Aerodynamic characteristics of two-dimensional wing configurations at angles of attack near -90 deg

Wind tunnel tests were conducted to determine the drag of two-dimensional wing sections operating in a near-vertical flow condition. Various leading- and trialing-edge configurations, including plain flaps of 25, 30, and 35% chord were tested at angles of attack from -75 to -105 deg. Reynolds numbers examined ranged from approximately 0.6 x 10 to the 6th power to 1.4 x 10 to the 6th power. The data were obtained using a wind tunnel force and moment balance system and arrays of chordwise pressure orifices. The results showed that significant reductions in drag, beyond what would be expected by virtue of the decreased frontal area, were obtainable with geometries that delayed flow separation. Rapid changes in drag with angle of attack were noted for many configurations. The results, however, were fairly insensitive to Reynolds number variations. Drag values computed from the pressure data generally agreed with the force data within 2%

On the efficiency of estimating penetrating rank on large graphs

P-Rank (Penetrating Rank) has been suggested as a useful measure of structural similarity that takes account of both incoming and outgoing edges in ubiquitous networks. Existing work often utilizes memoization to compute P-Rank similarity in an iterative fashion, which requires cubic time in the worst case. Besides, previous methods mainly focus on the deterministic computation of P-Rank, but lack the probabilistic framework that scales well for large graphs. In this paper, we propose two efficient algorithms for computing P-Rank on large graphs. The first observation is that a large body of objects in a real graph usually share similar neighborhood structures. By merging such objects with an explicit low-rank factorization, we devise a deterministic algorithm to compute P-Rank in quadratic time. The second observation is that by converting the iterative form of P-Rank into a matrix power series form, we can leverage the random sampling approach to probabilistically compute P-Rank in linear time with provable accuracy guarantees. The empirical results on both real and synthetic datasets show that our approaches achieve high time efficiency with controlled error and outperform the baseline algorithms by at least one order of magnitude

Airloads on bluff bodies, with application to the rotor-induced downloads on tilt-rotor aircraft

The aerodynamic characteristics of airfoils with several flap configurations were studied theoretically and experimentally in environments that simulate a wing immersed in the downwash of a hovering rotor. Special techniques were developed for correcting and validating the wind tunnel data for large blockage effects, and the test results were used to evaluate two modern blockage effects, and the test results were used to evaluate two modern computational aerodynamics codes. The combined computed and measured results show that improved flap and leading-edge configurations can be designed which will achieve large reductions in the downloads of tilt-rotor aircraft, and thereby improve their hover efficiency

NASA Ames Laminar Flow Supersonic Wind Tunnel (LFSWT) Tests of a 10 deg Cone at Mach 1.6

This work is part of the ongoing qualification of the NASA Ames Laminar Flow Supersonic Wind Tunnel (LFSWT) as a low-disturbance (quiet) facility suitable for transition research. A 10 deg cone was tested over a range of unit Reynolds numbers (Re = 2.8 to 3.8 million per foot (9.2 to 12.5 million per meter)) and angles of incidence (O deg to 10 deg) at Mach 1.6. The location of boundary layer transition along the cone was measured primarily from surface temperature distributions, with oil flow interferometry and Schlieren flow visualization providing confirmation measurements. With the LFSWT in its normal quiet operating mode, no transition was detected on the cone in the test core, over the Reynolds number range tested at zero incidence and yaw. Increasing the pressure disturbance levels in the LFSWT test section by a factor of five caused transition onset on the cone within the test core, at zero incidence and yaw. When operating the LFSWT in its normal quiet mode, transition could only be detected in the test core when high angles of incidence (greater than 5 deg) for cones were set. Transition due to elevated pressure disturbances (Tollmien-Schlichting) and surface trips produced a skin temperature rise of order 4 F (2.2 C). Transition due to cross flows on the leeward side of the cone at incidence produced a smaller initial temperature rise of only order 2.5 F (1.4 C), which indicates a slower transition process. We can conclude that these cone tests add further proof that the LFSWT test core is normally low-disturbance (pressure fluctuations greater than 0.1%), as found by associated direct flow quality measurements discussed in this report. Furthermore, in a quiet test environment, the skin temperature rise is sensitive to the type of dominant instability causing transition. The testing of a cone in the LFSWT provides an excellent experiment for the development of advanced transition detection techniques

Onset of collective and cohesive motion

We study the onset of collective motion, with and without cohesion, of groups of noisy self-propelled particles interacting locally. We find that this phase transition, in two space dimensions, is always discontinuous, including for the minimal model of Vicsek et al. [Phys. Rev. Lett. {\bf 75},1226 (1995)] for which a non-trivial critical point was previously advocated. We also show that cohesion is always lost near onset, as a result of the interplay of density, velocity, and shape fluctuations.Comment: accepted for publication in Phys. Rev. Let

A DNA Damage-Induced, SOS-Independent Checkpoint Regulates Cell Division in Caulobacter crescentus

Cells must coordinate DNA replication with cell division, especially during episodes of DNA damage. The paradigm for cell division control following DNA damage in bacteria involves the SOS response where cleavage of the transcriptional repressor LexA induces a division inhibitor. However, in Caulobacter crescentus, cells lacking the primary SOS-regulated inhibitor, sidA, can often still delay division post-damage. Here we identify didA, a second cell division inhibitor that is induced by DNA damage, but in an SOS-independent manner. Together, DidA and SidA inhibit division, such that cells lacking both inhibitors divide prematurely following DNA damage, with lethal consequences. We show that DidA does not disrupt assembly of the division machinery and instead binds the essential division protein FtsN to block cytokinesis. Intriguingly, mutations in FtsW and FtsI, which drive the synthesis of septal cell wall material, can suppress the activity of both SidA and DidA, likely by causing the FtsW/I/N complex to hyperactively initiate cell division. Finally, we identify a transcription factor, DriD, that drives the SOS-independent transcription of didA following DNA damage.National Institutes of Health (U.S.) (Grant R01GM082899)National Science Foundation (U.S.). Graduate Research Fellowship Progra

The statistical mechanics of complex signaling networks : nerve growth factor signaling

It is becoming increasingly appreciated that the signal transduction systems used by eukaryotic cells to achieve a variety of essential responses represent highly complex networks rather than simple linear pathways. While significant effort is being made to experimentally measure the rate constants for individual steps in these signaling networks, many of the parameters required to describe the behavior of these systems remain unknown, or at best, estimates. With these goals and caveats in mind, we use methods of statistical mechanics to extract useful predictions for complex cellular signaling networks. To establish the usefulness of our approach, we have applied our methods towards modeling the nerve growth factor (NGF)-induced differentiation of neuronal cells. Using our approach, we are able to extract predictions that are highly specific and accurate, thereby enabling us to predict the influence of specific signaling modules in determining the integrated cellular response to the two growth factors. We show that extracting biologically relevant predictions from complex signaling models appears to be possible even in the absence of measurements of all the individual rate constants. Our methods also raise some interesting insights into the design and possible evolution of cellular systems, highlighting an inherent property of these systems wherein particular ''soft'' combinations of parameters can be varied over wide ranges without impacting the final output and demonstrating that a few ''stiff'' parameter combinations center around the paramount regulatory steps of the network. We refer to this property -- which is distinct from robustness -- as ''sloppiness.''Comment: 24 pages, 10 EPS figures, 1 GIF (makes 5 multi-panel figs + caption for GIF), IOP style; supp. info/figs. included as brown_supp.pd