Abstract
The paper presents a new procedure to assess the compressive strength of regular masonry starting from results of non-destructive ultrasonic pulse velocity tests (UPV) on the constituent materials. The procedure has been calibrated on a soft calcarenitic stone used in the heritage masonry of Southern Italy, and starts from the knowledge of the regression between UPV and the compressive strength (UCS) of the material, determined by means of a wide experimental campaign on different varieties of quarry samples. Through an improved cross validation technique, the proposed method allows to estimate the compressive strength of new samples by making only non-destructive measurements without the need to conduct compression tests. The quality of the procedure was assessed both at the block scale and at the wall scale by comparing the estimated results with those obtained experimentally. In particular, the experiments were performed using new quarry stone blocks and blocks taken from existing walls of two ancient buildings during restoration works. The proposed method has proven to be reliable for the investigated material and it is easy to apply also for other materials as soon as it is possible to carry out a preliminary calibration in the laboratory, which allows knowing the UPV–UCS relationship over a wide range of strengths.
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References
Thaickavil NN, Thomas J (2018) Behaviour and strength assessment of masonry prisms. Case Stud Constr Mater 8:23–38. https://doi.org/10.1016/j.cscm.2017.12.007
ISCARSAH–International Scientific Committee for Analysis and Restoration of Structures of Architectural Heritage (2005) Recommendations for the analysis, conservation and structural restoration of architectural heritage, Barcelona
Valluzzi MR, Lorenzoni F, Deiana R et al (2019) Non-destructive investigations for structural qualification of the Sarno Baths, Pompeii. J Cultural Herit 40:280–287. https://doi.org/10.1016/j.culher.2019.04.015
Orenday-Tapia EE, Pacheco-Martínez J, Padilla-Ceniceros R, López-Doncel RA (2018) In situ and nondestructive characterization of mechanical properties of heritage stone masonry. Environ Earth Sci 77:1–10. https://doi.org/10.1007/s12665-018-7473-8
Moropoulou A, Labropoulos KC, Delegou ET et al (2013) Non-destructive techniques as a tool for the protection of built cultural heritage. Constr Build Mater 48:1222–1239. https://doi.org/10.1016/j.conbuildmat.2013.03.044
Faella G, Frunzio G, Guadagnuolo M et al (2012) The church of the nativity in Bethlehem: non-destructive tests for the structural knowledge. J Cultural Herit 13:e27–e41. https://doi.org/10.1016/j.culher.2012.10.014
European committee for standardization (2004) Eurocode 8: design of structures for earthquake resistance
Ministero delle Infrastrutture e dei Trasporti (2018) Aggiornamento delle “Norme tecniche per le costruzioni”. pp.1–198 (in Italian)
LL.GG. (2011) Linee guida per la valutazione e la riduzione del rischio sismico del patrimonio culturale con riferimento alle norme tecniche per le costruzioni di cui al decreto del ministero delle infrastrutture e dei trasporti del 14 gennaio 2008. 1:1–83
European committee for standardization (2005) Eurocode 6: design of masonry structures
CS.LL.PP. (2019) Istruzioni per l’applicazione dell’«Aggiornamento delle “Norme tecniche per le costruzioni”». Gazz Uff della Repubb Italiana 35:1–337
Breysse D, Balayssac J-P, Biondi S et al (2019) Recommendation of RILEM TC249-ISC on non destructive in situ strength assessment of concrete. Mater Struct 52:71
Del Río LM, Jiménez A, López F et al (2004) Characterization and hardening of concrete with ultrasonic testing. Ultrasonics 42:527–530. https://doi.org/10.1016/j.ultras.2004.01.053
Trtnik G, Kavčič F, Turk G (2009) Prediction of concrete strength using ultrasonic pulse velocity and artificial neural networks. Ultrasonics 49:53–60. https://doi.org/10.1016/j.ultras.2008.05.001
Hobbs B, Tchoketch Kebir M (2007) Non-destructive testing techniques for the forensic engineering investigation of reinforced concrete buildings. Forensic Sci Int 167:167–172. https://doi.org/10.1016/j.forsciint.2006.06.065
Amini K, Jalalpour M, Delatte N (2016) Advancing concrete strength prediction using non-destructive testing: development and verification of a generalizable model. Constr Build Mater 102:762–768. https://doi.org/10.1016/j.conbuildmat.2015.10.131
BS EN 13791:2019 (2020) Assessment of in situ compressive strength in structures and precast concrete components. CEN, Brussels
Yasar E, Erdogan Y (2004) Correlating sound velocity with the density, compressive strength and Young’s modulus of carbonate rocks. Int J Rock Mech Min Sci 41:871–875. https://doi.org/10.1016/j.ijrmms.2004.01.012
Kahraman S (2001) Evaluation of simple methods for assessing the uniaxial compressive strength of rock. Int J Rock Mech Min Sci 38:981–994. https://doi.org/10.1016/S1365-1609(01)00039-9
Vasconcelos G, Lourenço PB, Alves CAS, Pamplona J (2008) Ultrasonic evaluation of the physical and mechanical properties of granites. Ultrasonics 48:453–466. https://doi.org/10.1016/j.ultras.2008.03.008
Aliabdo AAE, Elmoaty AEMA (2012) Reliability of using nondestructive tests to estimate compressive strength of building stones and bricks. Alex Eng J 51:193–203. https://doi.org/10.1016/j.aej.2012.05.004
Çobanoǧlu I, Çelik SB (2008) Estimation of uniaxial compressive strength from point load strength, Schmidt hardness and P-wave velocity. Bull Eng Geol Env 67:491–498. https://doi.org/10.1007/s10064-008-0158-x
Grinzato E, Marinetti S, Bison PG et al (2004) Comparison of ultrasonic velocity and IR thermography for the characterisation of stones. Infrared Phys Technol 46:63–68. https://doi.org/10.1016/j.infrared.2004.03.009
Asadi M, Hossein Bagheripour M, Eftekhari M (2013) Development of optimal fuzzy models for predicting the strength of intact rocks. Comput Geosci 54:107–112. https://doi.org/10.1016/j.cageo.2012.11.017
Beiki M, Majdi A, Givshad AD (2013) Application of genetic programming to predict the uniaxial compressive strength and elastic modulus of carbonate rocks. Int J Rock Mech Min Sci 63:159–169. https://doi.org/10.1016/j.ijrmms.2013.08.004
Sharma LK, Vishal V, Singh TN (2017) Developing novel models using neural networks and fuzzy systems for the prediction of strength of rocks from key geomechanical properties. Meas J Int Meas Confed 102:158–169. https://doi.org/10.1016/j.measurement.2017.01.043
Singh R, Umrao RK, Ahmad M et al (2017) Prediction of geomechanical parameters using soft computing and multiple regression approach. Meas J Int Meas Confed 99:108–119. https://doi.org/10.1016/j.measurement.2016.12.023
Yilmaz I, Yuksek G (2009) Prediction of the strength and elasticity modulus of gypsum using multiple regression, ANN, and ANFIS models. Int J Rock Mech Min Sci 46:803–810. https://doi.org/10.1016/j.ijrmms.2008.09.002
Sýkora M, Diamantidis D, Holický M et al (2018) Assessment of compressive strength of historic masonry using non-destructive and destructive techniques. Constr Build Mater 193:196–210. https://doi.org/10.1016/j.conbuildmat.2018.10.180
Martini R, Carvalho J, Barraca N et al (2017) Advances on the use of non-destructive technique for mechanical characterization of stone masonry: GPR and sonic test. Procedia Struct Integr 5:1108–1115
Vasanelli E, Colangiuli D, Calia A et al (2015) Ultrasonic pulse velocity for the evaluation of physical and mechanical properties of a highly porous building limestone. Ultrasonics 60:33–40
Vasanelli E, Colangiuli D, Calia A, Luprano VAM (2017) Estimating in situ concrete strength combining direct and indirect measures via cross validation procedure. Constr Build Mater 151:916–924. https://doi.org/10.1016/j.conbuildmat.2017.06.141
Mosteller F, Tukey JW (1968) Data analysis, including statistics. In: Lindzey G, Aronson E (eds) Handbook of social psychology, vol 2. Addison-Wesley, Research Methods, pp 80–203
Geisser S (1974) A predictive approach to the random effect model. Biometrika 61:101–107. https://doi.org/10.1093/biomet/61.1.101
Arlot S, Celisse A (2010) A survey of cross-validation procedures for model selection. Stat Surv 4:40–79. https://doi.org/10.1214/09-SS054
Ross SM (2009) Distributions of sampling statistics. Introduction to probability and statistics for engineers and scientists. Academic Press, Cambridge, pp 203–229
Chai T, Draxler RR (2014) Root mean square error (RMSE) or mean absolute error (MAE)?: arguments against avoiding RMSE in the literature. Geosci Model Dev 7:1247–1250. https://doi.org/10.5194/gmd-7-1247-2014
Breysse D, Martınez-Fernandez JL (2014) Assessing concrete strength with rebound hammer: review of key issues and ideas for more reliable conclusions. Mater Struct 47:1589–1604. https://doi.org/10.1617/s11527-013-0139-9
ASTM D2845–08 (2008) Standard test method for laboratory determination of pulse velocities and ultrasonic elastic constants of rock.
UNI EN 772-1 (2011) Methods of test for masonry units: part 1—determination of compressive strength.
UNI EN 1052-1 (2001) Methods of test for masonry: determination of compressive strength
UNI EN 1015-11 (2007) Methods of test for mortar for masonry: part 11—determination of flexural and compressive strength of hardened mortar
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This study was funded by Regione Puglia (P.O. PUGLIA FESR-FSE 2007–2013).
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Vasanelli, E., Micelli, F., Colangiuli, D. et al. A non destructive testing method for masonry by using UPV and cross validation procedure. Mater Struct 53, 134 (2020). https://doi.org/10.1617/s11527-020-01568-8
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DOI: https://doi.org/10.1617/s11527-020-01568-8