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Effect of a Carbon Fibre-steel Fibre-graphite Conductive Filler on the Electrothermal Properties of Cementitious Materials

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Journal of Wuhan University of Technology(Materials Science) 2025年第1期40卷 141-151页

作者： FAN Yanan WEI Hong ZHENG Hongyong DU Hongxiu department of Architecture and Environmental engineering Taiyuan UniversityTaiyuan 030032China College of civil engineering Taiyuan University of TechnologyTaiyuan 030032China

Carbon fibre,steel fibre and graphite were used as conductive fillers to prepare cementitious materials with excellent electrothermal *** electrically conductive cementitious materials with different volume dosages were analysed through compressive and flexural strength,electrochemical impedance spectroscopy and temperature rise *** equivalent circuit model was established to study the electrically conductive heat generation mechanism in the electrically conductive cementitious *** results indicate that the mechanical properties of cementitious composite materials with a ternary conductive phase are better than those of pristine cementitious materials because the fibrous filler improves their mechanical ***,the incorporation of graphite in the material reduces its *** fibrous and point-like conductive phase materials into the cementitious material enhances the overall conductive pathway and considerably reduces the electrical resistance of the cementitious material,enhancing its conductive *** volume ratios of carbon fibre,steel fibre and graphite that achieve an optimal complex doping in the cementitious material were 0.35%,0.6%and 6%,*** was determined using the mutation point of each circuit element parameter as the percolation *** addition,at a certain safety voltage,there is a uniform change between the internal and surface temperatures of the conductive cementitious material,and the heating effect in this materialis is considerably better than that in the pristine cementitious material.

关键词： cementitious composites conductive fillers electrothermal properties electrochemical impedance spectroscopy

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Nano-Enhanced Dairy Scum Biodiesel Blends:Unleashing the Power of Aluminium Oxide for Sustainable and Efficient Engine Performance

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Journal of Thermal Science 2025年第1期34卷 283-302页

作者： Veeranna MODI Prasad B.RAMPURE Sunil Kumar SHETTY Madeva NAGARAL Channa Keshava NAIK N Johar MGM Muhammad Irsyad ABDULLAH Abdullah I.AL-MANSOUR Shamshad ALAM KLE College of engineering and Technology ChikodiVisvesvaraya Technological University Nitte (Deemed to be University) NMAM Institute of Technology (NMAMIT)Department of Mechanical Engineering Aircraft Research and Design Centre HAL department of Mechanical engineering BGS College of Engineering and TechnologyBengaluruAffiliated to Visvesvaraya Technological University Management and Science University department of civil engineering College of EngineeringKing Saud University

This study investigates the effect of aluminium oxide nanoparticlesaddition to biodiesel blends made from dairy milk scum on performance and combustion characteristics of the diesel *** dispersion of Al2O3nanoparticles in B20 blends at different concentrations was done with the help of *** number of blends were prepared for the *** Machine learning algorithms(Random Forest（RF）and CatBoost) was used for the *** results show that in comparison to biodiesel blends without nanoparticles,the kinematic viscosity and density is higher for fuel blends with *** these Fuel blends have higher calorific *** blends exhibited reduced Brake Specific Fuel Consumption（BSFC） of2.85% than the blends without nano particles(Dairy Scum Methyl Ester Biodiesel 20%+Neat Diesel 80%（in volume）,DSMEB20),57.14% less CO,40.8% less hydrocarbon,and increased NOxemissions compared to conventional diesel,contributing to the development of environmentally friendly and renewable biofuel blends with *** B20NP30 is the optimal blend for performance and emission *** study concludes with findings on enhanced Brake Thermal Efficiency（BTE） of 26.29% in 3×10-5（in volume） Al2O3nanoparticle-blended DSME B20 and other DSME B20 fuel blends,emphasizing the importance of optimal nanoparticle *** correlation matrix shows how engine load,efficiency measures（BTE,BSFC）,and emissions（CO,CO2,NOx,Smoke） are connected in complex *** results help us understand the complicated dynamics of engine performance and emission characteristics ***'s diagram for BTE and BSFC shows that CatBoost-based BTE models perform superior to RF-based models during the training as well as testing *** results were obtained for CO and CO2emission results.

关键词： Al2O3 concentration CI engine Dairy Scum Methyl Ester Biodiesel

Dynamic Multi-Graph Spatio-Temporal Graph Traffic Flow Prediction in Bangkok:An Application of a Continuous Convolutional Neural Network

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Computer Modeling in engineering & Sciences 2025年第1期142卷 579-607页

作者： Pongsakon Promsawat Weerapan Sae-dan Marisa Kaewsuwan Weerawat Sudsutad Aphirak Aphithana department of civil engineering Faculty of EngineeringRamkhamkaeng UniversityBangkok10240Thailand department of Computer engineering Faculty of EngineeringRamkhamkaeng UniversityBangkok10240Thailand department of Statistics Faculty of ScienceRamkhamkaeng UniversityBangkok10240Thailand

The ability to accurately predict urban traffic flows is crucial for optimising city ***,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to understand complex mobility *** learning techniques,such as graph neural networks(GNNs),are popular for their ability to capture spatio-temporal ***,these models often become overly complex due to the large number of hyper-parameters *** this study,we introduce Dynamic Multi-Graph Spatial-Temporal Graph Neural Ordinary Differential Equation Networks(DMST-GNODE),a framework based on ordinary differential equations(ODEs)that autonomously discovers effective spatial-temporal graph neural network(STGNN)architectures for traffic prediction *** comparative analysis of DMST-GNODE and baseline models indicates that DMST-GNODE model demonstrates superior performance across multiple datasets,consistently achieving the lowest Root Mean Square Error(RMSE)and Mean Absolute Error(MAE)values,alongside the highest *** the BKK(Bangkok)dataset,it outperformed other models with an RMSE of 3.3165 and an accuracy of 0.9367 for a 20-min interval,maintaining this trend across 40 and 60 ***,on the PeMS08 dataset,DMST-GNODE achieved the best performance with an RMSE of 19.4863 and an accuracy of 0.9377 at 20 min,demonstrating its effectiveness over longer *** Los_Loop dataset results further emphasise this model’s advantage,with an RMSE of 3.3422 and an accuracy of 0.7643 at 20 min,consistently maintaining superiority across all time *** numerical highlights indicate that DMST-GNODE not only outperforms baseline models but also achieves higher accuracy and lower errors across different time intervals and datasets.

关键词： Graph neural networks convolutional neural network deep learning dynamic multi-graph spatio-temporal

Efficient photocatalytic reduction of CO2 to formate by a molecular noble metal-free system

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Science China Chemistry 2025年第1期68卷 152-156页

作者： Lihua Zhang Lingjing Chen Huatian Shi Yue Wei Gui Chen Tai-Chu Lau School of Environment and civil engineering Research Center for Eco-environmental Engineering Dongguan University of Technology department of Chemistry and Institute of Molecular Functional Materials City University of Hong Kong

Reducing CO2to carbon-neutral solar fuels can not only alleviate the energy demand but also mitigate the greenhouse *** present,developing an efficient non-noble metal photo/electrocatalytic system for converting CO2to a specific product beyond CO is still a big ***,we report a new cobalt complex bearing 2,2′-bi-1,10-phenanthroline ligand that can photocatalytically reduce CO2to formate （HCOO-）.Turnover number （TON） for HCOO-up to 677 with 99%selectivity can be achieved using organic dyes purpurin as photosensitizer and 1,3-dimethyl-2-phenyl-2,3-dihydro-1H-benzo[d]imidazole （BIH） as sacrificial reductant in a CO2-saturated NMP/TEA （v/v,3:1） solution under visible light *** potential electrolysis at-1.41 V （***/Ag Cl） in the presence of 12 m M Et3NHBF4also produced HCOO-with Faradaic efficiency of 39%.Spectroscopic and electrochemical studies suggest that a[CoI-H]species is the key intermediate for CO2reduction.

关键词： photocatalysis noble metal-free CO2 reduction formate cobalt hydride

Landslide Susceptibility Mapping Using RBFN-Based Ensemble Machine Learning Models

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Computer Modeling in engineering & Sciences 2025年第1期142卷 467-500页

作者： Landslide Susceptibility Mapping Using RBFN-Based Ensemble Machine Learning Models Duc-Dam Nguyen Nguyen Viet Tiep Quynh-Anh Thi Bui Hiep Van Le Indra Prakash Romulus Costache Manish Pandey Binh Thai Pham Faculty of civil engineering University of Transport TechnologyThanh XuanHa Noi100000Vietnam Faculty of Hydraulic engineering Hanoi University of Civil EngineeringHa Noi100000Vietnam DDG(R)Geological Survey of India Gandhinagar382010India Research Institute of the University of Bucharest Bucharest050663Romania National Institute of Hydrology and Water Management Bucharest013686Romania department of civil engineering Transilvania University of BrasovBrasov500152Romania Danube Delta National Institute for Research and Development Tulcea820112Romania Marwadi University Research Center(MURC) Marwadi UniversityRajkotGujaratBharat360003India department of civil engineering Faculty of Engineering&TechnologyMarwadi UniversityRajkotGujaratBharat360003India

This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble learning techniques:DAGGING(DG),MULTIBOOST(MB),and ADABOOST(AB).This combination resulted in three distinct ensemble models:DG-RBFN,MB-RBFN,and ***,a traditional weighted method,Information Value(IV),and a benchmark machine learning(ML)model,Multilayer Perceptron Neural Network(MLP),were employed for comparison and *** models were developed using ten landslide conditioning factors,which included slope,aspect,elevation,curvature,land cover,geomorphology,overburden depth,lithology,distance to rivers and distance to *** factors were instrumental in predicting the output variable,which was the probability of landslide *** analysis of the models’performance indicated that the DG-RBFN model,with an Area Under ROC Curve(AUC)of 0.931,outperformed the other *** AB-RBFN model achieved an AUC of 0.929,the MB-RBFN model had an AUC of 0.913,and the MLP model recorded an AUC of *** results suggest that the advanced ensemble ML model DG-RBFN was more accurate than traditional statistical model,single MLP model,and other ensemble models in preparing trustworthy landslide susceptibility maps,thereby enhancing land use planning and decision-making.

关键词： Landslide susceptibility map spatial analysis ensemble modelling information values(IV)

Novel Methodologies for Preventing Crack Propagation in Steel Gas Pipelines Considering the Temperature Effect

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Structural Durability & Health Monitoring 2025年第1期19卷 1-23页

作者： Nurlan Zhangabay Ulzhan Ibraimova Marco Bonopera Ulanbator Suleimenov Konstantin Avramov Maryna Chernobryvko Aigerim Yessengali department of Architecture and Urban Planning Mukhtar Auezov South Kazakhstan UniversityShymkent160012Kazakhstan department of Industrial civil and Road Construction Mukhtar Auezov South Kazakhstan UniversityShymkent160012Kazakhstan Mechanics Sound&Vibration LaboratoryDepartment of Civil EngineeringCollege of EngineeringNational Taiwan UniversityTaipei10617Taiwan department of Reability&Dynamic Strength A.Pidhornyi Institute of Mechanical Engineering Problems of National Academy of Sciences of UkraineKharkiv61046Ukraine

Using the software ANSYS-19.2/Explicit Dynamics,this study performedﬁnite-element modeling of the large-diameter steel pipeline cross-section for the Beineu-Bozoy-Shymkent gas pipeline with a non-through straight crack,strengthened by steel wire *** effects of the thread tensile force of the steel winding in the form of single rings at the crack edges and the wires with different winding diameters and pitches were also *** results showed that the strengthening was preferably executed at a minimum value of the thread tensile force,which was 6.4%more effective than that at its maximum *** analysis of the inﬂuence of the winding dia-meters showed that the equivalent stresses increased by 32%from the beginning of the crack growth until the wire *** increment in winding diameter decelerated the disclosure of the edge crack and reduced its length by 8.2%.The analysis of the inﬂuence of the winding pitch showed that decreasing the distance between the winding turns also led to a 33.6%reduction in the length of the straight crack and a 7.9%reduction in the maximum stres-ses on the strengthened pipeline *** analysis of the temperature effect on the pipeline material,within a range from-40℃ to+50℃,resulted in a crack length change of up to 5.8%.As the temperature dropped,the crack length *** such a temperature range,the maximum stresses were observed along the cen-tral area of the crack,which were equal to 413 MPa at+50℃ and 440 MPa at-40℃.The results also showed that the presence of the steel winding in the pipeline signiﬁcantly reduced the length of crack propagation up to 8.4 times,depending on the temperature effect and design parameters of *** work integrated the existing methods for crack localization along steel gas pipelines.

关键词： Crack propagation ﬁnite-element internal pressure prestressing steel gas pipeline temperature effect

Aligned Ion Conduction Pathway of Polyrotaxane‑Based Electrolyte with Dispersed Hydrophobic Chains for Solid‑State Lithium–Oxygen Batteries

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Nano-Micro Letters 2025年第2期17卷 169-186页

作者： Bitgaram Kim Myeong‑Chang Sung Gwang‑Hee Lee Byoungjoon Hwang Sojung Seo Ji‑Hun Seo Dong‑Wan Kim department of Materials Science and engineering Korea University145 Anam‑RoSeongbuk‑GuSeoul 02841Republic of Korea School of civil Environmental and Architectural EngineeringKorea University145 Anam‑RoSeongbuk‑GuSeoul 02841Republic of Korea Materials Science and Chemical engineering Center Institute for Advanced Engineering(IAE)Yongin 17180Republic of Korea

A critical challenge hindering the practical application of lithium–oxygen batteries(LOBs)is the inevitable problems associated with liquid electrolytes,such as evaporation and safety *** study addresses these problems by proposing a modified polyrotaxane(mPR)-based solid polymer electrolyte(SPE)design that simultaneously mitigates solvent-related problems and improves ***-SPE exhibits high ion conductivity(2.8×10^(−3)S cm^(−1)at 25℃)through aligned ion conduction pathways and provides electrode protection ability through hydrophobic chain *** this mPR-SPE into solid-state LOBs resulted in stable potentials over 300 *** situ Raman spectroscopy reveals the presence of an LiO_(2)intermediate alongside Li_(2)O_(2)during oxygen *** situ X-ray diffraction confirm the ability of the SPE to hinder the permeation of oxygen and moisture,as demonstrated by the air permeability *** present study suggests that maintaining a low residual solvent while achieving high ionic conductivity is crucial for restricting the sub-reactions of solid-state LOBs.

关键词： Solid polymer electrolyte Lithium-oxygen batteries Polyrotaxane ion conductivity Hydrophobic chain

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Prediction of Shear Bond Strength of Asphalt Concrete Pavement Using Machine Learning Models and Grid Search Optimization Technique

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Computer Modeling in engineering & Sciences 2025年第1期142卷 691-712页

作者： Quynh-Anh Thi Bui Dam Duc Nguyen Hiep Van Le Indra Prakash Binh Thai Pham civil engineering department University of Transport Technology54 Trieu KhucThanh XuanHanoi100000Vietnam DDG(R)Geological Survey of India Gandhinagar382010India

Determination of Shear Bond strength(SBS)at interlayer of double-layer asphalt concrete is crucial in flexible pavement *** study used three Machine Learning(ML)models,including K-Nearest Neighbors(KNN),Extra Trees(ET),and Light Gradient Boosting Machine(LGBM),to predict SBS based on easily determinable input ***,the Grid Search technique was employed for hyper-parameter tuning of the ML models,and cross-validation and learning curve analysis were used for training the *** models were built on a database of 240 experimental results and three input variables:temperature,normal pressure,and tack coat *** validation was performed using three statistical criteria:the coefficient of determination(R2),the Root Mean Square Error(RMSE),and the mean absolute error(MAE).Additionally,SHAP analysis was also used to validate the importance of the input variables in the prediction of the *** show that these models accurately predict SBS,with LGBM providing outstanding ***(Shapley Additive explanation)analysis for LGBM indicates that temperature is the most influential factor on ***,the proposed ML models can quickly and accurately predict SBS between two layers of asphalt concrete,serving practical applications in flexible pavement structure design.

关键词： Shear bond asphalt pavement grid search optimization machine learning

An investigation on the wind profiles and gravity wave dynamics in MLT region based on the meteor radars from the Meridian Project

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Earth and Planetary Physics 2025年第1期9卷 29-38页

作者： Tai Liu Zhe Wang MengXi Shi Willie Soon ShiCan Qiu department of Geophysics College of the Geology Engineering and GeomaticsChang’an UniversityXi’an 710054China Center for Environmental Research and Earth Sciences(CERES) SalemMA 01970USA Institute of Earth Physics and Space Science(ELKH EPSS) 9400SopronHungary

The meteor radar can detect the zenith angle,azimuth,radial velocity,and altitude of meteor trails so that one can invert the wind profiles in the mesosphere and low thermosphere(MLT)region,based on the Interferometric and Doppler *** this paper,the horizontal wind field,gravity wave(GW)disturbance variance,and GW fluxes are analyzed through the meteor radar observation from 2012−2022,at Mohe(53.5°N,122.4°E)and Zuoling(30.5°N,114.6°E)stations of the(Chinese)Meridian *** Lomb−Scargle periodogram method has been utilized to analyze the periodic variations for time series with observational data *** results show that the zonal winds at both stations are eastward dominated,while the meridional winds are southward *** variance of GW disturbances in the zonal and meridional directions increases gradually with height,and there is a strong pattern of annual *** zonal momentum flux of GW changes little with height,showing weak annual *** meridional GW flux varies gradually from northward to southward with height,and the annual periodicity is *** both stations,the maximum values of zonal and meridional wind occur close to the peak heights of GW flux,with opposite *** observational evidence is consistent with the filtering *** horizontal wind velocity,GW flux,and disturbance variance of the GW at Mohe are overall smaller than those at Zuoling,indicating weaker activities in the MLT at *** power spectral density(PSD)calculated by the Lomb−Scargle periodogram shows that there are 12-month period and 6-month period in horizontal wind field,GW disturbance variance and GW flux at both stations,and especially there is also a 4-month cycle in the disturbance *** PSD of the 12-month and 6-month cycles exhibits maximum values below 88 km and above 94 km.

关键词： meteor radar wind field gravity wave Lomb−Scargle method

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