The uncertainty of a dynamic modulus of elasticity measuring in view of non-destructive tests of concrete compressive strength

被引:0
|
作者
Jurowski, Krystian [1 ]
Kaleta, Alina [1 ]
Krepa, Bronislaw [1 ]
机构
[1] Opole Univ Technol, Fac Civil Engn & Architecture, Katowicka 48 St, PL-45061 Opole, Poland
关键词
D O I
10.1051/matecconf/201817402010
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
In this work, the evaluation of measurement uncertainty of concrete dynamic elastic modulus testing method was conducted. The dynamic test was carried out using impulse excitation and modal analysis method, which can be used to determine the compressive strength of concrete in a non-destructive way. The tests were conducted using concrete samples in order to determine the practical usefulness of the mentioned method. It has been demonstrated that the impulse excitation and modal analysis method is characterized by very good repeatability.
引用
收藏
页数:9
相关论文
共 50 条
  • [21] Non-Destructive Assessment of the Dynamic Elasticity Modulus of Eucalyptus nitens Timber Boards
    Opazo-Vega, Alexander
    Rosales-Garces, Victor
    Oyarzo-Vera, Claudio
    MATERIALS, 2021, 14 (02) : 1 - 23
  • [22] Compressive strength and modulus of elasticity of freshly compressed concrete
    Nematzadeh, M.
    Naghipour, M.
    CONSTRUCTION AND BUILDING MATERIALS, 2012, 34 : 476 - 485
  • [23] Evaluation of elasticity and rupture modulus of woods by destructive and non-destructive techniques
    Medeiros Neto, Pedro Nico
    Paes, Juarez Benigno
    de Alcantara Segundinho, Pedro Gutemberg
    SCIENTIA FORESTALIS, 2016, 44 (111): : 683 - 690
  • [24] Models for Estimation of Concrete Compressive Strength Based on Experimental Research with Destructive and Non-destructive Methods
    Ivanchev, Ivan
    PROCEEDINGS OF SEVENTH INTERNATIONAL CONGRESS ON INFORMATION AND COMMUNICATION TECHNOLOGY, ICICT 2022, VOL. 2, 2023, 448 : 681 - 690
  • [25] Estimation of concrete compressive strength from non-destructive tests using a customized neural network and genetic algorithm
    Park, Jun Su
    Park, Sinwon
    Oh, Byung Kwan
    Hong, Taehoon
    Lee, Dong-Eun
    Park, Hyo Seon
    APPLIED SOFT COMPUTING, 2024, 164
  • [26] Non-destructive Tests for Estimating the Tensile Strength in Concrete with Deep Learning
    Guzman-Torres, Jose A.
    Junez-Ferreyra, Carlos A.
    Silva-Orozco, Ramiro
    Martinez-Molina, Wilfrido
    PROCEEDINGS OF THE 75TH RILEM ANNUAL WEEK 2021, 2023, 40 : 856 - 866
  • [27] Combined Use of Non-Destructive Tests for Assessment of Strength of Concrete in Structure
    Jain, Akash
    Kathuria, Ankit
    Kumar, Adarsh
    Verma, Yogesh
    Murari, Krishna
    2ND INTERNATIONAL CONFERENCE ON REHABILITATION AND MAINTENANCE IN CIVIL ENGINEERING (ICRMCE), 2013, 54 : 241 - 251
  • [28] Challenges for the Development of Artificial Intelligence Models to Predict the Compressive Strength of Concrete Using Non-destructive Tests: A Review
    Alavi, Seyed Alireza
    Noel, Martin
    PROCEEDINGS OF THE CANADIAN SOCIETY OF CIVIL ENGINEERING ANNUAL CONFERENCE 2022, VOL 3, CSCE 2022, 2024, 359 : 839 - 857
  • [29] Challenges for the Development of Artificial Intelligence Models to Predict the Compressive Strength of Concrete Using Non-destructive Tests: A Review
    Alavi, Seyed Alireza
    Noel, Martin
    PROCEEDINGS OF THE CANADIAN SOCIETY OF CIVIL ENGINEERING ANNUAL CONFERENCE 2022, VOL 4, CSCE 2022, 2024, 367 : 839 - 857
  • [30] EFFECT OF HYDROTHERMAL CURING OF CONCRETE ON ITS COMPRESSIVE STRENGTH AND ON THE MECHANICAL PROPERTIES DETERMINED BY NON-DESTRUCTIVE TESTS.
    Teodoru, George
    Durability of Building Materials, 1985, 2 (04): : 351 - 364