Geotechnical investigations and remediation design for failure of tunnel portal section： a case study in northern Turkey

Mass movements are very common problems in the eastern Black Sea region of Turkey due to its climate conditions, geological, and geomorphological characteristics. High slope angle, weathering, dense rainfalls, and anthropogenic impacts are generally reported as the most important triggering factors in the region. Following the portal slope excavations in the entrance section of Cankurtaran tunnel, located in the region, where the highly weathered andesitic tuff crops out, a circular toe failure occurred. The main target of the present study is to investigate the causes and occurrence mechanism of this failure and to determine the feasible remedial measures against it using finite element method(FEM) in four stages. These stages are slope stability analyses for pre-and postexcavation cases, and remediation design assessments for slope and tunnel. The results of the FEM-SSR analyses indicated that the insufficient initial support design and weathering of the andesitic tuffs are the main factors that caused the portal failure. After installing a rock retaining wall with jet grout columns and reinforced slope benching applications, the factor of safety increased from 0.83 to 2.80. In addition toslope stability evaluation, the Rock Mass Rating(RMR), Rock Mass Quality(Q) and New Austrian Tunneling Method(NATM) systems were also utilized as empirical methods to characterize the tunnel ground and to determine the tunnel support design. The performance of the suggested empirical support design, induced stress distributions and deformations were analyzed by means of numerical modelling. Finally, it was concluded that the recommended stabilization technique was essential for the dynamic long-term stability and prevents the effects of failure. Additionally, the FEM method gives useful and reasonably reliable results in evaluating the stability of cut slopes and tunnels excavated both in continuous and discontinuous rock masses.

CARIDIAC TRANSPLANTATION IN PATIENTS OVER 60 YEARS OLD

Objective To reevaluate the age limit for heart transplantation ( HTX) and the long-term outcomes in el derly patients. Methods From Oct. 1984 to Dec. 1996, 161 cases of HTX were performed in Hartford Hospital, with 35 pa tients aged 60～68 years (mean: 63.5±2.7, group A) and 126 under 60 years (mean: 47.6±11.3, group B). The causes of HTX for group A and group B were ischemic : 60% vs 48%, idiopathic: 29% vs 45%, valvular: 6% vs 4 %, congenital: 0 vs 2%, and graft failure : 6 % vs1% . Results The operative mortality (within 30d) were5.7%(2/35) in group A , and1. 6% (2/126) in group B. The overall late death were 13 (37%) in group A, and 50(40% ) in group B. The main causes of dea th were ( group A vs group B) infection: 46 % vs 24 %, rejection: 0 vs 28 % (P<0.05), malignancy: 23 % vs 8 %, multi-or gan system failure:23% vs 2%, cardiac events:8% vs 10%. The 1-,3-,5- ,8- and 10- year survival rate in group A and group B was 74% vs 88%, 67% vs 77%, 60% vs 65%, 49% vs 43%, and 49% vs 34% respectively. The quality of life for both groups was improved remarkably. Conclusion The survival rate for patients over 60 is as good as that of the younger group. HTX could be successfully performed in patients around 65 years old.

Feedback on a shared big dataset for intelligent TBM Part Ⅱ:Application and forward look

This review discusses the application scenarios of the machine learning-supported performance prediction and the optimization effi-ciency of tunnel boring machines(TBMs).The rock mass quality ratings,which are based on the Chinese code for geological survey,were used to provide"labels"suitable for supervised learning.As a result,the generation of machine prediction for rock mass grades reason-ably agreed with the ground truth documented in geological maps.In contrast,the main operational parameters,i.e.,thrust and torque,can be reasonably predicted based on historical data.Consequently,18 collapse sections of the Yinsong project have been successfully predicted by several researchers.Preliminary studies on the selection of the optimal penetration rate and cost were conducted.This review also presents a summary of the main achievements in response to the initiatives of the Lotus Pool Contest in China.For the first time,large and well-documented TBM performance data has been shared for joint scientific research.Moreover,the review discusses the technical problems that require further study and the perspectives in the future development of intelligent TBM construction based on big data and machine learning.