Fiber optic sensing and performance evaluation of a water conveyance tunnel with composite linings under super-high internal pressures

For long-distance water conveyance shield tunnels in operation,the high internal water pressure may cause excessive deformation of composite linings,affecting their structural integrity and serviceability.However,the deformation and failure characteristics of lining structures under internal water pressure are not well investigated in the literature,particularly for three-layer composite linings.This study presents an in situ experimental investigation on the response of two types of composite linings(i.e.separated and combined lining structures)subjected to internal pressures,in which a fiber optic nerve system(FONS)equipped with distributed strain and displacement sensing nerves was employed to monitor the performance of the two composite linings during testing.The experimental results clearly show that the damage of the tunnel lining under different internal pressures was mainly located in the self-compaction concrete layer.The separated lining structure responded more aggressively to the variations in internal pressures than the combined one.Moreover,two evaluation indices,i.e.radial displacement and effective stiffness coefficient,are proposed for describing the changes in the structural bearing performance.The effective stiffness coefficients of the two types of lining structures were reduced by 39.4%and 29.5%,respectively.Considering the convenience of field monitoring,it is suggested that the average strains at different layers can be used as characteristic parameters for estimating the health conditions of lining structures in service.The analysis results provide a practical reference for the design and health evaluation of water conveyance shield tunnels with composite linings.

Changes in groundwater levels and the response of natural vegetation to transfer of water to the lower reaches of the Tarim River

Restoration and reconstruction of the degraded Tarim River ecosystem is an important challenge. A goal of an ecological water conveyance project is to protect and restore the natural vegetation in the lower reaches of Tadm River by transferring water from Bosten Lake, through the river channel, to the lower reaches. This study describes the changes in groundwater depth during the water transfer and the respondence of riparian vegetation to alterations in groundwater levels. The results indicate that groundwater depth along the Tarim River channel has a significant spatial-temporal component. Groundwater levels closest to the river channel show the most immediate and pronounced changes as a response to water transfer while those further away respond more slowly, although the observed change appears to be longer in duration. With a rise in the groundwater level, natural vegetation responded with higher growth rates, biomass and biodiversity. These favorable changes show that it is feasible to protect and restore the degraded natural vegetation by raising the groundwater depth. Plant communities are likely to reflect the hysteresis phenomenon, requiting higher water levels to initiate and stimulate desired growth than what may be needed to maintain the plant community. Because different species have different ecologies, including different root depths and densities and water needs, their response to increasing water availability will be spatially and temporally heterogenous. The response of vegetation is also influenced by microtopography and watering style. This paper discusses strategies for the protection and restoration of the degraded vegetation in the lower reaches of the Tarim River and provides information to complement ongoing theoretical research into ecological restoration in add or semi-arid ecosystems.

3D Finite Element Simulation of Tunnel Boring Machine Construction Processes in Deep Water Conveyance Tunnel

Applying stiffness migration method,a 3D finite element mechanical model is established to simulate the excavation and advance processes.By using 3D nonlinear finite element method,the tunnel boring machine(TBM) excavation process is dynamically simulated to analyze the stress and strain field status of surrounding rock and segment.The maximum tensile stress of segment ring caused by tunnel construction mainly lies in arch bottom and presents zonal distribution.The stress increases slightly and limitedly in the course of excavation.The maximum and minimum displacements of segment,manifesting as zonal distribution,distribute in arch bottom and vault respectively.The displacements slightly increase with the advance of TBM and gradually tend to stability.

Optimal design of heat exchanger header for coal gasification in supercritical water through CFD simulations

Heat exchangers play an important role in supercritical water coal gasification systems for heating feed and cooling products. However, serious deposition and plugging problems always exist in heat exchangers. CFD modeling was used to simulate the transport characteristics of solid particles in supercdtical water through the shell and tube of heat exchangers to alleviate the problems. In this paper, we discuss seven types of exchangers CA, B, C D, E, F and G）, which vary in inlet nozzle configuration, header height, inlet pipe diameter and tube pass distribution. In the modeling, the possibility of deposition in the header was evaluated by accumulated mass of particles; we used the velocity contour of supercritical water （SCW） to evaluate the uniformity of the velocity dis- tribution among the tube passes. Simulation results indicated that the optimum heat exchanger had structure F, which had a rectangular configuration of tube pass distractions, a bottom inlet, a 200-mm header height and a 10-ram inlet pipe diameter.

Land use/land cover change responses to ecological water conveyance in the lower reaches of Tarim River,China

The Tarim River is the longest inland river in China and is considered as an important river to protect the oasis economy and environment of the Tarim Basin.However,excessive exploitation and over-utilization of natural resources,particularly water resources,have triggered a series of ecological and environmental problems,such as the reduction in the volume of water in the main river,deterioration of water quality,drying up of downstream rivers,degradation of vegetation,and land desertification.In this study,the land use/land cover change(LUCC)responses to ecological water conveyance in the lower reaches of the Tarim River were investigated using ENVI(Environment for Visualizing Images)and GIS(Geographic Information System)data analysis software for the period of 1990-2018.Multi-temporal remote sensing images and ecological water conveyance data from 1990 to 2018 were used.The results indicate that LUCC covered an area of 2644.34 km^(2) during this period,accounting for 15.79%of the total study area.From 1990 to 2018,wetland,farmland,forestland,and artificial surfaces increased by 533.42 km^(2)(216.77%),446.68 km^(2)(123.66%),284.55 km^(2)(5.67%),and 57.51 km^(2)(217.96%),respectively,whereas areas covered by grassland and other land use/land cover types,such as Gobi,bare soil,and deserts,decreased by 103.34 km2(14.31%)and 1218.83 km2(11.75%),respectively.Vegetation area decreased first and then increased,with the order of 2010<2000<1990<2018.LUCC in the overflow and stagnant areas in the lower reaches of the Tarim River was mainly characterized by fragmentation,irregularity,and complexity.By analyzing the LUCC responses to 19 rounds of ecological water conveyance in the lower reaches of the Tarim River from 2000 to the end of 2018,we proposed guidelines for the rational development and utilization of water and soil resources and formulation of strategies for the sustainable development of the lower reaches of the Tarim River.This study provides scientific guidance for optimal scheduling of water resources in the region.

Predictive analysis of stress regime and possible squeezing deformation for super-long water conveyance tunnels in Pakistan

The prediction of the stress field of deep-buried tunnels is a fundamental problem for scientists and engineers. In this study, the authors put forward a systematic solution for this problem. Databases from the World Stress Map and the Crustal Stress of China, and previous research findings can offer prediction of stress orientations in an engineering area. At the same time, the Andersonian theory can be used to analyze the possible stress orientation of a region. With limited in-situ stress measurements, the Hock-Brown Criterion can be used to estimate the strength of rock mass in an area of interest by utilizing the geotechnical investigation data, and the modified Sheorey＇s model can subsequently be employed to predict the areas＇ stress profile, without stress data, by taking the existing in-situ stress measurements as input parameters. In this paper, a case study was used to demonstrate the application of this systematic solution. The planned Kohala hydropower plant is located on the western edge of Qinghai-Tibet Plateau. Three hydro-fracturing stress measurement campaigns indicated that the stress state of the area is SH - Sh 〉 Sv or SH 〉Sv 〉 Sh. The measured orientation of Sn is NEE （N70.3°-89°E）, and the regional orientation of SH from WSM is NE, which implies that the stress orientation of shallow crust may be affected by landforms. The modified Sheorey model was utilized to predict the stress profile along the water sewage tunnel for the plant. Prediction results show that the maximum and minimum horizontal principal stres- ses of the points with the greatest burial depth were up to 56.70 and 40.14 MPa, respectively, and the stresses of areas with a burial depth of greater than 500 m were higher. Based on the predicted stress data, large deformations of the rock mass surrounding water conveyance tunnels were analyzed. Results showed that the large deformations will occur when the burial depth exceeds 300 m. When the burial depth is beyond 800 m, serious squeezing deformations will occur in the surrounding rock masses, thus requiring more attention in the design and construction. Based on the application efficiency in this case study, this prediction method proposed in this paper functions accurately.

Research on the Operational Conditions of Artificial Precipitation Enhancement in Liaoning Province

Taking precipitation process during May 17-18,2009 as an example,this paper analyzed and summarized the operational conditions of artificial precipitation enhancement in Liaoning Province.Operational conditions can be divided into two categories,namely,macro-weather and cloud micro-physical operational conditions,this paper described their respective indexes and criterions as well as their effect and application in formulation and command of artificial precipitation enhancement plan real-timely.

Analysis on the ecological benefits of the stream water conveyance to the dried-up river of the lower reaches of Tarim River,China

This paper analyzes the monitored data of the 4 times of stream water conveyances to the river section where the stream flow was cut-off, of 9 groundwater-monitoring sections and 18 vegetation plots in the lower reaches of Tarim River. The results show that the groundwater depth in the lower reaches of Tarim River rose from 9.87 m before the conveyances to 7.74 m and 3.79 m after the first and second conveyances, 3.61 and 3.16 m after the 2 phases of the third conveyance, and 2.66 m after the fourth conveyance. The transverse response scope of groundwater level was gradually enlarged along both sides of the channel of conveyances, i.e., from 450 m in width after the first conveyance to 1050 m after the fourth conveyance, but the response degree of groundwater level was reduced with the increase of the distance away from the channel of conveyances. The composition, distribution and growth status of the natural vegetation are directly related to the groundwater depth. The indexes of Simpson’s biodiversity, McIntosh’s evenness and Margalef’s richness, which reflect the change of the quantity of species and the degree of biodiversity, are reduced from 0.70, 0.48 and 0.90 to 0.26, 0.17 and 0.37 re- spectively along with the drawdown of groundwater level from the upper reaches to the lower reaches. After the stream water conveyances, the natural vegetation in the lower reaches is saved and restored along with the rise of groundwater level, the response scope of vegetation is gradually enlarged, i.e., from 200— 250 m in width after the first conveyance to 800 m after the fourth conveyance. However, there is still a great disparity to the objective of protecting the “Green Corridor”in the lower reaches of Tarim River. Thus, it is suggested to convey the stream water in double-channel way, combine the conveyance with water supply in surface scope, or construct the modern pipe-conveyance network systems so as to save the natural vegetation in an intensive way, achieve the efficient water consumption and speed up the restoration and re- generation of the damaged ecosystems in the lower reaches of Tarim River.

Efficient Identification of water conveyance tunnels siltation based on ensemble deep learning

The inspection of water conveyance tunnels plays an important role in water diversion projects.Siltation is an essential factor threatening the safety of water conveyance tunnels.Accurate and efficient identification of such siltation can reduce risks and enhance safety and reliability of these projects.The remotely operated vehicle(ROV)can detect such siltation.However,it needs to improve its intelligent recognition of image data it obtains.This paper introduces the idea of ensemble deep learning.Based on the VGG16 network,a compact convolutional neural network(CNN)is designed as a primary learner,called Silt-net,which is used to identify the siltation images.At the same time,the fully-connected network is applied as the meta-learner,and stacking ensemble learning is combined with the outputs of the primary classifiers to obtain satisfactory classification results.Finally,several evaluation metrics are used to measure the performance of the proposed method.The experimental results on the siltation dataset show that the classification accuracy of the proposed method reaches 97.2%,which is far better than the accuracy of other classifiers.Furthermore,the proposed method can weigh the accuracy and model complexity on a platform with limited computing resources.

Prediction of water table depths under soil water-groundwater interaction and stream water conveyance

Water table over an arid region can be elevated to a critical level to sustain terrestrial ecosystem along the natural channel by the stream water conveyance. Estimation of water table depth and soil moisture on river channel profile may be reduced to a two-dimensional moving boundary problem with soil water-groundwater interaction. The two-dimensional soil water flow with stream water transferred is divided into an unsaturated vertical soil water flow and a horizontal groundwater flow. Therefore, a prediction model scheme for water table depths under the interaction between soil water and groundwater with stream water transferred is presented, which includes a vertical soil water movement model, a horizontal groundwater movement model, and an interface model. The synthetic experiments are conducted to test the sensitivities of the river elevation, horizontal conductivity, and surface flux, and the results from the experiments show the robustness of the proposed scheme under different conditions. The groundwater horizontal conductivity of the proposed scheme is also calibrated by SCE-UA method and validated by data collected at the Yingsu section in the lower reaches of the Tarim River, which shows that the model can reasonably simulate the water table depths.

TBM penetration rate prediction based on the long short-term memory neural network

Tunnel boring machines(TBMs)are widely used in tunnel engineering because of their safety and efficiency.The TBM penetration rate(PR)is crucial,as its real-time prediction can reflect the adaptation of a TBM under current geological conditions and assist the adjustment of operating parameters.In this study,deep learning technology is applied to TBM performance prediction,and a PR prediction model based on a long short-term memory(LSTM)neuron network is proposed.To verify the performance of the proposed model,the machine parameters,rock mass parameters,and geological survey data from the water conveyance tunnel of the Hangzhou Second Water Source project were collected to form a dataset.Furthermore,2313 excavation cycles were randomly composed of training datasets to train the LSTM-based model,and 257 excavation cycles were used as a testing dataset to test the performance.The root mean square error and the mean absolute error of the proposed model are 4.733 and 3.204,respectively.Compared with Recurrent neuron network(RNN)based model and traditional time-series prediction model autoregressive integrated moving average with explanation variables(ARIMAX),the overall performance on proposed model is better.Moreover,in the rapidly increasing period of the PR,the error of the LSTM-based model prediction curve is significantly smaller than those of the other two models.The prediction results indicate that the LSTM-based model proposed herein is relatively accurate,thereby providing guidance for the excavation process of TBMs and offering practical application value.