupants will have smoke-free areas on the floors and inside of the fire escape stairwells. Results for several example cases are provided, and the results are used to illustrate how smoke movement can be managed in order to mitigate dangerous conditions within the building.     

An experimentally validated thermo-mechanical model for the prediction of thermal contact conductance

A predictive model for estimating thermal contact conductance between two nominally flat metallic rough surfaces has been developed and experimentally validated. The predictive model consists of two complementary parts, the first of which is a surface deformation analysis to calculate the actual area of contact for each contact spot, while the second accounts for the effects of constriction resistance and gas gap conductance between the contacting surfaces. A surface characterization technique is developed which generates an equivalent 3-D surface profile from multiple 2-D profiles and determines the unique wavelengths of importance for the surface deformation and constriction resistance models. For given surface profiles and material properties of two contacting surfaces, and a specified contact pressure, the surface characterization technique filters out non-essential wavelengths on the surface, after which the surface deformation analysis calculates the deformation and contact area of each contacting asperity by considering three different modes of deformation, namely, elastic, elastic–plastic, and plastic. The constriction resistance model is then used to calculate the constriction resistance for each contacting asperity based on the area of contact and radius of curvature of the asperity. The constriction resistance values for all the contacting asperities are then used to calculate the total thermal contact conductance. An experimental facility has also been constructed to measure thermal contact conductance of interfaces to verify the results of the predictive model. Good agreement has been found between the model predictions and experimental measurements, validating the modeling approach.     

Stability of wood fast pyrolysis oil

This study evaluates the effects of storage conditions on physical and chemical properties of biomass fast pyrolysis oils exposed to elevated temperatures over extended periods of time. It was performed on oak pyrolysis oil generated in the NREL vortex reactor. Oil samples were stored at three temperatures: 37, 60 and 90°C in glass vessels. Properties of the oils were measured after hours of storage at 90°C, and after days or weeks at lower temperatures. Chemical changes in the oils were measured using GPC (molecular weight distribution) and FTIR spectroscopy. The oil remained a single phase throughout the studied conditions. Its pH was not affected by storage. The water content, viscosity and molecular weight of the oil increased with the time and temperature of storage. First-order reaction kinetics were successfully used to predict changes in molecular weight of the stored oil. FTIR provided evidence that etherification or esterification are mechanisms for condensation of the oil during storage.     

Small-signal frequency response of long-wavelength vertical-cavitylasers

The small-signal frequency response of long-wavelength vertical-cavity lasers (LW-VCLs) is of interest in determining the ultimate bandwidth of these devices for use in terrestrial networks. This letter analyses two distinct device structures of double wafer-bonded vertical-cavity lasers operating at 1.5 μm and compares their high-speed performance. We demonstrate the highest modulation bandwidth and the highest modulation current efficiency of an electrically pumped LW-VCL of 7 and 4.1 GHz/√mA, respectively     

Robust anisotropic diffusion

Relations between anisotropic diffusion and robust statistics are described in this paper. Specifically, we show that anisotropic diffusion can be seen as a robust estimation procedure that estimates a piecewise smooth image from a noisy input image. The "edge-stopping" function in the anisotropic diffusion equation is closely related to the error norm and influence function in the robust estimation framework. This connection leads to a new "edge-stopping" function based on Tukey's biweight robust estimator that preserves sharper boundaries than previous formulations and improves the automatic stopping of the diffusion. The robust statistical interpretation also provides a means for detecting the boundaries (edges) between the piecewise smooth regions in an image that has been smoothed with anisotropic diffusion. Additionally, we derive a relationship between anisotropic diffusion and regularization with line processes. Adding constraints on the spatial organization of the line processes allows us to develop new anisotropic diffusion equations that result in a qualitative improvement in the continuity of edges.     

News: Presidential "green chemistry" awards promote industrial pollution prevention

Technology.     

Effects of finite-precision conversion on linear predictivecoefficients

Two novel methods are presented for improving the finite-precision conversion of linear prediction coefficients in the form of reflection coefficients. The first method is based on the improvement of the dynamic range of the intermediate variables in the Schur (1986) recursion using the block exponential format. For the second method, improvement is achieved by changing the statistical properties of the quantisation noise incurred during conversion. This is achieved with the addition of low-power uniform uncorrelated noise during the conversion from a lattice filter structure to direct-form filter structure. Statistical tests performed over a 1000 test frames reveal a significant reduction in both the variance and mean of the error compared with the standard fixed-point LPC filter     

A Low-Power Integrated Circuit for a Wireless 100-Electrode Neural Recording System

Recent work in field of neuroprosthetics has demonstrated that by observing the simultaneous activity of many neurons in specific regions of the brain, it is possible to produce control signals that allow animals or humans to drive cursors or prosthetic limbs directly through thoughts. As neuroprosthetic devices transition from experimental to clinical use, there is a need for fully-implantable amplification and telemetry electronics in close proximity to the recording sites. To address these needs, we developed a prototype integrated circuit for wireless neural recording from a 100-channel microelectrode array. The design of both the system-level architecture and the individual circuits were driven by severe power constraints for small implantable devices; chronically heating tissue by only a few degrees Celsius leads to cell death. Due to the high data rate produced by 100 neural signals, the system must perform data reduction as well. We use a combination of a low-power ADC and an array of "spike detectors" to reduce the transmitted data rate while preserving critical information. The complete system receives power and commands (at 6.5 kb/s) wirelessly over a 2.64-MHz inductive link and transmits neural data back at a data rate of 330 kb/s using a fully-integrated 433-MHz FSK transmitter. The 4.7times5.9 mm² chip was fabricated in a 0.5-mum 3M2P CMOS process and consumes 13.5 mW of power. While cross-chip interference limits performance in single-chip operation, a two-chip system was used to record neural signals from a Utah Electrode Array in cat cortex and transmit the digitized signals wirelessly to a receiver     

High‐Performance Air‐Processed Polymer–Fullerene Bulk Heterojunction Solar Cells

High photovoltaic device performance is demonstrated in ambient‐air‐processed bulk heterojunction solar cells having an active blend layer of organic poly(3‐hexylthiophene) (P3HT): [6,6]‐phenyl‐C₆₁‐butyric acid methyl ester (PCBM), with power conversion efficiencies as high as 4.1%, which is comparable to state‐of‐the‐art bulk heterojunction devices fabricated in air‐free environments. High‐resolution transmission electron microscopy is combined with detailed analysis of electronic carrier transport in order to quantitatively understand the effects of oxygen exposure and different thermal treatments on electronic conduction through the highly nanostructured active blend network. Improvement in photovoltaic device performance by suitable post‐fabrication thermal processing results from the reduced oxygen charge trap density in the active blend layer and is consistent with a corresponding slight increase in thickness of an ～4 nm aluminum oxide hole‐blocking layer present at the electron‐collecting contact interface.     

On the variability of manual spike sorting

The analysis of action potentials, or "spikes," is central to systems neuroscience research. Spikes are typically identified from raw waveforms manually for off-line analysis or automatically by human-configured algorithms for on-line applications. The variability of manual spike "sorting" is studied and its implications for neural prostheses discussed. Waveforms were recorded using a micro-electrode array and were used to construct a statistically similar synthetic dataset. Results showed wide variability in the number of neurons and spikes detected in real data. Additionally, average error rates of 23% false positive and 30% false negative were found for synthetic data.