239 research outputs found
Link between K-absorption edges and thermodynamic properties of warm-dense plasmas established by improved first-principles method
A precise calculation that translates shifts of X-ray K-absorption edges to
variations of thermodynamic properties allows quantitative characterization of
interior thermodynamic properties of warm dense plasmas by X-ray absorption
techniques, which provides essential information for inertial confinement
fusion and other astrophysical applications. We show that this interpretation
can be achieved through an improved first-principles method. Our calculation
shows that the shift of K-edges exhibits selective sensitivity to thermal
parameters and thus would be a suitable temperature index to warm dense
plasmas. We also show with a simple model that the shift of K-edges can be used
to detect inhomogeneity inside warm dense plasmas when combined with other
experimental tools
First-Principles Calculation of Principal Hugoniot and K-Shell X-ray Absorption Spectra for Warm Dense KCl
Principal Hugoniot and K-shell X-ray absorption spectra of warm dense KCl are
calculated using the first-principles molecular dynamics method. Evolution of
electronic structures as well as the influence of the approximate description
of ionization on pressure (caused by the underestimation of the energy gap
between conduction bands and valence bands) in the first-principles method are
illustrated by the calculation. Pressure ionization and thermal smearing are
shown as the major factors to prevent the deviation of pressure from global
accumulation along the Hugoniot. In addition, cancellation between electronic
kinetic pressure and virial pressure further reduces the deviation. The
calculation of X-ray absorption spectra shows that the band gap of KCl persists
after the pressure ionization of the electrons of Cl and K taking place at
lower energy, which provides a detailed understanding to the evolution of
electronic structures of warm dense matter
Seamlessly Unifying Attributes and Items: Conversational Recommendation for Cold-Start Users
Static recommendation methods like collaborative filtering suffer from the
inherent limitation of performing real-time personalization for cold-start
users. Online recommendation, e.g., multi-armed bandit approach, addresses this
limitation by interactively exploring user preference online and pursuing the
exploration-exploitation (EE) trade-off. However, existing bandit-based methods
model recommendation actions homogeneously. Specifically, they only consider
the items as the arms, being incapable of handling the item attributes, which
naturally provide interpretable information of user's current demands and can
effectively filter out undesired items. In this work, we consider the
conversational recommendation for cold-start users, where a system can both ask
the attributes from and recommend items to a user interactively. This important
scenario was studied in a recent work. However, it employs a hand-crafted
function to decide when to ask attributes or make recommendations. Such
separate modeling of attributes and items makes the effectiveness of the system
highly rely on the choice of the hand-crafted function, thus introducing
fragility to the system. To address this limitation, we seamlessly unify
attributes and items in the same arm space and achieve their EE trade-offs
automatically using the framework of Thompson Sampling. Our Conversational
Thompson Sampling (ConTS) model holistically solves all questions in
conversational recommendation by choosing the arm with the maximal reward to
play. Extensive experiments on three benchmark datasets show that ConTS
outperforms the state-of-the-art methods Conversational UCB (ConUCB) and
Estimation-Action-Reflection model in both metrics of success rate and average
number of conversation turns.Comment: TOIS 202
Chaos: a bridge from microscopic uncertainty to macroscopic randomness
It is traditionally believed that the macroscopic randomness has nothing to
do with the micro-level uncertainty. Besides, the sensitive dependence on
initial condition (SDIC) of Lorenz chaos has never been considered together
with the so-called continuum-assumption of fluid (on which Lorenz equations are
based), from physical and statistic viewpoints. A very fine numerical technique
(Liao, 2009) with negligible truncation and round-off errors, called here the
"clean numerical simulation" (CNS), is applied to investigate the propagation
of the micro-level unavoidable uncertain fluctuation (caused by the
continuum-assumption of fluid) of initial conditions for Lorenz equation with
chaotic solutions. Our statistic analysis based on CNS computation of 10,000
samples shows that, due to the SDIC, the uncertainty of the micro-level
statistic fluctuation of initial conditions transfers into the macroscopic
randomness of chaos. This suggests that chaos might be a bridge from
micro-level uncertainty to macroscopic randomness, and thus would be an origin
of macroscopic randomness. We reveal in this article that, due to the SDIC of
chaos and the inherent uncertainty of initial data, accurate long-term
prediction of chaotic solution is not only impossible in mathematics but also
has no physical meanings. This might provide us a new, different viewpoint to
deepen and enrich our understandings about the SDIC of chaos.Comment: 9 pages, 2 figure
Transonic flutter characteristic of an airfoil with morphing devices
An investigation into transonic flutter characteristic of an airfoil conceived with the morphing leading and trailing edges has been carried out. Computational fluid dynamics (CFD) is used to calculate the unsteady aerodynamic force in transonic flow. An aerodynamic reduced order model (ROM) based on autoregressive model with exogenous input (ARX) is used in the numerical simulation. The flutter solution is determined by eigenvalue analysis at specific Mach number. The approach is validated by comparing the transonic flutter characteristics of the Isogai wing with relevant literatures before applied to a morphing airfoil. The study reveals that by employing the morphing trailing edge, the shock wave forms and shifts to the trailing edge at a lower Mach number, and aerodynamic force stabilization happens earlier. Meanwhile, the minimum flutter speed increases and transonic dip occurs at a lower Mach number. It is also noted that leading edge morphing has negligible effect on the appearance of the shock wave and transonic flutter. The mechanism of improving the transonic flutter characteristics by morphing technology is discussed by correlating shock wave location on airfoil surface, unsteady aerodynamics with flutter solutio
Gust response and body freedom flutter of a flying-wing aircraft with a passive gust alleviation device
The effectiveness of a passive gust alleviation device (PGAD) mounted at the wingtip of aircraft in conventional and flying-wing configurations have been studied in previous research. However the PGAD influence on the aeroelastic stability in particular the body freedom flutter (BFF) of a flying-wing aircraft remains as a concern. This present investigation is focused on evaluating the beneficial effect of PGAD on both gust load alleviation and BFF of a small flying-wing aircraft of high aspect ratio wing made of composite. A small range of (1-cos) type of gust load has been considered to select a representative critical gust load case for the study. A parametric study indicates that there is a narrow band of optimal key parameters for the PGAD design. Subsequently a set of optimal parameters is selected to further the analysis of the PGAD mechanism. The case study results show that the PGAD can make the bending moment at the wing root due to gust reduced by 16%. In addition, the BFF speed of the flying-wing aircraft is increased by 4.2%. The investigation reveals that the PGAD mode and its interaction with the wing bending mode and short period oscillation of the aircraft can have beneficial aeroelastic effect on both gust alleviation and flutter suppression
Passive gust alleviation of a flying-wing aircraft by analysis and wind-tunnel test of a scaled model in dynamic similarity
An investigation was conducted to evaluate the effectiveness of a passive gust alleviation device (PGAD) installed in a flying-wing aircraft of 62.3m wing span at large swept back angle. It was performed by numerical analysis and validated by wind-tunnel test of a 1:25 reduced scale physical model of dynamic similarity to the full-scale aircraft. The 1-cosine gust model with a range of gust parameters specified in the airworthiness regulation CS-23 was taken in the gust response analysis that led to 7~9% gust alleviation results by employing the PGAD. The gust response dominated by the first three modes of the aircraft was most critical in the frequency close to the first bending mode of the wing. The wind-tunnel test model was designed and manufactured based on dynamic scaling law, and proved to be of excellent dynamic similarity by the deviation of less than 5.5% between the first three modes of the physical model measured by vibration test and the full-scale aircraft model. The wind tunnel test results show that the gust response of the model in the specified range was reduced by 8.3~14.3% according to the measured wing tip deflection associated with the PGAD oscillation amplitude at 4.0°~15.5°. The present study shows that the numerical analysis of gust response and alleviation of a full-scale aircraft installed with PGAD can be validated by wind tunnel test of a scaled physical model with dynamic similarity
Comparison between Numerical and Analytical Analysis of the Dynamic Behavior of Circular Tunnels
Dynamic behavior of underground structures is controlled by the strain field imposed by wave propagation and by the interaction between rock mass and structures. Shear and pressure waves propagating in the plane of the cross-section of the tunnel generate ground distortions, which tend to cause ovaling deformations of the lining. In this paper, the seismic response of a circular tunnel subjected respectively to shear waves and pressure waves will be analyzed both analytically and numerically at first, and then a complete 3D analysis will be given to show the overall effects on a tunnel induced by seismic events considering seismic inputs in three directions.El comportamiento dinámico de estructuras subterráneas se controla por el campo de deformación impuesta por la propagación de ondas y por la interacción entre la masa rocosa y las estructuras. La onda de cizallamiento y la onda de presión en el plano de sección transversal del túnel generan distorsiones del terreno que tienden a causar deformaciones ovaladas del revestimiento de la estructura. En este artÃculo se analiza la respuesta sÃsmica de un túnel circular sujeto respectivamente a ondas de cizallamiento y ondas de presión tanto analÃtica como numéricamente. Luego se muestra un análisis tridimensional completo para mostrar los efectos generales en un túnel producidos por eventos sÃsmicos y donde se consideran registros en tres direcciones
CIRS: Bursting Filter Bubbles by Counterfactual Interactive Recommender System
While personalization increases the utility of recommender systems, it also
brings the issue of filter bubbles. E.g., if the system keeps exposing and
recommending the items that the user is interested in, it may also make the
user feel bored and less satisfied. Existing work studies filter bubbles in
static recommendation, where the effect of overexposure is hard to capture. In
contrast, we believe it is more meaningful to study the issue in interactive
recommendation and optimize long-term user satisfaction. Nevertheless, it is
unrealistic to train the model online due to the high cost. As such, we have to
leverage offline training data and disentangle the causal effect on user
satisfaction.
To achieve this goal, we propose a counterfactual interactive recommender
system (CIRS) that augments offline reinforcement learning (offline RL) with
causal inference. The basic idea is to first learn a causal user model on
historical data to capture the overexposure effect of items on user
satisfaction. It then uses the learned causal user model to help the planning
of the RL policy. To conduct evaluation offline, we innovatively create an
authentic RL environment (KuaiEnv) based on a real-world fully observed user
rating dataset. The experiments show the effectiveness of CIRS in bursting
filter bubbles and achieving long-term success in interactive recommendation.
The implementation of CIRS is available via
https://github.com/chongminggao/CIRS-codes.Comment: 11 pages, 9 figure
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