Deformation Control And Back Analysis On Immune Intelligence Algorithm Of Tunnel With Weak Surrounding Rock Mass

In the construction for deep and long tunnel with New Austrian Tunneling Method(NATM),it is important to monitor dynamically the surrounding rock mass.According tothe monitor information,the physical and mechanical parameters and the initial stress fieldof rock mass can be obtained by the back analysis.Then the rock type,rock deformationand state of stress could be analyzed.This is the key step for the analysis of the stability ofthe surrounding rock mass.In the analysis the intelligent algorithm (IA)has shown itsstrong role and has become an important field of the back-analysis and related studies ofgeotechnical engineering.Immune algorithm (Immune algorithm,referred to as IA)as a new intelligent methodof calculating its application in geotechnical engineering is still in the exploratory stage,However,the biological immune system and underground works are characterized by agreat analogy can be.Therefore,the introduction of anti-algorithms biological immunesystem information-processing mechanism has a more wide application prospect inunderground engineering analysis.This dissertation based on practical projects,in thefollowing areas was studied:1.As the geological prospecting unit offers the results of a comprehensiveclassification of rock mass to design and construction,it may led to design andconstruction in the most unfavorable conditions of the surrounding rock mass and result ina great waste.In the studies,the influence of the fault zone of Yunxi and Yunxia on thecharacteristics of Yunling Tunnel construction is analyzed.Set up the judge system offuzzy inference (JSFI)based on the Self-Organizing-Feature-Map and fuzzy math to dealwith the uncertain information.The classification of the surrounding rock mass and thesupport program can be pointed out according to the geologic conditions.It coordinateswith the dynamic design of the tunnel construction and represents the soul of NATM.2.In the high geo-stress of weak rock,the large rock deformation is an obviousproblem to build the long tunnel.In the process of Yunling Tunnel construction,it needsto arrange the measuring points,monitor the measurement of the surrounding rock mass,and analyze the data processing.In the analysis of the monitoring data,the gross error ofanalysis is taken into account to the results.The unascertained mathematics is introducedinto the error analysis of the displacement measurement data,and the improved filteringmethod is used in the data processing.3.The methods of monitoring data analysis and deformation prediction of rock massare introduced.By monitoring the data processing,the convergence of the surroundingrock of the deformation characteristics and rheological behavior of the soft rock are studied.Based on the data analysis,the rock mass prediction is carried out,and theconvergence time and values are determined.The results can be verified by the practicalmeasurement.4.The biological immune system mechanism is introduced.The relationship betweenthe artificial and biological immune system are studied.The relevant factors of thecharacteristics with solving problem,the computing model and the design of intelligentalgorithms,the designed computing framework of artificial immune algorithm intelligentand calculation process are considered.The intelligent information treatment is obtainedand the effects are evaluated.5.Taking into account the characteristics of the tunnel project and the current trend ofthe immunization research,the targeted analysis of the immune genetic algorithm,theadaptive immune algorithm design as well as the way to achieve are studied.The antibodyselection mechanism of the similarity of the vector and adaptive immune mechanismsstrategy are introduced.The immune network ability of identify themselves and non-self,antibody diversity and the mechanism to deal with antigen,neural network optimizationand clustering features are combined.Through the immune algorithm for neural networkoptimization model,the immune neural network algorithm design and implementationsteps are studied.6.The intelligent direct back analysis of physical and mechanical parameters of thetunnel surrounding rock mass is studied based on the adaptive immunity algorithm and BPneural network.An intelligent analytic method based on the process of FLAC^3Ddirectcomputation-parameter intelligent direct analysis-back analysis results verification isproposed.In the process of the realization of algorithm,a series of problems,such as howto use the clustering algorithm to determine the weight of the initial collection of network,and how to choose the immune and structure the immunity operator,have been solved.Applying the intelligent analysis to the analysis of Yunling Tunnel rock mass,the resultshave been improved for the proposed values from the preliminary investigation.It showsthat the proposed methods have important role for stability evaluation of the tunnelsurrounding rock mass and information design.