Impact of seismic retrofitting on progressive collapse resistance of RC frame structures

Most of the existing buildings in seismic prone regions have been built before the publication of modern design provisions against earthquakes, resulting in the need for structural retrofitting. Furthermore, some of those buildings are also subjected to additional hazards that may be either triggered by earthquakes (e.g., landslides, soil liquefaction, tsunamis) or associated with other natural or anthropogenic events, such as floods, vehicle collision, blast, and fire. A multi-hazard performance assessment of building structures is thus of paramount importance to implement integrated retrofit strategies, which otherwise would not be economically sustainable if oriented to structural risk mitigation against a single hazard. While retrofit strategies to improve the seismic performance of reinforced concrete (RC) structures have been widely investigated, structural retrofitting against progressive collapse has received very little attention. Within this context, the present paper illustrates a numerical investigation on the influence of seismic retrofitting on structural robustness of a four-storey, five-bay, RC frame building designed only to gravity loads. Seismic performance and structural robustness were respectively evaluated in OpenSees through pushover and pushdown analyses of a fibre-based finite element model. Structural robustness was evaluated under two relevant column-removal scenarios, i.e., the sudden loss of a central and a corner column, whereas earthquake resistance was assessed according to the N2 method, evidencing the need for seismic retrofitting. A retrofit measure based on carbon fibre reinforced polymers was then considered to avoid premature brittle failures. Analysis results show that this retrofit strategy was able to increase both seismic safety and structural robustness. Subsequently, a parametric analysis was carried out in order to evaluate the impact of beam span length and shear strength of the retrofitting system

Data Multi-Pushdown Automata

We extend the classical model of multi-pushdown systems by considering systems that operate on a finite set of variables ranging over natural numbers. The conditions on variables are defined via gap-order constraints that allow to compare variables for equality, or to check that the gap between the values of two variables exceeds a given natural number. Furthermore, each message inside a stack is equipped with a data item representing its value. When a message is pushed to the stack, its value may be defined by a variable. When a message is popped, its value may be copied to a variable. Thus, we obtain a system that is infinite in multiple dimensions, namely we have a number of stacks that may contain an unbounded number of messages each of which is equipped with a natural number. It is well-known that the verification of any non-trivial property of multi-pushdown systems is undecidable, even for two stacks and for a finite data-domain. In this paper, we show the decidability of the reachability problem for the classes of data multi-pushdown system that admit a bounded split-width (or equivalently a bounded tree-width). As an immediate consequence, we obtain decidability for several subclasses of data multi-pushdown systems. These include systems with single stacks, restricted ordering policies on stack operations, bounded scope, bounded phase, and bounded context switches

Automatic Schema Design for Co-Clustered Tables

Schema design of analytical workloads provides opportunities to index, cluster, partition and/or materialize. With these opportunities also the complexity of finding the right setup rises. In this paper we present an automatic schema design approach for a table co-clustering scheme called Bitwise Dimensional Co-Clustering, aimed at schemas with a moderate amount dimensions, but not limited to typical star and snowflake schemas. The goal is to design one primary schema and keep the knobs to turn to a minimum while providing a robust schema for a wide range of queries. In our approach a clustered schema is derived by trying to apply dimensions throughout the whole schema and co-cluster as many tables as possible according to at least one common dimension. Our approach is based on the assumption that initially foreign key relationships and a set of dimensions are defined based on classic DDL

Seismic and Robustness Design of Steel Frame Buildings

In this paper, a design procedure that combines both progressive collapse design under column removal scenario and capacity design to produce a hierarchy of design strengths is presented. The procedure develops in the context of the European Standards, using the classification of European steel sections and considering the seismic design features. Three-dimensional models of typical multi-storey steel frame buildings are employed in numerical analysis. The design for progressive collapse is carried out with three types of analysis, namely linear static, nonlinear static and nonlinear dynamic. Since the behaviour following sudden column loss is likely to be inelastic and possibly implicate catenary effects, both geometric and material nonlinearities are considered. The influence of the fundamental parameters involved in seismic and robustness design is finally investigated

A Perfect Model for Bounded Verification

A class of languages C is perfect if it is closed under Boolean operations and the emptiness problem is decidable. Perfect language classes are the basis for the automata-theoretic approach to model checking: a system is correct if the language generated by the system is disjoint from the language of bad traces. Regular languages are perfect, but because the disjointness problem for CFLs is undecidable, no class containing the CFLs can be perfect. In practice, verification problems for language classes that are not perfect are often under-approximated by checking if the property holds for all behaviors of the system belonging to a fixed subset. A general way to specify a subset of behaviors is by using bounded languages (languages of the form w1* ... wk* for fixed words w1,...,wk). A class of languages C is perfect modulo bounded languages if it is closed under Boolean operations relative to every bounded language, and if the emptiness problem is decidable relative to every bounded language. We consider finding perfect classes of languages modulo bounded languages. We show that the class of languages accepted by multi-head pushdown automata are perfect modulo bounded languages, and characterize the complexities of decision problems. We also show that bounded languages form a maximal class for which perfection is obtained. We show that computations of several known models of systems, such as recursive multi-threaded programs, recursive counter machines, and communicating finite-state machines can be encoded as multi-head pushdown automata, giving uniform and optimal underapproximation algorithms modulo bounded languages.Comment: 14 pages, 6 figure