Estimation Of Strength Research Articles

Multiscale Models to Evaluate the Impact of Chemical Compositions and Test Conditions on the Mechanical Properties of Cement Mortar for Tile Adhesive Applications.

This study aims to develop systematic multiscale models to accurately predict the compressive strength of cement mortar for tile adhesive applications, specifically tailored for applications in the construction industry. Drawing on data from 200 cement mortar tests conducted in previous studies, various factors such as cement/water ratios, curing times, cement/sand ratios, and chemical compositions were analyzed through static modeling techniques. The model selection involved utilizing various approaches, including linear regression, pure quadratic, interaction, M5P tree, and artificial neural network models to identify the most influential parameters affecting mortar strength. The analysis considered the water/cement ratio, testing ages, cement/sand ratio, and chemical compositions, such as silicon dioxide, calcium dioxide, iron (III) oxide, aluminum oxide, and the pH value. Evaluation metrics, such as the determination coefficient, mean absolute error, root-mean-square error, objective function, scatter index, and a-20 index, were employed to ensure the accuracy of the compressive strength estimates. Additionally, empirical equations were utilized to predict flexural and tensile strengths based on the compressive strength of the cement mortar for tile adhesive applications.

Tension Lap Splices in Recycled-Aggregate Concrete Strengthened with Steel–Polyolefin Fibers

The bond strength of tension lap splices in recycled-coarse-aggregate-reinforced concrete strengthened with hybrid (steel–polyolefin) fibers was experimentally investigated. This study was conducted with the help of twelve lap-spliced beam specimens. The replacement level of coarse natural aggregates with recycled concrete aggregate (RCA) was 100%. The following variables were investigated: various ranges of steel–polyolefin fibers—100–0%, 75–25%, 50–50%, 25–75%, and 0–100%—in which the total volume fraction of fibers (Vf) remains constant at 1%; and two lengths of lap splices for rebars of 16 mm diameter (db): 10 db and 15 db. The test results showed that the best range of steel–polyolefin fibers that gave the highest bond strength was 50–50%. The ductility of the fiber-reinforced recycled-aggregate (FR-RA) concrete was significantly improved for all the cases of various relative ratios of steel and polyolefin fibers. The bond strength was also predicted using three empirical equations proposed by Orangun et al., Darwin et al., and Harajli. This study showed that the Harajli equation gave a more accurate estimation of the bond strength of reinforcing bars embedded in FR-RA concrete than those proposed by Orangun et al. and Darwin et al.

Are Load-Velocity Estimates of Bench Press Maximal Strength as Accurate as Actual 1-Repetition Maximum Testing?

Cabarkapa, DV, Fry, AC, Kavadas, NG, and Cabarkapa, D. Are load-velocity estimates of bench press maximal strength as accurate as actual 1-repetition maximum testing? J Strength Cond Res XX(X): 000-000, 2024-The purpose of the present investigation was to determine if using maximal velocity measures while lifting submaximal loads as a predictor of bench press maximal strength (i.e., 1 repetition maximum [1RM]) is more accurate than the actual 1RM test and determine which specific submaximal loads best estimate 1RM bench press strength with the lowest variability when compared with actual 1RM tests. Sixteen recreationally trained subjects performed 5 testing sessions. The first and second sessions included the actual 1RM bench press testing, whereas the remaining 3 sessions consisted of performing one repetition of a bench press exercise in a series of incremental loads, starting at 20% 1RM and increasing the resistance by 10% until reaching the 90% of individual's 1RM. For each participant, linear regressions using bar velocities at each relative load were used to estimate 1RM capabilities, using the predetermined 1RM barbell velocities from actual 1RM testing. The results of the present investigation indicated the following: (a) actual bench press 1RM can be a highly reliable assessment of maximal strength; (b) having a greater number of loads included in the equations increases the accuracy of 1RM estimation; (c) practitioners should incorporate light (e.g., 20% 1RM) and heavy (e.g., 80 and/or 90% 1RM) loads when estimating 1RM from load-velocity profiles; and (d) most load-velocity regression equations for estimating strength are not as accurate as actual 1RM tests for the free-weight bench press. Those who use load-velocity testing to estimate 1RM strength must be willing to accept the accompanying error for most loading protocols.

Theoretical method for predicting the failure mode of reinforced concrete shear walls subjected to axial tension and cyclic lateral loads

Reinforced concrete shear walls may exhibit various failure modes when subjected to combined axial tension-flexure-shear loads. This study developed a theoretical method for predicting the failure mode of RC walls subjected to combined axial tension and cyclic lateral loads, in which the force-displacement response curve was compared to the predicted flexural, shear and sliding strength capacity curves. The formulas for calculating the axial elongation and horizontal crack widths of tensile RC walls were proposed, and the influence of these two aspects was fully considered in the estimation of shear strength and sliding strength degradation. The proposed method was validated against test data of ten RC wall specimens which underwent various failure modes, including flexural, shear, sliding, flexural-sliding, and shear-sliding failure modes. Comparisons between experimental and theoretical results indicated that the proposed method predicted the failure modes and lateral strength with acceptable accuracy. As the proposed method accurately estimated the shear and sliding strength degradation, it provided the insights on the shifting of dominated behaviors (e.g., flexural- or shear-dominated behavior to sliding-dominated behavior). Finally, strength design formulas specified in Chinese, US and European codes were verified against test data. The flexural strength of RC walls was reasonably estimated by the JGJ 3–2010 (Chinese code), ACI 318–19 (US code) and Eurocode 8 (European code) design formulas. Among the three codes, JGJ 3–2010 provided a more reasonable estimate on shear strength of tensile RC walls than the other two codes.

Investigation of mechanical properties of high-performance concrete via multi-method of regression tree approach

Concrete's workability and durability are influenced by its mechanical properties, including Tensile and Compressive strength. High-performance concrete exhibits non-linear relationships between its compressive and tensile strength characteristics and the proportions of its constituent materials, such as water, aggregate, cement, and admixtures. The investigation of the relations between the constituents of concrete and its mechanical properties has posed a challenging issue. This paper seeks to develop a range of single, hybrid, and ensemble models to resolve the problem of accurately estimating the mechanical properties of concrete according to its constituent components as input variables. In this regard, various frameworks incorporating a machine learning technique called decision tree and four metaheuristic optimization algorithms were utilized in model development to emulate the values of tensile and compressive strength. The findings indicated that the decision tree-dynamic arithmetic optimization algorithm hybrid model produced results with an correlation of determination of 0.9919 in compressive strength and 0.9933 in tensile strength, which were on average 1–3 % higher than that of the decision tree-dandelion optimizer algorithm, decision tree-arithmetic optimization algorithm, and decision tree-coot optimization algorithm, indicating superior optimization performance of dynamic arithmetic optimization algorithm. Additionally, the powerful prediction capability of the decision tree + dynamic arithmetic optimization algorithm + dandelion optimizer algorithm + coot optimization algorithm + arithmetic optimization algorithm ensemble model was noticeable with R2 of 0.9882 and 0.9936 in compressive and tensile strength estimation reliable to be used for various data produced in the future. In general, the utilization of coupling techniques to generate hybrid and ensemble models can enhance the accuracy of predictions while reducing the time and costs associated with experimental procedures.

Comparative strength estimation model of recycled aggregate concrete modified with GGBS, Metakaolin, and fly ash

Comparative strength estimation model of recycled aggregate concrete modified with GGBS, Metakaolin, and fly ash

Experimental and numerical study on the shear behavior of hybrid BFRP/steel RC beams without shear reinforcement

Hybrid reinforcement of steel and fiber-reinforced polymer (FRP) bars can provide a balanced performance between strength, ductility, and durability for the concrete structures. Thus, this study evaluates the shear performance of hybrid Basalt-FRP/steel-RC beams without shear reinforcement. A total of twelve RC beams were cast and tested under four-point loading to study the influence of reinforcement type, reinforcement ratio of longitudinal bars and axial stiffness between FRP and steel ratio, [Formula: see text] on the shear performance of the concrete beams. The test results were analyzed in terms of crack patterns, load-midspan deflection, load-crack width relationships, and shear strength of the tested beams. In addition, the experimental results were compared with the theoretical results obtained from various design codes and guidelines. Moreover, a finite element (FE) model was created, and the experimental results were used for validation of the FE model. The test results revealed that the beam specimens designed with similar effective reinforcement ratio exhibits comparable shear strength nevertheless the tensile reinforcement used. Experimental test results demonstrated that using hybrid bars increased the shear capacity of the beams by 11% compared to steel bars. Furthermore, the energy absorption of the hybrid-RC beams was enhanced by 16% compared to FRP-RC beams. By elevating the [Formula: see text] ratio from 1.25 to 2.44, both the shear strength and energy absorption improved by approximately 10%. Notably, there was a significant decrease in the deflection and crack width of the hybrid-RC beams in comparison to the FRP-RC beams. The design codes ACI440.11-22 and CSA S806-12 displayed accurate enough estimates of the shear strength, while JSCE-1997 showed a conservative result.

Adaptive neural event-dependent intermittent fault-tolerant control of reaction–diffusion multi-agent systems

This article employs an event-dependent intermittent fault-tolerant control approach to address the adaptive consensus of reaction–diffusion multi-agent systems under directed topologies in both leaderless and leader-following networks. Initially, an event-dependent intermittent control mechanism is proposed to determine the work/rest time, relying on three partitions of the non-negative real region and the formulated Lyapunov function. Subsequently, under the introduced control mechanism, an adaptive consensus protocol is established, incorporating the updating law for adaptive coupling strength and adaptive weight estimation. Utilizing the neural network estimation theorem for fault estimation, the article presents explicit criteria to ensure the attainment of leaderless or leader-following consensus in reaction–diffusion multi-agent systems. Finally, two numerical simulation experiments are conducted to validate the robustness and effectiveness of the derived theorem.

Setrusumab for the treatment of osteogenesis imperfecta: 12-month results from the phase 2b asteroid study.

Osteogenesis imperfecta (OI) is a rare genetic disorder commonly caused by variants of the type I collagen genes COL1A1 and COL1A2. OI is associated with increased bone fragility, bone deformities, bone pain, and reduced growth. Setrusumab, a neutralizing antibody to sclerostin, increased areal bone mineral density (aBMD) in a 21-week phase 2a dose escalation study. The phase 2b Asteroid (NCT03118570) study evaluated the efficacy and safety of setrusumab in adults. Adults with a clinical diagnosis of OI type I, III, or IV, a pathogenic variant in COL1A1/A2, and a recent fragility fracture were randomized 1:1:1:1 to receive 2, 8, or 20mg/kg setrusumab doses or placebo by monthly intravenous infusion during a 12-mo treatment period. Participants initially randomized to the placebo group were subsequently reassigned to receive setrusumab 20mg/kg open label. Therefore, only results from the 2, 8, and 20mg/kg double-blind groups are presented herein. The primary endpoint of Asteroid was change in distal radial trabecular volumetric bone mineral density (vBMD) from baseline at month 12, supported by changes in high-resolution peripheral quantitative computed tomography micro-finite element (microFE)-derived bone strength. A total of 110 adults were enrolled with similar baseline characteristics across treatment groups. At 12mo, there was a significant increase in mean (SE) failure load in the 20mg/kg group (3.17% [1.26%]) and stiffness in the 8 (3.06% [1.70%]) and 20mg/kg (3.19% [1.29%]) groups from baseline. There were no changes in radial trabecula vBMD (p>05). Gains in failure load and stiffness were similar across OI types. There were no significant differences in annualized fracture rates between doses. Two adults in the 20mg/kg group experienced related serious adverse reactions. Asteroid demonstrated a beneficial effect of setrusumab on estimates of bone strength across the different types of OI and provides the basis for additional phase 3 evaluation.

Estimates of functional muscle strength from a novel progressive lateral step-up test are feasible, reliable, and related to physical activity in children with cerebral palsy.

To determine if estimates of functional muscle strength from a novel progressive lateral-step-up test (LSUT) are feasible, reliable, and related to physical activity in children with cerebral palsy (CP). Cross-sectional; test-retest reliability Subjects/Patients: Children with CP and typically developing control children (n = 45/group). An LSUT with 10, 15, and 20 cm step heights was completed. It was repeated 4 weeks later in 20 children with CP. A composite score of LSUT was calculated based on the step height and number of repetitions completed. Physical activity was assessed using monitors worn on the ankle and hip. Only 4 (13%) of the children with CP were unable to complete a lateral step-up repetition without assistance. All children were able to complete at least 1 repetition with assistance, though more than twice as many children with CP required assistance at 15 and 20 cm step heights than at the 10 cm step height (p < 0.01). Children with CP had 59 to 63% lower LSUT performance, 37% lower physical activity assessed at the ankle, and 22% lower physical activity assessed at the hip than controls (all p < 0.01). The intra-class correlation coefficient ranged from 0.91 to 0.96 for LSUT performance at the different step heights and was 0.97 for the composite score. All LSUT performance measures were positively related to ankle physical activity in children with CP (r range = 0.43 to 0.47, all p < 0.01). Only performance at 20 cm and the composite score were positively related to hip physical activity (r = 0.33 and 0.31, respectively, both p < 0.05). The relationship between the LSUT performance and physical activity at both the ankle and hip increased when age and sex were statistically controlled (model r range = 0.55 to 0.60, all p < 0.001). Estimates of functional muscle strength from a novel progressive LSUT are feasible, reliable, and positively related to physical activity in children with CP.

Proposed formulas for pillar stress estimation in a regular room-and-pillar pattern

Room-and-pillar mining is one of the oldest and most widely employed underground mining methods worldwide, while in recent years it has also been used for civil engineering projects and applications. The pillar design process is quite straightforward, requiring the assessment of two key elements, namely the pillar's strength and the anticipated loading imposed on it. Lots of research work has been elaborated for the estimation of pillars' strength and the main parameters associated with it, while, on the other hand, in terms of the loading the Tributary Area Theory (TAT) has been traditionally and successfully used as the dominant methodology to assess the post-mining pillar induced stresses. This paper focuses primarily on decoding the pillar loading regime by analyzing the identifying the stresses imposed to them through the use of modern computational tools offered by 2D and 3D numerical analyses, over a series of pillars' type (square, ribs), configurations and initial virgin stress fields. This allows for the development of a benchmarking framework that showcase the differences in the stress conditions and reveal the over-conservative behavior of TAT. More importantly though, it allowed for the expression of two (2) general analytical formulae for the direct estimation of the average vertical elastic stresses on pillars, both for the case of rib & square pillars layout; the most typical patterns applied in this method. They aim at providing an easy to use and more accurate estimation of the pillar stress - as compared to TAT - in alignment with the results obtained from numerical analyses. Thus, with the proposed formulas, the time-consuming numerical process needed for preliminary pillars' dimensioning is tackled in a swift and effective manner.

Synthesis of sexual selection: a systematic map of meta-analyses with bibliometric analysis.

Sexual selection has been a popular subject within evolutionary biology because of its central role in explaining odd and counterintuitive traits observed in nature. Consequently, the literature associated with this field of study became vast. Meta-analytical studies attempting to draw inferences from this literature have now accumulated, varying in scope and quality, thus calling for a synthesis of these syntheses. We conducted a systematic literature search to create a systematic map with a report appraisal of meta-analyses on topics associated with sexual selection, aiming to identify the conceptual and methodological gaps in this secondary literature. We also conducted bibliometric analyses to explore whether these gaps are associated with the gender and origin of the authors of these meta-analyses. We included 152 meta-analytical studies in our systematic map. We found that most meta-analyses focused on males and on certain animal groups (e.g. birds), indicating severe sex and taxonomic biases. The topics in these studies varied greatly, from proximate (e.g. relationship of ornaments with other traits) to ultimate questions (e.g. formal estimates of sexual selection strength), although the former were more common. We also observed several common methodological issues in these studies, such as lack of detailed information regarding searches, screening, and analyses, which ultimately impairs the reliability of many of these meta-analyses. In addition, most of the meta-analyses' authors were men affiliated to institutions from developed countries, pointing to both gender and geographical authorship biases. Most importantly, we found that certain authorship aspects were associated with conceptual and methodological issues in meta-analytical studies. Many of our findings might simply reflect patterns in the current state of the primary literature and academia, suggesting that our study can serve as an indicator of issues within the field of sexual selection at large. Based on our findings, we provide both conceptual and analytical recommendations to improve future studies in the field of sexual selection.

A New Methodology to Estimate the Early-Age Compressive Strength of Concrete before Demolding

Non-destructive testing has many advantages, such as the ability to obtain a large number of data without destroying existing structures. However, the reliability of the estimation accuracy and the limited range of applicable targets remain an issue. This study proposes a novel pin penetration test method to determine the early-age compressive strength of concrete before demolding. The timing of demolding and initial curing is determined according to the strength development of concrete. Therefore, it is important to determine the compressive strength at an early age before demolding at the actual construction site. The applicability of this strength estimation methodology at actual construction is investigated. Small test holes (12 mm in diameter) are prepared on the mold surface in real construction sites and mock-up specimens in advance. The pin is penetrated into these test holes to obtain the relationship between the compressive strength and the penetration depth. As a result, it is confirmed that the pin penetration test method is suitable for measuring the early-age compressive strength at the actual construction site. This allows the benchmark values for compressive strength, necessary to avoid early frost damage, to be directly verified on the concrete structural members at the construction site. For instance, the compressive strengths of greater than 5 MPa and 10 MPa can be confirmed by the penetration depths benchmark values of 8.0 mm and 6.7 mm or less, respectively.

Effect of Recycled Concrete Aggregates on the Concrete Breakout Resistance of Headed Bars Embedded in Slender Structural Elements

Recycled concrete aggregates are potentially interesting for the precast concrete industry as they provide a new use for high-quality waste from its products’ life cycle. In precast concrete structures, it is common to use headed bars in several connection types between structural members. This paper presents the results of experimental tests to investigate the impact of replacing coarse natural aggregates with coarse recycled concrete aggregates in the concrete breakout strength of cast-in headed bars embedded in slender structural elements. Results of 12 tests on 16 mm headed bars embedded in 500 × 200 × 900 mm concrete members with an effective embedment depth of 110 mm are presented. The percentage of replacement of natural aggregates by recycled concrete aggregates was 0%, 30%, and 100%, and the flexural reinforcement ratio of the structural elements varied from 0.5% to 3.5%. The behavior and strength of the tested specimens are discussed, and comparisons with theoretical strength estimates are presented. The results showed that the concrete breakout strength of the headed bars was not affected by the use of recycled concrete aggregates and that the flexural reinforcement ratio significantly impacts the load-carrying capacity of the headed bars as they control the crack widths before failure.

Estimation of concrete compressive strength from non-destructive tests using a customized neural network and genetic algorithm

This paper introduces a novel approach for deriving an equation aimed at predicting concrete compressive strength, leveraging two non-destructive test results: ultrasonic pulse velocity and rebound hammer value. Traditional regression methods often fail to capture the complex non-linear relationships crucial for accurate concrete CS estimation, leading to limited effectiveness. In contrast, while machine learning models excel at mapping these non-linear relationships from non-destructive test results, their intricate internal mechanisms can be opaque, posing challenges for practical application and comprehension by engineers. This study aims to bridge these gaps by developing an estimation equation derived from the decoded weights of a neural network specifically designed to capture the intricate nonlinear mapping relationship. Initially, the equation is intricate and lengthy, comprising multiple terms. To streamline and refine it, a genetic algorithm is employed, focusing solely on the most pivotal terms. Consequently, the refined prediction equation demonstrates superior estimation performance with an RMSE of 3.40 MPa, an MAE of 2.70 MPa, an R2 of 0.92, and an R of 0.97 compared to several existing formulations. Furthermore, a comparative analysis is undertaken to assess the impact of the degree of equation simplification on its predictive accuracy. The findings offer insights into the pivotal roles of exponential function terms in enhancing prediction performance, as well as elucidating trigonometric function terms contribute the model’s complex non-linear mapping capability.

Applying Ai Techniques To Analyze Soil Data And Improve Foundation Design In Construction In Iraq

In geotechnical engineering, building robust structures is crucial to ensure the bearing capacity of structures against external forces, so making sure soil strength and unreliable build cost and duration prediction are also very important and preliminary aspects of any construction project. Therefore, in this first-of-its-kind modern examine, the capability of various artificially intelligent (AI)-based models toward reliable forecasting and estimation of preliminary construction expenses, duration, and strength at shear is explored. First, background information about the revolutionary artificial intelligence (AI) technique along with its many distinct models ideal for geotechnical and building engineering problems is presented, The use of AI-based models in the literature for the aforementioned construction and maintenance applications is discussed in a number of current works, together with their benefits, drawbacks, and future directions. Several important input elements that significantly affect the preliminary price of construction, construction time, and soil's shear strength estimation are listed and given through analysis. Finally, some obstacles to employing AI-based models for precise forecasts in these applications are discussed, along with elements influencing the problems with cost overruns. Thus, this work can help civil engineers make effective use of artificial intelligence (AI) to solve difficult and risky tasks. It can also be used to Internet of Things (IoT) environments for self-learning applications like smart architectural health-monitoring systems

Investigation of the Influence of Roughness on the Shear Resistance of Concrete-Rock Interfaces Using Random Field Simulations, Numerical Simulations, and Neural Network Modeling: Proposition of Two Approaches for the Estimation of the Peak Shear Strength

Investigation of the Influence of Roughness on the Shear Resistance of Concrete-Rock Interfaces Using Random Field Simulations, Numerical Simulations, and Neural Network Modeling: Proposition of Two Approaches for the Estimation of the Peak Shear Strength

Comparison of analytical models for shear strength estimation of steel plate girders

Web shear buckling of steel plate girders limits their load-carrying capacity in bending. Several analytical models have been suggested in the literature to estimate the shear capacity of plate girders. This paper presents a critical evaluation of several of these analytical models using the data of experimentally tested plate girders available in the literature. It was found that these analytical models make a conservative estimation of critical buckling strength for plate girders with larger slenderness and/or aspect ratios. Although the predicted ultimate shear strength varied across the different analytical models, no particular trend was identified to show that the aspect and/or slenderness ratios influenced the shear strength. A parametrically conducted analysis indicated that the threshold slenderness ratio (to cause buckling in the web panel) decreases with increasing yield strength and aspect ratio. The paper proposes simplified guidelines for the preliminary sizing of steel plate girders by avoiding shear buckling. It has been shown that the sizes of plate girders determined using the proposed guidelines satisfy design requirements for both flexure and shear.

On estimating the drift capacity of reinforced concrete walls with lap splices at their bases

AbstractFailures in reinforced concrete (RC) structural walls have been reported to occur at longitudinal lap splices in earthquakes as far back as 1964 (Kunze et al. in JP 62:635–650, 1965) and as recently as 2023 (Pujol et al. in ES 63:777, 2024). Design codes such as ACI318-19 (2019) and JSCE Standard Specification for Concrete Structures (2007) have been adjusted accordingly and have banned the placement of lap splices near sections where longitudinal reinforcement is expected to yield in reinforced concrete structural walls. But minimizing lap splice vulnerabilities in new construction does not address existing buildings that may be vulnerable to earthquakes because of lap splices placed at or near critical sections. A simple, rapid assessment technique should be adopted to address the large number of existing buildings with potentially vulnerable RC walls. To investigate the deformation capacity of structural walls with lap splices near sections where longitudinal reinforcement yields, a two-part experimental program is ongoing: four large-scale walls with non-staggered lap splices were tested at Purdue University (Pollalis Drift capacity of reinforced concrete walls with lap splices, Purdue University: West Lafayette, 2021) and two large-scale walls with staggered lap splices have been tested at the University of Canterbury (Kerby et al. Experimental study of staggered lap splices in RC structural walls, 2023). Results from these six tests are added to a dataset of 15 previous tests of walls with non-staggered lap splices compiled by Almeida et al. (JSE 143:853, 2017). A method to estimate drift capacity of walls with lap splices is proposed based on estimates of lap splice strength, steel stress–strain relationships, and moment-area theorems. Two sets of assumptions can be used to produce estimates of drift capacity. The first set of assumptions applies when detailed information of reinforcement stress–strain relationships is available, and the second set of assumptions applies when reinforcement stress–strain relationships must be assumed. Both sets of assumptions produce reasonable estimates of the drift capacity of walls with lap splices, and the second set of assumptions can be used for rapid assessment given minimal information about the detailing and material properties of a wall.

Evaluation of Bone Microstructure Parameters by Using Tomographic Methods and Compressive Strength Estimation

Objective: The aim of this study was to evaluate the microstructure of the mandible by micro computed tomography (µCT), cone beam computed tomography (CBCT) and computed tomography (CT) and to estimate the compressive strength of the bone based on the values obtained by these methods. Methods: Thirty specimens obtained from ex-vivo sheep mandible were scanned by µCT cone beam computed tomography and computed tomography. These specimens were also subjected to compression testing and compression strength values were calculated. Morphometric parameters were evaluated using ImageJ software Bland-Altman lower upper bound agreement and ICC coefficient were used to evaluate the agreement between the tomography methods used and the gold standard. Linear and multivariate stepwise regression analysis was performed to calculate the compression strength value based on the radiomorphometric parameters. Statistical significance level was accepted as .05. Results: Bone Surface/Total Volume, Bone Volume/Total Volume and Degree of Anistoropy parameters evaluated by CBCT and Fractal Dimension parameter evaluated by CT showed a statistically significant agreement with the gold standard method µCT. Bone Volume/Total Volume and Degree of Anistoropy parameters obtained with µCT (R2:0.75), Bone Volume/Total Volume, Degree of Anistoropy , Connectivity Density parameters (R2:0.62), and the Structure Model Index parameter (R2:0.13) obtained by CT can be used to predict the compression strength value. Conclusion: Bone compression strength can be estimated by CBCT and µCT methods in a desired level. Bone Volume/Total Volume and Degree of Anistoropy parameters are significant determinants of bone mechanical property in not only µCT but also CBCT method.