Silica materials are located in various regions of Libya in large quantities and different mining conditions, so the purpose of this study is silica materials in the south-west of the Libyan region Edree in terms of q...Silica materials are located in various regions of Libya in large quantities and different mining conditions, so the purpose of this study is silica materials in the south-west of the Libyan region Edree in terms of quality and the possibility of using in various engineering industries, particularly construction. The results show that the sands of silica presented in Edree area are of a high degree of purity, as the percentage of silicon （SIO2） reached 99.5%, the percentage of impurities was negligible and represented in some chemical elements in different proportions, such as calcium 0.224%, sodium 0.004%, iron 0.0006%, zinc 0.0003%, boron 0.0003%, potassium 0.0001%, manganese 0.0001% and magnesium 0.0001%, making these materials very suitable in the manufacture of all types of glass, crystal and semi-crystalline high-quality without needing any important treatment, as well as its suitability as a refinement in manufacture of templates metal castings in addition to the possibility of use in the manufacture of cement, building materials and as a filler in paint and brick making and sand and concrete elements can also be used in electronic industries. A geological material of silica present in the form of a sequence of layers of clay and thin layers of sand stone and a large stock of high-quality near the surface, making mining operations of the type of surface and reduces the cost of extraction.展开更多
In this study, the position of all major rill and gully erosion sites were located using hand held GPS （Global Positioning System） receiver during reconnaissance surveys. Based on severity rating and geopolitical co...In this study, the position of all major rill and gully erosion sites were located using hand held GPS （Global Positioning System） receiver during reconnaissance surveys. Based on severity rating and geopolitical considerations, six of the erosion gully sites were selected for monitoring. Control points were established around each of the gully sites using three Leica 500 dual frequency GPS receivers by method of DGPS （differential GPS） surveys. Detailed topographical survey of the gully sites was carried out using total stations. With the aid of SPOT satellite imageries in combination with total station data and GIS （geographic information system） location maps, contoured maps along with DEM （digital elevation model） were generated using ARCGIS 9.2 software. The morphological parameters of the gullies including depth, width, length and area of the gullies were determined. Volumetric estimate of the amount of soil loss from gully erosion was also carried out. Soil samples were recovered from the gully sites to determine their erodibility and other parameters to be used for soil loss modeling. The result of the studies was used as an indicator for determining the gully initiation point. Slope-area relationship and threshold of gully initiation was established. The minimum volume of soil loss occurred in gully No. 2 （Queen Ede）. The minimum AS^2 value was 345 while the maximum was 3,267.展开更多
Rock bursts represent a formidable challenge in underground engineering,posing substantial risks to both infrastructure and human safety.These sudden and violent failures of rock masses are characterized by the rapid ...Rock bursts represent a formidable challenge in underground engineering,posing substantial risks to both infrastructure and human safety.These sudden and violent failures of rock masses are characterized by the rapid release of accumulated stress within the rock,leading to severe seismic events and structural damage.Therefore,the development of reliable prediction models for rock bursts is paramount to mitigating these hazards.This study aims to propose a tree-based model—a Light Gradient Boosting Machine(LightGBM)—to predict the intensity of rock bursts in underground engineering.322 actual rock burst cases are collected to constitute an exhaustive rock burst dataset,which serves to train the LightGBMmodel.Two population-basedmetaheuristic algorithms are used to optimize the hyperparameters of the LightGBM model.Finally,the sensitivity analysis is used to identify the predominant factors that may incur the occurrence of rock bursts.The results show that the population-based metaheuristic algorithms have a good ability to search out the optimal hyperparameters of the LightGBM model.The developed LightGBM model yields promising performance in predicting the intensity of rock bursts,with which accuracy on training and testing sets are 0.972 and 0.944,respectively.The sensitivity analysis discloses that the risk of occurring rock burst is significantly sensitive to three factors:uniaxial compressive strength(σc),stress concentration factor(SCF),and elastic strain energy index(Wet).Moreover,this study clarifies the particular impact of these three factors on the intensity of rock bursts through the partial dependence plot.展开更多
The current economic conditions have entailed the use of rational method and techniques and research and application of new techniques by utilizing advancements in technology in the field of production as well as in e...The current economic conditions have entailed the use of rational method and techniques and research and application of new techniques by utilizing advancements in technology in the field of production as well as in every field. Excess cost control requires to be maintained throughout the project life of building beginning from the initial stages of design. Scrutinizing the project well and considering all possible alternatives particularly in design stage are important for achieving optimum cost. In this study, how the principles of VE （value engineering） are applied in construction projects is explained, and by covering Bregana-Zagreb-Dubrovnik Motorway construction in Croatia by BECHTEL -ENKA joint venture as the sample project, practices of VE in this project are described. The satisfactory results of time and cost saving are achieved by applying value engineering principles through the VE team during the project preparation phase and project revision phase. Approximately 43,000,0005 and 12 months of time were saved in total thanks to all these VE works. This saving provided builder company with 6% financial saving and 17% work time reduction.展开更多
The railway engineering major shows extremely strong applicability,with the internationalization of railway engineering teaching and communication,how to solve the problem of cultivating the international students of ...The railway engineering major shows extremely strong applicability,with the internationalization of railway engineering teaching and communication,how to solve the problem of cultivating the international students of the railway engineering major experimental teaching is a core problem that the railway engineering majors in universities need to solve at this stage.Through reform,a new type of experimental teaching system for railway engineering specialty was constructed,that is,the experimental course system and content system determined by the international students training program were taken as the core,the construction of teachers,experimental facilities,practice bases and other conditions as the basis,and the system construction and operation organization to build an organic whole composed of four elements for guarantee.It is closely integrated with the theoretical teaching system and relatively independent.It guarantees the realization of the goal of international students training.And it can integrate and optimize the experimental teaching links,content,methods and evaluation system,and build a“gradual experimentprofessional experiment-comprehensive experiment”progressive gradient experiment teaching system.Form a benign pattern of collaborative training of laboratories,practice bases and scientific research bases,mutual promotion of teaching and scientific research,and effectively promote the improvement of students’experimental innovation ability.展开更多
Virtual simulation teaching is an addendum to the experimental teaching mode of railway engineering,and the two teaching methods complement each other and merge with each other.In view of the current research,there is...Virtual simulation teaching is an addendum to the experimental teaching mode of railway engineering,and the two teaching methods complement each other and merge with each other.In view of the current research,there is little discussion about the integration path of the two above.Based on the connotation and design of virtual simulation teaching,this research systematically expounds the integration of the real path and path optimization problems,and puts forward the railway engineering experimental teaching principles based on virtual simulation teaching.On the basis of this research,a virtual simulation experiment platform for vibration mechanics and its application in the floating slab vibration damping track was developed to make full use of three-dimensional modeling,virtual reality,human-computer interaction and other technologies,which can realistically simulate the vibration law and vibration damping effect of the rail transit system,and in the hope that the virtual simulation teaching can be widely used in the experimental teaching mode of railway engineering in the future.展开更多
Located downstream the Kupang Catchment in Indonesia,Pekalongan faces significant land subsidence issues,leading to severe coastal flooding.This study aimed to assess the impact of climate change on future flow regime...Located downstream the Kupang Catchment in Indonesia,Pekalongan faces significant land subsidence issues,leading to severe coastal flooding.This study aimed to assess the impact of climate change on future flow regimes and hydrological extremes to inform long-term water resources management strategies for the Kupang Catchment.Utilizing precipitation and air temperature data from general circulation models in the Coupled Model Intercomparison Project 6(CMIP6)and employing bias correction techniques,the Soil and Water Assessment Tool(SWAT)hydrological model was employed to analyze climate-induced changes in hydrological fluxes,specifically streamflow.Results indicated a consistent increase in monthly streamflow during the wet season,with a substantial rise of 22.8%,alongside a slight decrease of 18.0%during the dry season.Moreover,both the frequency and severity of extremely low and high flows were projected to intensify by approximately 50%and 70%,respectively,for a 20-year return period,suggesting heightened flood and drought risks in the future.The observed declining trend in low flow,by up to 11%,indicated the potential for long-term groundwater depletion exacerbating the threat of land subsidence and coastal flooding,especially in areas with inadequate surface water management policies and infrastructure.展开更多
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 lear...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 AB-RBFN.Additionally,a traditional weighted method,Information Value(IV),and a benchmark machine learning(ML)model,Multilayer Perceptron Neural Network(MLP),were employed for comparison and validation.The 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 roads.These factors were instrumental in predicting the output variable,which was the probability of landslide occurrence.Statistical analysis of the models’performance indicated that the DG-RBFN model,with an Area Under ROC Curve(AUC)of 0.931,outperformed the other models.The 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 0.926.These 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.展开更多
Open caissons are widely used in foundation engineering because of their load-bearing efficiency and adaptability in diverse soil conditions.However,accurately predicting their undrained bearing capacity in layered so...Open caissons are widely used in foundation engineering because of their load-bearing efficiency and adaptability in diverse soil conditions.However,accurately predicting their undrained bearing capacity in layered soils remains a complex challenge.This study presents a novel application of five ensemble machine(ML)algorithms-random forest(RF),gradient boosting machine(GBM),extreme gradient boosting(XGBoost),adaptive boosting(AdaBoost),and categorical boosting(CatBoost)-to predict the undrained bearing capacity factor(Nc)of circular open caissons embedded in two-layered clay on the basis of results from finite element limit analysis(FELA).The input dataset consists of 1188 numerical simulations using the Tresca failure criterion,varying in geometrical and soil parameters.The FELA was performed via OptumG2 software with adaptive meshing techniques and verified against existing benchmark studies.The ML models were trained on 70% of the dataset and tested on the remaining 30%.Their performance was evaluated using six statistical metrics:coefficient of determination(R²),mean absolute error(MAE),root mean squared error(RMSE),index of scatter(IOS),RMSE-to-standard deviation ratio(RSR),and variance explained factor(VAF).The results indicate that all the models achieved high accuracy,with R²values exceeding 97.6%and RMSE values below 0.02.Among them,AdaBoost and CatBoost consistently outperformed the other methods across both the training and testing datasets,demonstrating superior generalizability and robustness.The proposed ML framework offers an efficient,accurate,and data-driven alternative to traditional methods for estimating caisson capacity in stratified soils.This approach can aid in reducing computational costs while improving reliability in the early stages of foundation design.展开更多
The ability to accurately predict urban traffic flows is crucial for optimising city operations.Consequently,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to u...The ability to accurately predict urban traffic flows is crucial for optimising city operations.Consequently,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to understand complex mobility patterns.Deep learning techniques,such as graph neural networks(GNNs),are popular for their ability to capture spatio-temporal dependencies.However,these models often become overly complex due to the large number of hyper-parameters involved.In 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 tasks.The 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 accuracy.On 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 min.Similarly,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 periods.The 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 intervals.These 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.展开更多
This study investigates the innovative reuse of sewage sludge with eco-friendly alkaline solutes to improve clayey soil without conventional cementitious binders.The unconfined compressive strength(UCS)was the main cr...This study investigates the innovative reuse of sewage sludge with eco-friendly alkaline solutes to improve clayey soil without conventional cementitious binders.The unconfined compressive strength(UCS)was the main criterion to assess the quality and effectiveness of the proposed solutions,as this test was performed to measure the strength of the stabilized clay by varying binders’dosages and curing times.Moreover,the direct shear test(DST)was used to investigate the Mohr-Coulomb parameters of the treated soil.Microstructure observations of the natural and treated soil were conducted using scanning electron microscope(SEM),energy-dispersive spectroscopy(EDS),and FTIR.Furthermore,toxicity characteristic leaching procedure(TCLP)tests were performed on the treated soil to investigate the leachability of metals.According to the results,using 2.5%of sewage sludge activated by NaOH and Na_(2)SiO_(3)increases the UCS values from 176 kPa to 1.46 MPa after 7 d and 56 d of curing,respectively.The results of the DST indicate that sewage sludge as a precursor increases cohesion and enhances frictional resistance,thereby improving the Mohr-Coulomb parameters of the stabilized soil.The SEM micrographs show that alkali-activated sewage sludge increases the integrity and reduces the cavity volumes in the stabilized soil.Moreover,TCLP tests revealed that the solubility of metals in the treated soil alkaliactivated by sewage sludge significantly decreased.This study suggests that using sewage sludge can replace cement and lime in ground improvement,improve the circular economy,and reduce the carbon footprint of construction projects.展开更多
The precise identification of quartz minerals is crucial in mineralogy and geology due to their widespread occurrence and industrial significance.Traditional methods of quartz identification in thin sections are labor...The precise identification of quartz minerals is crucial in mineralogy and geology due to their widespread occurrence and industrial significance.Traditional methods of quartz identification in thin sections are labor-intensive and require significant expertise,often complicated by the coexistence of other minerals.This study presents a novel approach leveraging deep learning techniques combined with hyperspectral imaging to automate the identification process of quartz minerals.The utilizied four advanced deep learning models—PSPNet,U-Net,FPN,and LinkNet—has significant advancements in efficiency and accuracy.Among these models,PSPNet exhibited superior performance,achieving the highest intersection over union(IoU)scores and demonstrating exceptional reliability in segmenting quartz minerals,even in complex scenarios.The study involved a comprehensive dataset of 120 thin sections,encompassing 2470 hyperspectral images prepared from 20 rock samples.Expert-reviewed masks were used for model training,ensuring robust segmentation results.This automated approach not only expedites the recognition process but also enhances reliability,providing a valuable tool for geologists and advancing the field of mineralogical analysis.展开更多
This study investigates the seismic response mitigation of an offshore jacket platform via a novel damping system,the bidirectional tuned liquid column gas damper(BTLCGD).To efficiently model the complex platform stru...This study investigates the seismic response mitigation of an offshore jacket platform via a novel damping system,the bidirectional tuned liquid column gas damper(BTLCGD).To efficiently model the complex platform structure,an equivalent single degree of freedom approach was employed.Since the mass contribution of the first mode of the platform is more than 90%,this simplification significantly reduces the computational burden while maintaining accuracy.Therefore,this structure was modeled and analyzed on a scale of 1 to 36 using the Froudian law.To address the limitations of conventional tuned liquid column gas dampers(TLCGDs),which are susceptible to the directionality of seismic excitations,BTLCGD was proposed.This innovative damper is designed to operate effectively in two orthogonal directions,thereby improving seismic performance.Through numerical simulations,the performance of both TLCGD and BTLCGD was evaluated under seismic loading.The results demonstrated that BTLCGD significantly outperforms TLCGD in terms of reducing structural responses,particularly in the direction where TLCGD is ineffective.Furthermore,BTLCGD offers advantages in terms of installation and space requirements.The results of this research offer valuable perspectives into the design and implementation of effective damping systems for offshore structures,contributing to enhanced structural integrity and safety.展开更多
The growing importance of maintaining and extending the functional lifespan of reinforced concrete structures has resulted in an increased emphasis on non-destructive testing techniques as essential tools for evaluati...The growing importance of maintaining and extending the functional lifespan of reinforced concrete structures has resulted in an increased emphasis on non-destructive testing techniques as essential tools for evaluating structural conditions.Non-destructive testing procedures offer a notable benefit in assessing the uniformity,homogeneity,ability to withstand compression,durability,and degree of corrosion in reinforcing bars within reinforced concrete structures.This study aimed to evaluate the existing condition of partially constructed residential buildings in Rewari district,located in the state of Haryana.The reinforced concrete structure of the building had been completed eight years ago,however,the project was abruptly stopped.Prior to recommencing the construction,it is important to assess the present state of the structure in order to evaluate the deterioration in Reinforced Cement Concrete(RCC).The building’s state was evaluated by visually inspecting the building,conducting on-site examinations,and analyzing samples in a laboratory.The findings emphasize the assessment of the robustness and durability of concrete to ascertain the degree of deterioration and degradation in the structure.The study incorporates visual inspection,and non-destructive evaluation utilizing different instruments to evaluate the corrosion condition of reinforcing bars.In addition,selected RCC columns,beams,and slabs undergo chemical testing.It has been observed that the strength results and chemical results were within permissible limits.展开更多
Many researchers have focused on the behavior of fiber-reinforced concrete(FRC)in the construction of various defensive structures to resist against impact forces resulting from explosions and projectiles.However,the ...Many researchers have focused on the behavior of fiber-reinforced concrete(FRC)in the construction of various defensive structures to resist against impact forces resulting from explosions and projectiles.However,the lack of sufficient research regarding the resistance of functionally graded fiber-reinforced concrete against projectile impacts has resulted in a limited understanding of the performance of this concrete type,which is necessary for the design and construction of structures requiring great resistance against external threats.Here,the performance of functionally graded fiber-reinforced concrete against projectile impacts was investigated experimentally using a(two-stage light)gas gun and a drop weight testing machine.For this objective,12 mix designs,with which 35 cylindrical specimens and 30 slab specimens were made,were prepared,and the main variables were the magnetite aggregate vol%(55%)replacing natural coarse aggregate,steel fiber vol%,and steel fiber type(3D and 5D).The fibers were added at six vol%of 0%,0.5%,0.75%,1%,1.25%,and 1.5%in 10 specimen series(three identical specimens per each series)with dimensions of 40×40×7.5 cm and functional grading(three layers),and the manufactured specimens were subjected to the drop weight impact and projectile penetration tests by the drop weight testing machine and gas gun,respectively,to assess their performance.Parameters under study included the compressive strength,destruction level,and penetration depth.The experimental results demonstrate that using the magnetite aggregate instead of the natural coarse aggregate elevated the compressive strength of the concrete by 61%.In the tests by the drop weight machine,it was observed that by increasing the total vol%of the fibers,especially by increasing the fiber content in the outer layers(impact surface),the cracking resistance and energy absorption increased by around 100%.Note that the fiber geometry had little effect on the energy absorption in the drop weight test.Investigating the optimum specimens showed that using 3D steel fibers at a total fiber content of 1 vol%,consisting of a layered grading of 1.5 vol%,0 vol%,and 1.5 vol%,improved the penetration depth by 76%and lowered the destruction level by 85%.In addition,incorporating the 5D steel fibers at a total fiber content of 1 vol%,consisting of the layered fiber contents of 1.5%,0%,and 1.5%,improved the projectile penetration depth by 50%and lowered the damage level by 61%compared with the case of using the 3D fibers.展开更多
Soil liquefaction,a seismic-induced phenomenon,is of significant concern in geotechnical engineering due to its potential to cause severe structural damage and ground instability during earthquakes.This study explores...Soil liquefaction,a seismic-induced phenomenon,is of significant concern in geotechnical engineering due to its potential to cause severe structural damage and ground instability during earthquakes.This study explores the prediction of the Liquefaction Severity Index(LSI)by integrating extensive borehole investigation data with seismic records from the Kahramanmara?(M_(w)7.8)and Hatay(M_(w)6.4)earthquakes that occurred in 2023.Nine machine learning models,Random Forest(RF),M5P,REPTree,IBk,Random Tree(RT),Gaussian Processes(GP),SMOreg,Locally Weighted Learning(LWL),and Linear Regression(LR),were employed with 10-fold cross-validation to ensure reliable predictions.Twelve geotechnical and seismic parameters,groundwater level,earthquake magnitude,peak ground acceleration,V_(s30),dominant frequency,dominant period,longitudinal wave velocity,dynamic modulus of elasticity,dynamic shear modulus,modulus of incompressibility,standard penetration test(SPT)values,and cyclic stress ratio(CSR)values,were utilized as inputs.The analysis results were evaluated with respect to RMSE,MAE,R2,RAE,P/M,error category limits,Taylor diagram,and relative importance of input parameters.Among the models,Random Forest outperformed with an R2 of 0.94,MAE of 2.35,with minimal prediction errors,followed by M5P and REPTree.Error analysis indicated that 80%of Random Forest and REPTree predictions fell within±7,while M5P showed slightly higher variability.Model-based feature ranking demonstrated that Cyclic Stress Ratio(CSR),Ground Water Level(GWL),and Standard Penetration Test(SPT)value emerged as dominant predictors.These findings highlight the study’s contribution to developing a reliable,datadriven framework for LSI prediction,offering a robust basis for improving site-specific liquefaction risk assessment and informed geotechnical decisionmaking in future seismic events.展开更多
Concrete is one of the most important elements in building construction.However,concrete used in construction is susceptible to damage due to corrosion.The influence of corrosive substances causes changes in the reinf...Concrete is one of the most important elements in building construction.However,concrete used in construction is susceptible to damage due to corrosion.The influence of corrosive substances causes changes in the reinforcing steel and affects the strength of the structure.The repair method is one approach to overcome this problem.This research aims to determine the effect of grouting and jacketing repairs on corroded concrete.The concrete used has dimensions of 15 cm×15 cm×60 cm with planned corrosion variations of 50%,60%,and 70%.The test objects were tested using the Non-Destructive Testing(NDT)method using Ultrasonic Pulse Velocity(UPV).The test results show that the average speed of normal concrete is 5070 m/s,while the lowest average speed is 3070 m/s on the 70%planned corrosion test object.The test object was then given a load of 1600 kgf.At this stage,there is a decrease in speed and wave shape with the lowest average speed obtained at 2753 m/s.The repair method is an effort to restore concrete performance by using grouting and jacketing.Grouting is done by injecting mortar material into it.Jacketing involves adding thickness to the existing concrete layer with additional layers of concrete.After improvements were made,there was an improvement in the UPV test,with a peak speed value of 4910 m/s.Repairing concrete by filling cracks can improve concrete continuity and reduce waveform distortion,thereby increasing wave propagation speed.展开更多
Professional and trade skills are required for handling the construction related projects;Construction industries of the present day however lack useful information concerning different practices,patterns and trends i...Professional and trade skills are required for handling the construction related projects;Construction industries of the present day however lack useful information concerning different practices,patterns and trends involved in risk management.Considering this,the present study focuses on the aforementioned variables of risk management by quantitative analysis specifically in the domain of construction industry.This study has used IBM’s SPSS(Statistical Package for Social Sciences)version 25.0 to analyze the results.This study is an initiative to assess the impact of risk management in the construction sector of Jordan.It will assist the construction sector for exploring the limitations with respect to integrate effective risk management.A sense of competition will be developed through a comparison of risk factors of construction projects among the project stakeholders such as contractors should enhance their risk management practices.展开更多
Aging plays a critical role in determining the durability and long-term performance of asphalt pavements,as it is influenced by both external factors(e.g.,temperature,ultraviolet(UV)radiation,moisture,oxidative gases)...Aging plays a critical role in determining the durability and long-term performance of asphalt pavements,as it is influenced by both external factors(e.g.,temperature,ultraviolet(UV)radiation,moisture,oxidative gases)and internal factors such as binder composition.Although laboratory simulations of aging are well established for conventional bituminous binders,limited attention has been paid to replicating and evaluating aging processes in bio-based binders.This review provides a comprehensive analysis of current laboratory techniques for simulating and assessing binder aging,with a focus on two key areas:aging simulation protocols and evaluation methodologies.The analysis shows that although several efforts have been made to incorporate external aging factors into lab simulations,significant challenges persist,especially in the case of bio-based binders,which are characterized by a high variability in composition and limited understanding of their aging behavior.Current evaluation approaches also exhibit limitations.Improvements are needed in the molecular-level analysis of oxidation(e.g.,through more representative oxidation modelsin molecular dynamicssimulations),in the separation and quantification of binder constituents,and in the application of advanced techniques such as fluorescence microscopy to better characterize polymer dispersion.To enhance the reliability of laboratory simulations,future research should aim to improve the correlation between laboratory and field aging,define robust aging indexes,and refine characterization methods.These advancements are particularly critical for bio-based binders,whose performance is highly sensitive to aging and for which standard test protocols are still underdeveloped.A deeper understanding of aging mechanisms in both polymer-modified and biobased binders,along with improved analytical tools for assessing oxidative degradation and morphological changes,will be essential to support the development of sustainable,high-performance paving materials.展开更多
This research addresses the growing demand for high-performance protective materials against high-velocity projectile impacts.The performance of multi-layered steel fiber-reinforced mortar(SFRM)panels with varying thi...This research addresses the growing demand for high-performance protective materials against high-velocity projectile impacts.The performance of multi-layered steel fiber-reinforced mortar(SFRM)panels with varying thicknesses and air gaps,was experimentally investigated under single and repeated impacts of 7.62×51 mm bullets fired from a distance of 50 m.The impact events were recorded using a high-speed camera at 40000 fps.Panel performance was assessed in terms of failure modes,kinetic energy absorption,spalling diameter,and percentage of back-face damage area,and weight loss.Results showed that panel configuration significantly influenced performance.Panel P10,with 70 mm SFRM thickness and 20 mm air gaps,provided the highest resistance,dissipating 5223 J of kinetic energy and preventing back-face damage.In contrast,P7,which absorbed 4476 J,presented a back damage area percentage of 8.93%after three impacts.Weight loss analysis further confirmed durability improvements,with P10 showing only 1.53%cumulative loss compared to 3.26%in P7.The inclusion of wider air gaps enhanced energy dissipation and reduced damage.Comparison between single and repeated impacts demonstrated the sustained resistance of high-performance panels,with P10 maintaining minimal degradation across three consecutive impacts.These findings highlight the potential of multi-layer SFRM panels to enhance ballistic resistance,making them suitable for military,security,and civilian protective applications requiring long-term durability.展开更多
文摘Silica materials are located in various regions of Libya in large quantities and different mining conditions, so the purpose of this study is silica materials in the south-west of the Libyan region Edree in terms of quality and the possibility of using in various engineering industries, particularly construction. The results show that the sands of silica presented in Edree area are of a high degree of purity, as the percentage of silicon （SIO2） reached 99.5%, the percentage of impurities was negligible and represented in some chemical elements in different proportions, such as calcium 0.224%, sodium 0.004%, iron 0.0006%, zinc 0.0003%, boron 0.0003%, potassium 0.0001%, manganese 0.0001% and magnesium 0.0001%, making these materials very suitable in the manufacture of all types of glass, crystal and semi-crystalline high-quality without needing any important treatment, as well as its suitability as a refinement in manufacture of templates metal castings in addition to the possibility of use in the manufacture of cement, building materials and as a filler in paint and brick making and sand and concrete elements can also be used in electronic industries. A geological material of silica present in the form of a sequence of layers of clay and thin layers of sand stone and a large stock of high-quality near the surface, making mining operations of the type of surface and reduces the cost of extraction.
文摘In this study, the position of all major rill and gully erosion sites were located using hand held GPS （Global Positioning System） receiver during reconnaissance surveys. Based on severity rating and geopolitical considerations, six of the erosion gully sites were selected for monitoring. Control points were established around each of the gully sites using three Leica 500 dual frequency GPS receivers by method of DGPS （differential GPS） surveys. Detailed topographical survey of the gully sites was carried out using total stations. With the aid of SPOT satellite imageries in combination with total station data and GIS （geographic information system） location maps, contoured maps along with DEM （digital elevation model） were generated using ARCGIS 9.2 software. The morphological parameters of the gullies including depth, width, length and area of the gullies were determined. Volumetric estimate of the amount of soil loss from gully erosion was also carried out. Soil samples were recovered from the gully sites to determine their erodibility and other parameters to be used for soil loss modeling. The result of the studies was used as an indicator for determining the gully initiation point. Slope-area relationship and threshold of gully initiation was established. The minimum volume of soil loss occurred in gully No. 2 （Queen Ede）. The minimum AS^2 value was 345 while the maximum was 3,267.
文摘Rock bursts represent a formidable challenge in underground engineering,posing substantial risks to both infrastructure and human safety.These sudden and violent failures of rock masses are characterized by the rapid release of accumulated stress within the rock,leading to severe seismic events and structural damage.Therefore,the development of reliable prediction models for rock bursts is paramount to mitigating these hazards.This study aims to propose a tree-based model—a Light Gradient Boosting Machine(LightGBM)—to predict the intensity of rock bursts in underground engineering.322 actual rock burst cases are collected to constitute an exhaustive rock burst dataset,which serves to train the LightGBMmodel.Two population-basedmetaheuristic algorithms are used to optimize the hyperparameters of the LightGBM model.Finally,the sensitivity analysis is used to identify the predominant factors that may incur the occurrence of rock bursts.The results show that the population-based metaheuristic algorithms have a good ability to search out the optimal hyperparameters of the LightGBM model.The developed LightGBM model yields promising performance in predicting the intensity of rock bursts,with which accuracy on training and testing sets are 0.972 and 0.944,respectively.The sensitivity analysis discloses that the risk of occurring rock burst is significantly sensitive to three factors:uniaxial compressive strength(σc),stress concentration factor(SCF),and elastic strain energy index(Wet).Moreover,this study clarifies the particular impact of these three factors on the intensity of rock bursts through the partial dependence plot.
文摘The current economic conditions have entailed the use of rational method and techniques and research and application of new techniques by utilizing advancements in technology in the field of production as well as in every field. Excess cost control requires to be maintained throughout the project life of building beginning from the initial stages of design. Scrutinizing the project well and considering all possible alternatives particularly in design stage are important for achieving optimum cost. In this study, how the principles of VE （value engineering） are applied in construction projects is explained, and by covering Bregana-Zagreb-Dubrovnik Motorway construction in Croatia by BECHTEL -ENKA joint venture as the sample project, practices of VE in this project are described. The satisfactory results of time and cost saving are achieved by applying value engineering principles through the VE team during the project preparation phase and project revision phase. Approximately 43,000,0005 and 12 months of time were saved in total thanks to all these VE works. This saving provided builder company with 6% financial saving and 17% work time reduction.
文摘The railway engineering major shows extremely strong applicability,with the internationalization of railway engineering teaching and communication,how to solve the problem of cultivating the international students of the railway engineering major experimental teaching is a core problem that the railway engineering majors in universities need to solve at this stage.Through reform,a new type of experimental teaching system for railway engineering specialty was constructed,that is,the experimental course system and content system determined by the international students training program were taken as the core,the construction of teachers,experimental facilities,practice bases and other conditions as the basis,and the system construction and operation organization to build an organic whole composed of four elements for guarantee.It is closely integrated with the theoretical teaching system and relatively independent.It guarantees the realization of the goal of international students training.And it can integrate and optimize the experimental teaching links,content,methods and evaluation system,and build a“gradual experimentprofessional experiment-comprehensive experiment”progressive gradient experiment teaching system.Form a benign pattern of collaborative training of laboratories,practice bases and scientific research bases,mutual promotion of teaching and scientific research,and effectively promote the improvement of students’experimental innovation ability.
基金The research is financially supported by First-class Undergraduate Course Funding Project in Hunan Province-Virtual Simulation Experimental Teaching Course(Xiang Jiao Tong[2021]No.28),Hunan Engineering Teaching Team)(Xiang Jiao Tong[2019]No.370)National Experimental Teaching Center of Civil Engineering Virtual Simulation(Central South University)Open Project(202001)Education and Teaching Reform Project of Central South University(2020jy063),which is gratefully acknowledged by the authors.
文摘Virtual simulation teaching is an addendum to the experimental teaching mode of railway engineering,and the two teaching methods complement each other and merge with each other.In view of the current research,there is little discussion about the integration path of the two above.Based on the connotation and design of virtual simulation teaching,this research systematically expounds the integration of the real path and path optimization problems,and puts forward the railway engineering experimental teaching principles based on virtual simulation teaching.On the basis of this research,a virtual simulation experiment platform for vibration mechanics and its application in the floating slab vibration damping track was developed to make full use of three-dimensional modeling,virtual reality,human-computer interaction and other technologies,which can realistically simulate the vibration law and vibration damping effect of the rail transit system,and in the hope that the virtual simulation teaching can be widely used in the experimental teaching mode of railway engineering in the future.
基金supported by the funding Riset Unggulan Daerah 2022 of the Bureau of Development Planning and Research in Central Java Province(BAPPEDA Provinsi Jawa Tengah).
文摘Located downstream the Kupang Catchment in Indonesia,Pekalongan faces significant land subsidence issues,leading to severe coastal flooding.This study aimed to assess the impact of climate change on future flow regimes and hydrological extremes to inform long-term water resources management strategies for the Kupang Catchment.Utilizing precipitation and air temperature data from general circulation models in the Coupled Model Intercomparison Project 6(CMIP6)and employing bias correction techniques,the Soil and Water Assessment Tool(SWAT)hydrological model was employed to analyze climate-induced changes in hydrological fluxes,specifically streamflow.Results indicated a consistent increase in monthly streamflow during the wet season,with a substantial rise of 22.8%,alongside a slight decrease of 18.0%during the dry season.Moreover,both the frequency and severity of extremely low and high flows were projected to intensify by approximately 50%and 70%,respectively,for a 20-year return period,suggesting heightened flood and drought risks in the future.The observed declining trend in low flow,by up to 11%,indicated the potential for long-term groundwater depletion exacerbating the threat of land subsidence and coastal flooding,especially in areas with inadequate surface water management policies and infrastructure.
基金the University of Transport Technology under the project entitled“Application of Machine Learning Algorithms in Landslide Susceptibility Mapping in Mountainous Areas”with grant number DTTD2022-16.
文摘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 AB-RBFN.Additionally,a traditional weighted method,Information Value(IV),and a benchmark machine learning(ML)model,Multilayer Perceptron Neural Network(MLP),were employed for comparison and validation.The 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 roads.These factors were instrumental in predicting the output variable,which was the probability of landslide occurrence.Statistical analysis of the models’performance indicated that the DG-RBFN model,with an Area Under ROC Curve(AUC)of 0.931,outperformed the other models.The 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 0.926.These 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.
文摘Open caissons are widely used in foundation engineering because of their load-bearing efficiency and adaptability in diverse soil conditions.However,accurately predicting their undrained bearing capacity in layered soils remains a complex challenge.This study presents a novel application of five ensemble machine(ML)algorithms-random forest(RF),gradient boosting machine(GBM),extreme gradient boosting(XGBoost),adaptive boosting(AdaBoost),and categorical boosting(CatBoost)-to predict the undrained bearing capacity factor(Nc)of circular open caissons embedded in two-layered clay on the basis of results from finite element limit analysis(FELA).The input dataset consists of 1188 numerical simulations using the Tresca failure criterion,varying in geometrical and soil parameters.The FELA was performed via OptumG2 software with adaptive meshing techniques and verified against existing benchmark studies.The ML models were trained on 70% of the dataset and tested on the remaining 30%.Their performance was evaluated using six statistical metrics:coefficient of determination(R²),mean absolute error(MAE),root mean squared error(RMSE),index of scatter(IOS),RMSE-to-standard deviation ratio(RSR),and variance explained factor(VAF).The results indicate that all the models achieved high accuracy,with R²values exceeding 97.6%and RMSE values below 0.02.Among them,AdaBoost and CatBoost consistently outperformed the other methods across both the training and testing datasets,demonstrating superior generalizability and robustness.The proposed ML framework offers an efficient,accurate,and data-driven alternative to traditional methods for estimating caisson capacity in stratified soils.This approach can aid in reducing computational costs while improving reliability in the early stages of foundation design.
文摘The ability to accurately predict urban traffic flows is crucial for optimising city operations.Consequently,various methods for forecasting urban traffic have been developed,focusing on analysing historical data to understand complex mobility patterns.Deep learning techniques,such as graph neural networks(GNNs),are popular for their ability to capture spatio-temporal dependencies.However,these models often become overly complex due to the large number of hyper-parameters involved.In 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 tasks.The 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 accuracy.On 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 min.Similarly,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 periods.The 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 intervals.These 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.
文摘This study investigates the innovative reuse of sewage sludge with eco-friendly alkaline solutes to improve clayey soil without conventional cementitious binders.The unconfined compressive strength(UCS)was the main criterion to assess the quality and effectiveness of the proposed solutions,as this test was performed to measure the strength of the stabilized clay by varying binders’dosages and curing times.Moreover,the direct shear test(DST)was used to investigate the Mohr-Coulomb parameters of the treated soil.Microstructure observations of the natural and treated soil were conducted using scanning electron microscope(SEM),energy-dispersive spectroscopy(EDS),and FTIR.Furthermore,toxicity characteristic leaching procedure(TCLP)tests were performed on the treated soil to investigate the leachability of metals.According to the results,using 2.5%of sewage sludge activated by NaOH and Na_(2)SiO_(3)increases the UCS values from 176 kPa to 1.46 MPa after 7 d and 56 d of curing,respectively.The results of the DST indicate that sewage sludge as a precursor increases cohesion and enhances frictional resistance,thereby improving the Mohr-Coulomb parameters of the stabilized soil.The SEM micrographs show that alkali-activated sewage sludge increases the integrity and reduces the cavity volumes in the stabilized soil.Moreover,TCLP tests revealed that the solubility of metals in the treated soil alkaliactivated by sewage sludge significantly decreased.This study suggests that using sewage sludge can replace cement and lime in ground improvement,improve the circular economy,and reduce the carbon footprint of construction projects.
文摘The precise identification of quartz minerals is crucial in mineralogy and geology due to their widespread occurrence and industrial significance.Traditional methods of quartz identification in thin sections are labor-intensive and require significant expertise,often complicated by the coexistence of other minerals.This study presents a novel approach leveraging deep learning techniques combined with hyperspectral imaging to automate the identification process of quartz minerals.The utilizied four advanced deep learning models—PSPNet,U-Net,FPN,and LinkNet—has significant advancements in efficiency and accuracy.Among these models,PSPNet exhibited superior performance,achieving the highest intersection over union(IoU)scores and demonstrating exceptional reliability in segmenting quartz minerals,even in complex scenarios.The study involved a comprehensive dataset of 120 thin sections,encompassing 2470 hyperspectral images prepared from 20 rock samples.Expert-reviewed masks were used for model training,ensuring robust segmentation results.This automated approach not only expedites the recognition process but also enhances reliability,providing a valuable tool for geologists and advancing the field of mineralogical analysis.
文摘This study investigates the seismic response mitigation of an offshore jacket platform via a novel damping system,the bidirectional tuned liquid column gas damper(BTLCGD).To efficiently model the complex platform structure,an equivalent single degree of freedom approach was employed.Since the mass contribution of the first mode of the platform is more than 90%,this simplification significantly reduces the computational burden while maintaining accuracy.Therefore,this structure was modeled and analyzed on a scale of 1 to 36 using the Froudian law.To address the limitations of conventional tuned liquid column gas dampers(TLCGDs),which are susceptible to the directionality of seismic excitations,BTLCGD was proposed.This innovative damper is designed to operate effectively in two orthogonal directions,thereby improving seismic performance.Through numerical simulations,the performance of both TLCGD and BTLCGD was evaluated under seismic loading.The results demonstrated that BTLCGD significantly outperforms TLCGD in terms of reducing structural responses,particularly in the direction where TLCGD is ineffective.Furthermore,BTLCGD offers advantages in terms of installation and space requirements.The results of this research offer valuable perspectives into the design and implementation of effective damping systems for offshore structures,contributing to enhanced structural integrity and safety.
文摘The growing importance of maintaining and extending the functional lifespan of reinforced concrete structures has resulted in an increased emphasis on non-destructive testing techniques as essential tools for evaluating structural conditions.Non-destructive testing procedures offer a notable benefit in assessing the uniformity,homogeneity,ability to withstand compression,durability,and degree of corrosion in reinforcing bars within reinforced concrete structures.This study aimed to evaluate the existing condition of partially constructed residential buildings in Rewari district,located in the state of Haryana.The reinforced concrete structure of the building had been completed eight years ago,however,the project was abruptly stopped.Prior to recommencing the construction,it is important to assess the present state of the structure in order to evaluate the deterioration in Reinforced Cement Concrete(RCC).The building’s state was evaluated by visually inspecting the building,conducting on-site examinations,and analyzing samples in a laboratory.The findings emphasize the assessment of the robustness and durability of concrete to ascertain the degree of deterioration and degradation in the structure.The study incorporates visual inspection,and non-destructive evaluation utilizing different instruments to evaluate the corrosion condition of reinforcing bars.In addition,selected RCC columns,beams,and slabs undergo chemical testing.It has been observed that the strength results and chemical results were within permissible limits.
文摘Many researchers have focused on the behavior of fiber-reinforced concrete(FRC)in the construction of various defensive structures to resist against impact forces resulting from explosions and projectiles.However,the lack of sufficient research regarding the resistance of functionally graded fiber-reinforced concrete against projectile impacts has resulted in a limited understanding of the performance of this concrete type,which is necessary for the design and construction of structures requiring great resistance against external threats.Here,the performance of functionally graded fiber-reinforced concrete against projectile impacts was investigated experimentally using a(two-stage light)gas gun and a drop weight testing machine.For this objective,12 mix designs,with which 35 cylindrical specimens and 30 slab specimens were made,were prepared,and the main variables were the magnetite aggregate vol%(55%)replacing natural coarse aggregate,steel fiber vol%,and steel fiber type(3D and 5D).The fibers were added at six vol%of 0%,0.5%,0.75%,1%,1.25%,and 1.5%in 10 specimen series(three identical specimens per each series)with dimensions of 40×40×7.5 cm and functional grading(three layers),and the manufactured specimens were subjected to the drop weight impact and projectile penetration tests by the drop weight testing machine and gas gun,respectively,to assess their performance.Parameters under study included the compressive strength,destruction level,and penetration depth.The experimental results demonstrate that using the magnetite aggregate instead of the natural coarse aggregate elevated the compressive strength of the concrete by 61%.In the tests by the drop weight machine,it was observed that by increasing the total vol%of the fibers,especially by increasing the fiber content in the outer layers(impact surface),the cracking resistance and energy absorption increased by around 100%.Note that the fiber geometry had little effect on the energy absorption in the drop weight test.Investigating the optimum specimens showed that using 3D steel fibers at a total fiber content of 1 vol%,consisting of a layered grading of 1.5 vol%,0 vol%,and 1.5 vol%,improved the penetration depth by 76%and lowered the destruction level by 85%.In addition,incorporating the 5D steel fibers at a total fiber content of 1 vol%,consisting of the layered fiber contents of 1.5%,0%,and 1.5%,improved the projectile penetration depth by 50%and lowered the damage level by 61%compared with the case of using the 3D fibers.
基金supported by Osmaniye Korkut Ata University Scientific Research Projects Unit(Project No:OKüBAP-2024-PT1-015)。
文摘Soil liquefaction,a seismic-induced phenomenon,is of significant concern in geotechnical engineering due to its potential to cause severe structural damage and ground instability during earthquakes.This study explores the prediction of the Liquefaction Severity Index(LSI)by integrating extensive borehole investigation data with seismic records from the Kahramanmara?(M_(w)7.8)and Hatay(M_(w)6.4)earthquakes that occurred in 2023.Nine machine learning models,Random Forest(RF),M5P,REPTree,IBk,Random Tree(RT),Gaussian Processes(GP),SMOreg,Locally Weighted Learning(LWL),and Linear Regression(LR),were employed with 10-fold cross-validation to ensure reliable predictions.Twelve geotechnical and seismic parameters,groundwater level,earthquake magnitude,peak ground acceleration,V_(s30),dominant frequency,dominant period,longitudinal wave velocity,dynamic modulus of elasticity,dynamic shear modulus,modulus of incompressibility,standard penetration test(SPT)values,and cyclic stress ratio(CSR)values,were utilized as inputs.The analysis results were evaluated with respect to RMSE,MAE,R2,RAE,P/M,error category limits,Taylor diagram,and relative importance of input parameters.Among the models,Random Forest outperformed with an R2 of 0.94,MAE of 2.35,with minimal prediction errors,followed by M5P and REPTree.Error analysis indicated that 80%of Random Forest and REPTree predictions fell within±7,while M5P showed slightly higher variability.Model-based feature ranking demonstrated that Cyclic Stress Ratio(CSR),Ground Water Level(GWL),and Standard Penetration Test(SPT)value emerged as dominant predictors.These findings highlight the study’s contribution to developing a reliable,datadriven framework for LSI prediction,offering a robust basis for improving site-specific liquefaction risk assessment and informed geotechnical decisionmaking in future seismic events.
基金supported by the Ministry of Education,Culture,Research,and Technology(Indonesia),Grant number 107/E5/PG.02.00.PL/2024,AZ.
文摘Concrete is one of the most important elements in building construction.However,concrete used in construction is susceptible to damage due to corrosion.The influence of corrosive substances causes changes in the reinforcing steel and affects the strength of the structure.The repair method is one approach to overcome this problem.This research aims to determine the effect of grouting and jacketing repairs on corroded concrete.The concrete used has dimensions of 15 cm×15 cm×60 cm with planned corrosion variations of 50%,60%,and 70%.The test objects were tested using the Non-Destructive Testing(NDT)method using Ultrasonic Pulse Velocity(UPV).The test results show that the average speed of normal concrete is 5070 m/s,while the lowest average speed is 3070 m/s on the 70%planned corrosion test object.The test object was then given a load of 1600 kgf.At this stage,there is a decrease in speed and wave shape with the lowest average speed obtained at 2753 m/s.The repair method is an effort to restore concrete performance by using grouting and jacketing.Grouting is done by injecting mortar material into it.Jacketing involves adding thickness to the existing concrete layer with additional layers of concrete.After improvements were made,there was an improvement in the UPV test,with a peak speed value of 4910 m/s.Repairing concrete by filling cracks can improve concrete continuity and reduce waveform distortion,thereby increasing wave propagation speed.
文摘Professional and trade skills are required for handling the construction related projects;Construction industries of the present day however lack useful information concerning different practices,patterns and trends involved in risk management.Considering this,the present study focuses on the aforementioned variables of risk management by quantitative analysis specifically in the domain of construction industry.This study has used IBM’s SPSS(Statistical Package for Social Sciences)version 25.0 to analyze the results.This study is an initiative to assess the impact of risk management in the construction sector of Jordan.It will assist the construction sector for exploring the limitations with respect to integrate effective risk management.A sense of competition will be developed through a comparison of risk factors of construction projects among the project stakeholders such as contractors should enhance their risk management practices.
文摘Aging plays a critical role in determining the durability and long-term performance of asphalt pavements,as it is influenced by both external factors(e.g.,temperature,ultraviolet(UV)radiation,moisture,oxidative gases)and internal factors such as binder composition.Although laboratory simulations of aging are well established for conventional bituminous binders,limited attention has been paid to replicating and evaluating aging processes in bio-based binders.This review provides a comprehensive analysis of current laboratory techniques for simulating and assessing binder aging,with a focus on two key areas:aging simulation protocols and evaluation methodologies.The analysis shows that although several efforts have been made to incorporate external aging factors into lab simulations,significant challenges persist,especially in the case of bio-based binders,which are characterized by a high variability in composition and limited understanding of their aging behavior.Current evaluation approaches also exhibit limitations.Improvements are needed in the molecular-level analysis of oxidation(e.g.,through more representative oxidation modelsin molecular dynamicssimulations),in the separation and quantification of binder constituents,and in the application of advanced techniques such as fluorescence microscopy to better characterize polymer dispersion.To enhance the reliability of laboratory simulations,future research should aim to improve the correlation between laboratory and field aging,define robust aging indexes,and refine characterization methods.These advancements are particularly critical for bio-based binders,whose performance is highly sensitive to aging and for which standard test protocols are still underdeveloped.A deeper understanding of aging mechanisms in both polymer-modified and biobased binders,along with improved analytical tools for assessing oxidative degradation and morphological changes,will be essential to support the development of sustainable,high-performance paving materials.
基金funded by Thailand Research Fund under Research and Researchers for Industries (contract no. MSD62I0063)
文摘This research addresses the growing demand for high-performance protective materials against high-velocity projectile impacts.The performance of multi-layered steel fiber-reinforced mortar(SFRM)panels with varying thicknesses and air gaps,was experimentally investigated under single and repeated impacts of 7.62×51 mm bullets fired from a distance of 50 m.The impact events were recorded using a high-speed camera at 40000 fps.Panel performance was assessed in terms of failure modes,kinetic energy absorption,spalling diameter,and percentage of back-face damage area,and weight loss.Results showed that panel configuration significantly influenced performance.Panel P10,with 70 mm SFRM thickness and 20 mm air gaps,provided the highest resistance,dissipating 5223 J of kinetic energy and preventing back-face damage.In contrast,P7,which absorbed 4476 J,presented a back damage area percentage of 8.93%after three impacts.Weight loss analysis further confirmed durability improvements,with P10 showing only 1.53%cumulative loss compared to 3.26%in P7.The inclusion of wider air gaps enhanced energy dissipation and reduced damage.Comparison between single and repeated impacts demonstrated the sustained resistance of high-performance panels,with P10 maintaining minimal degradation across three consecutive impacts.These findings highlight the potential of multi-layer SFRM panels to enhance ballistic resistance,making them suitable for military,security,and civilian protective applications requiring long-term durability.
