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At least 109 records · Page 6

Xenon lighting adjusted to plant requirements

Xenon lamps are available as low and high power lamps with relatively high efficiency and a relatively long lifetime up to several thousand hours. Different construction types of short-arc and long-arc lamps permit a good adaptation to various applications in projection and illumination techniques without substantial changes of the spectral quality. Hence, the xenon lamp was the best choice for professional technical purposes where high power at simultaneously good spectral quality of the light was required. However, technical development does not stand still. Between the luminous efficacy of xenon lamps of 25-50 lm/W and the theoretical limit for 'white light' of 250 lm/W is still much room for improvement. The present development mainly favors other lamp types, like metal halide lamps and fluorescent lamps for commercial lighting purposes. The enclosed sections deal with some of the properties of xenon lamps relevant to plant illumination; particularly the spectral aspects, the temporal characteristics of the emission, and finally the economy of xenon lamps will be addressed. Due to radiation exceeding the natural global radiation in both the ultraviolet (UV) and the infrared (IR) regions, filter techniques have to be included into the discussion referring to the requirements of plant illumination. Most of the presented results were obtained by investigations in the GSF phytotron or in the closed Phytocell chambers of the University of Erlangen. As our experiences are restricted to area plant illumination rather than spot lights our discussion will concentrate on low pressure long-arc xenon lamps which are commonly used for such plant illuminations. As the spectral properties of short-arc lamps do not differ much from those of long-arc lamps most of our conclusions will be valid for high pressure xenon lamps too. These lamps often serve as light sources for small sun simulators and for monochromators which are used for action spectroscopy of plant responses.

Koefferlein, M.↗

Jet engine applications for materials with nanometer-scale dimensions

The performance of advanced military and commercial gas turbine engines is often linked to advances in materials technology. High performance gas turbine engines being developed require major material advances in strength, toughness, reduced density and improved temperature capability. The emerging technology of nanostructured materials has enormous potential for producing materials with significant improvements in these properties. Extraordinary properties demonstrated in the laboratory include material strengths approaching theoretical limit, ceramics that demonstrate ductility and toughness, and materials with ultra-high hardness. Nanostructured materials and coatings have the potential for meeting future gas turbine engine requirements for improved performance, reduced weight and lower fuel consumption.

Appleby, J. W., Jr.↗

Turbulence Studies of a Rectangular Slotted Noise-Suppressor Nozzle

The problem of noise suppression of turbojet engines has shown a need for turbulence data within the flow field of various types of nozzles used in ad hoc investigations of the sound power. The result of turbulence studies in a nozzle configuration of four parallel rectangular slots is presented in this report with special attention to the effect of the spacing of the nozzles on the intensity of turbulence, scale of turbulence, spectrum of turbulence, and the mean stream velocity. Taylor's hypothesis, which describes the convection of the turbulence eddies, was tested and found correct within experimental error and certain experimental and theoretical limitations. The convection of the pressure patterns was also investigated, and the value of the convection velocity was found to be about 0.43 times the central core velocity of the jets. The effect of the spacing-to-width ratio of the nozzles upon the turbulence intensity, the scale of turbulence, and the spectral distribution of the noise was found in general to produce a maximum change for spacing-to-width ratios of 1.5 to 2.0. These changes may be the cause of the reduction in sound power reported for similar full-scale nozzles and test conditions under actual (static) engine operation. A noise reduction parameter is defined from Lighthill's theory which gives qualitative agreement with experiments which show the noise reduction is greatest for spacing-to-width ratios of 1.5 to 2.0.

Laurence, James C.↗

Solving Upwind-Biased Discretizations: Multigrid Solver Using Semicoarsening - 2

This paper studies a novel multigrid approach to the solution for a second order upwind biased discretization of the convection equation in two dimensions. This approach is based on semi-coarsening and well balanced explicit correction terms added to coarse-grid operators to maintain on coarse-grid the same cross-characteristic interaction as on the target (fine) grid. Colored relaxation schemes are used on all the levels allowing a very efficient parallel implementation. The results of the numerical tests can be summarized as follows: 1) The residual asymptotic convergence rate of the proposed V(0, 2) multigrid cycle is about 3 per cycle. This convergence rate far surpasses the theoretical limit (4/3) predicted for standard multigrid algorithms using full coarsening. The reported efficiency does not deteriorate with increasing the cycle, depth (number of levels) and/or refining the target-grid mesh spacing. 2) The full multi-grid algorithm (FMG) with two V(0, 2) cycles on the target grid and just one V(0, 2) cycle on all the coarse grids always provides an approximate solution with the algebraic error less than the discretization error. Estimates of the total work in the FMG algorithm are ranged between 18 and 30 minimal work units (depending on the target (discretizatioin). Thus, the overall efficiency of the FMG solver closely approaches (if does not achieve) the goal of the textbook multigrid efficiency. 3) A novel approach to deriving a discrete solution approximating the true continuous solution with a relative accuracy given in advance is developed. An adaptive multigrid algorithm (AMA) using comparison of the solutions on two successive target grids to estimate the accuracy of the current target-grid solution is defined. A desired relative accuracy is accepted as an input parameter. The final target grid on which this accuracy can be achieved is chosen automatically in the solution process. the actual relative accuracy of the discrete solution approximation obtained by AMA is always better than the required accuracy; the computational complexity of the AMA algorithm is (nearly) optimal (comparable with the complexity of the FMG algorithm applied to solve the problem on the optimally spaced target grid).

Diskin, Boris↗

Shear/Defocus Sensitivity of the Mid Infrared Channel (MIR) of the Composite Infrared Spectrometer (CIRS) for the Cassini Mission to Saturn

The Composite Infrared Spectrometer (CIRS) of the Cassini mission to Saturn has two interferometers covering the far infrared and mid infrared wavelength region. The mid infrared wavelength interferometer has a focal plane consisting of a germanium focus lens and HgCdTe array. System level calibration of the CIRS Flight Unit indicated a discrepancy between the expected and actual signal levels. Testing on the CIRS breadboard and Engineering Unit indicated that defocus of the germanium lens could significantly reduce the modulation efficiency of the interferometer in the presence of a moderate degree of wavefront shear. Defocus of the lens in the focal plane was of concern because of the temperature dependence of the index of refraction of germanium and our nominal operation temperature of 170 K. The shear/defocus interaction was extensively investigated and correlated to a newly developed analytical model, It was eventually determined that the CIRS instrument was in focus, had no appreciable wavefront shear and was operating near theoretical limits. The shear/defocus effect is however, of considerable interest, since it has not been described in previous literature on interferometers.

Martino, Anthony J.↗

Detector Assembly and the Ultralow-Temperature Refrigerator for XRS

The X-ray spectrometer (XRS) on the Japanese Astro-E Spacecraft is the first ultra low temperature space borne instrument. The system utilizes a 900g Ferric Ammonium Alum (FAA) Adiabatic Demagnetization Refrigerator (ADR) with a helium-3 gas gap heat switch to cool the detector assembly to 0.060K. The system operates in a "single shot" configuration allowing the system to remain at its operating temperature for about 40 hours in the lab. The on-orbit performance is expected to be about 35 hours with a 97% duty cycle. The detector assembly for XRS consists of a 32 channel microcalorimeter array bias electronics, thermometry, and an anti-coincidence detector that are attached to the cold stage of the ADR. To thermally Isolate the detector system from the superfluid helium reservoir, the detector system is suspended by Kevlar cords and electrical connection in made by L30, 17-micron diameter, tensioned NbTi leads. The detectors are read out in a source-follower arrangement using FET amplifiers operating at 130K mounted in multiply-thermally-isolated assemblies that also use Kevlar and stainless steel wiring. The design and thermal performance of this system will be discussed and compared to the theoretical limits.

Porter, F. S.↗

Modeling and Analysis of Global and Regional Climate Change in Relation to Atmospheric Hydrologic Processes

This research was directed to the development and application of global isentropic modeling and analysis capabilities to describe hydrologic processes and energy exchange in the climate system, and discern regional climate change. An additional objective was to investigate the accuracy and theoretical limits of global climate predictability which are imposed by the inherent limitations of simulating trace constituent transport and the hydrologic processes of condensation, precipitation and cloud life cycles.

Johnson, Donald R.↗

Basic Equations for the Modeling of Gallium Nitride (gan) High Electron Mobility Transistors (hemts)

Gallium nitride (GaN) is a most promising wide band-gap semiconductor for use in high-power microwave devices. It has functioned at 320 C, and higher values are well within theoretical limits. By combining four devices, 20 W has been developed at X-band. GaN High Electron Mobility Transistors (HEMTs) are unique in that the two-dimensional electron gas (2DEG) is supported not by intentional doping, but instead by polarization charge developed at the interface between the bulk GaN region and the AlGaN epitaxial layer. The polarization charge is composed of two parts: spontaneous and piezoelectric. This behavior is unlike other semiconductors, and for that reason, no commercially available modeling software exists. The theme of this document is to develop a self-consistent approach to developing the pertinent equations to be solved. A Space Act Agreement, "Effects in AlGaN/GaN HEMT Semiconductors" with Silvaco Data Systems to implement this approach into their existing software for III-V semiconductors, is in place (summer of 2002).

Freeman, Jon C.↗

A New Approach to using a Cloud-Resolving Model to Study the Interactions between Clouds, Precipitation and Aerosols

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 kilometers, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-kilometer scales are resolved in horizontal domains as large as 10,000 kilometers in two dimensions, and 1,000 x 1,000 square kilometers in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically-based parameterizations for climate models and numerical weather prediction models. A review of developments and applications of cloud models in the past, present and future will be presented in this talk. In particular, a new approach to using cloud-resolving models to study the interactions between clouds, precipitation and aerosols will be presented.

Tao, Wei-Kuo↗

A New Approach to Using a Cloud-resolving Model to Study the Interactions Between Clouds, Precipitation and Aerosols

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as l0,OOO km in two-dimensions, and 1,OOO x 1,OOO km2 in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically-based parameterizations for climate models and numerical weather prediction models. A review of developments and applications of cloud models in the past, present and future will be presented in this talk. In particular, a new approach to using cloud-resolving models to study the interactions between clouds, precipitation and aerosols will be presented.

Tao, Wei-Kuo↗

Bridgman Growth of Germanium Crystals in a Rotating Magnetic Field

A series of (100)-oriented gallium-doped germanium crystals has been grown by the vertical Bridgman method and under the influence of a rotating magnetic field (RMF). Time-dependent flow instabilities occur when the critical magnetic Taylor number (Tm(sup c)) is exceeded, and this can be observed by noting the appearance of striations in the grown crystals. Tm(sup c) decreases as the aspect ratio of the melt increases, and approaches the theoretical limit expected for an infinite cylinder. Intentional interface demarcations are introduced by pulsing the RMF on and off The RMF has a marked affect on the interface shape, changing it from concave to nearly flat as the RMF strength is increased.

Volz, M. P.↗

A New Approach to using a Cloud-Resolving Model to Study the Interactions between Clouds, Precipitation and Aerosols

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 square kilometers in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically-based parameterizations for climate models and numerical weather prediction models. A review of developments and applications of cloud models in the past, present and future will be presented in this talk. In particular, a new approach to using cloud-resolving models to study the interactions between clouds, precipitation and aerosols will be presented.

Tao, Wei-Kuo↗

Using Multi-scale Modeling System to Study the Interactions between Clouds, Precipitation, Aerosols, Radiation and Land Surface

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 kilometers, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-kilometer scales are resolved in horizontal domains as large as 10,000 kilometers in two-dimensions, and 1,000 x 1,000 square kilometers in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. A review of developments, improvements and applications of cloud models (GCE and WRF) at Goddard will be presented in this talk. In particular, a new approach to using multi-scale modeling system to study the interactions between clouds, precipitation, aerosols and land will be presented.

Tao, Wei-Kuo↗

Using Multi-scale Modeling System to Study the Interactions between Clouds, Precipitation, Aerosols, Radiation and Land Surface

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 kilometers, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial-lkm scales are resolved in horizontal domains as large as 10,000 kilometers in two-dimensions, and 1,000 x 1,000 square kilometers in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. A review of developments, improvements and applications of cloud models (GCE and WRF) at Goddard wlll be is presented in this talk. In particular, a new approach to using multi-scale modeling system to study the interactions between clouds, precipitation, aerosols and land will be presented.

Tao, Wei-Kuo↗

Using Multi-scale Modeling Systems to Study the Precipitation Processes

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (CRM), (2) a regional scale model, (3) a coupled CRM and global model, and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer processes and the explicit cloud-radiation, and cloudland surface interactive processes are applied in this multi-scale modeling system. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the interactions between clouds, precipitation, and aerosols will be presented.

Tao, Wei-Kuo↗

Design of Test Articles and Monitoring System for the Characterization of HIRF Effects on a Fault-Tolerant Computer Communication System

This report describes the design of the test articles and monitoring systems developed to characterize the response of a fault-tolerant computer communication system when stressed beyond the theoretical limits for guaranteed correct performance. A high-intensity radiated electromagnetic field (HIRF) environment was selected as the means of injecting faults, as such environments are known to have the potential to cause arbitrary and coincident common-mode fault manifestations that can overwhelm redundancy management mechanisms. The monitors generate stimuli for the systems-under-test (SUTs) and collect data in real-time on the internal state and the response at the external interfaces. A real-time health assessment capability was developed to support the automation of the test. A detailed description of the nature and structure of the collected data is included. The goal of the report is to provide insight into the design and operation of these systems, and to serve as a reference document for use in post-test analyses.

Torres-Pomales, Wilfredo↗

A Multi-Scale Modeling System with Unified Physics

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. In recent years, exponentially increasing computer power has extended cloud-resolving-mode1 integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique.

Tao, Wei-Kuo↗

Using Multi-scale Modeling System to Study the Interactions between Clouds, Precipitation, Aerosols, Radiation and Land Surface

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 sq km in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. A review of developments, improvements and applications of cloud models (GCE and WRF) at Goddard will be presented in this talk. In particular, a new approach to using multi-scale modeling system to study the interactions between clouds, precipitation, aerosols and land will be presented.

Tao, Wei-Kuo↗