1,721,025 research outputs found
The role of the fiber–matrix interfacial properties on the tensile behavior of FRCM coupons
No full textFiber-reinforced cementitious matrix (FRCM) composites are usually mechanically characterized by means of tensile and bond tests. The former, in the clevis-grip version, is referred to by the American guidelines ACI 549.4R (2013) to determine the tensile properties of the FRCM composite. The latter, in the single-lap version, is used in the Italian guidelines CNR-DT 215 (2018) to determine the effective strain. The effective strain is the strain at which debonding occurs and therefore composite action is lost. In this paper, the poliparafenilene benzobisoxazole (PBO) fiber–matrix stress transfer law, also known as cohesive material law (CML), is employed in an analytical model that describes clevis-grip tensile tests of PBO-FRCM composites. The CML was previously obtained by the authors from single-lap shear tests. The load responses provided by the model are compared with the results of tensile tests herein presented in addition to selected tests from the literature. The experimental cracking process, tensile strength, and deformation capacity can be accurately predicted by the analytical model. The comparison indicates that the knowledge of the CML of the fiber–matrix interface allows for an accurate prediction of the main tensile properties of the PBO-FRCM coupon
Cost-based domain filtering
No full textConstraint propagation is aimed at removing from variable domains combinations of values which cannot appear in any consistent solution. Pruning derives from feasibility reasoning. When coping with optimization problems, pruning can be performed also on the basis of costs, i.e., optimality reasoning. Propagation can be aimed at removing combination of values which cannot lead to solutions whose cost is better then the best one found so far. For this purpose, we embed in global constraints optimization components representing suitable relaxations of the constraint itself. These components provide efficient Operations Research algorithms computing the optimal solution of the relaxed problem and a gradient function representing the estimated cost of each variable value assignment. We exploit these pieces of information for pruning and for guiding the search. We have applied these techniques to a couple of ILOG Solver global constraints (a constraint of difference and a path constraint) and tested the approach on a variety of combinatorial optimization problems such as Timetabling, Travelling Salesman Problems and Scheduling Problems with setup. Comparisons with pure Constraint Programming approaches and related literature clearly show the benefits of the proposed approach. By using cost-based filtering in global constraints, we can optimally solve problems that are one order of magnitude greater than those solved by pure CP approaches, and we outperform other hybrid approaches integrating OR techniques in Constraint Programming
Approximate Evaluation of Maximum Force Transferable at FRP-Masonry Interface
No full textThe debonding phenomenon between fiber-reinforced polymer (FRP) composites and masonry is influenced by the presence of mortar joints that could reduce the bond capacity of the FRP-brick interface (i.e., in the absence of the joints). The actual estimate of the maximum load transferable at the FRP-masonry interface is cumbersome. Thus, the aim of this paper is twofold. First, the paper provides a set of useful key remarks to understand how the presence of joints influence the behavior of the FRP-masonry interface with respect to the FRP-brick interface. This is an important aspect of the paper because it summarizes previous work and provides guidance for designers and researchers. Secondly, this paper proposes a step-by-step procedure to obtain an approximate estimate of the maximum transferable load at the FRP-masonry interface provided that the characteristics of the FRP-brick and FRP-mortar interfaces are known or can be derived from codes and guidelines, and the thickness of brick and joints is assigned. To the best knowledge of the authors, an approximate formulation for the FRP-masonry interface is presented in this paper for the first time together with guidance to evaluate when an approximate formulation might be necessary based on the desired acceptable error. The comparison between the maximum load transferable at the FRP-masonry interface and its approximation presented in this paper provides a relative error of roughly 0.4% for case of practical interest. Finally, the paper provides an example application of the proposed procedure
Simplified Procedure to Determine the Cohesive Material Law of Fiber-Reinforced Cementitious Matrix (FRCM)–Substrate Joints
Full text linkFiber-reinforced cementitious matrix (FRCM) composites have been largely used to strengthen existing concrete and masonry structures in the last decade. To design FRCM-strengthened members, the provisions of the Italian CNR-DT 215 (2018) or the American ACI 549.4R and 6R (2020) guidelines can be adopted. According to the former, the FRCM effective strain, i.e., the composite strain associated with the loss of composite action, can be obtained by combining the results of direct shear tests on FRCM–substrate joints and of tensile tests on the bare reinforcing textile. According to the latter, the effective strain can be obtained by testing FRCM coupons in tension, using the so-called clevis-grip test set-up. However, the complex bond behavior of the FRCM cannot be fully captured by considering only the effective strain. Thus, a cohesive approach has been used to describe the stress transfer between the composite and the substrate and cohesive material laws (CMLs) with different shapes have been proposed. The determination of the CML associated with a specific FRCM–substrate joint is fundamental to capture the behavior of the FRCM-strengthened member and should be determined based on the results of experimental bond tests. In this paper, a procedure previously proposed by the authors to calibrate the CML from the load response obtained by direct shear tests of FRCM–substrate joints is applied to different FRCM composites. Namely, carbon, AR glass, and PBO FRCMs are considered. The results obtained prove that the procedure allows to estimate the CML and to associate the idealized load response of a specific type of FRCM to the corresponding CML. The estimated CML can be used to determine the onset of debonding in FRCM–substrate joints, the crack number and spacing in FRCM coupons, and the locations where debonding occurs in FRCM-strengthened members
Meccanismi di collasso delle costruzioni storiche per azione sismica ed interventi compatibili di miglioramento mediante materiali compositi
No full textCutting planes in constraint programming: An hybrid approach
No full textIn recent years, a growing number of attempts have been performed in order to integrate well known Operations Research(OR) techniques in Constraint Programming (CP) tools. The aim of the integration is to maintain the modelling facilities of the CP paradigm, while improving its performances by exploiting effective OR techniques. In our previous work, we proposed the use of optimization constraints [9], embedding a linear relaxation of the constraint itself and performing pruning on the basis of costs. In particular, domain values can be removed whenever it can be shown that their assignment will necessarily lead to solutions worse than the best solution found. In this setting, the use of cutting planes in global constraints allows to tighten the relaxation so as to infer more accurate bounds on the problem. We propose different ways of using cutting-planes in optimization constraints achieving different levels of tightness of the integration and pruning power. Even if the proposed technique is general, we use as testing application the Travelling Salesman Problem (TSPs) and its time constrained variant. Computational results compare different relaxations in terms of pruning achieved and computational complexity
Driven Failure mechanism in fiber-reinforced plastic prestressed beams for ductility requirements
No full textEmbedding relaxations in global constraints for solving TSP and TSPTW
No full textConstraint Programming (CP) has been successfully applied to several combinatorial optimization problems. One of its advantages is the availability of complex global constraints performing efficient propagation and interacting with each other through shared variables. However, CP techniques have shown their limitations in dealing with optimization problems since the link between the objective function and problem decision variables is often quite loose and does not produce an effective propagation. We propose to integrate optimization components in global constraints, aimed at optimally solving a relaxation corresponding to the constraint itself. The optimal solution of the relaxation provides pieces of information which can be exploited in order to perform pruning on the basis of cost-based reasoning. In fact, we exploit reduction rules based on lower bound and reduced costs calculation to remove those branches which cannot improve the best solution found so far. The interest of integrating efficient well-known Operations Research (OR) algorithms into CP is mainly due to the smooth interaction between CP domain reduction and information provided by the relaxation acting on variable domains which can be seen as a communication channel among different techniques. We have applied this technique to symmetric and asymmetric Traveling Salesman Problem (TSP) instances both because the TSP is an interesting problem arising in many real-life applications, and because pure CP techniques lead to disappointing results for this problem. We have tested the proposed optimization constraints using ILOG solver. Computational results on benchmarks available from literature, and comparison with related approaches are described in the paper. The proposed method on pure TSPs improves the performances of CP solvers, but is still far from the OR state of the art techniques for solving the problem. However, due to the flexibility of the CP framework, we could easily use the same technique on TSP with Time Windows, a time constrained variant of the TSP. For this type of problem, we achieve results that are comparable with state of the art OR results
Optimization-oriented global constraints
No full textIn this paper, we propose a way of exploiting Operations Research techniques within global constraints for cost-based domain filtering. In Constraint Programming, constraint propagation is aimed at removing from variable domains combinations of values which are proven infeasible. Pruning derives from feasibility reasoning. When coping with optimization problems, pruning can be performed also on the basis of costs, i.e., optimality reasoning. Cost-based filtering removes combination of values which are proven sub-optimal. For this purpose, we encapsulate in global constraints optimization components representing suitable relaxations of the constraint itself. These components embed efficient Operations Research algorithms computing the optimal solution of the relaxed problem and a gradient function representing the estimated cost of each variable-value assignment. We exploit these pieces of information for pruning and for guiding the search. We have applied these techniques to a couple of ILOG Solver global constraints (a constraint of difference and a path constraint) and tested the approach on a variety of combinatorial optimization problems such as Timetabling, Travelling Salesman Problems and Scheduling Problems with sequence dependent setup times. Comparisons with pure Constraint Programming approaches and related literature clearly show the benefits of the proposed approach
Mathematical programming techniques in constraint programming: A short overview
No full textIn recent years, the integration of techniques from Artificial Intelligence and Operations Research has shown to improve the solutions of complex and large scale combinatorial optimization problems, in terms of efficiency, scalability and optimality. In this context, Constraint Programming is an emerging discipline situated at the confluence of the two fields that has been recognized as a suitable environment for achieving such an integration. This paper briefly presents the integration directions explored in the literature, and provides some pointers to relevant work in these directions
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