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Water Science and engineering 2022年第1期15卷 78-88页

作者： Shu-xin Wei Zuo-dong Liang Lin Cui Hua-ling Zhai Dong-sheng Jeng school of Civil engineering Qingdao University of TechnologyQingdao 266033China school of Civil engineering Southwest Jiaotong UniversityChengdu 610031China School of Engineering&Built Environment Griffith University Gold Coast CampusQueensland 4222Australia

The seabed instability induced by the transient liquefaction when exposed to wave-current may threaten the safety of offshore structures.In this study,the Reynolds-averaged Navier-Stokes(RANS)equations with the k-e turbulence model were used to imitate the fluid dynamics,and Biot's poro-elastic theory was used to simulate the transient seabed response.An in-house solver(porous-fluid-seabed-structure interactions-field operation and manipulation)integrating the flow model and seabed model with the finite volume method was developed.The present model was confirmed with published experimental results and then used to analyze the dynamic process of the fluid-seabed-structure interactions as well as seafloor liquefaction around the jacket foundation under wave-current loading.The simulated results showed that the depth and range for the liquefaction area around the jacket foundation tended to increase at first and then declined as the wave propagated forward in the absence of current.In addition,the results demonstrated that the liquefaction depth under current and wave in the same orientation was greater than that without current.It is worth mentioning that the downstream piles were more prone to liquefaction than the upstream piles when the forward current existed.

关键词： Jacket Wave and current Liquefaction Seafloor dynamic Fluid-seabed-structure interactions

地下煤矿锚杆(索)过早失效腐蚀环境的水文地球化学模拟

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Journal of Central South University 2020年第5期27卷 1599-1610页

作者：彭亚 Wendy TIMMS school of Civil and Resource engineering University of Science and Technology BeijingBeijing 100083China school of Minerals and Energy Resources engineering UNSW SydneySydney 2052Australia Faculty of Science engineering&built environment Deakin UniversityGeelong 3216Australia

锚杆(索)被广泛应用于地下采矿和巷道掘进过程中以提高顶板稳定性。由于锚固材料的腐蚀敏感性、所处潮湿、腐蚀环境以及拉伸应力的影响,锚杆(索)的过早失效是地下开采工程中存在的重大安全隐患。本文将实验室实验与水文地球化学模型相结... 详细信息

锚杆(索)被广泛应用于地下采矿和巷道掘进过程中以提高顶板稳定性。由于锚固材料的腐蚀敏感性、所处潮湿、腐蚀环境以及拉伸应力的影响,锚杆(索)的过早失效是地下开采工程中存在的重大安全隐患。本文将实验室实验与水文地球化学模型相结合,对地下煤矿水环境下锚杆(索)的腐蚀破坏进行了研究。根据实验数据和矿井水水化学数据,采用PHREEQC软件对锚杆(索)与矿井地下水和岩层材料间腐蚀反应进行了模拟分析。建立了一系列的模型量化铁和碳元素反应量,模拟了有氧和无氧条件下水环境中的化学反应,得到各离子浓度、pH和随反应进度的变化趋势,并与实验结果进行对比。结果表明,锚杆(索)的腐蚀受到某些自然环境因素的抑制,因为水中溶解氧可以促进更多铁氧化。通过水文地球化学模拟等手段,阐明了锚杆(索)周边环境是影响其应力腐蚀开裂过程的重要因素。

关键词：锚杆(索) 水文地球化学模拟锚杆和锚索应力腐蚀开裂水化学分析

Formation mechanism and application potential of carbon dots synthesized from palm kernel shell via microwave assisted method

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Carbon Resources Conversion 2022年第2期5卷 150-166页

作者： Thivyah Balakrishnan Wei Lun Ang Ebrahim Mahmoudi Abdul Wahab Mohammad Nonni Soraya Sambudi Department of Chemical and Process engineering Faculty of Engineering&Built EnvironmentUniversiti Kebangsaan Malaysia43600 BangiSelangorMalaysia Centre for Sustainable Process Technology Faculty of Engineering&Built EnvironmentUniversiti Kebangsaan Malaysia43600 BangiSelangorMalaysia Department of Chemical engineering Universiti Teknologi PETRONAS32610 Seri IskandarPerakMalaysia

The present study systematically investigated the influence of synthesis conditions(duration,reaction medium,and doping concentration)and formation mechanism of carbon dots(CDs)derived from low-cost and abundant biomass palm kernel shell(PKS).Surprisingly,the dopant(urea)did not enhance the photoluminescence of CDs as expected,which could be attributed to the low reactivity between the dopant and PKS macromolecules.Variation of synthesis duration from 30 to 120 s clearly indicated the formation mechanism of CDs,involving the stages of dehydration,carbonization,and nucleation.The CDs with the highest photoluminescent intensity and quantum yield was obtained at synthesis duration of 90 s,aligned well with the perfect spherical shape of CDs and the synergistic effects of both surface and carbogenic core conditions.Understanding the formation mechanism could be used to optimize the synthesis of CDs,and hence linked to quantum yield and fluorescent intensity.In terms of application potential,the CDs illuminated well as fluorescent ink and in bacteria cells imaging.The potential of CDs as sensing material has also been proven with the quenching of fluorescence in the presence of metal ions.The linear range for detection of Cu2+ions was 0.1–0.5 mM with a detection limit as low as 0.05 mM.This signifies the potential of CDs fabricated from PKS as a low-cost and easily available material for Cu2+ions detection in aqueous solution.The CDs possessed reasonable photo stability as indicated by its consistent fluorescence level even after exposure to UV radiation for a prolonged period of 180 minutes.Overall,a simple,straightforward,and fast method is developed to synthesis strong blue emissive CDs from green PKS that are potentially suitable for Cu2+ions sensing in real application.

关键词： Carbon dots Microwave radiation Palm kernel shell Cell imaging Metal ions detection

Comparison of light absorption and oxidative potential of biodiesel/diesel and chemicals/diesel blends soot particles

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Journal of environmental Sciences 2020年第1期32卷 184-193页

作者： Yu Kuang Yi Guo Jiaqi Chai Jing Shang Jiali Zhu Svetlana Stevanovic Zoran Ristovski State Key Joint Laboratory of environmental Simulation and Pollution Control College of Environmental Sciences and Engineeringand Center for Environment and HealthPeking UniversityBeijing 100871China International Laboratoryfor Air Quality&Health(ILAQH) School of ChemistryPhysics and Mechanical EngineeringQueensland University of TechnologyBrisbaneQLD 4001Australia school of engineering Faculty of Science Engineering&Built EnvironmentDe akin UniversityGeelong Waum Ponds CampusLocked Bag 20000GeelongVIC 3220Australia

Soot particles,mainly coming from fuel combustion,affect climate forcing through absorbing light and also result in adverse human health outcomes.Though biodiesel or additives blending with diesel was considered environmentally friendly,the understanding on absorbing and oxidative capacity of soot emitted from them are still unclear.The watersoluble organic carbon(WSOC)content,surface chemical structure,light absorption and oxidative potential(OPDTT)of soot from biodiesel/diesel and chemicals/diesel blends were investigated utilizing total organic carbon analyzer,X-ray photoelectron spectrometer,ultraviolet–visible spectrophotometry and dithiothreitol(DTT)assay.The differences and correlations between soot properties were statistically analyzed.Chemicals/diesel blends soot owned significantly higher WSOC content,ratio of mass absorbing efficiency(MAE)in250 and 365 nm(E2/E3),OPDTT,and higher surface carbonyl content.Coconut biodiesel/diesel blends soot contained evidently higher aromatic carbon–oxygen single bond(ArC–O)content,and higher MAE365.The individual comparison of biodiesel/diesel blends showed20%coconut biodiesel blend owned the lowest WSOC,E2/E3 and OPDTT,while highest ArC–O and MAE365,representing strongest absorbing properties.Association analysis showed OPDTTwas significantly positively correlated with WSOC.Further,the evident negative correlation between MAE365 and OPDTT was observed.Our results showed coconut biodiesel/diesel blends soot induced lower levels of oxidative potential,whereas absorption of light was higher,which have far reaching consequences on climate forcing.Therefore,it is important to evaluate the balance point between light-absorbing properties and oxidative potential,under the wide use of biodiesel.

关键词： Soot particle Biodiesel Light absorption Mass absorbing efficiency Oxidative potential Dithiothreitol(DTT)

Multi-criteria prioritization of the renewable power plants in Australia using the fuzzy logic in decision-making method(FMCDM)

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Clean Energy 2022年第1期6卷 16-34页

作者： Amin Aryanfar Aslan Gholami Payam Ghorbannezhad Bijan Yeganeh Mahdi Pourgholi Majid Zandi Svetlana Stevanovic Faculty of Mechanical and Energy engineering Shahid Beheshti UniversityTehranIran Faculty of New Technologies and Energy engineering Shahid Beheshti UniversityTehranIran Faculty of Civil Water&Environmental EngineeringShahid Beheshti UniversityTehranIran Centre for Air Pollution Energy and Health ResearchGlebeNew South Wales 2037Australia Faculty of Electrical engineering Shahid Beheshti UniversityTehranIran Faculty of Science Engineering&Built EnvironmentSchool of EngineeringDeakin UniversityGeelongVictoria 3220Australia

The presented study focused on developing an innovative decision-making framework to select the best renewable-power-plant technologies,considering comprehensive techno-economic and environmental variables.Due to the favourable conditions,Australia was selected as the case study.A fuzzy-logic method and analytical hierarchy process were applied to prioritize different renewable-energy power plants.The techno-economic factors included levelized cost of energy,initial cost,simple payback time,and operation and maintenance costs along with environmental factors including carbon payback time,energy payback time and greenhouse-gas emissions were used to rank the power plants.The results showed that the capital cost and simple payback time had the highest priority from an economic point of view.In comparison,greenhouse-gas emissions and carbon payback time were the dominant environmental factors.The analysis results provided economic and environmental priority tables for developing different power plants in the current state and a future scenario by 2030.The fuzzy results and pairwise composite matrix of alternatives indicated that the onshore wind,offshore wind,single-axis tracker polycrystalline photovoltaic,single-axis tracker monocrystalline photovoltaic,fix-tilted polycrystalline photovoltaic and fix-tilted monocrystalline photovoltaic scored the highest in the current state.In contrast,by 2030,the single-axis tracker photovoltaic power plants will be the best choice in the future scenario in Australia.Finally,the results were used and analysed to recommend and suggest several policy implementations and future research studies.

关键词： photovoltaic wind fuzzy logic analytical hierarchy process prioritization

Intelligent modelling of clay compressibility using hybrid meta-heuristic and machine learning algorithms

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Geoscience Frontiers 2021年第1期12卷 441-452页

作者： Pin Zhang Zhen-Yu Yin Yin-Fu Jin Tommy HTChan Fu-Ping Gao Department of Civil and environmental engineering The Hong Kong Polytechnic UniversityHung HomKowloonHong KongChina school of Civil engineering&built environment Science and Engineering FacultyQueensland University of Technology(QUT)BrisbaneQld4001Australia Key Laboratory for Mechanics in Fluid Solid Coupling Systems Institute of MechanicsChinese Academy of SciencesBeijing100190China China school of engineering Science University of Chinese Academy of SciencesBeijing100049China

Compression index Ccis an essential parameter in geotechnical design for which the effectiveness of correlation is still a challenge.This paper suggests a novel modelling approach using machine learning(ML)technique.The performance of five commonly used machine learning(ML)algorithms,i.***.back-propagation neural network(BPNN),extreme learning machine(ELM),support vector machine(SVM),random forest(RF)and evolutionary polynomial regression(EPR)in predicting Cc is comprehensively investigated.A database with a total number of 311 datasets including three input variables,i.***.initial void ratio e0,liquid limit water content wL,plasticity index Ip,and one output variable Cc is first established.Genetic algorithm(GA)is used to optimize the hyper-parameters in five ML algorithms,and the average prediction error for the 10-fold cross-validation(CV)sets is set as thefitness function in the GA for enhancing the robustness of ML models.The results indicate that ML models outperform empirical prediction formulations with lower prediction error.RF yields the lowest error followed by BPNN,ELM,EPR and SVM.If the ranges of input variables in the database are large enough,BPNN and RF models are recommended to predict Cc.Furthermore,if the distribution of input variables is continuous,RF model is the best one.Otherwise,EPR model is recommended if the ranges of input variables are small.The predicted correlations between input and output variables using five ML models show great agreement with the physical explanation.

关键词： Compressibility Clays Machine learning Optimization Random forest Genetic algorithm

Spatio-visual experience of movement through the Yuyuan Garden:A computational analysis based on isovists and visibility graphs

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Frontiers of Architectural Research 2018年第4期7卷 497-509页

作者： Rongrong Yu Michael J.Ostwald school of engineering and built environment Griffith UniversityAustralia school of Architecture and built environment The University of NewcastleAustralia

A traditional Chinese private garden (TCPG) is a historically important spatial type of garden that is well-known for its rich experiential properties. Although several theories have been used to explain the creation of these experiential properties, little evidence exists for any of the current explanations because TCPGs are complex environments and their visual properties change as a person moves through them. This study uses computational analysis—isovists, isovist fields, and visibility graphs—to measure the spatio-visual character of movement along a path through a well-known TCPG, namely, the 16th century Yuyuan Garden in Shanghai. The measures derived from this process are used to evaluate four theories on the spatial experience of the TCPG.

关键词： Traditional Chinese private garden Visual property Isovist analysis Spatial experience

On-site solar PV generation and use: Self-consumption andself-sufficiency

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Building Simulation 2023年第10期16卷 1835-1849页

作者： Zheng Wang Mark B.Luther Peter Horan Jane Matthews Chunlu Liu school of Architecture and built environment Deakin UniversityGeelongAustralia

As energy storage systems are typically not installed with residential solar photovoltaic (PV) systems,any “excess” solar energy exceeding the house load remains unharvested or is exported to the grid.This paper introduces an approach towards a system design for improved PV self-consumptionand self-sufficiency. As a result, a polyvalent heat pump, offering heating, cooling and domestic hotwater, is considered alongside water storage tanks and batteries. Our method of system analysisbegins with annual hourly thermal loads for heating and cooling a typical Australian house inGeelong, Victoria. These hourly heating and cooling loads are determined using Transient SystemSimulation (TRNSYS) software. The house’s annual hourly electricity consumption is analysed usingsmart meter data downloaded from the power supplier and PV generation data measured with aPV system controller. The results reveal that the proposed system could increase PV self-consumptionand self-sufficiency to 41.96% and 86.34%, respectively, resulting in the annual imported energybeing reduced by about 74%. The paper also provides sensitivity analyses for the hot and coldstorage tank sizes, the coefficient of performance of the heat pump, solar PV and battery sizes.After establishing the limits of thermal storage size, a significant impact on self-efficiency can berealised through battery storage. This study demonstrates the feasibility of using a polyvalent heatpump together with water storage tanks and, ultimately, batteries to increase PV self-consumptionand self-sufficiency. Future work will concentrate on determining a best-fit approach to systemsizing embedded within the TRNSYS simulation tool.

关键词： solar photovoltaic polyvalent heat pump energy storage self-consumption self-sufficiency

Coupled thermo-mechanical constitutive damage model for sandstone

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Journal of Rock Mechanics and Geotechnical engineering 2022年第6期14卷 1710-1721页

作者： Savani Vidana Pathiranagei Ivan Gratchev school of engineering and built environment Gold Coast CampusGriffith UniversitySouthportQLD 4222Australia

Underground rock dynamic disasters are becoming more severe due to the increasing depth of human operations underground.Underground temperature and pressure conditions contribute significantly to these disasters.Therefore,it is important to understand the coupled thermo-mechanical(TM)behaviour of rocks for the long-term safety and maintenance of underground tunnelling and mining.Moreover,investigation of the damage,strength and failure characteristics of rocks under triaxial stress conditions is important to avoid underground rock disasters.In this study,based on Weibull distribution and Lemaitre's strain equivalent principle,a statistical coupled TM constitutive model for sandstone was established under high temperature and pressure conditions.The triaxial test results of sandstone under different temperature and pressure conditions were used to validate the model.The proposed model was in good agreement with the experimental results up to 600℃.The total TM damage was decreased with increasing temperature,while it was increased with increasing confining pressure.The model's parameters can be calculated using conventional laboratory test results.

关键词： High temperature Confining pressure Thermo-mechanical(TM)damage Thermal damage Mechanical damage

Combination of sensitivity and uncertainty analyses for sediment transport modeling in sewer pipes

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International Journal of Sediment Research 2020年第2期35卷 157-170页

作者： Isa Ebtehaj Hossein Bonakdari Mir Jafar Sadegh Safari Bahram Gharabaghi Amir Hossein Zaji Hossien Riahi Madavar Zohreh Sheikh Khozani Mohammad Sadegh Es-haghi Aydin Shishegaran Ali Danandeh Mehr Department of Civil engineering Razi University environmental Research Center Razi University Department of Civil engineering Yasar University 4. School of EngineeringUniversity of Guelph 5. Department of Water EngineeringVali-e-Asr University of Rafsanjan 6. Smart and Sustainable Township Research CenterFaculty of Engineering&Built EnvironmentUniversiti Kebangsaan Malaysia 7. School of Civil EngineeringK.N.Toosi University of Technology 8. Department of Waterand EnvironmentalIran University of Science and Technology 9. Department of Civil EngineeringAntalya Bilim University

Mitigation of sediment deposition in lined open channels is an essential issue in hydraulic engineering practice.Hence,the limiting velocity should be determined to keep the channel bottom clean from sediment deposits.Recently,sediment transport modeling using various artificial intelligence(AI) techniques has attracted the interest of many researchers.The current integrated study highlights unique insight for modeling of sediment transport in sewer and urban drainage systems.A novel methodology based on the combination of sensitivity and uncertainty analyses with a machine learning technique is proposed as a tool for selection of the best input combination for modeling process at non-deposition conditions of sediment transport.Utilizing one to seven dimensionless parameters,127 models are developed in the current study.In order to evaluate the different parameter co mbinations and select the training and te sting data,four strategies are considered.Considering the densimetric Froude number(Fr) as the dependent parameter,a model with independent parameters of volumetric sediment concentration(CV) and relative particle size(d/R) gave the best results with a mean absolute relative error(MARE) of 0.1 and a root means square error(RMSE) of 0.67.Uncertainty analysis is applied with a machine learning technique to investigate the credibility of the proposed methods.The percentage of the observed sample data bracketed by95% predicted uncertainty bound(95 PPU) is computed to assess the uncertainty of the best models.

关键词： Non-deposition Sediment transport Sensitivity analysis Sewer Uncertainty analysis Urban drainage