Inverse reliability analysis and design for tunnel face stability considering soil spatial variability

The traditional deterministic analysis for tunnel face stability neglects the uncertainties of geotechnical parameters,while the simplified reliability analysis which models the potential uncertainties by means of random variables usually fails to account for soil spatial variability.To overcome these limitations,this study proposes an efficient framework for conducting reliability analysis and reliability-based design(RBD)of tunnel face stability in spatially variable soil strata.The three-dimensional(3D)rotational failure mechanism of the tunnel face is extended to account for the soil spatial variability,and a probabilistic framework is established by coupling the extended mechanism with the improved Hasofer-Lind-Rackwits-Fiessler recursive algorithm(iHLRF)as well as its inverse analysis formulation.The proposed framework allows for rapid and precise reliability analysis and RBD of tunnel face stability.To demonstrate the feasibility and efficacy of the proposed framework,an illustrative case of tunnelling in frictional soils is presented,where the soil's cohesion and friction angle are modelled as two anisotropic cross-correlated lognormal random fields.The results show that the proposed method can accurately estimate the failure probability(or reliability index)regarding the tunnel face stability and can efficiently determine the required supporting pressure for a target reliability index with soil spatial variability being taken into account.Furthermore,this study reveals the impact of various factors on the support pressure,including coefficient of variation,cross-correlation between cohesion and friction angle,as well as autocorrelation distance of spatially variable soil strata.The results also demonstrate the feasibility of using the forward and/or inverse first-order reliability method(FORM)in high-dimensional stochastic problems.It is hoped that this study may provide a practical and reliable framework for determining the stability of tunnels in complex soil strata.

Transformer-Aided Deep Double Dueling Spatial-Temporal Q-Network for Spatial Crowdsourcing Analysis

With the rapid development ofmobile Internet,spatial crowdsourcing has becomemore andmore popular.Spatial crowdsourcing consists of many different types of applications,such as spatial crowd-sensing services.In terms of spatial crowd-sensing,it collects and analyzes traffic sensing data from clients like vehicles and traffic lights to construct intelligent traffic prediction models.Besides collecting sensing data,spatial crowdsourcing also includes spatial delivery services like DiDi and Uber.Appropriate task assignment and worker selection dominate the service quality for spatial crowdsourcing applications.Previous research conducted task assignments via traditional matching approaches or using simple network models.However,advanced mining methods are lacking to explore the relationship between workers,task publishers,and the spatio-temporal attributes in tasks.Therefore,in this paper,we propose a Deep Double Dueling Spatial-temporal Q Network(D3SQN)to adaptively learn the spatialtemporal relationship between task,task publishers,and workers in a dynamic environment to achieve optimal allocation.Specifically,D3SQNis revised through reinforcement learning by adding a spatial-temporal transformer that can estimate the expected state values and action advantages so as to improve the accuracy of task assignments.Extensive experiments are conducted over real data collected fromDiDi and ELM,and the simulation results verify the effectiveness of our proposed models.

Geospatial Analysis of Urban Heat Island Effects and Tree Equity

In recent decades, Urban Heat Island Effects have become more pronounced and more widely examined. Despite great technological advances, our current societies still experience great spatial disparity in urban forest access. Urban Heat Island Effects are measurable phenomenon that are being experienced by the world’s most urbanized areas, including increased summer high temperatures and lower evapotranspiration from having impervious surfaces instead of vegetation and trees. Tree canopy cover is our natural mitigation tool that absorbs sunlight for photosynthesis, protects humans from incoming radiation, and releases cooling moisture into the air. Unfortunately, urban areas typically have low levels of vegetation. Vulnerable urban communities are lower-income areas of inner cities with less access to heat protection like air conditioners. This study uses mean evapotranspiration levels to assess the variability of urban heat island effects across the state of Tennessee. Results show that increased developed land surface cover in Tennessee creates measurable changes in atmospheric evapotranspiration. As a result, the mean evapotranspiration levels in areas with less tree vegetation are significantly lower than the surrounding forested areas. Central areas of urban cities in Tennessee had lower mean evapotranspiration recordings than surrounding areas with less development. This work demonstrates the need for increased tree canopy coverage.

Environmental Analysis Using Integrated GIS and Spatial Configurations in Israel

The scope for environmental analysis constitutes a critical factor in recent times, yet demanding importance due to the concerns of environmental sustainability. The study aims at analysing the prospects of implementing an integrated GIS and spatial configuration for environment analysis in Israel. The study adopts an empirical study design to consider the multi-dimensional utilisation of an integrated GIS and spatial configuration for environment analysis. The study considers the materials and methods of the GIS system modelling as well, consisting of satellite imagery, GPS-based location identification, Esri ArcGIS, CyberGIS, and BIM integration to present a comprehensive system for the environmental analysis of Israel. The results of the study indicate that the threats of natural disasters and climate change can be identified based on the synergy of spatial data within an integrated GIS modelling. In many cases, it is also used in collaboration with a BIM to ensure that planning and decision-making processes are sustainable, economically beneficial and environmentally considered. Thus, it is concluded that environmental analysis through the projection of visually represented satellite imagery within an integrated GIS with spatial configurations in Israel can minimise the conflicts between the infrastructural designs, human activities, and environmental sustainability.

Stochastic analysis of excavation-induced wall deflection and box culvert settlement considering spatial variability of soil stiffness

In this study, a three-dimensional (3D) finite element modelling (FEM) analysis is carried out to investigate the effects of soil spatial variability on the response of retaining walls and an adjacent box culvert due to a braced excavation. The spatial variability of soil stiffness is modelled using a variogram and calibrated by high-quality experimental data. Multiple random field samples (RFSs) of soil stiffness are generated using geostatistical analysis and mapped onto a finite element mesh for stochastic analysis of excavation-induced structural responses by Monte Carlo simulation. It is found that the spatial variability of soil stiffness can be described by an exponential variogram, and the associated vertical correlation length is varied from 1.3 m to 1.6 m. It also reveals that the spatial variability of soil stiffness has a significant effect on the variations of retaining wall deflections and box culvert settlements. The ignorance of spatial variability in 3D FEM can result in an underestimation of lateral wall deflections and culvert settlements. Thus, the stochastic structural responses obtained from the 3D analysis could serve as an effective aid for probabilistic design and analysis of excavations.

Seismic isolation analysis of FPS bearings in spatial lattice shell structures

A theoretical model of a friction pendulum system （FPS） is introduced to examine its application for the seismic isolation of spatial lattice shell structures. An equation of motion of the lattice shell with FPS bearings is developed. Then, seismic isolation studies are performed for both double-layer and single-layer lattice shell structures under different seismic input and design parameters of the FPS. The influence of frictional coefficients and radius of the FPS on seismic performance are discussed. Based on the study, some suggestions for seismic isolation design of lattice shells with FPS bearings are given and conclusions are made which could be helpful in the application of FPS.

Spatial analysis and evaluation of a coal deposit by coupling AHP & GIS techniques

Nowadays,the evaluation of coal deposits becomes crucial,due to many uncontrollable factors,which affect the energy sector.A comparative evaluation of coal deposits is essential for their hierarchical classification regarding their sustainable exploitation,when compared to other coal deposits or competitive fuels,which may be used as alternative solutions for electricity generation.In this paper,a method for spatial analysis and evaluation of a lignite deposit is proposed,by creating four spatial key indicators via GIS analysis,which are then aggregated by applying a weighted linear combination.The analytical hierarchy process is applied to estimate the relative weights of the indicators,in order to perform a weighted cartographic overlay.Through the synthesis of the indicators,an overall,total spatial quality indicator is calculated.The weighted analysis was shown to be more effective compared to the unweighted one,because it can provide more reliable results regarding the exploitation of the examined lignite deposit.The implementation of GIS-based analytical hierarchy process in spatial analysis and evaluation of lignite deposits,in terms of sustainable exploitation,demonstrates that this method can be extensively applied for evaluating the economic potential of mineral deposits.

The SIA method for spatial analysis of precipitation in the upper-middle reaches of the Yangtze River

Using geographic information system (GIS) techniques and the newest seasonal and annual average precipitation data of 679 meteorological stations from 1971 to 2000, the multiple regressions equations of the precipitation and topographical variables are established to extract the effect of topography on the annual and seasonal precipitation in the upper-middle reaches of the Yangtze River. Then, this paper uses a successive interpolation approach (SIA), which combines GIS techniques with the multiple regressions, to improve the accuracy of the spatial interpolation of annual and seasonal rainfall. The results are very satisfactory in the case of seasonal rainfall, with the relative error of 6.86%, the absolute error of 13.07 mm, the average coefficient of variation of 0.070, and the correlation coefficient of 0.9675; in the case of annual precipitation, with the relative error of 7.34%, the absolute error of 72.1 mm, the average coefficient of variation of 0.092, and the correlation coefficient of 0.9605. The analyses of annual mean precipitation show that the SIA calculation of 3-5 steps considerably improves the interpolation accuracy, decreasing the absolute error from 211.0 mm to 62.4 mm, the relative error from 20.74% to 5.97%, the coefficient of variation from 0.2312 to 0.0761, and increasing the correlation coefficient from 0.5467 to 0.9619. The SIA iterative results after 50 steps identically converge to the observed precipitation.

An operational modal analysis method in frequency and spatial domain

A frequency and spatial domain decomposition method （FSDD） for operational modal analysis （OMA） is presented in this paper, which is an extension of the complex mode indicator function （CMIF） method for experimental modal analysis （EMA）. The theoretical background of the FSDD method is clarified, Singular value decomposition is adopted to separate the signal space from the noise space. Finally, an enhanced power spectrum density （PSD） is proposed to obtain more accurate modal parameters by curve fitting in the frequency domain. Moreover, a simulation case and an application case are used to validate this method.

A spatial geostatistical analysis of impact of land use development on groundwater resources in the Sangong Oasis Region using remote sensing imagery and data

In this study, the relationship between land use and cover change (LUCC) and variation of groundwater level and quality in the Sangong Oasis Region was investigated using a spatial geostatistical approach. Specifically, interactions among groundwater, surface water, and LUCC were analyzed through the utilization of geographical information system (GIS), remote sensing (RS) Imagery processing, and geostatistics. Study outputs indicated that recharging into the groundwater did not change significantly during the period from 1978 to 1998. However, both LUCC and groundwater level changed substantially in the Sangong Oasis Region, and their variations were closely correlated to each other spatially and temporally over the past two decades. It confirmed that urbanization process and increased industrial activities were the direct reasons of groundwater table descending and the deterioration of water quality. The results of this research provided a scientific basis for understanding sustainability-related problems and solution options in the oasis areas of western China.

Spatial analysis increases efficiency of progeny testing of Chinese fir

We used spatial, global trend and post-blocking analysis to examine the effectiveness of a progeny trial in a tree breeding program for Chinese fir （Cunninghamia lanceolata （Lamb.） Hook） on a hilly site with an environmental gradient from hill top to bottom. Diameter at breast height （DBH） and tree height data had significant spatial auto-correlations among rows and columns. Adding a firstorder separable autoregressive term more effectively modelled the spatial variation than did the incomplete block （IB） model used for the experimental design. The spatial model also accounted for effects of experimental design factors and greatly reduced residual variances. The spatial analysis rel- ative to the IB analysis improved estimation of genetic parameters with the residual variance reduced 13 and 19% for DBH and tree height, respectively; heritability increased 35 and 51% for DBH and tree height, respectively; and genetic gain improved 3-5%. Fitting global trend and postblocking did not improve the analyses under IB model. The use of a spatial model or combined with a design model is recommended for forest genetic trials, particularly with global trend and local spatial variation of hilly sites.

Quantitative analysis of the dynamic change and spatial differences of the ecological security: a case study of Loess Plateau in northern Shaanxi Province

Using the theory and method of the ecological footprint, and combining the changes of regional land use, resource environment, population, society and economy, this paper calculated the ecological footprint, ecological carrying capacity and ecological surplus/loss in 1986-2002 on the Loess Plateau in northern Shaanxi Province. What is more, this paper has put forward the concept of ecological pressure index, set up ecological pressure index models, and ecological security grading systems, and the prediction models of different ecological footprints, ecological carrying capacity, ecological surplus and ecological safety change, and also has assessed the ecological footprint demands of 10,000 yuan GDE The results of this study are as follows： （1） the ecological carrying capacity in northern Shaanxi shows a decreasing trend, the difference of reducing range is the fastest; （2） the ecological footprint appears an increasing trend; （3） ecological pressure index rose to 0.91 from 0.44 during 1986-2002 on the Loess Plateau of northern Shaanxi with an increase of 47%; and （4） the ecological security in the study area is in a critical state, and the ecological oressure index has been increasing rapidlv.

Spatial-temporal Evolution Characteristics and Decoupling Analysis of Influencing Factors of China’s Aviation Carbon Emissions

The aviation industry has become one of the top ten greenhouse gas emission industries in the world. China’s aviation carbon emissions continue to increase, but the analysis of its influencing factors at the provincial level is still incomplete. This paper firstly uses Stochastic Impacts by Regression on Population, Affluence and Technology model(STIRPAT) model to analyze the time series evolution of China’s aviation carbon emissions from 2000 to 2019. Secondly, it uses the Logarithmic Mean Divisia Index(LDMI) model to analyze the influencing characteristics and degree of four factors on China’s aviation carbon emissions, which are air transportation revenue, aviation route structure, air transportation intensity and aviation energy intensity. Thirdly, it determines the various factors’ influencing direction and evolution trend of 31 provinces’ aviation carbon emissions in China(not including Hong Kong, Macao, Taiwan of China due to incomplete data). Finally, it derives the decoupling effort model and analyzes the decoupling relationship and decoupling effort degree between air carbon emissions and air transportation revenue in different provinces. The study found that from 2000 to2019, China’s total aviation carbon emissions continued to grow, while the growth rate of aviation carbon emissions showed a fluctuating downward trend. Air transportation revenue and aviation route structure promote the growth of total aviation carbon emissions, and air transportation intensity and aviation energy intensity have a restraining effect on the growth of total aviation carbon emissions. The scope of negative driving effect of air transportation revenue and air transportation intensity on total aviation carbon emissions in various provinces has increased. While the scope of positive driving influence of aviation route structure on total aviation carbon emissions of various provinces has increased, aviation energy intensity mainly has negative driving influence on total aviation carbon emissions of each province. Overall, the emission reduction trend in the areas to the west and north of the Qinling-Huaihe River Line is obvious. The decoupling mode between air carbon emissions and air transportation revenue in 31 provinces is mainly expansion negative decoupling.The air transportation intensity effect shows strong decoupling efforts in most provinces, the decoupling effort of aviation route structure effect and aviation energy intensity effect is not prominent.

Spatial pattern analysis for quantification of landscape structure of Tadoba-Andhari Tiger Reserve,Central India

Landscape structure is often regarded as an important factor that governs the distribution and abundance of species. Therefore it is critical to understand the landscapes and their dynamics. Patterns of landscape elements strongly influence the ecological characteristics. This study was designed to document and map the current status of the tropi-cal dry deciduous forest of the Tadoba-Andhari Tiger Reserve （TATR）, Central India, （using IRS P6 LISS IV data） and to describe its landscape structure at three levels of organization viz. landscape, class, and patch. The study area was classified into 10 land cover classes that include 6 vegetation classes. The landscape structure was analyzed using FRAG-STATS using 12 set of indices. The TATR landscapes have a total of 2,307 patches with a mean patch size of 25.67 ha and patch density of 1.7 patches per km2. Amongst all land cover classes, mixed bamboo forest is dominant-it occupied maximum area （77.99%）-while riparian forest is least represented （0.32%）. Mixed forest has maximum number of patches among all vegetation classes. Results have shown that despite being dominant in the area, mixed bamboo forest has low patch density （0.25/100 ha）. Dominance of mixed bamboo forest is attributed to large patch sizes and not to the number of patches. This study has focussed on the approach of integrating satellite forest classification and forest inven-tory data for studying forest landscape patterns.

Probabilistic stability analysis of embankment slopes considering the spatial variability of soil properties and seismic randomness

The safety of embankments under seismic conditions is a primary concern for geotechnical engineering societies.The reliability analysis approach offers an effective tool to quantify the safety margin of geotechnical structures from a probabilistic perspective and has gained increasing popularity in geotechnical engineering.This study presents an approach for probabilistic stability analysis of embankment slopes under transient seepage considering both the spatial variability of soil parameters and seismic randomness.The spatial varying soil parameters are firstly characterized by the random field theory,where a large number of random field samples of the soil parameters can be readily generated.Then,the factor of safety(FS)of the embankment slope under seismic conditions corresponding to each random field sample is evaluated through performing seismic stability analysis based on the pseudo-static method.A hypothetical embankment example is adopted in this study for illustration,and the influences of shear strength parameters,seismic coefficient,and the external water level on the embankment slope failure probability are systematically investigated.Results show that the coefficient of variation of the friction angle and the horizontal scale of fluctuation have more significant effects on the embankment slope failure probability.Besides,the seismic coefficient also affects the embankment slope failure probability considerably.For a given external water level,the failure probability corresponding to the downstream slope of the embankment is larger than that in the upstream slope.

Advanced reliability analysis of slopes in spatially variable soils using multivariate adaptive regression splines

This study aims to extend the multivariate adaptive regression splines(MARS)-Monte Carlo simulation(MCS) method for reliability analysis of slopes in spatially variable soils. This approach is used to explore the influences of the multiscale spatial variability of soil properties on the probability of failure(P_f) of the slopes. In the proposed approach, the relationship between the factor of safety and the soil strength parameters characterized with spatial variability is approximated by the MARS, with the aid of Karhunen-Loeve expansion. MCS is subsequently performed on the established MARS model to evaluate Pf.Finally, a nominally homogeneous cohesive-frictional slope and a heterogeneous cohesive slope, which are both characterized with different spatial variabilities, are utilized to illustrate the proposed approach.Results showed that the proposed approach can estimate the P_f of the slopes efficiently in spatially variable soils with sufficient accuracy. Moreover, the approach is relatively robust to the influence of different statistics of soil properties, thereby making it an effective and practical tool for addressing slope reliability problems concerning time-consuming deterministic stability models with low levels of P_f.Furthermore, disregarding the multiscale spatial variability of soil properties can overestimate or underestimate the P_f. Although the difference is small in general, the multiscale spatial variability of the soil properties must still be considered in the reliability analysis of heterogeneous slopes, especially for those highly related to cost effective and accurate designs.

Reliability analysis of slopes considering spatial variability of soil properties based on efficiently identified representative slip surfaces

Slope reliability analysis considering inherent spatial variability(ISV)of soil properties is timeconsuming when response surface method(RSM)is used,because of the"curse of dimensionality".This paper proposes an effective method for identification of representative slip surfaces(RSSs)of slopes with spatially varied soils within the framework of limit equilibrium method(LEM),which utilizes an adaptive K-means clustering approach.Then,an improved slope reliability analysis based on the RSSs and RSM considering soil spatial variability,in perspective of computation efficiency,is established.The detailed implementation procedure of the proposed method is well documented,and the ability of the method in identifying RSSs and estimating reliability is investigated via three slope examples.Results show that the proposed method can automatically identify the RSSs of slope with only one evaluation of the conventional deterministic slope stability model.The RSSs are invariant with the statistics of soil properties,which allows parametric studies that are often required in slope reliability analysis to be efficiently achieved with ease.It is also found that the proposed method provides comparable values of factor of safety(FS)and probability of failure(Pf)of slopes with those obtained from direct analysis and lite rature.

Slope deformation partitioning and monitoring points optimization based on cluster analysis

The scientific and fair positioning of monitoring locations for surface displacement on slopes is a prerequisite for early warning and forecasting.However,there is no specific provision on how to effectively determine the number and location of monitoring points according to the actual deformation characteristics of the slope.There are still some defects in the layout of monitoring points.To this end,based on displacement data series and spatial location information of surface displacement monitoring points,by combining displacement series correlation and spatial distance influence factors,a spatial deformation correlation calculation model of slope based on clustering analysis was proposed to calculate the correlation between different monitoring points,based on which the deformation area of the slope was divided.The redundant monitoring points in each partition were eliminated based on the partition's outcome,and the overall optimal arrangement of slope monitoring points was then achieved.This method scientifically addresses the issues of slope deformation zoning and data gathering overlap.It not only eliminates human subjectivity from slope deformation zoning but also increases the efficiency and accuracy of slope monitoring.In order to verify the effectiveness of the method,a sand-mudstone interbedded CounterTilt excavation slope in the Chongqing city of China was used as the research object.Twenty-four monitoring points deployed on this slope were monitored for surface displacement for 13 months.The spatial location of the monitoring points was discussed.The results show that the proposed method of slope deformation zoning and the optimized placement of monitoring points are feasible.

Black Spot Determination of Traffic Accident Locations and Its Spatial Association Characteristic Analysis Based on GIS

In general, the location of traffic accidents is described as an address with text, so they are difficult to display on the map. The paper discusses how to utilize the geocoding technology and VRS-GPS positioning technology to record the traffic accidents with Geo-spatial information. Based on the spatial relationship between traffic accidents and road network elements, two-way association relationship is defined by spatial relationship computation. Then the paper presents the method which takes the potential of reducing accidents as an index to extract the black spots. Finally, in the discussion, the association relationship between black spots and traffic attributes is used to analyze the factors that resulting in traffic accidents.

Analysis of the Spatial Structure of Tourism Resources in Ji'an City

This paper analyzed characteristics of tourism resources in Ji'an City,and carried out quantitative analysis of local tourism resources based on agglomeration effect of resources,connectivity analysis,and accessibility analysis. The results showed that the city has poor loop of tourism network,major scenic areas(spots) have moderate network accessibility,in view of this,suggestions for the optimum development of local tourism industry were proposed.