Predicting Shear Capacity of NSC and HSC Slender Beams without Stirrups using Artificial Intelligence (Record no. 815258)

MARC details
000 -LEADER
fixed length control field 02795aab a2200253 4500
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 240607b20052005|||br||| |||| 00| 0 eng d
022 ## - INTERNATIONAL STANDARD SERIAL NUMBER
International Standard Serial Number 1598-8198
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name H. El-Chabib
9 (RLIN) 882334
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name M. Nehdi
9 (RLIN) 882335
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name A. Said
9 (RLIN) 882336
245 ## - TITLE STATEMENT
Title Predicting Shear Capacity of NSC and HSC Slender Beams without Stirrups using Artificial Intelligence
300 ## - PHYSICAL DESCRIPTION
Extent 79-96 p.
520 ## - SUMMARY, ETC.
Summary, etc. The use of high-strength concrete (HSC) has significantly increased over the last decade, especially in offshore structures, long-span bridges, and tall buildings. The behavior of such concrete is noticeably different from that of normal-strength concrete (NSC) due to its different microstructure and mode of failure. In particular, the shear capacity of structural members made of HSC is a concern and must be carefully evaluated. The shear fracture surface in HSC members is usually trans-granular (propagates across coarse aggregates) and is therefore smoother than that in NSC members, which reduces the effect of shear transfer mechanisms through aggregate interlock across cracks, thus reducing the ultimate shear strength. Current code provisions for shear design are mainly based on experimental results obtained on NSC members having compressive strength of up to 50MPa. The validity of such methods to calculate the shear strength of HSC members is still questionable. In this study, a new approach based on artificial neural networks (ANNs) was used to predict the shear capacity of NSC and HSC beams without shear reinforcement. Shear capacities predicted by the ANN model were compared to those of five other methods commonly used in shear investigations: the ACI method, the CSA simplified method, Response 2000, Eurocode-2, and Zsutty\'s method. A sensitivity analysis was conducted to evaluate the ability of ANNs to capture the effect of main shear design parameters (concrete compressive strength, amount of longitudinal reinforcement, beam size, and shear span to depth ratio) on the shear capacity of reinforced NSC and HSC beams. It was found that the ANN model outperformed all other considered methods, providing more accurate results of shear capacity, and better capturing the effect of basic shear design parameters. Therefore, it offers an efficient alternative to evaluate the shear capacity of NSC and HSC members without stirrups.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Artificial Intelligence
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Analysis
9 (RLIN) 673343
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Aggregate Interlock
9 (RLIN) 684657
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Concrete
9 (RLIN) 3869
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element High-Strength
9 (RLIN) 171039
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Prediction
9 (RLIN) 675736
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Shear
773 0# - HOST ITEM ENTRY
Title Computers and Concrete: An International Journal
International Standard Serial Number 15988198
Place, publisher, and date of publication Daejeon, Korea : Techno Press
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="DOI: 10.12989/cac.2005.2.1.079">DOI: 10.12989/cac.2005.2.1.079</a>
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Suppress in OPAC No
Koha item type Articles
-- 14993
-- Mr. Muhammad Rafique Al Haj Rajab Ali (Late)
Holdings
Not for loan Home library Serial Enumeration / chronology Total Checkouts Date last seen Koha item type
  Periodical Section Vol.2, No.1 (February 2005)   07/06/2024 Articles