Life-cycle robustness : quantification and challenges

Life-cycle robustness is achieved when a structural member or a system is designed to maintain its intended function and required safety level within its desired life-cycle. The different character of effects that each element of the system needs to undergo (damage, ageing, extreme events, changes in usage) in conjunction with the diversity in the intrinsic material properties, form a demanding problem. Further complexity emerges when one realizes that time is not simply a variable, but a factor permeating model choices and uncertainty representation approaches. Different effects in the load side, and properties in the resistance side develop differently in time. Depending on the scale of the problem, the spatial randomness of materials such as concrete may be relevant for the accurate quantification of failure probabilities, and may require careful modelling, even at a mesoscale. For a long-term analysis, where the influence of uncertainties may dominate over predictability, robust design concepts and analyses methods that are relatively insensitive to small variations in variable inputs related to secondary effects and processes can prove decisive. On the computational side, challenges are associated with the computational cost of simulations and nonlinear analyses required to determine time-variable reliability profiles, considering all likely scenarios. Furthermore, statistical characteristics of the inputs, in particular their tail behaviour and their statistical dependence, needs to be properly captured and reproduced while maintaining sufficiently small sample size, and thus acceptable computational cost. Within this contribution, a framework for the quantification of life-cycle robustness is presented in the context of fasteners subjected to sustained load and extreme events. The emerging challenges are presented and briefly discussed

Life-cycle robustness : prospects and challenges

Life-cycle robustness is achieved when a structural member or a whole system is designed to maintain its intended function and required safety level within its desired life-cycle. The different characters of effects that each element will need to undergo (damage, ageing, extreme events, changes in usage) in conjunction with the diversity in the intrinsic material properties, form a demanding problem. Further complexity emerges when one realises that time is not simply a variable, but a factor permeating model choices and uncertainty representation approaches. Different effects on the load side and properties on the resistance side develop differently in time, as does the dependence structure. Spatial randomness of materials, such as concrete, requires careful modelling, especially at a meso-scale. For a log-term analysis, where the influence of uncertainty may dominate over predictability, robust design can prove decisive. On the computational side, challenges often appear since the computational costs of simulations and non-linear analyses may quickly prove infeasible. Suitable numerical techniques for small scale sampling, accounting for arbitrary distribution types and dependence structures, are yet to be developed. The realistic prediction of spatial randomness for now fails due to a lack of understanding regarding the physical basis of main input parameters. Within this contribution the authors present the general concept of life-cycle robustness and the expected prospects that arise from its application to fastening systems. A detailed discussion of the aforementioned challenges and review of the state of the art complement the paper

Life-cycle robustness : quantification and challenges

Life-cycle robustness is achieved when a structural member or a system is designed tomaintain its intended function and required safety level within its desired life-cycle. The different characterof effects that each element of the system needs to undergo (damage, ageing, extreme events, changesin usage) in conjunction with the diversity in the intrinsic material properties, form a demanding problem.Further complexity emerges when one realizes that time is not simply a variable, but a factor permeatingmodel choices and uncertainty representation approaches. Different effects in the load side, and propertiesin the resistance side develop differently in time. Depending on the scale of the problem, the spatialrandomness of materials such as concrete may be relevant for the accurate quantification of failure probabilities,and may require careful modelling, even at a mesoscale. For a long-term analysis, where theinfluence of uncertainties may dominate over predictability, robust design concepts and analyses methodsthat are relatively insensitive to small variations in variable inputs related to secondary effects andprocesses can prove decisive. On the computational side, challenges are associated with the computationalcost of simulations and nonlinear analyses required to determine time-variable reliability profiles,considering all likely scenarios. Furthermore, statistical characteristics of the inputs, in particular theirtail behaviour and their statistical dependence, needs to be properly captured and reproduced while maintainingsufficiently small sample size, and thus acceptable computational cost. Within this contribution, aframework for the quantification of life-cycle robustness is presented in the context of fasteners subjectedto sustained load and extreme events. The emerging challenges are presented and briefly discussed.Life-cycle robustness is achieved when a structural member or a system is designed tomaintain its intended function and required safety level within its desired life-cycle. The different characterof effects that each element of the system needs to undergo (damage, ageing, extreme events, changesin usage) in conjunction with the diversity in the intrinsic material properties, form a demanding problem.Further complexity emerges when one realizes that time is not simply a variable, but a factor permeatingmodel choices and uncertainty representation approaches. Different effects in the load side, and propertiesin the resistance side develop differently in time. Depending on the scale of the problem, the spatialrandomness of materials such as concrete may be relevant for the accurate quantification of failure probabilities,and may require careful modelling, even at a mesoscale. For a long-term analysis, where theinfluence of uncertainties may dominate over predictability, robust design concepts and analyses methodsthat are relatively insensitive to small variations in variable inputs related to secondary effects andprocesses can prove decisive. On the computational side, challenges are associated with the computationalcost of simulations and nonlinear analyses required to determine time-variable reliability profiles,considering all likely scenarios. Furthermore, statistical characteristics of the inputs, in particular theirtail behaviour and their statistical dependence, needs to be properly captured and reproduced while maintainingsufficiently small sample size, and thus acceptable computational cost. Within this contribution, aframework for the quantification of life-cycle robustness is presented in the context of fasteners subjectedto sustained load and extreme events. The emerging challenges are presented and briefly discussed.C