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Computational Experiments for Complex Social Systems:Experiment Design and Generative Explanation 被引量:2
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作者 Xiao Xue Deyu Zhou +5 位作者 Xiangning Yu Gang Wang Juanjuan Li Xia Xie Lizhen Cui Fei-Yue Wang 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第4期1022-1038,共17页
Powered by advanced information technology,more and more complex systems are exhibiting characteristics of the cyber-physical-social systems(CPSS).In this context,computational experiments method has emerged as a nove... Powered by advanced information technology,more and more complex systems are exhibiting characteristics of the cyber-physical-social systems(CPSS).In this context,computational experiments method has emerged as a novel approach for the design,analysis,management,control,and integration of CPSS,which can realize the causal analysis of complex systems by means of“algorithmization”of“counterfactuals”.However,because CPSS involve human and social factors(e.g.,autonomy,initiative,and sociality),it is difficult for traditional design of experiment(DOE)methods to achieve the generative explanation of system emergence.To address this challenge,this paper proposes an integrated approach to the design of computational experiments,incorporating three key modules:1)Descriptive module:Determining the influencing factors and response variables of the system by means of the modeling of an artificial society;2)Interpretative module:Selecting factorial experimental design solution to identify the relationship between influencing factors and macro phenomena;3)Predictive module:Building a meta-model that is equivalent to artificial society to explore its operating laws.Finally,a case study of crowd-sourcing platforms is presented to illustrate the application process and effectiveness of the proposed approach,which can reveal the social impact of algorithmic behavior on“rider race”. 展开更多
关键词 Agent-based modeling computational experiments cyber-physical-social systems(CPSS) generative deduction generative experiments meta model
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From the perspective of experimental practice: High-throughput computational screening in photocatalysis
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作者 Yunxuan Zhao Junyu Gao +2 位作者 Xuanang Bian Han Tang Tierui Zhang 《Green Energy & Environment》 SCIE EI CAS CSCD 2024年第1期1-6,共6页
Photocatalysis,a critical strategy for harvesting sunlight to address energy demand and environmental concerns,is underpinned by the discovery of high-performance photocatalysts,thereby how to design photocatalysts is... Photocatalysis,a critical strategy for harvesting sunlight to address energy demand and environmental concerns,is underpinned by the discovery of high-performance photocatalysts,thereby how to design photocatalysts is now generating widespread interest in boosting the conversion effi-ciency of solar energy.In the past decade,computational technologies and theoretical simulations have led to a major leap in the development of high-throughput computational screening strategies for novel high-efficiency photocatalysts.In this viewpoint,we started with introducing the challenges of photocatalysis from the view of experimental practice,especially the inefficiency of the traditional“trial and error”method.Sub-sequently,a cross-sectional comparison between experimental and high-throughput computational screening for photocatalysis is presented and discussed in detail.On the basis of the current experimental progress in photocatalysis,we also exemplified the various challenges associated with high-throughput computational screening strategies.Finally,we offered a preferred high-throughput computational screening procedure for pho-tocatalysts from an experimental practice perspective(model construction and screening,standardized experiments,assessment and revision),with the aim of a better correlation of high-throughput simulations and experimental practices,motivating to search for better descriptors. 展开更多
关键词 PHOTOCATALYSIS High-throughput computational screening PHOTOCATALYST Theoretical simulations Experiments
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Effect of solvent on the initiation mechanism of living anionic polymerization of styrene:A computational study
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作者 Shen Li Yin-Ning Zhou +1 位作者 Zhong-Xin Liu Zheng-Hong Luo 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2024年第5期135-142,共8页
For living anionic polymerization(LAP),solvent has a great influence on both reaction mechanism and kinetics.In this work,by using the classical butyl lithium-styrene polymerization as a model system,the effect of sol... For living anionic polymerization(LAP),solvent has a great influence on both reaction mechanism and kinetics.In this work,by using the classical butyl lithium-styrene polymerization as a model system,the effect of solvent on the mechanism and kinetics of LAP was revealed through a strategy combining density functional theory(DFT)calculations and kinetic modeling.In terms of mechanism,it is found that the stronger the solvent polarity,the more electrons transfer from initiator to solvent through detailed energy decomposition analysis of electrostatic interactions between initiator and solvent molecules.Furthermore,we also found that the stronger the solvent polarity,the higher the monomer initiation energy barrier and the smaller the initiation rate coefficient.Counterintuitively,initiation is more favorable at lower temperatures based on the calculated results ofΔG_(TS).Finally,the kinetic characteristics in different solvents were further examined by kinetic modeling.It is found that in benzene and n-pentane,the polymerization rate exhibits first-order kinetics.While,slow initiation and fast propagation were observed in tetrahydrofuran(THF)due to the slow free ion formation rate,leading to a deviation from first-order kinetics. 展开更多
关键词 Living anionic polymerization Solvent effect Reaction kinetics computational chemistry Mathematical modeling Kinetic modeling
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Computational fluid dynamics modeling of rapid pyrolysis of solid waste magnesium nitrate hydrate under different injection methods
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作者 Wenchang Wu Kefan Yu +1 位作者 Liang Zhao Hui Dong 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2024年第2期224-237,共14页
This study developed a numerical model to efficiently treat solid waste magnesium nitrate hydrate through multi-step chemical reactions.The model simulates two-phase flow,heat,and mass transfer processes in a pyrolysi... This study developed a numerical model to efficiently treat solid waste magnesium nitrate hydrate through multi-step chemical reactions.The model simulates two-phase flow,heat,and mass transfer processes in a pyrolysis furnace to improve the decomposition rate of magnesium nitrate.The performance of multi-nozzle and single-nozzle injection methods was evaluated,and the effects of primary and secondary nozzle flow ratios,velocity ratios,and secondary nozzle inclination angles on the decomposition rate were investigated.Results indicate that multi-nozzle injection has a higher conversion efficiency and decomposition rate than single-nozzle injection,with a 10.3%higher conversion rate under the design parameters.The decomposition rate is primarily dependent on the average residence time of particles,which can be increased by decreasing flow rate and velocity ratios and increasing the inclination angle of secondary nozzles.The optimal parameters are injection flow ratio of 40%,injection velocity ratio of 0.6,and secondary nozzle inclination of 30°,corresponding to a maximum decomposition rate of 99.33%. 展开更多
关键词 MULTI-NOZZLE computational fluid dynamics Thermal decomposition reaction Pyrolysis furnace
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Computational Fluid Dynamics Approach for Predicting Pipeline Response to Various Blast Scenarios: A Numerical Modeling Study
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作者 Farman Saifi Mohd Javaid +1 位作者 Abid Haleem S.M.Anas 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第9期2747-2777,共31页
Recent industrial explosions globally have intensified the focus in mechanical engineering on designing infras-tructure systems and networks capable of withstanding blast loading.Initially centered on high-profile fac... Recent industrial explosions globally have intensified the focus in mechanical engineering on designing infras-tructure systems and networks capable of withstanding blast loading.Initially centered on high-profile facilities such as embassies and petrochemical plants,this concern now extends to a wider array of infrastructures and facilities.Engineers and scholars increasingly prioritize structural safety against explosions,particularly to prevent disproportionate collapse and damage to nearby structures.Urbanization has further amplified the reliance on oil and gas pipelines,making them vital for urban life and prime targets for terrorist activities.Consequently,there is a growing imperative for computational engineering solutions to tackle blast loading on pipelines and mitigate associated risks to avert disasters.In this study,an empty pipe model was successfully validated under contact blast conditions using Abaqus software,a powerful tool in mechanical engineering for simulating blast effects on buried pipelines.Employing a Eulerian-Lagrangian computational fluid dynamics approach,the investigation extended to above-surface and below-surface blasts at standoff distances of 25 and 50 mm.Material descriptions in the numerical model relied on Abaqus’default mechanical models.Comparative analysis revealed varying pipe performance,with deformation decreasing as explosion-to-pipe distance increased.The explosion’s location relative to the pipe surface notably influenced deformation levels,a key finding highlighted in the study.Moreover,quantitative findings indicated varying ratios of plastic dissipation energy(PDE)for different blast scenarios compared to the contact blast(P0).Specifically,P1(25 mm subsurface blast)and P2(50 mm subsurface blast)showed approximately 24.07%and 14.77%of P0’s PDE,respectively,while P3(25 mm above-surface blast)and P4(50 mm above-surface blast)exhibited lower PDE values,accounting for about 18.08%and 9.67%of P0’s PDE,respectively.Utilising energy-absorbing materials such as thin coatings of ultra-high-strength concrete,metallic foams,carbon fiber-reinforced polymer wraps,and others on the pipeline to effectively mitigate blast damage is recommended.This research contributes to the advancement of mechanical engineering by providing insights and solutions crucial for enhancing the resilience and safety of underground pipelines in the face of blast events. 展开更多
关键词 Blast loading computational fluid dynamics computer modeling pipe networks response prediction structural safety
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Numerical Analysis of Bacterial Meningitis Stochastic Delayed Epidemic Model through Computational Methods
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作者 Umar Shafique Mohamed Mahyoub Al-Shamiri +3 位作者 Ali Raza Emad Fadhal Muhammad Rafiq Nauman Ahmed 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第10期311-329,共19页
Based on theWorld Health Organization(WHO),Meningitis is a severe infection of the meninges,the membranes covering the brain and spinal cord.It is a devastating disease and remains a significant public health challeng... Based on theWorld Health Organization(WHO),Meningitis is a severe infection of the meninges,the membranes covering the brain and spinal cord.It is a devastating disease and remains a significant public health challenge.This study investigates a bacterial meningitis model through deterministic and stochastic versions.Four-compartment population dynamics explain the concept,particularly the susceptible population,carrier,infected,and recovered.The model predicts the nonnegative equilibrium points and reproduction number,i.e.,the Meningitis-Free Equilibrium(MFE),and Meningitis-Existing Equilibrium(MEE).For the stochastic version of the existing deterministicmodel,the twomethodologies studied are transition probabilities and non-parametric perturbations.Also,positivity,boundedness,extinction,and disease persistence are studiedrigorouslywiththe helpofwell-known theorems.Standard and nonstandard techniques such as EulerMaruyama,stochastic Euler,stochastic Runge Kutta,and stochastic nonstandard finite difference in the sense of delay have been presented for computational analysis of the stochastic model.Unfortunately,standard methods fail to restore the biological properties of the model,so the stochastic nonstandard finite difference approximation is offered as an efficient,low-cost,and independent of time step size.In addition,the convergence,local,and global stability around the equilibria of the nonstandard computational method is studied by assuming the perturbation effect is zero.The simulations and comparison of the methods are presented to support the theoretical results and for the best visualization of results. 展开更多
关键词 Bacterial Meningitis disease stochastic delayed model stability analysis extinction and persistence computational methods
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Outage Analysis of Optimal UAV Cooperation with IRS via Energy Harvesting Enhancement Assisted Computational Offloading
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作者 Baofeng Ji Ying Wang +2 位作者 Weixing Wang Shahid Mumtaz Charalampos Tsimenidis 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第2期1885-1905,共21页
The utilization of mobile edge computing(MEC)for unmanned aerial vehicle(UAV)communication presents a viable solution for achieving high reliability and low latency communication.This study explores the potential of e... The utilization of mobile edge computing(MEC)for unmanned aerial vehicle(UAV)communication presents a viable solution for achieving high reliability and low latency communication.This study explores the potential of employing intelligent reflective surfaces(IRS)andUAVs as relay nodes to efficiently offload user computing tasks to theMEC server system model.Specifically,the user node accesses the primary user spectrum,while adhering to the constraint of satisfying the primary user peak interference power.Furthermore,the UAV acquires energy without interrupting the primary user’s regular communication by employing two energy harvesting schemes,namely time switching(TS)and power splitting(PS).The selection of the optimal UAV is based on the maximization of the instantaneous signal-to-noise ratio.Subsequently,the analytical expression for the outage probability of the system in Rayleigh channels is derived and analyzed.The study investigates the impact of various system parameters,including the number of UAVs,peak interference power,TS,and PS factors,on the system’s outage performance through simulation.The proposed system is also compared to two conventional benchmark schemes:the optimal UAV link transmission and the IRS link transmission.The simulation results validate the theoretical derivation and demonstrate the superiority of the proposed scheme over the benchmark schemes. 展开更多
关键词 Unmanned aerial vehicle(UAV) intelligent reflective surface(IRS) energy harvesting computational offloading outage probability
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Computational intelligence interception guidance law using online off-policy integral reinforcement learning
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作者 WANG Qi LIAO Zhizhong 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2024年第4期1042-1052,共11页
Missile interception problem can be regarded as a two-person zero-sum differential games problem,which depends on the solution of Hamilton-Jacobi-Isaacs(HJI)equa-tion.It has been proved impossible to obtain a closed-f... Missile interception problem can be regarded as a two-person zero-sum differential games problem,which depends on the solution of Hamilton-Jacobi-Isaacs(HJI)equa-tion.It has been proved impossible to obtain a closed-form solu-tion due to the nonlinearity of HJI equation,and many iterative algorithms are proposed to solve the HJI equation.Simultane-ous policy updating algorithm(SPUA)is an effective algorithm for solving HJI equation,but it is an on-policy integral reinforce-ment learning(IRL).For online implementation of SPUA,the dis-turbance signals need to be adjustable,which is unrealistic.In this paper,an off-policy IRL algorithm based on SPUA is pro-posed without making use of any knowledge of the systems dynamics.Then,a neural-network based online adaptive critic implementation scheme of the off-policy IRL algorithm is pre-sented.Based on the online off-policy IRL method,a computa-tional intelligence interception guidance(CIIG)law is developed for intercepting high-maneuvering target.As a model-free method,intercepting targets can be achieved through measur-ing system data online.The effectiveness of the CIIG is verified through two missile and target engagement scenarios. 展开更多
关键词 two-person zero-sum differential games Hamilton–Jacobi–Isaacs(HJI)equation off-policy integral reinforcement learning(IRL) online learning computational intelligence inter-ception guidance(CIIG)law
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End-to-end computational design for an EUV solar corona multispectral imager with stray light suppression
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作者 Jinming Gao Yue Sun +6 位作者 Yinxu Bian Jilong Peng Qian Yu Cuifang Kuang Xiangzhao Wang Xu Liu Xiangqun Cui 《Astronomical Techniques and Instruments》 CSCD 2024年第1期31-41,共11页
An extreme ultraviolet solar corona multispectral imager can allow direct observation of high temperature coronal plasma,which is related to solar flares,coronal mass ejections and other significant coronal activities... An extreme ultraviolet solar corona multispectral imager can allow direct observation of high temperature coronal plasma,which is related to solar flares,coronal mass ejections and other significant coronal activities.This manuscript proposes a novel end-to-end computational design method for an extreme ultraviolet(EUV)solar corona multispectral imager operating at wavelengths near 100 nm,including a stray light suppression design and computational image recovery.To suppress the strong stray light from the solar disk,an outer opto-mechanical structure is designed to protect the imaging component of the system.Considering the low reflectivity(less than 70%)and strong-scattering(roughness)of existing extreme ultraviolet optical elements,the imaging component comprises only a primary mirror and a curved grating.A Lyot aperture is used to further suppress any residual stray light.Finally,a deep learning computational imaging method is used to correct the individual multi-wavelength images from the original recorded multi-slit data.In results and data,this can achieve a far-field angular resolution below 7",and spectral resolution below 0.05 nm.The field of view is±3 R_(☉)along the multi-slit moving direction,where R☉represents the radius of the solar disk.The ratio of the corona's stray light intensity to the solar center's irradiation intensity is less than 10-6 at the circle of 1.3 R_(☉). 展开更多
关键词 EUV solar corona imager Curved grating Stray light suppression computational multispectral imaging
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Integration between Genomic and Computational Statistical Surveys for the Screening of SNP Genetic Variants in Inflammatory Bowel Disease (IBD) Pediatric Patients*
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作者 Dago Dougba Noel Koffi N’Guessan Bénédicte Sonia +8 位作者 Dagnogo Olefongo Daramcoum Wentoin Alimata Marie-Pierre Mauro Giacomelli Dagnogo Dramane Eboulé Ago Eliane Rebecca Yao Saraka Didier Martial Diarrassouba Nafan Giovanni Malerba Raffaele Badolato 《Computational Molecular Bioscience》 2024年第3期146-191,共46页
Inflammatory bowel diseases (IBD) are complex multifactorial disorders that include Crohn’s disease (CD) and ulcerative colitis (UC). Considering that IBD is a genetic and multifactorial disease, we screened for the ... Inflammatory bowel diseases (IBD) are complex multifactorial disorders that include Crohn’s disease (CD) and ulcerative colitis (UC). Considering that IBD is a genetic and multifactorial disease, we screened for the distribution dynamism of IBD pathogenic genetic variants (single nucleotide polymorphisms;SNPs) and risk factors in four (4) IBD pediatric patients, by integrating both clinical exome sequencing and computational statistical approaches, aiming to categorize IBD patients in CD and UC phenotype. To this end, we first aligned genomic read sequences of these IBD patients to hg19 human genome by using bowtie 2 package. Next, we performed genetic variant calling analysis in terms of single nucleotide polymorphism (SNP) for genes covered by at least 20 read genomic sequences. Finally, we checked for biological and genomic functions of genes exhibiting statistically significant genetic variant (SNPs) by introducing Fitcon genomic parameter. Findings showed Fitcon parameter as normalizing IBD patient’s population variability, as well as inducing a relative good clustering between IBD patients in terms of CD and UC phenotypes. Genomic analysis revealed a random distribution of risk factors and as well pathogenic SNPs genetic variants in the four IBD patient’s genome, claiming to be involved in: i) Metabolic disorders, ii) Autoimmune deficiencies;iii) Crohn’s disease pathways. Integration of genomic and computational statistical analysis supported a relative genetic variability regarding IBD patient population by processing IBD pathogenic SNP genetic variants as opposite to IBD risk factor variants. Interestingly, findings clearly allowed categorizing IBD patients in CD and UC phenotypes by applying Fitcon parameter in selecting IBD pathogenic genetic variants. Considering as a whole, the study suggested the efficiency of integrating clinical exome sequencing and computational statistical tools as a right approach in discriminating IBD phenotypes as well as improving inflammatory bowel disease (IBD) molecular diagnostic process. 展开更多
关键词 Inflammatory Bowel Disease (IBD) Crohn Disease (CD) Ulcerative Colitis (UC) Clinical Exome Analysis computational Statistic SNP Genetic Variants
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Reform and Practice of the Course“Introduction to Computer Science”in Universities Based on the Cultivation of Computational Thinking and Systematic Abilities
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作者 Kun Zhang Zhengjie Deng +2 位作者 Qi Peng Jinyang Zhou Fuyun Li 《Journal of Contemporary Educational Research》 2024年第7期197-203,共7页
Introduction to Computer Science,as one of the fundamental courses in computer-related majors,plays an important role in the cultivation of computer professionals.However,traditional teaching models and content can no... Introduction to Computer Science,as one of the fundamental courses in computer-related majors,plays an important role in the cultivation of computer professionals.However,traditional teaching models and content can no longer fully meet the needs of modern information technology development.In response to these issues,this article introduces the concept of computational creative thinking,optimizes course content,adopts exploratory teaching methods,and innovates course assessment methods,aiming to comprehensively enhance students’computational thinking and innovative abilities.By continuously improving and promoting this teaching model,it will undoubtedly promote computer education in universities to a new level. 展开更多
关键词 Introduction to Computer Science Curriculum reform computational thinking PRACTICE
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Research on the Assessment System of Computational Mechanics Courses Based on the TOPSIS Entropy Weight Model
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作者 Huijun Ning Ruhuan Yu +1 位作者 Qianshu Wang Mingming Lin 《Journal of Contemporary Educational Research》 2024年第6期166-182,共17页
This paper takes the assessment and evaluation of computational mechanics course as the background,and constructs a diversified course evaluation system that is student-centered and integrates both quantitative and qu... This paper takes the assessment and evaluation of computational mechanics course as the background,and constructs a diversified course evaluation system that is student-centered and integrates both quantitative and qualitative evaluation methods.The system not only pays attention to students’practical operation and theoretical knowledge mastery but also puts special emphasis on the cultivation of students’innovative abilities.In order to realize a comprehensive and objective evaluation,the assessment and evaluation method of the entropy weight model combining TOPSIS(Technique for Order Preference by Similarity to Ideal Solution)multi-attribute decision analysis and entropy weight theory is adopted,and its validity and practicability are verified through example analysis.This method can not only comprehensively and objectively evaluate students’learning outcomes,but also provide a scientific decision-making basis for curriculum teaching reform.The implementation of this diversified course evaluation system can better reflect the comprehensive ability of students and promote the continuous improvement of teaching quality. 展开更多
关键词 TOPSIS entropy weight model computational mechanics Course assessment and evaluation system Assessment model
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A fast forward computational method for nuclear measurement using volumetric detection constraints
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作者 Qiong Zhang Lin-Lv Lin 《Nuclear Science and Techniques》 SCIE EI CAS CSCD 2024年第2期47-63,共17页
Owing to the complex lithology of unconventional reservoirs,field interpreters usually need to provide a basis for interpretation using logging simulation models.Among the various detection tools that use nuclear sour... Owing to the complex lithology of unconventional reservoirs,field interpreters usually need to provide a basis for interpretation using logging simulation models.Among the various detection tools that use nuclear sources,the detector response can reflect various types of information of the medium.The Monte Carlo method is one of the primary methods used to obtain nuclear detection responses in complex environments.However,this requires a computational process with extensive random sampling,consumes considerable resources,and does not provide real-time response results.Therefore,a novel fast forward computational method(FFCM)for nuclear measurement that uses volumetric detection constraints to rapidly calculate the detector response in various complex environments is proposed.First,the data library required for the FFCM is built by collecting the detection volume,detector counts,and flux sensitivity functions through a Monte Carlo simulation.Then,based on perturbation theory and the Rytov approximation,a model for the detector response is derived using the flux sensitivity function method and a one-group diffusion model.The environmental perturbation is constrained to optimize the model according to the tool structure and the impact of the formation and borehole within the effective detection volume.Finally,the method is applied to a neutron porosity tool for verification.In various complex simulation environments,the maximum relative error between the calculated porosity results of Monte Carlo and FFCM was 6.80%,with a rootmean-square error of 0.62 p.u.In field well applications,the formation porosity model obtained using FFCM was in good agreement with the model obtained by interpreters,which demonstrates the validity and accuracy of the proposed method. 展开更多
关键词 Nuclear measurement Fast forward computation Volumetric constraints
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Two-Stage IoT Computational Task Offloading Decision-Making in MEC with Request Holding and Dynamic Eviction
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作者 Dayong Wang Kamalrulnizam Bin Abu Bakar Babangida Isyaku 《Computers, Materials & Continua》 SCIE EI 2024年第8期2065-2080,共16页
The rapid development of Internet of Things(IoT)technology has led to a significant increase in the computational task load of Terminal Devices(TDs).TDs reduce response latency and energy consumption with the support ... The rapid development of Internet of Things(IoT)technology has led to a significant increase in the computational task load of Terminal Devices(TDs).TDs reduce response latency and energy consumption with the support of task-offloading in Multi-access Edge Computing(MEC).However,existing task-offloading optimization methods typically assume that MEC’s computing resources are unlimited,and there is a lack of research on the optimization of task-offloading when MEC resources are exhausted.In addition,existing solutions only decide whether to accept the offloaded task request based on the single decision result of the current time slot,but lack support for multiple retry in subsequent time slots.It is resulting in TD missing potential offloading opportunities in the future.To fill this gap,we propose a Two-Stage Offloading Decision-making Framework(TSODF)with request holding and dynamic eviction.Long Short-Term Memory(LSTM)-based task-offloading request prediction and MEC resource release estimation are integrated to infer the probability of a request being accepted in the subsequent time slot.The framework learns optimized decision-making experiences continuously to increase the success rate of task offloading based on deep learning technology.Simulation results show that TSODF reduces total TD’s energy consumption and delay for task execution and improves task offloading rate and system resource utilization compared to the benchmark method. 展开更多
关键词 Decision making internet of things load prediction task offloading multi-access edge computing
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Optimization method of Hadamard coding plate inγ‑ray computational ghost imaging 被引量:3
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作者 Zhi Zhou San‑Gang Li +5 位作者 Qing‑Shan Tan Li Yang Ming‑Zhe Liu Ming Wang Lei Wang Yi Cheng 《Nuclear Science and Techniques》 SCIE EI CAS CSCD 2023年第1期146-156,共11页
Owing to the constraints on the fabrication ofγ-ray coding plates with many pixels,few studies have been carried out onγ-ray computational ghost imaging.Thus,the development of coding plates with fewer pixels is ess... Owing to the constraints on the fabrication ofγ-ray coding plates with many pixels,few studies have been carried out onγ-ray computational ghost imaging.Thus,the development of coding plates with fewer pixels is essential to achieveγ-ray computational ghost imaging.Based on the regional similarity between Hadamard subcoding plates,this study presents an optimization method to reduce the number of pixels of Hadamard coding plates.First,a moving distance matrix was obtained to describe the regional similarity quantitatively.Second,based on the matrix,we used two ant colony optimization arrangement algorithms to maximize the reuse of pixels in the regional similarity area and obtain new compressed coding plates.With full sampling,these two algorithms improved the pixel utilization of the coding plate,and the compression ratio values were 54.2%and 58.9%,respectively.In addition,three undersampled sequences(the Harr,Russian dolls,and cake-cutting sequences)with different sampling rates were tested and discussed.With different sampling rates,our method reduced the number of pixels of all three sequences,especially for the Russian dolls and cake-cutting sequences.Therefore,our method can reduce the number of pixels,manufacturing cost,and difficulty of the coding plate,which is beneficial for the implementation and application ofγ-ray computational ghost imaging. 展开更多
关键词 γ-ray computational ghost imaging Regional similarity Hadamard coding plate
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Application of computational fluid dynamics in design of viscous dampers-CFD modeling and full-scale dynamic testing 被引量:1
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作者 Hassan Lak Seyed Mehdi Zahrai +1 位作者 Seyed Mohammad Mirhosseini Ehsanollah Zeighami 《Earthquake Engineering and Engineering Vibration》 SCIE EI CSCD 2023年第4期1065-1080,共16页
Computational fluid dynamics(CFD)provides a powerful tool for investigating complicated fluid flows.This paper aims to study the applicability of CFD in the preliminary design of linear and nonlinear fluid viscous dam... Computational fluid dynamics(CFD)provides a powerful tool for investigating complicated fluid flows.This paper aims to study the applicability of CFD in the preliminary design of linear and nonlinear fluid viscous dampers.Two fluid viscous dampers were designed based on CFD models.The first device was a linear viscous damper with straight orifices.The second was a nonlinear viscous damper containing a one-way pressure-responsive valve inside its orifices.Both dampers were detailed based on CFD simulations,and their internal fluid flows were investigated.Full-scale specimens of both dampers were manufactured and tested under dynamic loads.According to the tests results,both dampers demonstrate stable cyclic behaviors,and as expected,the nonlinear damper generally tends to dissipate more energy compared to its linear counterpart.Good compatibility was achieved between the experimentally measured damper force-velocity curves and those estimated from CFD analyses.Using a thermography camera,a rise in temperature of the dampers was measured during the tests.It was found that output force of the manufactured devices was virtually independent of temperature even during long duration loadings.Accordingly,temperature dependence can be ignored in CFD models,because a reliable temperature compensator mechanism was used(or intended to be used)by the damper manufacturer. 展开更多
关键词 fluid viscous damper passive control dynamic testing energy dissipation device computational fluid dynamic THERMOGRAPHY
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Large-scale computational screening of metal–organic frameworks for D_(2)/H_(2) separation 被引量:1
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作者 Fei Wang Zhiyuan Bi +1 位作者 Lifeng Ding Qingyuan Yang 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2023年第2期323-330,共8页
Deuterium(D_(2)) is one of the important fuel sources that power nuclear fusion reactors. The existing D_(2)/H_(2) separation technologies that obtain high-purity D_(2) are cost-intensive. Recent research has shown th... Deuterium(D_(2)) is one of the important fuel sources that power nuclear fusion reactors. The existing D_(2)/H_(2) separation technologies that obtain high-purity D_(2) are cost-intensive. Recent research has shown that metal-organic frameworks(MOFs) are of good potential for D_(2)/H_(2) separation application. In this work, a high-throughput computational screening of 12020 computation-ready experimental MOFs is carried out to determine the best MOFs for hydrogen isotope separation application. Meanwhile, the detailed structure-performance correlation is systematically investigated with the aid of machine learning. The results indicate that the ideal D_(2)/H_(2) adsorption selectivity calculated based on Henry coefficient is strongly correlated with the 1/ΔAD feature descriptor;that is, inverse of the adsorbility difference of the two adsorbates. Meanwhile, the machine learning(ML) results show that the prediction accuracy of all the four ML methods is significantly improved after the addition of this feature descriptor. In addition, the ML results based on extreme gradient boosting model also revealed that the 1/ΔAD descriptor has the highest relative importance compared to other commonly-used descriptors. To further explore the effect of hydrogen isotope separation in binary mixture, 1548 MOFs with ideal adsorption selectivity greater than 1.5 are simulated at equimolar conditions. The structure-performance relationship shows that high adsorption selectivity MOFs generally have smaller pore size(0.3-0.5 nm) and lower surface area. Among the top 200 performers, the materials mainly have the sql, pcu, cds, hxl, and ins topologies.Finally, three MOFs with high D_(2)/H_(2) selectivity and good D_(2) uptake are identified as the best candidates,of all which had one-dimensional channel pore. The findings obtained in this work may be helpful for the identification of potentially promising candidates for hydrogen isotope separation. 展开更多
关键词 Metal–organic frameworks computational screening Hydrogen isotope separation
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Computational design of promising 2D electrode materials for Li-ion and Li–S battery applications 被引量:1
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作者 Ke Fan Yuen Hong Tsang Haitao Huang 《Materials Reports(Energy)》 2023年第3期1-23,共23页
Lithium-ion batteries(LIBs)and lithium-sulfur(Li–S)batteries are two types of energy storage systems with significance in both scientific research and commercialization.Nevertheless,the rational design of electrode m... Lithium-ion batteries(LIBs)and lithium-sulfur(Li–S)batteries are two types of energy storage systems with significance in both scientific research and commercialization.Nevertheless,the rational design of electrode materials for overcoming the bottlenecks of LIBs and Li–S batteries(such as low diffusion rates in LIBs and low sulfur utilization in Li–S batteries)remain the greatest challenge,while two-dimensional(2D)electrodes materials provide a solution because of their unique structural and electrochemical properties.In this article,from the perspective of ab-initio simulations,we review the design of 2D electrode materials for LIBs and Li–S batteries.We first propose the theoretical design principles for 2D electrodes,including stability,electronic properties,capacity,and ion diffusion descriptors.Next,classified examples of promising 2D electrodes designed by theoretical simulations are given,covering graphene,phosphorene,MXene,transition metal sulfides,and so on.Finally,common challenges and a future perspective are provided.This review paves the way for rational design of 2D electrode materials for LIBs and Li–S battery applications and may provide a guide for future experiments. 展开更多
关键词 Lithium-ion batteries Lithium-sulfur batteries 2D electrode materials computational design
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Deep Learning Applied to Computational Mechanics:A Comprehensive Review,State of the Art,and the Classics 被引量:1
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作者 Loc Vu-Quoc Alexander Humer 《Computer Modeling in Engineering & Sciences》 SCIE EI 2023年第11期1069-1343,共275页
Three recent breakthroughs due to AI in arts and science serve as motivation:An award winning digital image,protein folding,fast matrix multiplication.Many recent developments in artificial neural networks,particularl... Three recent breakthroughs due to AI in arts and science serve as motivation:An award winning digital image,protein folding,fast matrix multiplication.Many recent developments in artificial neural networks,particularly deep learning(DL),applied and relevant to computational mechanics(solid,fluids,finite-element technology)are reviewed in detail.Both hybrid and pure machine learning(ML)methods are discussed.Hybrid methods combine traditional PDE discretizations with ML methods either(1)to help model complex nonlinear constitutive relations,(2)to nonlinearly reduce the model order for efficient simulation(turbulence),or(3)to accelerate the simulation by predicting certain components in the traditional integration methods.Here,methods(1)and(2)relied on Long-Short-Term Memory(LSTM)architecture,with method(3)relying on convolutional neural networks.Pure ML methods to solve(nonlinear)PDEs are represented by Physics-Informed Neural network(PINN)methods,which could be combined with attention mechanism to address discontinuous solutions.Both LSTM and attention architectures,together with modern and generalized classic optimizers to include stochasticity for DL networks,are extensively reviewed.Kernel machines,including Gaussian processes,are provided to sufficient depth for more advanced works such as shallow networks with infinite width.Not only addressing experts,readers are assumed familiar with computational mechanics,but not with DL,whose concepts and applications are built up from the basics,aiming at bringing first-time learners quickly to the forefront of research.History and limitations of AI are recounted and discussed,with particular attention at pointing out misstatements or misconceptions of the classics,even in well-known references.Positioning and pointing control of a large-deformable beam is given as an example. 展开更多
关键词 Deep learning breakthroughs network architectures backpropagation stochastic optimization methods from classic to modern recurrent neural networks long short-term memory gated recurrent unit attention transformer kernel machines Gaussian processes libraries Physics-Informed Neural Networks state-of-the-art history limitations challenges Applications to computational mechanics Finite-element matrix integration improved Gauss quadrature Multiscale geomechanics fluid-filled porous media Fluid mechanics turbulence proper orthogonal decomposition Nonlinear-manifold model-order reduction autoencoder hyper-reduction using gappy data control of large deformable beam
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A computational framework for improving genetic variants identification from 5,061 sheep sequencing data
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作者 Shangqian Xie Karissa Isaacs +1 位作者 Gabrielle Becker Brenda M.Murdoch 《Journal of Animal Science and Biotechnology》 SCIE CAS CSCD 2023年第6期2332-2344,共13页
Background Pan-genomics is a recently emerging strategy that can be utilized to provide a more comprehensive characterization of genetic variation.Joint calling is routinely used to combine identified variants across ... Background Pan-genomics is a recently emerging strategy that can be utilized to provide a more comprehensive characterization of genetic variation.Joint calling is routinely used to combine identified variants across multiple related samples.However,the improvement of variants identification using the mutual support information from mul-tiple samples remains quite limited for population-scale genotyping.Results In this study,we developed a computational framework for joint calling genetic variants from 5,061 sheep by incorporating the sequencing error and optimizing mutual support information from multiple samples’data.The variants were accurately identified from multiple samples by using four steps:(1)Probabilities of variants from two widely used algorithms,GATK and Freebayes,were calculated by Poisson model incorporating base sequencing error potential;(2)The variants with high mapping quality or consistently identified from at least two samples by GATK and Freebayes were used to construct the raw high-confidence identification(rHID)variants database;(3)The high confidence variants identified in single sample were ordered by probability value and controlled by false discovery rate(FDR)using rHID database;(4)To avoid the elimination of potentially true variants from rHID database,the vari-ants that failed FDR were reexamined to rescued potential true variants and ensured high accurate identification variants.The results indicated that the percent of concordant SNPs and Indels from Freebayes and GATK after our new method were significantly improved 12%-32%compared with raw variants and advantageously found low frequency variants of individual sheep involved several traits including nipples number(GPC5),scrapie pathology(PAPSS2),sea-sonal reproduction and litter size(GRM1),coat color(RAB27A),and lentivirus susceptibility(TMEM154).Conclusion The new method used the computational strategy to reduce the number of false positives,and simulta-neously improve the identification of genetic variants.This strategy did not incur any extra cost by using any addi-tional samples or sequencing data information and advantageously identified rare variants which can be important for practical applications of animal breeding. 展开更多
关键词 computational framework Genetic variants Multiple samples SHEEP
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