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Deep learning to develop zero-equation based turbulence model for CFD simulations of the built environment

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Building Simulation 2024年第3期17卷 399-414页

作者： Giovanni Calzolari Wei liu Division of Sustainable Buildings Department of Civil and Architectural EngineeringKTH Royal Institute of TechnologyBrinnelvägen 23Stockholm11428Sweden

This study aims to improve the accuracy and speed of predictions for thermal comfort and air quality in built environments by creating a coupled framework between computational fluid dynamics(CFD)simulations and deep learning *** coupling approach is showcased by the development of a data-driven turbulence *** new turbulence model is built using a deep learning neural network,whose mapping structure is based on a zero-equation turbulence model for built environment simulations,and is coupled with the CFD software OpenFOAM to create a hybrid *** neural network is a standard shallow multi-layer *** number of hidden layers and nodes per layer was optimized using Bayesan optimization *** framework is trained on an indoor environment case study,as well as tested on an indoor office simulation and an outdoor building array *** show that the deep learning based turbulence model is more robust and faster than traditional two-equation Reynolds average Navier-Stokes(RANS)turbulence models,while maintaining a similar level of *** model also outperforms the standard algebraic zero-equation model due to its superior ability to generalize to various flow *** some challenges,namely the mapping constraint,the limited training dataset size and the source of generation of training data,the hybrid framework demonstrates the viability of the coupling technique and serves as a starting point for future development of more reliable and advanced models.

关键词： neural networks computational fluid dynamics(CFD) turbulence model OpenFOAM

MRm-DLDet:a memory-resident malware detection framework based on memory forensics and deep neural network

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Cybersecurity 2024年第1期7卷 88-109页

作者： Jiaxi liu Yun Feng Xinyu liu Jianjun Zhao Qixu liu Institute of Information Engineering Chinese Academy of SciencesBeijing 100085China School of Cyber Security University of Chinese Academy of SciencesBeijing 100049China

Cyber attackers have constantly updated their attack techniques to evade antivirus software detection in recent *** popular evasion method is to execute malicious code and perform malicious actions only in ***-cious programs that use this attack method are called memory-resident malware,with excellent evasion capability,and have posed huge threats to cyber *** static and dynamic methods are not effective in detect-ing memory-resident *** addition,existing memory forensics detection solutions perform unsatisfactorily in detection rate and depend on massive expert knowledge in memory *** paper proposes MRm-DLDet,a state-of-the-art memory-resident malware detection framework,to overcome these ***-DLDet first builds a virtual machine environment and captures memory dumps,then creatively processes the memory dumps into RGB images using a pre-processing technique that combines deduplication and ultra-high resolution image cropping,followed by our neural network MRmNet in MRm-DLDet to fully extract high-dimensional features from memory dump files and detect *** receives the labeled sub-images of the cropped high-resolution RGB images as input of ResNet-18,which extracts the features of the *** trains a network of gated recurrent units with an attention ***,it determines whether a program is memory-resident malware based on the detection results of each sub-image through a specially designed voting *** created a high-quality dataset consisting of 2,060 benign and memory-resident *** other words,the dataset contains 1,287,500 labeled sub-images cut from the MRm-DLDet transformed ultra-high resolution RGB *** implement MRm-DLDet for Windows 10,and it performs better than the latest methods,with a detection accuracy of up to 98.34%.Moreover,we measured the effects of mimicry and adversarial attacks on MRm-DLDet,and the experimental results demonstrated the robustness

关键词： Memory-resident malware Memory forensics Malware detection Deep learning Ultra-high resolution image

A study on vector mediator top-philic dark matter

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Communications in Theoretical Physics 2024年第8期76卷 67-78页

作者： Yanyan Hu Yandong liu Yuanyuan liu College of Nuclear Science and Technology Beijing Normal UniversityJoint Laboratory of Jinping Ultra-low Radiation Background Measurement of Ministry of Ecology and EnvironmentJinping Deep Underground Frontier Science and Dark Matter Key Laboratory of Sichuan ProvinceKey Laboratory of Beam Technology of Ministry of EducationBeijing 100875China Beijing Radiation Center Beijing 100875China

We conducted a study on a simplified dark matter model that introduces a vector-like intermediate particle,facilitating exclusive interactions between dark matter and the top quark in the Standard *** analysis focused on the relic density of Dirac-type fermion dark matter and highlighted the complementary role of direct detection in constraining the dark matter ***,in instances when dark matter mass is small,the tree-level two-body annihilation process experiences *** such scenarios,the contributions of the threebody process(χχ→tbW-)and the one-loop process(χχ→gg)dominate the relic *** regard to direct detection,calculations were performed for the two-loop contribution to the dark-matter-gluon interaction,yielding the corresponding spin-independent scattering cross section.

关键词： dark matter new physics effective field theory

Modeling urban scale human mobility through big data analysis and machinelearning

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Building Simulation 2024年第1期17卷 3-21页

作者： Yapan liu Bing Dong Department of Mechanical&Aerospace Engineering Syracuse University263 Link HallSyracuseNY 13244USA

In the United States,the buildings sector consumes about 76%of electricity use and 40% of all primary energy use and associated greenhouse gas *** behavior has drawn increasing research interests due to its impacts on the building energy ***,occupant behavior study at urban scale remains a challenge,and very limited studies have been *** an effort to couple big data analysis with human mobility modeling,this study has explored urban scale human mobility utilizing three months Global Positioning System(GPS)data of 93,o00 users at Phoenix Metropolitan *** research extracted stay points from raw data,and identified users'home,work,and other locations by Density-Based Spatial Clustering ***,daily mobility patterns were constructed using different types of *** propose a novel approach to predict urban scale daily human mobility patterns with 12-hour prediction horizon,using Long Short-Term Memory(LSTM)neural network *** shows the developed models achieved around 85%average accuracy and about 86%mean *** developed models can be further applied to analyze urban scale occupant behavior,building energy demand and flexibility,and contributed to urban planning.

关键词： urban human mobility big data analysis urban scale occupant behavior recurrent neural networks

Needs and challenges of optical atmospheric monitoring on the background of carbon neutrality in China

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Frontiers of Environmental Science & Engineering 2024年第6期18卷 49-62页

作者： Wenqing liu Chengzhi Xing Anhui Institute of Optics and Fine Mechanics Hefei Institutes of Physical ScienceChinese Academy of SciencesHefei 23001China

The achievement of the targets of coordinated control of PM2.5 and O3 and the carbon peaking and carbon neutrality depend on the development of pollution and greenhouse gas monitoring *** monitoring technology,based on its technical characteristics of high scalability,high sensitivity and wide-targets detection,has obvious advantages in pollution/greenhouse gases monitoring and has become an important direction in the development of environmental monitoring *** present,a system of environmental optical monitoring technology with differential optical absorption spectroscopy(DOAS),cavity ring-down spectroscopy(CRDS),light detection and ranging(LIDAR),laser heterodyne spectroscopy(LHS),tunable diode laser absorption spectroscopy(TDLAS),fourier transform infrared spectroscopy(FTIR)and fluorescence assay by gas expansion(FAGE)as the main body has been ***,with the promotion of“reduction of pollution and carbon emissions”strategy,there have been significant changes in the sources of pollution/greenhouse gases,emission components and emission concentrations,which have put forward new and higher requirements for the development of monitoring *** the future,we should pay more attention to the development of new optical monitoring techniques and the construction of stereoscopic monitoring system,the interdisciplinarity(among mathematics,physics,chemistry and biology,etc.),and the monitoring of greenhouse gases and research on atmospheric chemistry.

关键词： Pollution Greenhouse gas Optical atmospheric monitoring Needs and challenges

Uniform decomposition of velocity gradient tensor

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Journal of Hydrodynamics 2024年第1期36卷 24-34页

作者： Chenxi Ma Chaoqun liu Department of Mathematics University of Texas at ArlingtonArlingtonTXUSA

In this paper,the principal decomposition of the velocity gradient tensor[∇v]is discussed in 3 cases based on the discriminant∆:∆0 with 3 distinct real eigen values,and∆=0 with 1 or 2 distinct real eigen *** velocity gradient tensor can also be classified as rotation point,which can be decomposed into three parts,i.e.,rotation[R],shear[S]and stretching/compression[SC],and non-rotation point,we defined a new resistance term[L],and the tensor can be decomposed into three parts,i.e.,resistance[L],shear[S]and stretching/compression[SC].Example matric are also displayed to demonstrate the new *** of principal decomposition between 3 different cases,and between Resistance and liutex will also be discussed.

关键词： Velocity gradient liutex resistance fluid kinematics

Hydrogen and nitrogen absorption properties of Ce-added Zr_(2)(Fe_(1-x)Ni_(x)) alloys

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Journal of Rare Earths 2024年第6期42卷 1136-1141,I0005页

作者： Kai Yin Xiaopeng liu State Key Laboratory of Advanced Materials for Smart Sensing GRINM Group Co.Ltd.Beijing10088China GRIMAT Engineering Institute Co. Ltd.Beijing101407China General Research Institute of Nonferrous Metals Beijing100088China

To improve the nitriding resistance of Zr_(2)Fe alloy,the Ce-added Zr_(2)(Fe_(1-x)Ni_(x))(x=0,0.15,0.3,0.5)alloys were prepared by magnetic levitation melting *** effects of Ni substitution for Fe on the phase structure,hydrogen and nitrogen absorption properties of the alloys were investigated by X-ray diffraction,scanning electron microscopy and p-c isotherm *** experimental results show that Ni substitution can effectively inhibit the formation of both α-Zr and ZrFe_(2) phases and promote the formation of C16 structure Zr_(2)(Fe,Ni)phase,causing Ni-substituted alloys to exhibit low nitrogen absorption rate and *** 623 K under 0.5 MPa nitrogen pressure,the nitrogen absorption capacity of Ce-added Zr_(2)(Fe_(0.5)Ni_(0.5))alloy reaches to 0.8 mL/g,much lower than that of Zr_(2)Fe alloy(1.5 mL/g).Ni substitution decreases the crystal cell volume of the C_(16)Zr_(2)(Fe,Ni)phase,resulting in an increase in the hydrogen absorption equilibrium *** 623 K under 0.05 MPa hydrogen pressure,the hydrogen absorption capacity decreases from 1.46 wt%of Zr_(2)Fe alloy to 1.41 wt%of Ce-added Zr_(2)(Fe_(0.5)Ni_(0.5))alloy.

关键词： Zr_(2)Fe alloy Ce Pressure-composition isotherm Hydrogen absorption Nitrogen absorption Rare earths

An Industrial Intrusion Detection Method Based on Hybrid Convolutional Neural Networks with Improved TCN

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Computers, Materials & Continua 2024年第1期78卷 411-433页

作者： Zhihua liu Shengquan liu Jian Zhang College of Computer Science and Technology Xinjiang UniversityXinjiang Uygur Autonomous RegoinUrumqi830000China

Network intrusion detection systems(NIDS)based on deep learning have continued to make significant ***,the following challenges remain:on the one hand,simply applying only Temporal Convolutional Networks(TCNs)can lead to models that ignore the impact of network traffic features at different scales on the detection *** the other hand,some intrusion detection methods considermulti-scale information of traffic data,but considering only forward network traffic information can lead to deficiencies in capturing multi-scale temporal *** address both of these issues,we propose a hybrid Convolutional Neural Network that supports a multi-output strategy(BONUS)for industrial internet intrusion ***,we create a multiscale Temporal Convolutional Network by stacking TCN of different scales to capture the multiscale information of network ***,we propose a bi-directional structure and dynamically set the weights to fuse the forward and backward contextual information of network traffic at each scale to enhance the model’s performance in capturing the multi-scale temporal features of network *** addition,we introduce a gated network for each of the two branches in the proposed method to assist the model in learning the feature representation of each *** experiments reveal the effectiveness of the proposed approach on two publicly available traffic intrusion detection datasets named UNSW-NB15 and NSL-KDD with F1 score of 85.03% and 99.31%,respectively,which also validates the effectiveness of enhancing the model’s ability to capture multi-scale temporal features of traffic data on detection performance.

关键词： Intrusion detection industrial internet channel spatial attention multiscale features dynamic fusion multi-output learning strategy

Recent Progress of Bionic Hierarchical Structure in the Field of Thermal Insulation Protection

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Journal of Bionic Engineering 2024年第1期21卷 1-18页

作者： Yina Zhuge Fujuan liu National Engineering Laboratory for Modern Silk College of Textile and Clothing EngineeringSoochow UniversitySuzhou 215123China

Some living organisms with hierarchical structures in nature have received extensive attention in various *** hierarchical structure with multiple pores,a large number of solid-gas interfaces and tortuous conduction paths provide a new direction for the development of thermal insulation materials,making the living creatures under these extreme conditions become the bionic objects of scientific *** this review,the research progress of bionic hierarchical structure in the field of heat insulation is *** bears,cocoons,penguin feathers and wool are typical examples of heat preservation hierarchy in nature to introduce their morphological *** the same time,the thermal insulation mechanism,fractal model and several preparation methods of bionic hierarchical structures are emphatically *** application of hierarchical structures in various fields,especially in thermal insulation and infrared thermal stealth,is ***,the hierarchical structure is prospected.

关键词： Hierarchical structure Bionic Heat insulation Fractal model Cocoons