arXiv subjects

Nan Li

Publications and source records attributed to Nan Li.

At least 271 records · Page 15Linked to original sources

arXiv2021

Mass production and characterization of 3-inch PMTs for the JUNO experiment

26,000 3-inch photomultiplier tubes (PMTs) have been produced for Jiangmen Underground Neutrino Observatory (JUNO) by the Hainan Zhanchuang Photonics Technology Co., Ltd (HZC) company in China and passed all acceptance tests with only 15 tubes rejected. The mass production began in 2018 and elapsed for about 2 years at a rate of $\sim$1,000~PMTs per month. The characterization of the PMTs was performed in the factory concurrently with production as a joint effort between HZC and JUNO. Fifteen performance parameters were tracked at different sampling rates, and novel working strategies were implemented to improve quality assurance. This constitutes the largest sample of 3-inch PMTs ever produced and studied in detail to date.

physics.ins-det↗

arXiv2021

Damage accumulation during high temperature fatigue of Ti/SiC$_f$ metal matrix composites under different stress amplitudes

The damage mechanisms and load redistribution of high strength TC17 titanium alloy/unidirectional SiC fibre composite (fibre diameter = 100 $μ$m) under high temperature (350 °C) fatigue cycling have been investigated in situ using synchrotron X-ray computed tomography (CT) and X-ray diffraction (XRD) for high cycle fatigue (HCF) under different stress amplitudes. The three-dimensional morphology of the crack and fibre fractures has been mapped by CT. During stable growth, matrix cracking dominates with the crack deflecting (by 50-100 $μ$m in height) when bypassing bridging fibres. A small number of bridging fibres have fractured close to the matrix crack plane especially under relatively high stress amplitude cycling. Loading to the peak stress led to rapid crack growth accompanied by a burst of fibre fractures. Many of the fibre fractures occurred 50-300 $μ$m from the matrix crack plane during rapid growth, in contrast to that in the stable growth stage, leading to extensive fibre pull-out on the fracture surface. The changes in fibre loading, interfacial stress, and the extent of fibre-matrix debonding in the vicinity of the crack have been mapped for the fatigue cycle and after the rapid growth by high spatial resolution XRD. The fibre/matrix interfacial sliding extends up to 600 $μ$m (in the stable growth zone) or 700 $μ$m (in the rapid growth zone) either side of the crack plane. The direction of interfacial shear stress reverses with the loading cycle, with the maximum frictional sliding stress reaching ~55 MPa in both the stable growth and rapid growth regimes.

cond-mat.mtrl-sci↗

arXiv2021

Kinematics and star formation toward W33: a central hub as a hub--filament system

We performed a large-scale mapping observation toward the W33 complex and its surroundings, covering an area of $1.3^\circ \times 1.0^\circ$ , in $^{12}$CO (1-0), $^{13}$CO (1-0), and C$^{18}$O (1-0) lines from the Purple Mountain Observatory (PMO). We found a new hub--filament system ranging from 30 to 38.5 \kms located at the W33 complex. Three supercritical filaments are directly converging into the central hub W33. Velocity gradients are detected along the filaments and the accretion rates are in order of $\rm 10^{-3}\,M_\odot\, yr^{-1}$. The central hub W33 has a total mass of $\rm\sim 1.8\times10^5\,M_\odot$, accounting for $\sim 60\%$ of the mass of the hub--filament system. This indicates that the central hub is the mass reservoir of the hub-filament system. Furthermore, 49 ATLASGAL clumps are associated with the hub--filament system. We find $57\%$ of the clumps to be situated in the central hub W33 and clustered at the intersections between the filaments and the W33 complex. Moreover, the distribution of Class I young stellar objects (YSOs) forms a structure resembling the hub--filament system and peaks at where the clumps group; it seems to suggest that the mechanisms of clump formation and star formation in this region are correlated. Gas flows along the filaments are likely to feed the materials into the intersections and lead to the clustering and formation of the clumps in the hub--filament system W33. The star formation in the intersections between the filaments and the W33 complex might be triggered by the motion of gas converging into the intersections.

astro-ph.GA↗

arXiv2021

Measuring the gravitomagnetic distortion from rotating halos I: methods

Source galaxy images are distorted not only by a static gravitational potential, but also by frame-dragging induced by massive rotating objects like clusters of galaxies. Such effect is well understood theoretically, it is therefore of great interest to estimate its detectability for future surveys. In this work, we analyze the lensing convergence $κ$ around rotating dark matter halos. The rotation of the massive objects generates a gravitomagnetic potential giving rise to an anisotropic contribution to the lensing potential. We construct an estimator $δκ$ to describe the difference between the symmetric enhancement and reduction of $κ$ around the halo rotation axis, finding that it is well approximated by a function proportional to the halo velocity dispersion squared times a dimensionless angular momentum parameter. Using simulation mocks with realistic noise level for a survey like LSST, we test our estimator, and show that the signal from frame-dragging of stacked rotating lenses is consistent with zero within $1σ$. However, we find that the most massive cluster in SDSS DR7 spectroscopic selected group catalog has a line-of-sight rotation velocity of 195.0km/s and velocity dispersion of 667.8km/s, which is at $1.2\times 10^{-8}$ odds according to the angular momentum probability distribution inferred from N-body simulations. By studying SDSS DR7 spectroscopic selected group catalog, we show how rotating clusters can be identified, and, finding that fast rotating clusters might be more abundant than in estimates based on simulations, a detection of gravitomagnetic distortion may be at reach in future surveys

astro-ph.CO↗

arXiv2021

Coordinated Receding-Horizon Control of Battery Electric Vehicle Speed and Gearshift Using Relaxed Mixed Integer Nonlinear Programming

In this paper, we propose an approach to coordinated receding-horizon control of vehicle speed and transmission gearshift for automated battery electric vehicles (BEVs) to achieve improved energy efficiency. The introduction of multi-speed transmissions in BEVs creates an opportunity to manipulate the operating point of electric motors under given vehicle speed and acceleration command, thus providing the potential to further improve the energy efficiency. However, co-optimization of vehicle speed and transmission gearshift leads to a mixed integer nonlinear program (MINLP), solving which can be computationally very challenging. In this paper, we propose a novel continuous relaxation technique to treat such MINLPs that makes it possible to compute solutions with conventional nonlinear programming solvers. After analyzing its theoretical properties, we use it to solve the optimization problem involved in coordinated receding-horizon control of BEV speed and gearshift. Through simulation studies, we show that co-optimizing vehicle speed and transmission gearshift can achieve considerably greater energy efficiency than optimizing them sequentially, and the proposed relaxation technique can reduce the online computational cost to a level that is comparable to the time available for real-time implementation.

eess.SY↗

arXiv2021

Beating humans in a penny-matching game by leveraging cognitive hierarchy theory and Bayesian learning

It is a long-standing goal of artificial intelligence (AI) to be superior to human beings in decision making. Games are suitable for testing AI capabilities of making good decisions in non-numerical tasks. In this paper, we develop a new AI algorithm to play the penny-matching game considered in Shannon's "mind-reading machine" (1953) against human players. In particular, we exploit cognitive hierarchy theory and Bayesian learning techniques to continually evolve a model for predicting human player decisions, and let the AI player make decisions according to the model predictions to pursue the best chance of winning. Experimental results show that our AI algorithm beats 27 out of 30 volunteer human players.

cs.AI↗

arXiv2021

Auto-identification of unphysical source reconstructions in strong gravitational lens modelling

With the advent of next-generation surveys and the expectation of discovering huge numbers of strong gravitational lens systems, much effort is being invested into developing automated procedures for handling the data. The several orders of magnitude increase in the number of strong galaxy-galaxy lens systems is an insurmountable challenge for traditional modelling techniques. Whilst machine learning techniques have dramatically improved the efficiency of lens modelling, parametric modelling of the lens mass profile remains an important tool for dealing with complex lensing systems. In particular, source reconstruction methods are necessary to cope with the irregular structure of high-redshift sources. In this paper, we consider a Convolutional Neural Network (CNN) that analyses the outputs of semi-analytic methods which parametrically model the lens mass and linearly reconstruct the source surface brightness distribution. We show the unphysical source reconstructions that arise as a result of incorrectly initialised lens models can be effectively caught by our CNN. Furthermore, the CNN predictions can be used to automatically re-initialise the parametric lens model, avoiding unphysical source reconstructions. The CNN, trained on reconstructions of lensed Sérsic sources, accurately classifies source reconstructions of the same type with a precision $P > 0.99$ and recall $R > 0.99$. The same CNN, without re-training, achieves $P=0.89$ and $R=0.89$ when classifying source reconstructions of more complex lensed HUDF sources. Using the CNN predictions to re-initialise the lens modelling procedure, we achieve a 69 per cent decrease in the occurrence of unphysical source reconstructions. This combined CNN and parametric modelling approach can greatly improve the automation of lens modelling.

astro-ph.GA↗

arXiv2021

Some results on transcendental entire solutions of certain nonlinear differential-difference equations

In this paper, we study the transcendental entire solutions for the nonlinear differential-difference equations of the forms: $f^{2}(z)+\widetildeω f(z)f'(z)+q(z)e^{Q(z)}f(z+c)=u(z)e^{v(z)}$, and $f^{n}(z)+ωf^{n-1}(z)f'(z)+q(z)e^{Q(z)}f(z+c)=p_{1}e^{λ_{1} z}+p_{2}e^{λ_{2} z}, \quad n\geq 3,$ where $ω$ is a constant, $\widetildeω, c, λ_{1}, λ_{2}, p_{1}, p_{2}$ are non-zero constants, $q, Q, u, v$ are polynomials such that $Q,v$ are not constants and $q,u\not\equiv0$. Our results are improvements and complements of some previous results.

math.CV↗

arXiv2021

The LSST DESC DC2 Simulated Sky Survey

We describe the simulated sky survey underlying the second data challenge (DC2) carried out in preparation for analysis of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) by the LSST Dark Energy Science Collaboration (LSST DESC). Significant connections across multiple science domains will be a hallmark of LSST; the DC2 program represents a unique modeling effort that stresses this interconnectivity in a way that has not been attempted before. This effort encompasses a full end-to-end approach: starting from a large N-body simulation, through setting up LSST-like observations including realistic cadences, through image simulations, and finally processing with Rubin's LSST Science Pipelines. This last step ensures that we generate data products resembling those to be delivered by the Rubin Observatory as closely as is currently possible. The simulated DC2 sky survey covers six optical bands in a wide-fast-deep (WFD) area of approximately 300 deg^2 as well as a deep drilling field (DDF) of approximately 1 deg^2. We simulate 5 years of the planned 10-year survey. The DC2 sky survey has multiple purposes. First, the LSST DESC working groups can use the dataset to develop a range of DESC analysis pipelines to prepare for the advent of actual data. Second, it serves as a realistic testbed for the image processing software under development for LSST by the Rubin Observatory. In particular, simulated data provide a controlled way to investigate certain image-level systematic effects. Finally, the DC2 sky survey enables the exploration of new scientific ideas in both static and time-domain cosmology.

astro-ph.IM↗

arXiv2021

Hawking--Page phase transitions in four-dimensional Einstein--Gauss--Bonnet gravity

The Hawking-Page (HP) phase transitions of the anti-de Sitter black holes in the extended phase space are studied in a novel four-dimensional Einstein-Gauss-Bonnet (4EGB) gravity, which is proposed by rescaling the Gauss--Bonnet (GB) coupling constant $α\toα/(d-4)$ in $d$ dimensions and redefining the four-dimensional gravity in the limit $d \to 4$. The GB term shows nontrivial contributions to both black hole mass and entropy simultaneously, and decreases the HP phase transition temperature $T_{\rm HP}$. Moreover, the HP phase transitions can happen only within a range of pressure in the 4EGB gravity. For the charged black holes, $T_{\rm HP}$ also decreases with the electric potential in the grand canonical ensemble. A general discussion of the HP phase transitions in the Einstein, GB, and 4EGB gravities is also presented.

gr-qc↗

arXiv2020

A practical approach of high precision U and Th concentration measurement in acrylic

The Jiangmen Underground Neutrino Observatory will build the world's largest liquid scintillator detector to study neutrinos from various sources. The 20 kt liquid scintillator will be stored in a $\sim$600 t acrylic sphere with 35.4 m diameter due to the good light transparency, chemical compatibility and low radioactivity of acrylic. The concentration of U/Th in acrylic is required to be less than 1 ppt (10$^{-12}$ g/g) to achieve a low radioactive background in the fiducial volume of the JUNO detector. The mass production of acrylic has started, and the quality control requires a fast and reliable radioassay on U/Th in acrylic. We have developed a practical method of measuring U/Th in acrylic to sub-ppt level using the Inductively Coupled Plasma Mass Spectrometer (ICP-MS). The U/Th in acrylic can be concentrated by vaporizing acrylic in a class 100 environment, and the residue will be collected and sent to ICP-MS for measuring U/Th. All the other chemical operation is done in a class 100 clean room, and the ICP-MS measurement is done in a class 1000 clean room. The recovery efficiency is studied by adding the natural nonexistent nuclei $^{229}$Th and $^{233}$U as the tracers. The resulting method detection limit (MDL) with 99% confidence can reach 0.02/0.06 pg $^{238}$U/$^{232}$Th /g acrylic with $\sim$75% recovery efficiency. This equipment and method can not only be used for the quality control of JUNO acrylic, but also be further optimized for the radioassay on other materials with extremely low radioactivity, such as ultra-pure water and liquid scintillator.

physics.ins-det↗

arXiv2020

Predicting Terrain Mechanical Properties in Sight for Planetary Rovers with Semantic Clues

Non-geometric mobility hazards such as rover slippage and sinkage posing great challenges to costly planetary missions are closely related to the mechanical properties of terrain. In-situ proprioceptive processes for rovers to estimate terrain mechanical properties need to experience different slip as well as sinkage and are helpless to untraversed regions. This paper proposes to predict terrain mechanical properties with vision in the distance, which expands the sensing range to the whole view and can partly halt potential slippage and sinkage hazards in the planning stage. A semantic-based method is designed to predict bearing and shearing properties of terrain in two stages connected with semantic clues. The former segmentation phase segments terrain with a light-weighted network promising to be applied onboard with competitive 93% accuracy and high recall rate over 96%, while the latter inference phase predicts terrain properties in a quantitative manner based on human-like inference principles. The prediction results in several test routes are 12.5% and 10.8% in full-scale error and help to plan appropriate strategies to avoid suffering non-geometric hazards.

cs.RO↗

arXiv2020

Chance-Constrained Controller State and Reference Governor

The controller state and reference governor (CSRG) is an add-on scheme for nominal closed-loop systems with dynamic controllers which supervises the controller internal state and the reference input to the closed-loop system to enforce pointwise-in-time constraints. By admitting both controller state and reference modifications, the CSRG can achieve an enlarged constrained domain of attraction compared to conventional reference governor schemes where only reference modification is permitted. This paper studies the CSRG for systems subject to stochastic disturbances and chance constraints. We describe the CSRG algorithm in such a stochastic setting and analyze its theoretical properties, including chance-constraint enforcement, finite-time reference convergence, and closed-loop stability. We also present examples illustrating the application of CSRG to constrained aircraft flight control.

eess.SY↗

arXiv2020

A study on using image based machine learning methods to develop the surrogate models of stamp forming simulations

In the design optimization of metal forming, it is increasingly significant to use surrogate models to analyse the finite element analysis (FEA) simulations. However, traditional surrogate models using scalar based machine learning methods (SBMLMs) fall in short of accuracy and generalizability. This is because SBMLMs fail to harness the location information of the simulations. To overcome these shortcomings, image based machine learning methods (IBMLMs) are leveraged in this paper. The underlying theory of location information, which supports the advantages of IBMLM, is qualitatively interpreted. Based on this theory, a Res-SE-U-Net IBMLM surrogate model is developed and compared with a multi-layer perceptron (MLP) as a referencing SBMLM surrogate model. It is demonstrated that the IBMLM model is advantageous over the MLP SBMLM model in accuracy, generalizability, robustness, and informativeness. This paper presents a promising methodology of leveraging IBMLMs in surrogate models to make maximum use of info from FEA results. Future prospective studies that inspired by this paper are also discussed.

cs.CV↗

arXiv2020

Domain Priori Knowledge based Integrated Solution Design for Internet of Services

Various types of services, such as web APIs, IoT services, O2O services, and many others, have flooded on the Internet. Interconnections among these services have resulted in a new phenomenon called "Internet of Services" (IoS). By IoS,people don't need to request multiple services by themselves to fulfill their daily requirements, but it is an IoS platform that is responsible for constructing integrated solutions for them. Since user requirements (URs) are usually coarse-grained and transboundary, IoS platforms have to integrate services from multiple domains to fulfill the requirements. Considering there are too many available services in IoS, a big challenge is how to look for a tradeoff between the construction efficiency and the precision of final solutions. For this challenge, we introduce a framework and a platform for transboundary user requirement oriented solution design in IoS. The main idea is to make use of domain priori knowledge derived from the commonness and similarities among massive historical URs and among historical integrated service solutions(ISSs). Priori knowledge is classified into three types: requirement patterns (RPs), service patterns (SPs), and probabilistic matching matrix (PMM) between RPs and SPs. A UR is modeled in the form of an intention tree (ITree) along with a set of constraints on intention nodes, and then optimal RPs are selected to cover the I-Tree as much as possible. By taking advantage of the PMM, a set of SPs are filtered out and composed together to form the final ISS. Finally, the design of a platform supporting the above process is introduced.

cs.SE↗

arXiv2020

Game-theoretic Modeling of Traffic in Unsignalized Intersection Network for Autonomous Vehicle Control Verification and Validation

For a foreseeable future, autonomous vehicles (AVs) will operate in traffic together with human-driven vehicles. Their planning and control systems need extensive testing, including early-stage testing in simulations where the interactions among autonomous/human-driven vehicles are represented. Motivated by the need for such simulation tools, we propose a game-theoretic approach to modeling vehicle interactions, in particular, for urban traffic environments with unsignalized intersections. We develop traffic models with heterogeneous (in terms of their driving styles) and interactive vehicles based on our proposed approach, and use them for virtual testing, evaluation, and calibration of AV control systems. For illustration, we consider two AV control approaches, analyze their characteristics and performance based on the simulation results with our developed traffic models, and optimize the parameters of one of them.

cs.RO↗

arXiv2020

Maximizing Cumulative User Engagement in Sequential Recommendation: An Online Optimization Perspective

To maximize cumulative user engagement (e.g. cumulative clicks) in sequential recommendation, it is often needed to tradeoff two potentially conflicting objectives, that is, pursuing higher immediate user engagement (e.g., click-through rate) and encouraging user browsing (i.e., more items exposured). Existing works often study these two tasks separately, thus tend to result in sub-optimal results. In this paper, we study this problem from an online optimization perspective, and propose a flexible and practical framework to explicitly tradeoff longer user browsing length and high immediate user engagement. Specifically, by considering items as actions, user's requests as states and user leaving as an absorbing state, we formulate each user's behavior as a personalized Markov decision process (MDP), and the problem of maximizing cumulative user engagement is reduced to a stochastic shortest path (SSP) problem. Meanwhile, with immediate user engagement and quit probability estimation, it is shown that the SSP problem can be efficiently solved via dynamic programming. Experiments on real-world datasets demonstrate the effectiveness of the proposed approach. Moreover, this approach is deployed at a large E-commerce platform, achieved over 7% improvement of cumulative clicks.

cs.IR↗

arXiv2020

Action Governor for Discrete-Time Linear Systems with Non-Convex Constraints

This paper introduces an add-on, supervisory scheme, referred to as Action Governor (AG), for discrete-time linear systems to enforce exclusion-zone avoidance requirements. It does so by monitoring, and minimally modifying when necessary, the nominal control signal to a constraint-admissible one. The AG operates based on set-theoretic techniques and online optimization. This paper establishes its theoretical foundation, discusses its computational realization, and uses two simulation examples to illustrate its effectiveness.

eess.SY↗