On the public citation graph

Development of Open Tbm Tunnelling Performance Prediction Model Based on Hydropower Classification (Hc) System

0 signed · 26 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/s00603-012-0314-2openalex-extracted
Simultaneous Effects of Joint Spacing and Orientation on TBM Cutting Efficiency in Jointed Rock Masses
inferredcites →https://doi.org/10.1007/s00603-014-0619-4openalex-extracted
Application of RMR for Estimating Rock-Mass–Related TBM Utilization and Performance Parameters: A Case Study
inferredcites →https://doi.org/10.1007/s00603-022-02782-2openalex-extracted
Prediction of TBM Advance Rate Considering Geotechnical and Operating Risks: An Example of the Lanzhou Long Water Conveyance Tunnel, China
inferredcites →https://doi.org/10.1007/s10064-009-0260-8openalex-extracted
Risk assessment based selection of rock TBM for adverse geological conditions using Fuzzy-AHP
inferredcites →https://doi.org/10.1007/s12517-014-1465-0openalex-extracted
Prediction of TBM penetration rate using intact and mass rock properties (case study: Zagros long tunnel, Iran)
inferredcites →https://doi.org/10.1007/s12594-016-0382-0openalex-extracted
Estimation of the Performance of the Tunnel Boring Machine (TBM) Using Uniaxial Compressive Strength and Rock Mass Rating Classification (RMR) – A Case Study from the Deccan Traps, India
inferredcites →https://doi.org/10.1016/0148-9062(85)93229-2openalex-extracted
Prediction of the performance of disc cutters in anisotropic rock
inferredcites →https://doi.org/10.1016/j.ijrmms.2008.03.003openalex-extracted
Development of a rock mass characteristics model for TBM penetration rate prediction
inferredcites →https://doi.org/10.1016/j.ijrmms.2011.07.001openalex-extracted
A multi-dimensional approach to the assessment of tunnel excavation methods
inferredcites →https://doi.org/10.1016/j.ijrmms.2020.104551openalex-extracted
A modified rock mass classification system for TBM tunnels and tunneling based on the HC method of China
inferredcites →https://doi.org/10.1016/j.tust.2004.08.006openalex-extracted
Numerical modeling of the effects of joint orientation on rock fragmentation by TBM cutters
inferredcites →https://doi.org/10.1016/j.tust.2008.12.006openalex-extracted
Effect of adverse geological condition on TBM operation in Ghomroud tunnel conveyance project
inferredcites →https://doi.org/10.1016/j.tust.2010.01.008openalex-extracted
Performance prediction of hard rock TBM using Rock Mass Rating (RMR) system
inferredcites →https://doi.org/10.1016/j.tust.2012.02.021openalex-extracted
Tunnel Boring Machine (TBM) selection using fuzzy multicriteria decision making methods
inferredcites →https://doi.org/10.1016/j.tust.2013.07.011openalex-extracted
Reinforcement design and stability analysis for large-span tailrace bifurcated tunnels with irregular geometry
inferredcites →https://doi.org/10.1016/j.tust.2014.10.009openalex-extracted
Experimental study on failure behaviour of deep tunnels under high in-situ stresses
inferredcites →https://doi.org/10.1016/j.tust.2016.01.009openalex-extracted
Performance prediction of hard rock Tunnel Boring Machines (TBMs) in difficult ground
inferredcites →https://doi.org/10.1016/j.tust.2016.01.038openalex-extracted
An appraisal of TBM performances in Turkey in difficult ground conditions and some recommendations
inferredcites →https://doi.org/10.1016/j.tust.2016.02.015openalex-extracted
Experiences and lessons from the use of TBM in the Himalaya – A review
inferredcites →https://doi.org/10.1016/j.tust.2016.04.002openalex-extracted
TBM tunnelling under adverse geological conditions: An overview
inferredcites →https://doi.org/10.1016/j.tust.2017.03.002openalex-extracted
A case study of TBM performance prediction using a Chinese rock mass classification system – Hydropower Classification (HC) method
inferredcites →https://doi.org/10.1016/j.tust.2018.02.012openalex-extracted
Geological and mechanical rock mass conditions for TBM performance prediction. The case of “La Maddalena” exploratory tunnel, Chiomonte (Italy)
inferredcites →https://doi.org/10.1016/j.tust.2018.10.001openalex-extracted
A case study of TBM performance prediction using field tunnelling tests in limestone strata
inferredcites →https://doi.org/10.1016/j.tust.2019.103046openalex-extracted
Application of rock mass classification systems for performance estimation of rock TBMs using regression tree and artificial intelligence algorithms
inferredcites →https://doi.org/10.1016/j.tust.2021.104183openalex-extracted
Prediction of TBM performance in fresh through weathered granite using empirical and statistical approaches
inferredcites →https://doi.org/10.1016/s1365-1609(02)00069-2openalex-extracted
TBM performance estimation using rock mass classifications
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.