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This testing utilizes air driven turbines to deliver power to the article being studied. These air turbines exhaust directly downstream of the model in the wind tunnel test section and have been found to produce significant unwanted noise that reduces the quality of the acoustic measurements of the engine model being tested. This report describes an acoustic test of a muffler designed to mitigate the extraneous turbine noise. The muffler was found to provide acoustic attenuation of at least 8 dB between 700 Hz and 20 kHz which significantly improves the quality of acoustic measurements in the facility. The need for large- scale maps has raised various approaches implementing conjugations between forest biomass and geospatial predictors such as climate, forest type, soil property, and topography. Despite the improved modeling techniques (e. . machine learning and spatial statistics), a common limitation is that biophysical mechanisms governing tree growth are neglected in these black-box type models. The absence of a priori knowledge may lead to false interpretation of modeled results or unexplainable shifts in outputs due to the inconsistent training samples or study sites. Here, we present a gray-box approach combining known biophysical processes and geospatial predictors through parametric optimizations (inversion of reference measures). Total aboveground biomass in forest stands is estimated by incorporating the Forest Inventory and Analysis (FIA) and Parameter-elevation Regressions on Independent Slopes Model (PRISM). Two main premises of this research are: (a) The Allometric Scaling and Resource Limitations (ASRL) theory can provide a relationship between tree geometry and local resource availability constrained by environmental conditions; and (b) The zeroth order theory (size-frequency distribution) can expand individual tree allometry into total aboveground biomass at the forest stand level. In addition to the FIA estimates, two reference maps from the National Biomass and Carbon Dataset (NBCD) and U. . Forest Service (USFS) were produced to evaluate the model.

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Metamerism lets us display yellows orskin tones on a computer monitor without dedicated yellow or skin-color Chapter 1: What Is Color? 29 phosphors. Metamerism lets us reproduce the green characteristic of chlorophyll (the pigment found in plants) without chlorophyll-coloredinkor even an ink we would call green (see Figure 1-16). Figure M6Metamerism in action Thanks to metamerism, we can reproducethe color of this leafin print without using a single drop ofgreen ink. Without metamerism, we'd have to reproduce colors by duplicatingthe exact spectral content of the original color stimulus. (Incidentally, this is what we have to do with sound reproductionduplicate the stimulus of the original sound wavelength by wavelength. If you think your ink costs are high today, imagine if you had to have thousands of colors of ink instead of just four. We mentioned that a metameric re- lationship between two color samples is dependent not only on the light source, but also on the specific observer viewing the two samples. A pairof color samples can produce one color sensation to one observer, but a different color sensation to a second observer. Ifa scanner's red, green, and blue detectors respond differently than our cone sensors, the scanner can see a metameric match where you and I see separate colors, or conversely, a pair of samples may appear identical 30 Real World Color Management, Second Edition to us but different to the scanner (see Figure 1-17). This is sometimescalled scanner metamerism, and we shall see in Chapter 8 that this is thereason it's difficult to use a scanner as a measurement device for makingprofiles. Similarly, if a film or digital camera has different sets of meta- meric matches than we do, we would call this camera metamerism, andwhile there's little that color management can do about it, you need to beaware of it as an issue. We see the same color. by an observer withcertain color vision. under a scanner lampthe same as light sourceA.

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We are fortunate enough to be entering the era of precision cosmology, where the standard model of gravity can be subjected to more rigorous testing. Various techniques will be employed over the next decade or two in the effort to better understand cosmic acceleration and the theory behind it. In this talk, I will describe cosmic acceleration, current proposals to explain it, and weak gravitational lensing, an observational effect that allows us to do the necessary precision cosmology. A Design of Experiments (DOE) method was imposed to produce an array of tests from a fixed set of constraints and a coupled response model was developed. Supplementary tests were run without experimental design to additionally vary select parameters such as initial chamber pressure. The starting chamber pressure for each test was set below atmospheric to prevent chamber overpressure. Bottom ignition, or upward propagating burns, produced rapid acceleratory turbulent flame spread. Pressure rise in the chamber increases as the amount of fuel burned increases mainly because of the larger amount of heat generation and, to a much smaller extent, due to the increase in gaseous number of moles. Top ignition, or downward propagating burns, produced a steady flame spread with a very small flat flame across the burning edge. Steady-state pressure is achieved during downward flame spread as the pressure rises and plateaus. This indicates that the heat generation by the flame matches the heat loss to surroundings during the longer, slower downward burns. One heat loss mechanism included mounting a heat exchanger directly above the burning sample in the path of the plume to act as a heat sink and more efficiently dissipate the heat due to the combustion event. This proved an effective means for chamber overpressure mitigation for those tests producing the most total heat release and thusly was determined to be a feasible mitigation. Carlos; T'ien, James S. Torero, Jose L.

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