Schmidt Rebound Hammer Test Research Articles

Damage to monumental masonry buildings in Hatay and Osmaniye following the 2023 Turkey earthquake sequence: The role of wall geometry, construction quality, and material properties

Damage to monumental masonry buildings in Hatay and Osmaniye following the 2023 Turkey earthquake sequence: The role of wall geometry, construction quality, and material properties

Comparative study on convolutional neural network and regression analysis to evaluate uniaxial compressive strength of Sandy Dolomite

Sandy Dolomite is a kind of widely distributed rock. The uniaxial compressive strength (UCS) of Sandy Dolomite is an important metric in the application in civil engineering, geotechnical engineering, and underground engineering. Direct measurement of UCS is costly, time-consuming, and even infeasible in some cases. To address this problem, we establish an indirect measuring method based on the convolutional neural network (CNN) and regression analysis (RA). The new method is straightforward and effective for UCS prediction, and has significant practical implications. To evaluate the performance of the new method, 158 dolomite samples of different sandification grades are collected for testing their UCS along and near the Yuxi section of the Central Yunnan Water Diversion (CYWD) Project in Yunnan Province, Southwest of China. Two regression equations with high correlation coefficients are established according to the RA results, to predict the UCS of Sandy Dolomites. Moreover, the minimum thickness of Sandy Dolomite was determined by the Schmidt hammer rebound test. Results show that CNN outperforms RA in terms of prediction the precision of Sandy Dolomite UCS. In addition, CNN can effectively deal with uncertainty in test results, making it one of the most effective tools for predicting the UCS of Sandy Dolomite.

Compressive Strength Prediction Model of High Strength Concrete by Destructive and Nondestructive Technique

Concrete’s compressive strength can be tested in a laboratory before construction begins. Since concrete is a natural material and cannot be destroyed, it is not possible to determine its compressive strength through destructive testing. Rebound hammers are typically used in the field to evaluate the structural elements’ ability to withstand hardened concrete. As part of the current study, a comparison was made between concrete’s compressive strength measured by destructive testing and its surface hardness measured by rebound hammering. Tests were conducted on laboratory-made concrete cubes in this study to determine destructive and non-destructive behavior. Minitab software was used for regression analysis. Schmidt rebound hammer tests, a type of nondestructive testing (NDT), were shown to have very strong relationships with concrete destructive compression tests. Schmidt rebound hammers are commonly used to measure the surface hardness of concrete, since the hammer rebound number and concrete strength are theoretically correlated. Utilising a Schmidt hammer, it was applied. Standard concrete cubes with crushing strengths between 20 and 30 MPa were created using various mix proportions. Using regression analysis, destructive and non-destructive values are correlated. The linear regression equation is well suited for obtaining the compressive strength using rebound value by using linear regression equation.

Comparatively Study of Non-Destructive test with different methods in various curing days

In non-destructive testing, materials, components, or assemblies are inspected, tested, or evaluated without being destroyed. In nondestructive testing, materials, components, and assemblies are evaluated for quality and integrity without damaging them. The use of non-destructive testing (NDT) is a popular method for assessing the strength and durability of existing concrete structures. An ultrasound pulse velocity test and a rebound hammer test are included in the NDT test. An NDT test includes both ultrasound pulse velocity testing and rebound hammer testing. Strength tests are conducted with rebound hammers, while quality tests are conducted with ultrasonic pulse velocity tests. A lab-made concrete cube was tested on three different ages-seven, fourteen, and 28 days-without destroying it. There were 15 cubes that were treated using non-destructive methods. Using both Schmidt rebound hammer and ultrasonic pulse velocity tests, we determined which non-destructive testing method was faster. In addition to surfaces, Schmidt rebound hammers are the toughest tools to use. Rebound number and concrete strength seem to be connected. Schmidt hammers were employed in both vertical and horizontal settings. Concrete’s ultrasonic pulse velocity is mostly determined by its identity and modulus of elasticity, that are motivated by the substances used in making the concrete in addition to its placement, compaction, and curing techniques.

Sinking and sleeping of Himalayan city Joshimath

Most of the Greater Himalayan cities recurrently face multiple natural hazards or disasters such as earthquake, landslide, sinking, glacier busts and flash flood. So, Joshimath is no exception because it is situated on tectonically very active young fold Himalayan mountain chain. Previously, many incidents like landslides, subsidence or sinking and flash flood occurred in and around Joshimath city and multiple major and minor cracks also exposed on roads, walls and floors of houses. From 11 January 2023, major portion of Joshimath city is continuously started to sink and major and minor cracks have been developed on roads, floors, ceilings and walls of houses. Around 1000 people have been evacuated from the unsafe area and risky buildings. Here, schmidt hammer rebound test for rock strength, deep learning technique (landslide susceptibility) and geo-hydrological techniques have been applied. This geospatial with field based study investigated the reasons behind the recent big disaster and this research finding will definitely assist to policy makers for sustainable planning and management.

Non-destructive test analysis for silica fume and iron dust added concrete

Damage to the structure may be prevented by using Non-destructive techniques. Non-destructive tests (NDT) play a crucial role in exploring the performance of concrete without damaging the actual structure. In this research work, the concrete quality is determined using the Schmidt rebound hammer test and the Ultrasonic Pulse Velocity (UPV) test. Seven different concrete series were prepared by varying the percentage of silica fume and iron dust. Silica fume was used as a partial replacement of cement and iron dust was used to replace fine aggregate partially. Percentage of silica fume (SF) and Iron dust (ID) utilized were 0 to 15% and 0 to 30% respectively. Ratio of iron dust and silica fume was kept constant as 2 in all series. The dosage of super plasticizer was adjusted to meet the slump requirement. Different series were tested for curing age of 28, 56 and 84 days. The best results of rebound hammer and UPV is obtained at 10% cement and 20% fine aggregate replace with silica fume and iron dust respectively. Optimum mix have 18%, 23.5% and 27.3% greater compressive strength value as compared to control mix for 28 days, 56 days and 84 days respectively.

Mechanical Properties of Concrete Containing Coconut Shells as Coarse Aggregate Partial Replacement

In most tropical countries, especially in Asia, where afflicted nations included the Philippines, Thailand and Malaysia, agricultural waste was disposed of in enormous amounts. Poorly designed garbage disposal techniques are one of the biggest environmental ills. Environmental conservation efforts have been severely hampered by the disposal and management problems posed by wastes produced by industrial and agricultural operations. This study was carried out to find optimal replacement of coconut shell taken at 7, 14, and 28 days of curing by conducting mechanical properties tests. In this investigation, coconut shell concrete was produced by replacing coarse aggregate with coconut shells by 0%, 10%, 20%, and 30% of the total coarse aggregates. The results suggest that 10% replacement of coconut shell produces the optimum value for coarse aggregate replacement based on the compressive strength and Schmidt rebound hammer test results.

Prediksi Kuat Tekan Beton Agregat Recycled Campuran Air Laut dengan Schmidt Rebound Hammer Test

Nowadays, using recyled aggregate and seawater as replacing natural aggregate and freshwater in mixing have been main priority to be a new concrete construction material. However, in order to asses their strength performance in fast and accurate, an appropriate method needs to be determined. Therefore, the aim of this research is to evaluate and predict the compressive strength of recycled aggregate concrete (RAC) mixed seawater using Schmidt rebound hammer test (SRH) and the result value was corresponded to concrete compressive testing machine (CTM) as control test of concrete specimens. Total 72 samples divided into three concrete mixtures were designed and prepared in cylindrical samples with w/c ratio of 0.45 and target compressive strength of 25 MPa. The first mixture was named natural aggregate concrete (NAC) or BAN as control concrete with 100% natural aggregate and fresh water. The second and third mixtures were named BAR-50 and BAR-100 with the BAN replacement of 50% and 100% RAC respectively. Seawater as mixing was performed in mixture concrete of BAR-50 and BAR-100. All sample mixtures were then wet cured at different age of 7, 28, 56 and 90 days in fresh water. The results show a good correlation between SRH and CTM tests with having high correlation of R2=0.9908. Also, a proposed mathematical model, equation 1, is created for quick calculation in predicting compressive strength of RCA. Therefore, the usage of SRH test is a realistic alternative to predict the compressive strength of recycled concrete with different percentage of replacement of NAC and mixing seawater.

Aggregate Evaluation and Geochemical Investigation of Limestone for Construction Industries in Pakistan: An Approach for Sustainable Economic Development

The present study investigates the aggregate suitability and geochemical characteristics of limestone (LS) from the Samana Suk Formation, Pakistan, for the construction industry. With the advent of CPEC, the demand for construction materials has seen a manifold increase. The Sheikh Budin Hills and Trans Indus Ranges comprise huge deposits of limestone and provide great potential for source rocks for construction materials in the region. In the Upper Indus Basin of Pakistan, the Samana Suk Formation is acknowledged as the most significant carbonate deposits of Mesozoic strata. The results of aggregate parameters reveal that specific gravity (SG = 2.6); water absorption (WA = 0.47%); bulk density (BD = 1.58 g/cm3); flakiness index (FI = 16.8%); elongation index (EI = 16.39%); soundness (S = 1.6%); aggregate impact value (AIV = 14%); Los Angeles Abrasion value (LAAV = 23.51%); clay lumps (CL = 0.35%); uniaxial compressive strength (UCS = 86.7 MPa); point load test (PLT = 5.18 MPa); ultrasonic pulse velocity (UPV = 5290 m/s); and Schmidt hammer rebound test (SHRT = 49 N) are in accordance with the ASTM, ISRM, and BSI. Petrographically, the LS is dominantly composed of ooids, peloids, bioclasts, and calcite mineral (CaCO3) with a trace concentration of dolomite [(Ca,Mg)CO3]. The mineralogical and geochemical study (n = 18) revealed that the LS is dominantly composed of calcite (95.81%); on average, it is composed of 52.08 wt.% CaO; 1.13 wt.% SiO2; 0.66 wt.% MgO; 0.80 wt.% Al2O3; and 0.76 wt.% Fe2O3, and loss on ignition (LOI) was recorded as 42.13 wt.%. On the other hand, P2O5, TiO2, MnO, K2O and Na2O were found in trace amounts. The regression analysis demonstrated that the empirical correlation equation for estimating uniaxial compressive strength with ultrasonic pulse velocity is more reliable than the Schmidt hammer rebound test and point load test. Consequently, the feasibility of using LS of the Samana Suk Formation as an aggregate for construction materials and cement manufacturing is recommended based on the testing results of mechanical, physical, and geochemical properties.

Weathering phenomena, rock physical properties and long-term restoration intervention: a case study from the St. Johannis Chapel of Lütgenrode (Lower Saxony, Germany)

Small historical churches in rural villages are mainly functional buildings, lacking spectacular architectural or ornamental features. This is also true for the St. Johannis Chapel Lütgenrode near Göttingen (Lower Saxony, Germany), which dates back to the 13th century. The use of ca. 10 different natural building stones (Triassic sandstone and limestone, Holocene fresh water carbonate), scattered roof tiles and bricks result in a highly heterogeneous character of the chapel’s ascending walls. In addition, various repairs over the last centuries, using inadequate materials, amplified damages and produced critical stability problems, in particular at the southern wall. Here, the suitability of the dimensional stones are evaluated for construction and replacement purposes. A semi-quantitative distribution of lithotypes was performed, and weathering forms were mapped in detail. On-site analyses (micro-drilling resistance, the Schmidt hammer rebound test, capillary water absorption) provide data on the deterioration state of the main lithologies. The petrophysical data show that stratigraphically comparable building stones exhibit different technical characteristics and weathering behavior. All data serve to characterize the state of weathering and provide the data set to plan for future restoration work. The amount needed for restoration work has been estimated to be approximately 435,000–550,000 EUR. Because the local church authorities evaluate the significance of a church based on the frequency of its use, a secular use would be able to save the Lütgenrode chapel, but then the church political leaders would have to act quickly.

Determination of some engineering properties of volcanic tuff using non-destructive method

Volcanic tuffs extracted from the quarries of Bayburt province in Turkey are of three different types locally identified as white, yellow and green Bayburt stones. This study was intended to estimate the compressive strength of white, yellow and green Bayburt stones by non-destructive testing methods. For this, non-destructive tests such as the nail penetration test (NPT), Schmidt rebound hammer (SRH) test and ultrasonic pulse velocity (UPV) test were performed. A uniaxial compression test was also performed so as to assess the accuracy of the results obtained from the non-destructive tests. For the NPT, nails manufactured for the gun having 27 and 39 mm length were used. In total, 45 nails were nailed and average the values were taken. Also, uniaxial compressive strength (UCS) and UPV tests were performed on 30 samples in total; furthermore, a total of 60 impacts for the SRH test were performed. The relationship between the results recorded from NPT and UCS, SRH and UPV was determined by regression analysis and comparison. The relative absolute errors between the measured values and the predicted values are below 4% for SRH-NPT comparison and below 9% for UPV-NPT comparison. This method of estimating the compressive strength, by using these non-destructive experiments, was appraised as suitable.

Nondestructive Determination of Strength of Concrete Incorporating Industrial Wastes as Partial Replacement for Fine Aggregate.

Schmidt rebound hammer test was employed in this study as a nondestructive test. This test method has been universally utilized due to its non-destructiveness for quick and easy assessment of material strength properties and quality of concrete of an existing structure. Industrial waste materials (air-dried alum sludge, treated alum sludge, limestone dust and quarry dust) were employed as replacement material for fine aggregates in this study. A normal strength concrete was designed to achieve 35 MPa at 28 days, with industrial waste materials replacing fine aggregate at different percentages (0%, 5%, 10% and 15%), and then cured for 7, 28 and 180 days. The compressive strength values and rebound numbers for all the mixes obtained were correlated, and a regression equation was established between compressive strength and Schmidt rebound number. The correlation result showed an excellent relationship between rebound number and compressive strength of concrete produced in this study at all curing ages, with correlation coefficients of R2 = 0.98, R2 = 0.99 and R2 = 0.98. The predicted equation showed a strong relationship with the experimental compressive strength. Therefore, it can be used for the prediction of compressive strength of concrete with industrial waste as a replacement for fine aggregate.

Formation processes of tafoni on pyroclastic rock surfaces with hydrothermal alteration on the Isotake coast, Shimane, Japan

Cliffs along the Isotake coast, Shimane, Japan, have two types of distinctive surfaces with different colours, with tafoni and without tafoni, even though they consist of the same pyroclastic rock. Rockfalls, which result in severe accidents, occur only on the surface without tafoni. Geochemical analyses of the cliff materials and the Schmidt hammer rebound test were conducted to elucidate the process of salt weathering in the formation of tafoni. The strontium stable isotope ratio (87Sr/86Sr) of the calcite (i.e., 0.706298) found on the backwall of tafoni indicated that the calcium in this calcite is derived from cliff materials, although the cliff receives seawater through splashing. Carbon, hydrogen, nitrogen and sulfur elemental analyses and X-ray diffraction pattern measurements revealed that clinoptilolite formed by hydrothermal alteration was more abundant in the cliff surfaces with tafoni than in those without tafoni, indicating a high abundance of calcium available for incorporation into calcite. The hardness of the cliff materials increases as the clinoptilolite content increases in any surface type. Consequently, tafoni preferentially form on surfaces with abundant clinoptilolite produced by hydrothermal alteration, although the surfaces have also been strengthened by hydrothermal alteration. Our results imply that the presence of tafoni indicates an overall lower risk of rockfalls.

Stability of weathered cut slope by using kinematic analysis

Rock slope engineering involves the designing of safe and stable rock slopes for a certain lifespan. Different rock slopes exhibit different strengths of material that reacts differently to external forces. Rock strength can decrease over time due to weathering process. In addition, the presence of discontinuity can lead to structurally controlled slope failure. The study focuses on a large exposed rock slope in Sri Jaya area, where the exposed granitic rock was cut by several sets of discontinuities. In addition to the discontinuities, the slope exhibited several weathering grades. The objective of this study is to map the weathering and discontinuity of the rock slope, in order to determine the stability of the slope. Schmidt rebound hammer tests were carried out to determine the extent of the weathering grade of the slope material. The collected field data were then analysed using the kinematic analysis to determine potential mode(s) of failure. From the analysis, it is predicted that there is significant percentage for toppling failure and wedge failure to occur in the weathered rock material.

Engineering characterisation of weathered rock at Sri Jaya, Pahang, Malaysia

Erosion and weathering are major processes that may reduce the strength of rock slope material or may cause significant change in the physical state of the slope. These can lead to landslide or slope failure, bringing significant risk in terms of properties damage and/or human safety. In Sri Jaya, Pahang, a large body of granite is exposed as cut rock slope, which shows different zones of weathering grade. Field and laboratory tests were carried out to determine the mechanical properties and the physical properties of weathered rocks of the slope, which involved a number of testing for the Schmidt rebound hammer test, point load test, moisture content, water absorption and specific gravity. From the tests, the study has determined the engineering properties of weathered rock of the slope where weathering grade and engineering properties of rock were correlated. A strong correlation was found between the weathering grade and engineering properties where they showed significant correlations for this site. It is proven that the engineering properties could be used as reliable parameters in determining the weathering grade of material in the field.

Mechanical and Physical Based Artificial Neural Network Models for the Prediction of the Unconfined Compressive Strength of Rock

Basalt rocks as building stones were used in many historical buildings in Jordan, and maintenance of these buildings is usually required with time. As part of the effort to collect the necessary information that is needed for future works in repair/strengthen the basaltic structures against any possible future damage. The dry density, Ultrasonic Pulse Velocity, Schmidt Hammer Rebound test, Brazilian Tensile Strength Test, Slake durability, and Point Load test were recorded for specimens tested in the lab to develop indirect methods of estimating the rocks Unconfined Compressive Strength (UCS). Simple regression (SR) analyses were performed to establish correlations between UCS and the results of each above-mentioned rock indices. The SR results showed that a regression model with multiple inputs is needed. In this study, the Back Propagation-Artificial Neural Network (BP-ANN) approach was utilized to predict the USC of Basalt Rock. Two ANN models were developed; one using the physical properties of rocks and the other one using the mechanical properties of rocks. Part of the data collected was used to train the ANN, and a set of independent data was used to validate the developed model. The performance of the ANN model in predicting UCS was compared to that of Multivariate Regression (MVR). The obtained results showed that the ANN model gave higher prediction performance compared to other models. A sensitivity analysis for the developed ANN model was performed to verify the importance of each input. The prediction of UCS can be used to design the proper conservation and repair/strengthen strategies that will allow dealing with the current conditions and the future natural hazards to which these structures are exposed.

In-situ strength estimation of polypropylene fibre reinforced recycled aggregate concrete using Schmidt rebound hammer and point load test

An appropriate amount of polypropylene fibre (PF) content is generally able to compensate for the low compressive strength of the recycled aggregate concrete. This mechanical strength is required to reliably estimate at the building site using partially and non-destructive testing methods. Therefore, in the present study, the compressive strength of concrete with PF at 0.1% by volume and different replacement levels of recycled coarse aggregate (RCA) was assessed using point load test (PLT) and Schmidt rebound hammer. According to the results, the sensitivity of the core specimens to the concentrated point load and the short size of PF in the failure zone of the PLT caused to appear a difference among the enhancement trends of PLI values by increasing the age. In addition, a two-variable equation between the rebound number and point load index (PLI) reliably predicted either strength of coarse natural concrete or recycled aggregate concrete or PRAC.

Concrete compressive strength using artificial neural networks

The non-destructive testing of concrete structures with methods such as ultrasonic pulse velocity and Schmidt rebound hammer test is of utmost technical importance. Non-destructive testing methods do not require sampling, and they are simple, fast to perform, and efficient. However, these methods result in large dispersion of the values they estimate, with significant deviation from the actual (experimental) values of compressive strength. In this paper, the application of artificial neural networks (ANNs) for predicting the compressive strength of concrete in existing structures has been investigated. ANNs have been systematically used for predicting the compressive strength of concrete, utilizing both the ultrasonic pulse velocity and the Schmidt rebound hammer experimental results, which are available in the literature. The comparison of the ANN-derived results with the experimental findings, which are in very good agreement, demonstrates the ability of ANNs to estimate the compressive strength of concrete in a reliable and robust manner. Thus, the (quantitative) values of weights for the proposed neural network model are provided, so that the proposed model can be readily implemented in a spreadsheet and accessible to everyone interested in the procedure of simulation.

Analysis of Compressive Strength of Existing Higher Educational Institutions (HEI) Concrete Column using a Schmidt Rebound Hammer

The Schmidt rebound hammer is principally a surface hardness tester with an apparent theoretical relationship between the strength of hardened concrete block and the rebound number of the hammer. This study analysed compressive strength of some selected concrete columns of Civil Engineering block at Covenant University Ota, using the Schmidt rebound hammer. It is aimed at determining variation in the concrete column strength of the HEI building in relation to standard compressive strength required of a concrete column. Data for the study was collected by carrying our Schmidt rebound hammer test (non-destructive test) on the concrete column within the study area and the rebound value (R) was measured to determine the present compressive strength of the concrete column. In carrying out this experiment, the standard experiment procedure of the Schmidt hammer test was followed. The analysis of the performed nondestructive test on the HEI concrete column was presented through tables and figures. The result of the study shows that there is variation in the compressive strength of the HEI concrete columns sampled using Schmidt rebound hammer test. The result indicated that the average compressive strength gotten through the rebound values of the sampled concrete columns compressive strength falls within the minimum required strength between 25N/mm2 and 30N/mm2 expected of a concrete column of an existing structure. The study therefore, concluded that the concrete columns of the HEI building sampled is safe, stable and it can satisfy the need for which it was built. Furthermore, because of it stability it can resist the load coming to it and this make it habitable for learning.

Estimation of uniaxial compressive strength of pyroclastic rocks (Cappadocia, Turkey) by gene expression programming

Compressive strength of rocks is an important factor in structural design in rock engineering. Compressive strength can be determined in the laboratory by means of the uniaxial compressive strength (UCS) test, or it can be estimated indirectly by simple experiments such as point load strength (PLT) test and Schmidt hammer rebound test. Although the UCS test method is time-consuming and expensive, it is simple when compared to other methods. Therefore, many studies have been performed to estimate UCS values of rocks. Studies indicated that correlation coefficient of rock groups is low unless they are classified as metamorphic, sedimentary, or volcanic. Pyroclastic rocks are widely used as construction materials because of the fact that they crop out over extensive areas in the world. To estimate the UCS values of pyroclastic rocks in Central and Western Anatolia region, Turkey, multiple linear regression (MLR) analysis and gene expression programming (GEP) were employed and during the analysis, and PLT, ρd, ρs, and n were used as the independent variables. Based on the analysis results, it was detected that the GEP methods gave better results than MLR method. Additionally, the correlation coefficient (R2) values of training and sets of validation of the GEP-I model are 0.8859 and 0.9325, respectively, and this model, thereby, is detected the best of generation individuals for prediction of the UCS.