8,480 research outputs found
A bifurcation study to guide the design of a landing gear with a combined uplock/downlock mechanism
This paper discusses the insights that a bifurcation analysis can provide when designing mechanisms. A model, in the form of a set of coupled steady-state equations, can be derived to describe the mechanism. Solutions to this model can be traced through the mechanism's state versus parameter space via numerical continuation, under the simultaneous variation of one or more parameters. With this approach, crucial features in the response surface, such as bifurcation points, can be identified. By numerically continuing these points in the appropriate parameter space, the resulting bifurcation diagram can be used to guide parameter selection and optimization. In this paper, we demonstrate the potential of this technique by considering an aircraft nose landing gear, with a novel locking strategy that uses a combined uplock/downlock mechanism. The landing gear is locked when in the retracted or deployed states. Transitions between these locked states and the unlocked state (where the landing gear is a mechanism) are shown to depend upon the positions of two fold point bifurcations. By performing a two-parameter continuation, the critical points are traced to identify operational boundaries. Following the variation of the fold points through parameter space, a minimum spring stiffness is identified that enables the landing gear to be locked in the retracted state. The bifurcation analysis also shows that the unlocking of a retracted landing gear should use an unlock force measure, rather than a position indicator, to de-couple the effects of the retraction and locking actuators. Overall, the study demonstrates that bifurcation analysis can enhance the understanding of the influence of design choices over a wide operating range where nonlinearity is significant
Probing quasiparticle excitations in a hybrid single electron transistor
We investigate the behavior of quasiparticles in a hybrid electron turnstile
with the aim of improving its performance as a metrological current source. The
device is used to directly probe the density of quasiparticles and monitor
their relaxation into normal metal traps. We compare different trap geometries
and reach quasiparticle densities below 3um^-3 for pumping frequencies of 20
MHz. Our data show that quasiparticles are excited both by the device operation
itself and by the electromagnetic environment of the sample. Our observations
can be modelled on a quantitative level with a sequential tunneling model and a
simple diffusion equation
Positional match demands of professional rugby league competition
The purpose of this study was to examine the differences in physical performance and game-specific skill demands between 5 positional groups in a professional rugby league team. Positional groups consisted of the backs (n = 8), forwards (n = 8), fullback (n = 7), hooker (n = 8), and service players (n = 8). Time-motion analysis was used to determine physical performance measures (exercise intensity, distance travelled, time, frequency, and speed measures) and game-specific skill measures (ball carries, supports, ball touches, play the balls, and tackling indices) per minute of playing time. The main finding was that the fullback completed more very high-intensity running (VHIR) because of more support runs when compared to all other positional groups (p = 0.017). THe VHIR (p = 0.004) and sprinting indices (p < 0.002) were also greater in the second half of a match for the fullback than in any other positional group. The hooker spent more time jogging than the backs and forwards (p < 0.001) and touched the ball on more occasions than any other positional group (p < 0.001). The backs spent more time walking than the forwards, hooker, and service players (p < 0.001). The forwards, hooker, and service players completed more tackles per minute during a match than the backs and fullback (p < 0.001). The fullback and forwards also ran the ball on more occasions than the backs, hooker, and service players did (p < 0.001). These results show that positional roles play an important part in determining the amount of physical and game-specific skill involvement during match play. © 2011 National Strength and Conditioning Association
Correlation effects in ionic crystals: I. The cohesive energy of MgO
High-level quantum-chemical calculations, using the coupled-cluster approach
and extended one-particle basis sets, have been performed for (Mg2+)n (O2-)m
clusters embedded in a Madelung potential. The results of these calculations
are used for setting up an incremental expansion for the correlation energy of
bulk MgO. This way, 96% of the experimental cohesive energy of the MgO crystal
is recovered. It is shown that only 60% of the correlation contribution to the
cohesive energy is of intra-ionic origin, the remaining part being caused by
van der Waals-like inter-ionic excitations.Comment: LaTeX, 20 pages, no figure
Ground state properties of heavy alkali halides
We extend previous work on alkali halides by calculations for the heavy-atom
species RbF, RbCl, LiBr, NaBr, KBr, RbBr, LiI, NaI, KI, and RbI. Relativistic
effects are included by means of energy-consistent pseudopotentials,
correlations are treated at the coupled-cluster level. A striking deficiency of
the Hartree-Fock approach are lattice constants deviating by up to 7.5 % from
experimental values which is reduced to a maximum error of 2.4 % by taking into
account electron correlation. Besides, we provide ab-initio data for in-crystal
polarizabilities and van der Waals coefficients.Comment: accepted by Phys. Rev.
A New Technique for Finding Needles in Haystacks: A Geometric Approach to Distinguishing Between a New Source and Random Fluctuations
We propose a new test statistic based on a score process for determining the
statistical significance of a putative signal that may be a small perturbation
to a noisy experimental background. We derive the reference distribution for
this score test statistic; it has an elegant geometrical interpretation as well
as broad applicability. We illustrate the technique in the context of a model
problem from high-energy particle physics. Monte Carlo experimental results
confirm that the score test results in a significantly improved rate of signal
detection.Comment: 5 pages, 4 figure
Correlation effects in MgO and CaO: Cohesive energies and lattice constants
A recently proposed computational scheme based on local increments has been
applied to the calculation of correlation contributions to the cohesive energy
of the CaO crystal. Using ab-initio quantum chemical methods for evaluating
individual increments, we obtain 80% of the difference between the experimental
and Hartree-Fock cohesive energies. Lattice constants corrected for correlation
effects deviate by less than 1% from experimental values, in the case of MgO
and CaO.Comment: LaTeX, 4 figure
Resonant Formation of Molecules in Deuterium: An Atomic Beam Measurement of Muon Catalyzed dt Fusion
Resonant formation of molecules in collisions of muonic tritium
() on D was investigated using a beam of atoms,
demonstrating a new direct approach in muon catalyzed fusion studies. Strong
epithermal resonances in formation were directly revealed for the
first time. From the time-of-flight analysis of fusion
events, a formation rate consistent with times the theoretical prediction was obtained. For the largest
peak at a resonance energy of eV, this corresponds to a rate
of s, more than an order of magnitude larger
than those at low energies.Comment: To appear in Phys. Rev. Let
Quantifying Model Complexity via Functional Decomposition for Better Post-Hoc Interpretability
Post-hoc model-agnostic interpretation methods such as partial dependence
plots can be employed to interpret complex machine learning models. While these
interpretation methods can be applied regardless of model complexity, they can
produce misleading and verbose results if the model is too complex, especially
w.r.t. feature interactions. To quantify the complexity of arbitrary machine
learning models, we propose model-agnostic complexity measures based on
functional decomposition: number of features used, interaction strength and
main effect complexity. We show that post-hoc interpretation of models that
minimize the three measures is more reliable and compact. Furthermore, we
demonstrate the application of these measures in a multi-objective optimization
approach which simultaneously minimizes loss and complexity
- âŠ