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Brittle failures of connections with self- tapping screws on CLT plates
Abstract
For general safety reasons, the occurrence of a ductile failure mechanism in the global scale of the building is desirable. Recent works have proposed analytical models to predict the brittle capacity of dowel-type timber connections, some of them discussed in previous INTER meetings [1-5]. It is planned to include brittle failure models in the future version of
Eurocode 5 and the design provisions for self-tapping screws in the Canadian timber design standard (CSA O86), both currently under development. However, most of the previous works were related to the brittle failure of solid and glued-laminated timber. It is usually assumed that connections with dowel-type fastener inserted into the CLT side face and loaded laterally typically behave in a quite ductile manner. Even the current CSA O86 explicitly states that ‘for CLT, the row shear failure and group tear-out failure need not be considered’ [2]. However, as shown in previous works [1-2], brittle failures may also occur in CLT.
Zarnani and Quenneville [1] adapted their brittle failure model for plug shear for its application on CLT connections.
Connections in CLT are typically produced with self-tapping screws (STS), which partially penetrate into the timber
element. The corresponding brittle failure is plug-shear, in which bottom, lateral and head failure planes are observed.
Zarnani and Quenneville described different types of failures related to the different fastener penetration depth.
This work presents two recent experimental campaigns on brittle failures of CLT connections with self-tapping screws,
done in Europe and Canada. The connections were tested in tension parallel to the grain of the outer CLT layer. The tests
provide a preliminary insight into the brittle failures of connections in CLT panels, a matter which has been barely studied.
However, it is of importance, due to the current prevalence of this type of timber product and its increased use.
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Cross laminated timber (CLT) is becoming increasingly popular in timber construction due to its versatility. However, its structural anistropy requires the application of particular concepts and design methods. The article on hand presents the results of a worldwide survey conducted among engineers working with this product. Thus, it presents the current state of knowledge and practice on CLT construction: an overview of the experience of engineers working with CLT design, the commonly used verification methods, and the implementation of the material properties and different required assumptions in the software. An outlook to design problems in complex design situations relevant for multi-storey buildings and potential research fields is indicated additionally. The general picture is quite heterogeneous, with little consensus on the assumptions, design methods or applied tools. A wide repertoire of different approaches based on a large range of literature is found in practice. This is in part the result of the current lack of standardisation and currently incomplete regulations. Future efforts should focus on these two aspects to increase the applicability of CLT globally and strengthen its competitiveness.
The performance of structural timber connections is of utmost importance since they control the global response of the building. A ductile failure mechanism on the global scale is desirable, especially in the design of structures in seismic areas, where dissipative components in which ductile failure modes need to be ensured are considered. Therefore, the knowledge of possible brittle failure modes of connections is crucial. The paper investigates the brittle failures of laterally loaded dowel-type connections in cross-laminated timber subjected to tensile load in a lap joint configuration through experimental investigations and analytical estimations. A set of 13 different test series has been performed with fully threaded self-tapping screws of 8 mm diameter and different lengths (40 to 100 mm) in cross-laminated timber composed of 3 or 5 layers (layer thickness range from 20 to 40 mm), giving rise to the activation of different brittle failure modes at different depths. Plug shear was among the most typically observed failure modes. A previously proposed model for the brittle capacity was applied to the tested connections at the characteristic level. As shown by the performed statistical analysis, the existing model is not reliable and mainly unconservative. A very low performance is observed (CCC = 0.299), but with a good correlation (c = 0.750) for the tests in the parallel direction. Further research work is required to improve the current model predictions and to gain a better understanding of the underlying resisting mechanisms.
Novel solutions with large-diameter connectors for cross-laminated timber (CLT) assemblies require wood brittle failure to be avoided through capacity-design-based provisions to protect the CLT panels. Current design standards, such as the Canadian Standard for Engineering Design in Wood (CSA-O86), do not cover the block tear-out resistance of CLT panels associated with large-diameter connectors. The primary objective of the research presented herein was to assess the block tear-out and net-section tension resistances of CLT panels loaded in plane and to provide guidance for the required end distances of single large-diameter connectors such as internal-bearing hold-downs. A total of 117 full-scale CLT specimens were tested to determine their in-plane tear-out resistance. 3-ply and 5-ply CLT panels with different loaded end and the edge distances and varying the grain direction of the outer layers were tested under quasi-static monotonic loading. The results demonstrate that brittle block tear-out or net-section tension failure can occur in CLT panels. These failure modes have to be accounted for in design. A simple stress-based strength criterion considering the rolling shear strength of wood delivers conservative and reasonably accurate predictions of the CLT brittle resistance.
Timber connections with steel dowel-type fasteners may fail in ductile or brittle ways. The design of this joints was traditionally focused on ductile failure, assuming that brittle failure could be avoided by means of geometrical limitations. However, recent studies demonstrated that these assumptions do not always guarantee ductile failure. A new design model for timber connections with small diameter dowel-type fasteners is provided in this paper. Its improved accuracy is demonstrated by analysing an extensive database of experimental tests and comparing its prediction accuracy to that of existing models.
Existing prediction models for parallel to grain wood failure in timber connections using dowel-type fasteners consider the minimum, maximum, or summation of the tensile and shear capacities of the failed wood block planes. This results in disagreements between the experimental values and the predictions because the stiffness of the tensile and shear planes differs, which leads to uneven load distribution among the resisting planes. The present study focuses on timber rivet connections. A closed-form analytical method is proposed to determine the load-carrying capacity of wood under longitudinal loading in rivet connections in timber products. For the wood strength, the stiffness and strength of the planes subjected to nonuniform shear and tension stresses are taken into account. Furthermore, an algorithm is presented that allows the designer to predict the possible brittle, ductile, and mixed failure modes. The results of tests on New Zealand Radiata Pine Laminated Veneer Lumber (LVL) and glulam, and data available from the literature, confirm the validity of this new method and show that this predictive method can be used advantageously in comparison with other existing models.
The performance of prediction models can be assessed using a variety of methods and metrics. Traditional measures for binary and survival outcomes include the Brier score to indicate overall model performance, the concordance (or c) statistic for discriminative ability (or area under the receiver operating characteristic [ROC] curve), and goodness-of-fit statistics for calibration.Several new measures have recently been proposed that can be seen as refinements of discrimination measures, including variants of the c statistic for survival, reclassification tables, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Moreover, decision-analytic measures have been proposed, including decision curves to plot the net benefit achieved by making decisions based on model predictions.We aimed to define the role of these relatively novel approaches in the evaluation of the performance of prediction models. For illustration, we present a case study of predicting the presence of residual tumor versus benign tissue in patients with testicular cancer (n = 544 for model development, n = 273 for external validation).We suggest that reporting discrimination and calibration will always be important for a prediction model. Decision-analytic measures should be reported if the predictive model is to be used for clinical decisions. Other measures of performance may be warranted in specific applications, such as reclassification metrics to gain insight into the value of adding a novel predictor to an established model.
Timber connections with small diameter fasteners that do not go through the whole timber member (such as screws or nails). may fail in brittle or ductile ways. In order to better understand their behaviour, an experimental campaign of tests of connections with small diameter fasteners loaded parallel-to-grain has been performed. The results and analysis of this work provide further information on the role of different parameters in the brittle failure. Existing models are benchmarked against these tests.
Timber connections may collapse in a brittle or in a ductile mode. The calculation models of timber joints are mainly focused on ductile failure mode, since it has been traditionally assumed that brittle failure was avoided by respecting a minimum spacing between fasteners. However, this assumption alone does not guarantee a ductile failure. This paper proposes a new design model dealing with brittle failure modes of timber connections with large diameter fasteners (those protruding the whole thickness of the timber member such as dowels or bolts). A comparison between the proposal and the existing models, using an extensive database of tests, is used to demonstrate the improved accuracy of the proposed design method.
For safety reasons, ductile failure in timber connections with dowel-type fasteners is always recommended. It has usually been assumed that it can be achieved by fulfilling minimum spacing requirements between fasteners. However, recent works address the need to account for brittle failure modes (namely splitting, row-shear, and block and plug-shear) in connections loaded parallel-to-the-grain in an explicit manner, in order to evaluate them and achieve the desired ductility. This article describes the brittle failure modes and reviews the existing calculation models proposed by several authors – some of them included in standards. Finally, the performance of these models is assessed against an extensive database of tests gathered from the literature following a comprehensive methodology.
In the last years, external validation of QSAR models was the subject of intensive debate in the scientific literature. Different groups have proposed different metrics to find “the best” parameter to characterize the external predictivity of a QSAR model. This editorial summarizes the history of parameter development for the external QSAR model validation and suggests, once again, the concurrent use of several different metrics, to assess the real predictive capability of QSAR models.
The statistical metrics used to characterize the external predictivity of a model, i.e., how well it predicts the properties of an independent test set, have proliferated over the past decade. This paper clarifies some apparent confusion over the use of the coefficient of determination, R^2, as a measure of model fit and predictive power in QSAR and QSPR modelling. R^2 has been used in various contexts in the literature in conjunction with training and test data, for both ordinary linear regression and regression through the origin as well as with linear and nonlinear regression models. We analyse the widely adopted model fit criteria suggested by Golbraikh and Tropsha1 in a strict statistical manner. Shortcomings in these criteria are identified and a clearer and simpler alternative method to characterize model predictivity is provided. The intent is not to repeat the well-documented arguments for model validation using test data, but to guide the application of R^2 as a model fit statistic. Examples are used to illustrate both correct and incorrect use of R^2. Reporting the root mean squared error or equivalent measures of dispersion, typically of more practical importance than R^2, is also encouraged and important challenges in addressing the needs of different categories of users such as computational chemists, experimental scientists, and regulatory decision support specialists are outlined.
The evaluation of regression QSAR model performance, in fitting, robustness, and external prediction, is of pivotal importance. Over the past decade, different external validation parameters have been proposed: Q(F1)(2), Q(F2)(2), Q(F3)(2), r(m)(2), and the Golbraikh-Tropsha method. Recently, the concordance correlation coefficient (CCC, Lin), which simply verifies how small the differences are between experimental data and external data set predictions, independently of their range, was proposed by our group as an external validation parameter for use in QSAR studies. In our preliminary work, we demonstrated with thousands of simulated models that CCC is in good agreement with the compared validation criteria (except r(m)(2)) using the cutoff values normally applied for the acceptance of QSAR models as externally predictive. In this new work, we have studied and compared the general trends of the various criteria relative to different possible biases (scale and location shifts) in external data distributions, using a wide range of different simulated scenarios. This study, further supported by visual inspection of experimental vs predicted data scatter plots, has highlighted problems related to some criteria. Indeed, if based on the cutoff suggested by the proponent, r(m)(2) could also accept not predictive models in two of the possible biases (location, location plus scale), while in the case of scale shift bias, it appears to be the most restrictive. Moreover, Q(F1)(2) and Q(F2)(2) showed some problems in one of the possible biases (scale shift). This analysis allowed us to also propose recalibrated, and intercomparable for the same data scatter, new thresholds for each criterion in defining a QSAR model as really externally predictive in a more precautionary approach. An analysis of the results revealed that the scatter plot of experimental vs predicted external data must always be evaluated to support the statistical criteria values: in some cases high statistical parameter values could hide models with unacceptable predictions.
The main utility of QSAR models is their ability to predict activities/properties for new chemicals, and this external prediction ability is evaluated by means of various validation criteria. As a measure for such evaluation the OECD guidelines have proposed the predictive squared correlation coefficient Q(2)(F1) (Shi et al.). However, other validation criteria have been proposed by other authors: the Golbraikh-Tropsha method, r(2)(m) (Roy), Q(2)(F2) (Schüürmann et al.), Q(2)(F3) (Consonni et al.). In QSAR studies these measures are usually in accordance, though this is not always the case, thus doubts can arise when contradictory results are obtained. It is likely that none of the aforementioned criteria is the best in every situation, so a comparative study using simulated data sets is proposed here, using threshold values suggested by the proponents or those widely used in QSAR modeling. In addition, a different and simple external validation measure, the concordance correlation coefficient (CCC), is proposed and compared with other criteria. Huge data sets were used to study the general behavior of validation measures, and the concordance correlation coefficient was shown to be the most restrictive. On using simulated data sets of a more realistic size, it was found that CCC was broadly in agreement, about 96% of the time, with other validation measures in accepting models as predictive, and in almost all the examples it was the most precautionary. The proposed concordance correlation coefficient also works well on real data sets, where it seems to be more stable, and helps in making decisions when the validation measures are in conflict. Since it is conceptually simple, and given its stability and restrictiveness, we propose the concordance correlation coefficient as a complementary, or alternative, more prudent measure of a QSAR model to be externally predictive.
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