13,513 research outputs found
Aeronautical engineering: A continuing bibliography, supplement 122
This bibliography lists 303 reports, articles, and other documents introduced into the NASA scientific and technical information system in April 1980
Space processes for extended low-G testing
Results of an investigation of verifying the capabilities of space processes in ground based experiments at low-g periods are presented. Limited time experiments were conducted with the processes. A valid representation of the complete process cycle was achieved at low-g periods ranging from 40 to 390 seconds. A minimum equipment inventory, is defined. A modular equipment design, adopted to assure low cost and high program flexibility, is presented as well as procedures and data established for the synthesis and definition of dedicated and mixed rocket payloads
The Parametric Aircraft Noise Analysis Module - status overview and recent applications
The German Aerospace Center (DLR) is investigating aircraft noise prediction and noise reduction capabilities. The Parametric Aircraft Noise Analysis Module (PANAM) is a fast prediction tool by the DLR Institute of Aerodynamics and Flow Technology to address overall aircraft noise. It was initially developed to (1) enable comparative design studies with respect to overall aircraft ground noise and to (2) indentify promising low-noise technologies at early aircraft design stages. A brief survey of available and established fast
noise prediction codes is provided in order to rank and classify PANAM among existing tools. PANAM predicts aircraft noise generated during arbitrary 3D approach and take-off
flight procedures. Noise generation of an operating aircraft is determined by its design, the relative observer position, configuration settings, and operating condition along the flight
path. Feasible noise analysis requires a detailed simulation of all these dominating effects. Major aircraft noise components are simulated with individual models and interactions are
neglected. Each component is simulated with a separate semi-empirical and parametric noise source model. These models capture major physical effects and correlations yet allow
for fast and accurate noise prediction. Sound propagation and convection effects are applied to the emitting noise source in order to transfer static emission into aircraft ground noise
impact with respect to the actual flight operating conditions. Recent developments and process interfaces are presented and prediction results are compared with experimental
data recorded during DLR flyover noise campaigns with an Airbus A319 (2006), a VFW-614 (2009), and a Boeing B737-700 (2010). Overall, dominating airframe and engine noise
sources are adequately modeled and overall aircraft ground noise levels can sufficiently be predicted. The paper concludes with a brief overview on current code applications towards selected noise reduction technologies
Patterns of Scalable Bayesian Inference
Datasets are growing not just in size but in complexity, creating a demand
for rich models and quantification of uncertainty. Bayesian methods are an
excellent fit for this demand, but scaling Bayesian inference is a challenge.
In response to this challenge, there has been considerable recent work based on
varying assumptions about model structure, underlying computational resources,
and the importance of asymptotic correctness. As a result, there is a zoo of
ideas with few clear overarching principles.
In this paper, we seek to identify unifying principles, patterns, and
intuitions for scaling Bayesian inference. We review existing work on utilizing
modern computing resources with both MCMC and variational approximation
techniques. From this taxonomy of ideas, we characterize the general principles
that have proven successful for designing scalable inference procedures and
comment on the path forward
Overview of the JET results in support to ITER
The 2014–2016 JET results are reviewed in the light of their significance for optimising
the ITER research plan for the active and non-active operation. More than 60 h of plasma
operation with ITER first wall materials successfully took place since its installation in
2011. New multi-machine scaling of the type I-ELM divertor energy flux density to ITER
is supported by first principle modelling. ITER relevant disruption experiments and first
principle modelling are reported with a set of three disruption mitigation valves mimicking
the ITER setup. Insights of the L–H power threshold in Deuterium and Hydrogen are given,
stressing the importance of the magnetic configurations and the recent measurements of
fine-scale structures in the edge radial electric. Dimensionless scans of the core and pedestal
confinement provide new information to elucidate the importance of the first wall material on
the fusion performance. H-mode plasmas at ITER triangularity (H = 1 at βN ~ 1.8 and n/nGW
~ 0.6) have been sustained at 2 MA during 5 s. The ITER neutronics codes have been validated
on high performance experiments. Prospects for the coming D–T campaign and 14 MeV
neutron calibration strategy are reviewed.European Commission (EUROfusion 633053
Quantum Thermodynamics
Quantum thermodynamics addresses the emergence of thermodynamical laws from
quantum mechanics. The link is based on the intimate connection of quantum
thermodynamics with the theory of open quantum systems. Quantum mechanics
inserts dynamics into thermodynamics giving a sound foundation to
finite-time-thermodynamics. The emergence of the 0-law I-law II-law and III-law
of thermodynamics from quantum considerations is presented. The emphasis is on
consistence between the two theories which address the same subject from
different foundations. We claim that inconsistency is the result of faulty
analysis pointing to flaws in approximations
Coherent Bayesian inference on compact binary inspirals using a network of interferometric gravitational wave detectors
Presented in this paper is a Markov chain Monte Carlo (MCMC) routine for
conducting coherent parameter estimation for interferometric gravitational wave
observations of an inspiral of binary compact objects using data from multiple
detectors. The MCMC technique uses data from several interferometers and infers
all nine of the parameters (ignoring spin) associated with the binary system,
including the distance to the source, the masses, and the location on the sky.
The Metropolis-algorithm utilises advanced MCMC techniques, such as importance
resampling and parallel tempering. The data is compared with time-domain
inspiral templates that are 2.5 post-Newtonian (PN) in phase and 2.0 PN in
amplitude. Our routine could be implemented as part of an inspiral detection
pipeline for a world wide network of detectors. Examples are given for
simulated signals and data as seen by the LIGO and Virgo detectors operating at
their design sensitivity.Comment: 10 pages, 4 figure
Aeronautical engineering: A continuing bibliography with indexes, supplement 100
This bibliography lists 295 reports, articles, and other documents introduced into the NASA Scientific and Technical Information System in August 1978
Optimal quantum operations at zero energy cost
Quantum technologies are developing powerful tools to generate and manipulate
coherent superpositions of different energy levels. Envisaging a new generation
of energy-efficient quantum devices, here we explore how coherence can be
manipulated without exchanging energy with the surrounding environment. We
start from the task of converting a coherent superposition of energy
eigenstates into another. We identify the optimal energy-preserving operations,
both in the deterministic and in the probabilistic scenario. We then design a
recursive protocol, wherein a branching sequence of energy-preserving filters
increases the probability of success while reaching maximum fidelity at each
iteration. Building on the recursive protocol, we construct efficient
approximations of the optimal fidelity-probability trade-off, by taking
coherent superpositions of the different branches generated by probabilistic
filtering. The benefits of this construction are illustrated in applications to
quantum metrology, quantum cloning, coherent state amplification, and
ancilla-driven computation. Finally, we extend our results to transitions where
the input state is generally mixed and we apply our findings to the task of
purifying quantum coherence.Comment: 35 pages, 10 figures; published versio
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