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Wind tunnel tests of wing stall, performance, and longitudinal stability & control of large model v/stol tilt wing transport aircraft
In-flight icing is an important consideration that affects aircraft design, performance, certification and safety. Newer regulations combined with increasing demand to reduce fuel burn, emissions and noise are driving a need for improvements in icing simulation capability. To that end, this paper presents the results of additional ice accretion testing conducted in the NASA Icing Research Tunnel in January 2022 with a large swept wing section typical of a modern commercial transport. The model was based upon a section of the Common Research Model wing at the 64% semispan station with a streamwise chord length of 136 in. The test conditions were developed with an icing scaling analysis to generate similar conditions for a small median volumetric diameter (MVD) = 25 μm cloud and a large MVD = 110 μm cloud. A series of tests were conducted over a range of total temperature from -23.8 ˚C to -1.4 ˚C with all other conditions held constant. Another series of tests explored cloud MVD variations from 50 μm to 230 μm while holding constant certain scaling parameters. The variation in ice mass and scanned ice volume across repeat conditions was approximately 50% lower than the uncertainty in the cloud MVD and liquid water content. The measured ice mass and volume calculated from the 3D scans were used to compute the mass to volume ratio that is sometimes referred to as ice density or void fraction. When the ice volume based on the ice shape maximum combined cross section was used to determine this ratio, the resulting values were in the range of 240 to 455 kg/m3. This is consistent with analogous values previously reported in the literature. The ice shape mass and volume increased with MVD from 50 to 230 μm at fixed values of the scaling parameters. The ice mass to volume ratio was approximately constant for all of the cases which showed that the accreted mass and volume increased at approximately the same rate. These results demonstrate the significance of cloud MVD on ice shape mass and volume.
In-flight icing is an important consideration that affects aircraft design, performance, certification and safety. Newer regulations combined with increasing demand to reduce fuel burn, emissions and noise are driving a need for improvements in icing simulation capability. To that end, this paper presents the results of additional ice accretion testing conducted in the NASA Icing Research Tunnel in January 2022 with a large swept wing section typical of a modern commercial transport. The model was based upon a section of the Common Research Model wing at the 64% semispan station with a streamwise chord length of 136 in. The test conditions were developed with an icing scaling analysis to generate similar conditions for a small median volumetric diameter (MVD) = 25 μm cloud and a large MVD = 110 μm cloud. A series of tests were conducted over a range of total temperature from -23.8 ˚C to -1.4 ˚C with all other conditions held constant. Another series of tests explored cloud MVD variations from 50 μm to 230 μm while holding constant certain scaling parameters. The variation in ice mass and scanned ice volume across repeat conditions was approximately 50% lower than the uncertainty in the cloud MVD and liquid water content. The measured ice mass and volume calculated from the 3D scans were used to compute the mass to volume ratio that is sometimes referred to as ice density or void fraction. When the ice volume based on the ice shape maximum combined cross section was used to determine this ratio, the resulting values were in the range of 240 to 455 kg/m 3 . This is consistent with analogous values previously reported in the literature. The ice shape mass and volume increased with MVD from 50 to 230 μm at fixed values of the scaling parameters. The ice mass to volume ratio was approximately constant for all of the cases which showed that the accreted mass and volume increased at approximately the same rate. These results demonstrate the significance of cloud MVD on ice shape mass and volume.
Remote sensing in combination with deep learning has become instrumental for efficiently and accurately classifying land-use and land-cover across large geographic areas. These technologies have also been successful in characterizing urban environments in terms of their structural units, structure types, or morphological regions. In these approaches, an urban area is partitioned into regions that exhibit homogeneous physical characteristics. However, existing approaches are typically limited to a single city, use inconsistent typologies, and lack scalability and generalization capacity. In this article, we propose an urban structural units categorization scheme and demonstrate its utility by applying it to 13 cities. Inspired by the lack of scalability and generalization capacity in urban structural units mapping, we extend the reach of deep learning and conduct a set of classification experiments in all 13 cities. These experiments offer insights into the strengths and limitations of deep neural networks for classifying urban structural units over diverse geographic regions and on heterogeneous collections of satellite imagery. The efficacy of the proposed deep learning approach is compared to a baseline method of multiscale image features and support vector machines. Our validation on five cities shows that better performance is achieved with deep neural networks. Additionally, we evaluate the impact of input size, model depth, and spatial pyramid pooling to assess the generalization capacity of deep neural networks.
The unique design and operational characteristics of a prototype magnetic suspension and balance facility which utilizes superconductor technology are described and discussed from the point of view of scalability to large sizes. The successful experimental demonstration of the feasibility of this new magnetic suspension concept of the University of Virginia, together with the success of the cryogenic wind-tunnel concept developed at Langley Research Center, appear to have finally opened the way to clean-tunnel, high-Re aerodynamic testing. Results of calculations corresponding to a two-step design extrapolation from the observed performance of the prototype magnetic suspension system to a system compatible with the projected cryogenic transonic research tunnel are presented to give an order-of-magnitude estimate of expected performance characteristics. Research areas where progress should lead to improved design and performance of large facilities are discussed.
Recent demonstration of advanced liquid hydrogen storage techniques using Integrated Refrigeration and Storage technology at NASA Kennedy Space Center led to the production of large quantities of densified liquid and slush hydrogen in a 125,000 L tank. Production of densified hydrogen was performed at three different liquid levels and LH2 temperatures were measured by twenty silicon diode temperature sensors. Overall densification performance of the system is explored, and solid mass fractions are calculated. Experimental data reveal hydrogen temperatures dropped well below the triple point during testing, and were continuing to trend downward prior to system shutdown. Sub-triple point temperatures were seen to evolve in a time dependent manner along the length of the horizontal, cylindrical vessel. The phenomenon, observed at two fill levels, is detailed herein. The implications of using IRAS for energy storage, propellant densification, and future cryofuel systems are discussed.
Recent demonstration of advanced liquid hydrogen storage techniques using Integrated Refrigeration and Storage technology at NASA Kennedy Space Center led to the production of large quantities of densified liquid and slush hydrogen in a 125,000 L tank. Production of densified hydrogen was performed at three different liquid levels and LH2 temperatures were measured by twenty silicon diode temperature sensors. Overall densification performance of the system is explored, and solid mass fractions are calculated. Experimental data reveal hydrogen temperatures dropped well below the triple point during testing, and were continuing to trend downward prior to system shutdown. Sub-triple point temperatures were seen to evolve in a time dependent manner along the length of the horizontal, cylindrical vessel. The phenomenon, observed at two fill levels, is detailed herein. The implications of using IRAS for energy storage, propellant densification, and future cryofuel systems are discussed.
A new sting model support has been developed for the NASA/Ames 40- by 80-Foot Wind Tunnel. This addition to the facility permits testing of relatively large models to large angles of attack or angles of yaw depending on model orientation. An initial test on the sting is described. This test used a 0.4-scale powered V/STOL model designed for testing at angles of attack to 90 deg and greater. A method for correcting wake blockage was developed and applied to the force and moment data. Samples of this data and results of surface-pressure measurements are presented.
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A hierarchy of steady, nonlinear, semianalytic models of different types of convection were produced. These provide a theoretical framework for determining cloud outflow fluxes of both dynamic and thermodynamic quantities, which can be used to formulate dynamical transports in parameterization schemes. This was achieved by exploiting certain Lagrangian conservation properties of steady flow, from which an equation for the vertical displacement of particles can be obtained and the outflow entropy, energy and momentum fluxes and the infow/outflow mass fluxes can be determined from solution to the equation. These fluxes are determined in terms of grid scale parameters such as convective available potential energy (CAPE), cloud layer shear, and horizontal pressure gradients. Five main types of system models are identified, respectively representing archtypes of convection in zero shear, large shear, midlatitude squall lines, tropical squall lines and cellular convection. The downdraught is an important aspect in the first four of these and the cloud scale transport of momentum is very distinctive.
The work on the ROSAT Deep Survey has been successfully completed. A number of interesting results have been established within this joint MPE, Cal Tech, JHU, ST Scl, ESO collaboration. First, a very large fraction, 70-80 percent, of the X-ray background has been directly resolved into point sources. We have derived a new log N-log S for X- ray sources and have measured a source density of 970 sources per square degree at a limiting flux level of 10(exp -15)/erg s sq cm (0.5-2.0 keV). Care was taken in these studies to accurately model and measure the effects of sources confusion. This was possible because of our observing strategy which included both deep PSPC and HRI observations. In the last year we initiated work in the design and development of the Next Generation Space Telescope.
Recent demonstration of advanced liquid hydrogen storage techniques using Integrated Refrigeration and Storage (IRAS) technology at NASA Kennedy Space Center led to the production of large quantities of solid densified liquid and slush hydrogen in a 125,000 L tank. Production of densified hydrogen was performed at three different liquid levels and LH2 temperatures were measured by twenty silicon diode temperature sensors. System energy balances and solid mass fractions are calculated. Experimental data reveal hydrogen temperatures dropped well below the triple point during testing (up to 1 K), and were continuing to trend downward prior to system shutdown. Sub-triple point temperatures were seen to evolve in a time dependent manner along the length of the horizontal, cylindrical vessel. Twenty silicon diode temperature sensors were recorded over approximately one month for testing at two different fill levels (33 67). The phenomenon, observed at both two fill levels, is described and presented detailed and explained herein., and The implications of using IRAS for energy storage, propellant densification, and future cryofuel systems are discussed.
We present OpenAWSEM and Open3SPN2, new cross-compatible implementations of coarse-grained models for protein (AWSEM) and DNA (3SPN2) molecular dynamics simulations within the OpenMM framework. These new implementations retain the chemical accuracy and intrinsic efficiency of the original models while adding GPU acceleration and the ease of forcefield modification provided by OpenMM’s Custom Forces software framework. By utilizing GPUs, we achieve around a 30-fold speedup in protein and protein-DNA simulations over the existing LAMMPS-based implementations running on a single CPU core. We showcase the benefits of OpenMM’s Custom Forces framework by devising and implementing two new potentials that allow us to address important aspects of protein folding and structure prediction and by testing the ability of the combined OpenAWSEM and Open3SPN2 to model protein-DNA binding. The first potential is used to describe the changes in effective interactions that occur as a protein becomes partially buried in a membrane. We also introduced an interaction to describe proteins with multiple disulfide bonds. Using simple pairwise disulfide bonding terms results in unphysical clustering of cysteine residues, posing a problem when simulating the folding of proteins with many cysteines. We now can computationally reproduce Anfinsen’s early Nobel prize winning experiments by using OpenMM’s Custom Forces framework to introduce a multi-body disulfide bonding term that prevents unphysical clustering. Our protein-DNA simulations show that the binding landscape is funneled towards structures that are quite similar to those found using experiments. In summary, this paper provides a simulation tool for the molecular biophysics community that is both easy to use and sufficiently efficient to simulate large proteins and large protein-DNA systems that are central to many cellular processes. These codes should facilitate the interplay between molecular simulations and cellular studies, which have been hampered by the large mismatch between the time and length scales accessible to molecular simulations and those relevant to cell biology.
Abstract 2D perovskite (PVSK) single crystals have received significant attention due to their unique optical and optoelectronic properties. However, current synthesis methods face limitations, particularly in large‐area fabrication, which remain critical barriers to practical applications. In this study, the synthesis of red/green/purple‐blue‐colored 2D PVSK nanocrystals over a large area (4‐inch wafer) and the fabrication of high‐performance photodetector arrays are presented via a facile yet efficient spray‐coating approach with a liquid‐bridge transport effect. The photodetector array achieves 100% working yield, high photo‐responsivity (1.5 × 10 6 A W −1 ) and specific‐detectivity (1.1 × 10 16 Jones) with competitive photomapping characteristics. An intelligent vision system for automatic shape recognition is further demonstrated with a recognition rate exceeding 90%. This study provides significant advances in the scalable synthesis of nanoscale 2D PVSK crystals, their integration into large‐area optoelectronic devices, and their potential use in artificial‐intelligence systems.
Tests were made in the N.A.C.A. 20-foot wind tunnel on: (1) a wing, of 6.5-foot span, 5.5-foot chord, and 30 percent maximum thickness, fitted with large end plates and (2) a 16-foot span 2.67-foot chord wing of 15 percent maximum thickness to determine the increase in lift obtainable by removing the boundary layer and the power required for the blower. The results of the tests on the stub wing appeared more favorable than previous small-scale tests and indicated that: (1) the suction method was considerably superior to the pressure method, (2) single slots were more effective than multiple slots (where the same pressure was applied to all slots), the slot efficiency increased rapidly for increasing slot widths up to 2 percent of the wing chord and remained practically constant for all larger widths tested, (3) suction pressure and power requirements were quite low (a computation for a light airplane showed that a lift coefficient of 3.0 could be obtained with a suction as low as 2.3 times the dynamic pressure and a power expenditure less than 3 percent of the rated engine power), and (4) the volume of air required to be drawn off was quite high (approximately 0.5 cubic feet per second per unit wing area for an airplane landing at 40 miles per hour with a lift coefficient of 3,0), indicating that considerable duct area must be provided in order to prevent flow losses inside the wing and insure uniform distribution of suction along the span. The results from the tests of the large-span wing were less favorable than those on the stub wing. The reasons for this were, probably: (1) the uneven distribution of suction along the span, (2) the flow losses inside the wing, (3) the small radius of curvature of the leading edge of the wing section, and (4) the low Reynolds Number of these tests, which was about one half that of the stub wing. The results showed a large increase in the maximum lift coefficient with an increase in Reynolds Number in the range of the tests. The results of drag tests showed that the profile drag of the wing was reduced and the L/D ratio was increased throughout the range of lift coefficients corresponding to take-off and climb but that the minimum drag was increased. The slot arrangement that is best for low drag is not the same, however, as that for maximum lift.
An important new direction in computer architecture centers around the achievement of very high computational power (capacity, speed and reliability) through the use of tens of thousands of microprocessors, micromemories, and switch modules, all interconnected into a large homogeneous network using one of certain advanced connection schemes. When surrounded and supported by conventional computers and memories, such a machine holds potential for out-performing both conventional and array-based computers of the mid-1980's by one to two orders of magnitude, at least for particular classes of applications amenable to high parallelism, such as aerodynamic simulation. The homogeneous feature of this machine concept also implies size extendability, fault tolerance, and improved flexibility to handle a variety of algorithms of interest. Current work is addressing the design of technologically efficient interconnection configurations and the development of new computation algorithms that are especially efficient for highly parallel computation.
The origin of distinct 3d vs. 4d transition metal complex sensitivity to exchange is explored over a large data set.
The mean age since air was last at the Northern Hemisphere midlatitude surface is a fundamental property of tropospheric transport. Recent comparisons among chemistry climate models, however, reveal that there are large differences in the mean age among models and that these differences are most likely related to differences in tropical (parameterized) convection. Here we use aquaplanet simulations of the Goddard Earth Observing System Model Version 5 (GEOS-5) to explore the sensitivity of the mean age to changes in the tropical circulation. Tropical circulation changes are forced by prescribed localized off-equatorial warm sea surface temperature anomalies that (qualitatively) reproduce the convection and circulation differences among the comprehensive models. Idealized chemical species subject to prescribed OH loss are also integrated in parallel in order to illustrate the impact of tropical transport changes on interhemispheric constituent transport.