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Building Simulation 2024年第4期17卷 639-655页

作者： Shanshuo Xing Jili Zhang song Mu Dalian University of Technology Dalian116024China Guangdong Airport Baiyun Information Technology Co. Ltd.Guangzhou510000China

Optimization for the multi-chiller system is an indispensable approach for the operation of highly efficient chiller *** optima obtained by model-based optimization algorithms are dependent on precise and solvable objective *** classical neural networks cannot provide convex input-output mappings despite capturing impressive nonlinear fitting capabilities,resulting in a reduction in the robustness of model-based *** this paper,we leverage the input convex neural networks(ICNN)to identify the chiller model to construct a convex mapping between control variables and the objective function,which enables the NN-based OCL as a convex optimization problem and apply it to multi-chiller optimization for optimal chiller loading(OCL).Approximation performances are evaluated through a four-model comparison based on an experimental data set,and the statistical results show that,on the premise of retaining prior convexities,the proposed model depicts excellent approximation power for the data set,especially the unseen ***,the ICNN model is applied to a typical OCL problem for a multi-chiller system and combined with three types of optimization *** with conventional and meta-heuristic methods,the numerical results suggest that the gradient-based BFGS algorithm provides better energy-saving ratios facing consecutive cooling load inputs and an impressive convergence speed.

关键词： chiller plant input convex neural network optimal load distribution convex optimization

Elasto-inertial microfluidic separation of microspheres with submicron resolution at high-throughput

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Microsystems & Nanoengineering 2024年第1期10卷 203-216页

作者： Hyunwoo Jeon song Ha Lee Jongho Shin Kicheol song Nari Ahn Jinsoo Park Department of Mechanical Engineering Chonnam National University77 Yongbong-ro Buk-guGwangju 61186Republic of Korea Analytical Engineering Team Samsung Display Co.Ltd.181 Samsung-roTangjeong-myeonAsan-siChungcheongnam-do 31454Republic of Korea

Elasto-inertial microfluidic separation offers many advantages including high throughput and separation *** though the separation efficiency highly depends on precise control of the flow conditions,no concrete guidelines have been reported yet in elasto-inertial ***,we propose a dimensionless analysis for precise estimation of the microsphere behaviors across the interface of Newtonian and viscoelastic *** number,modified Weissenberg number,and modified elastic number are used to investigate the balance between inertial and elastic lift *** on the findings,we introduce a new dimensionless number defined as the width of the Newtonian fluid stream divided by microsphere *** proposed dimensionless analysis allows us to predict whether the microspheres migrate across the co-flow *** theoretical estimation is found to be in good agreement with the experimental results using 2.1-and 3.2-μm-diameter polystyrene microspheres in a co-flow of water and polyethylene oxide *** on the theoretical estimation,we also realize submicron separation of the microspheres with 2.1 and 2.5μm in diameter at high throughput,high purity(>95%),and high recovery rate(>97%).The applicability of the proposed method was validated by separation of platelets from similar-sized Escherichia coli(***).

关键词： solution. separation estimation

Multi-scale modeling for prediction of mechanical performance in brazed GH99 thin-walled structure

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Chinese Journal of Aeronautics 2024年第7期37卷 550-563页

作者： Yazhou LIU Shengpeng HU Yanyu song Wei FU Xiaoguo song Ning GUO Weimin LONG State Key Laboratory of Advanced Welding and Joining Harbin Institute of TechnologyHarbin 150001China Shandong Institute of Shipbuilding Technology Weihai 264209China China Machinery Intelligent Equipment Innovation Research Institute(Ningbo)Co. Ltd.Ningbo 315700China

Superalloy thin-walled structures are achieved mainly by brazing,but the deformation process of brazed joints is non-uniform,making it a challenging research *** paper records a thorough investigation of the effect of brazing parameters on the microstructure of joints and its mechanical properties,which mainly inquires into the deformation and fracture mechanisms in the shearing process of GH99/BNi-5a/GH99 *** macroscopic-microscopic deformation mechanism of the brazing interface during shearing was studied by Crystal Plasticity(CP)and Molecular Dynamics(MD)on the basis of the optimal brazing *** experimental results show that the brazing interface is mainly formed by(Ni,Cr,Co)(s,s)and possesses a shear strength of approximately 546 *** shearing fracture of the brazed joint occurs along the brazing seam,displaying the characteristics of intergranular *** simulations show that dislocations disassociate and transform into fine twinning with increased *** simulated the shear deformation process of the brazed *** multiscale simulation results are consistent with the experimental *** mechanical properties of thin-walled materials for brazing are predicted using MD and CP methods.

关键词： Multi-scale modeling Brazing Shear mechanisms Crystal plasticity GH99 superalloy

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Low profile cavity-embedded ultra-wideband UHF array antenna with end-fire beams

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Journal of Electronic Science and Technology 2024年第2期22卷 24-35页

作者： Huan He Wen-song Wang Southwest China Institute of Electronic Technology Chengdu610036China School of Electrical and Electronic Engineering Department Nanyang Technological UniversitySingapore639798Singapore

A low-profile,vertically polarized,ultra-wideband array antenna with end-fire beams operating in an ultra-high frequency(UHF)band is developed in this *** array antenna consists of 1×16 log-periodic top-hat loaded monopole antenna arrays and is feasible to embed into a shallow cavity to further reduce the array *** is introduced in the proposed antenna element to reduce profile height and the rectangular top hats are carefully designed to minimize the transverse *** results show that when the antenna array operates in a frequency range of 300 MHz-900 MHz,the end-fire radiation pattern achieves±45°scanning range in the horizontal *** prototypes of the proposed end-fire antenna element and a uniformly spaced linear array(1×2)are fabricated and *** end-fire antenna array should be suitable for airborne applications where low-profile and conformal scanning phased antenna arrays with end-fire radiations are *** design is attractive for airborne platform applications that are used to search,discover,identify,and scout the aerial target with vertically polarized beams.

关键词： End-fire radiation Low-profile Vertical polarization Log-periodic array

Type I interferon pathway in pediatric systemic lupus erythematosus

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World Journal of Pediatrics 2024年第7期20卷 653-668页

作者： Yu Zhou Hong‑Mei song Department of Pediatrics Peking Union Medical College HospitalChinese Academy of Medical SciencesBeijingChina State Key Laboratory of Complex Severe and Rare Diseases Peking Union Medical College HospitalBeijingChina

Background The role of type I interferon(IFN-I)signaling in systemic lupus erythematosus(SLE)has been well ***,unanswered questions remain regarding the applicability of these findings to pediatric-onset *** aim of this review is to provide an overview of the novel discoveries on IFN-I signaling in pediatric-onset *** sources A literature search was conducted in the PubMed database using the following keywords:“pediatric systemic lupus erythematosus”and“type I interferon”.Results IFN-I signaling is increased in pediatric SLE,largely due to the presence of plasmacytoid dendritic cells and pathways such as cyclic GMP-AMP synthase–stimulator of interferon genes–TANK-binding kinase 1 and Toll-like receptor(TLR)4/*** extracellular traps and oxidative DNA damage further stimulate IFN-I *** variants in IFN-I-related genes,such as IFN-regulatory factor 5 and tyrosine kinase 2,are linked to SLE susceptibility in pediatric *** addition,type I interferonopathies,characterized by sustained IFN-I activation,can mimic SLE symptoms and are thus important to *** on interferonopathies also contribute to exploring the pathogenesis of *** IFN-I activation is crucial for SLE diagnosis and *** IFNstimulated gene expression and serum IFN-α2 levels are common *** cytometry markers such as CD169 and galectin-9 are promising ***-IFN therapies,such as sifalimumab and anifrolumab,show promise in adult patients with SLE,but their efficacy in pediatric patients requires further *** kinase inhibitors are another treatment option for severe pediatric SLE *** This review presents an overview of the IFN-I pathway in pediatric *** the intricate relationship between IFN-I and pediatric SLE may help to identify potential diagnostic markers and targeted therapies,paving the way for improved patient care and outcomes.

关键词： Interferonopathies Pediatric systemic lupus erythematosus Type I interferon

When debugging encounters artificial intelligence: state of the art and open challenges

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Science China(Information Sciences) 2024年第4期67卷 42-84页

作者： Yi song Xiaoyuan XIE Baowen XU School of Computer Science Wuhan University State Key Laboratory of Novel Software Technology Nanjing University

Both software debugging and artificial intelligence techniques are hot topics in the current field of software engineering. Debugging techniques, which comprise fault localization and program repair, are an important part of the software development lifecycle for ensuring the quality of software systems. As the scale and complexity of software systems grow, developers intend to improve the effectiveness and efficiency of software debugging via artificial intelligence(artificial intelligence for software debugging, AI4SD). On the other hand, many artificial intelligence models are being integrated into safety-critical areas such as autonomous driving, image recognition, and audio processing, where software debugging is highly necessary and urgent(software debugging for artificial intelligence, SD4AI). An AI-enhanced debugging technique could assist in debugging AI systems more effectively, and a more robust and reliable AI approach could further guarantee and support debugging techniques. Therefore, it is important to take AI4SD and SD4AI into consideration comprehensively. In this paper, we want to show readers the path, the trend, and the potential that these two directions interact with each other. We select and review a total of 165 papers in AI4SD and SD4AI for answering three research questions, and further analyze opportunities and challenges as well as suggest future directions of this cross-cutting area.

关键词： software debugging fault localization program repair artificial intelligence machine learning

Constraint Learning-based Optimal Power Dispatch for Active Distribution Networks with Extremely Imbalanced Data

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 51-65页

作者： Yonghua song Ge Chen Hongcai Zhang State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering University of MacaoMacao 999078China School of Electrical and Computer Engineering Purdue UniversityWest LafayetteIN 47907 USA

Transition towards carbon-neutral power systems has necessitated optimization of power dispatch in active distribution networks(ADNs)to facilitate integration of distributed renewable *** to unavailability of network topology and line impedance in many distribution networks,physical model-based methods may not be applicable to their *** tackle this challenge,some studies have proposed constraint learning,which replicates physical models by training a neural network to evaluate feasibility of a decision(i.e.,whether a decision satisfies all critical constraints or not).To ensure accuracy of this trained neural network,training set should contain sufficient feasible and infeasible ***,since ADNs are mostly operated in a normal status,only very few historical samples are ***,the historical dataset is highly imbalanced,which poses a significant obstacle to neural network *** address this issue,we propose an enhanced constraint learning ***,it leverages constraint learning to train a neural network as surrogate of ADN's ***,it introduces Synthetic Minority Oversampling Technique to generate infeasible samples to mitigate imbalance of historical *** incorporating historical and synthetic samples into the training set,we can significantly improve accuracy of neural ***,we establish a trust region to constrain and thereafter enhance reliability of the *** confirm the benefits of the proposed method in achieving desirable optimality and feasibility while maintaining low computational complexity.

关键词： Deep learning demand response distribution networks imbalanced data optimal power flow

A credible traffic prediction method based on self-supervised causal discovery

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Science China(Information Sciences) 2024年第5期67卷 244-258页

作者： Dan WANG Yingjie LIU Bin song State Key Laboratory of Integrated Services Networks Xidian University

Next-generation wireless network aims to support low-latency, high-speed data transmission services by incorporating artificial intelligence(AI) technologies. To fulfill this promise, AI-based network traffic prediction is essential for pre-allocating resources, such as bandwidth and computing power. This can help reduce network congestion and improve the quality of service(QoS) for users. Most studies achieve future traffic prediction by exploiting deep learning and reinforcement learning, to mine spatio-temporal correlated variables. Nevertheless, the prediction results obtained only by the spatio-temporal correlated variables cannot reflect real traffic changes. This phenomenon prevents the true prediction variables from being inferred, making the prediction algorithm perform poorly. Inspired by causal science, we propose a novel network traffic prediction method based on self-supervised spatio-temporal causal discovery(SSTCD). We first introduce the Granger causal discovery algorithm to build a causal graph among prediction variables and obtain spatio-temporal causality in the observed data, which reflects the real reasons affecting traffic ***, a graph neural network(GNN) is adopted to incorporate causality for traffic prediction. Furthermore,we propose a self-supervised method to implement causal discovery to to address the challenge of lacking ground-truth causal graphs in the observed data. Experimental results demonstrate the effectiveness of the SSTCD method.

关键词： wireless network traffic prediction causal discovery self-supervised

A Least-squares-based Iterative Method with Better Convergence for PF/OPF in Integrated Transmission and Distribution Networks

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CSEE Journal of Power and Energy Systems 2024年第3期10卷 953-962页

作者： Kunjie Tang Shufeng Dong Yonghua song College of Electrical Engineering Zhejiang UniversityHangzhou 310027China State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering University of MacaoMacao SARChina IEEE

The limitations of the conventional master-slavesplitting(MSS)method,which is commonly applied to power flow and optimal power flow in integrated transmission and distribution(I-T&D)networks,are first *** that the MSS method suffers from a slow convergence rate or even divergence under some circumstances,a least-squares-based iterative(LSI)method is *** with the MSS method,the LSI method modifies the iterative variables in each iteration by solving a least-squares problem with the information in previous iterations.A practical implementation and a parameter tuning strategy for the LSI method are ***,a LSI-PF method is proposed to solve I-T&D power flow and a LSIheterogeneous decomposition(LSI-HGD)method is proposed to solve optimal power *** experiments demonstrate that the proposed LSI-PF and LSI-HGD methods can achieve the same accuracy as the benchmark ***,these LSI methods,with appropriate settings,significantly enhance the convergence and efficiency of conventional ***,in some cases,where conventional methods diverge,these LSI methods can still converge.

关键词： Fixed-point theory integrated transmission and distribution networks least-squares-based iterative method master-slave-splitting method optimal power flow power flow

Multiscale feature learning and attention mechanism for infrared and visible image fusion

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Science China(Technological Sciences) 2024年第2期67卷 408-422页

作者： GAO Li LUO DeLin WANG song School of Aerospace Engineering Xiamen UniversityXiamen 361102China Electric Power Research Institute China Southern Power GridGuangzhou 510063China

Current fusion methods for infrared and visible images tend to extract features at a single scale,which results in insufficient detail and incomplete feature *** address these issues,we propose an infrared and visible image fusion network based on a multiscale feature learning and attention mechanism(MsAFusion).A multiscale dilation convolution framework is employed to capture image features across various scales and broaden the perceptual ***,an attention network is introduced to enhance the focus on salient targets in infrared images and detailed textures in visible *** compensate for information loss during convolution,jump connections are utilized during the image reconstruction *** fusion process utilizes a combined loss function consisting of pixel loss and gradient loss for unsupervised fusion of infrared and visible *** experiments on the dataset of electricity facilities demonstrate that our proposed method outperforms nine state-of-theart methods in terms of visual perception and four objective evaluation metrics.

关键词： infrared and visible images image fusion attention mechanism CNN feature extraction

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