1,455 research outputs found
Study of high resistance inorganic coatings on graphite fibers
Coatings made of boron, silicon carbide, silica, and silica-like materials were studied to determine their ability to increase resistance of graphite fibers. The most promising results were attained by chemical vapor depositing silicon carbide on graphite fiber followed by oxidation, and drawing graphite fiber through ethyl silicate followed by appropriate heat treatments. In the silicon carbide coating studies, no degradation of the graphite fibers was observed and resistance values as high as three orders of magnitude higher than that of the uncoated fiber was attained. The strength of a composite fabricated from the coated fiber had a strength which compared favorably with those of composites prepared from uncoated fiber. For the silica-like coated fiber prepared by drawing the graphite fiber through an ethyl silicate solution followed by heating, coated fiber resistances about an order of magnitude greater than that of the uncoated fiber were attained. Composites prepared using these fibers had flexural strengths comparable with those prepared using uncoated fibers, but the shear strengths were lower
Coatings for graphite fibers
Graphite fibers released from composites during burning or an explosion caused shorting of electrical and electronic equipment. Silicon carbide, silica, silicon nitride and boron nitride were coated on graphite fibers to increase their electrical resistances. Resistances as high as three orders of magnitude higher than uncoated fiber were attained without any significant degradation of the substrate fiber. An organo-silicone approach to produce coated fibers with high electrical resistance was also used. Celion 6000 graphite fibers were coated with an organo-silicone compound, followed by hydrolysis and pyrolysis of the coating to a silica-like material. The shear and flexural strengths of composites made from high electrically resistant fibers were considerably lower than the shear and flexural strengths of composites made from the lower electrically resistant fibers. The lower shear strengths of the composites indicated that the coatings on these fibers were weaker than the coating on the fibers which were pyrolyzed at higher temperature
Surrogate probabilistic seismic demand modelling of inelastic single-degree-of-freedom systems for efficient earthquake risk applications
This paper proposes surrogate models (or metamodels) mapping the parameters controlling the dynamic behaviour of inelastic single-degree-of-freedom (SDoF) systems (i.e., force-displacement capacity curve, hysteretic behaviour) and the parameters of their probabilistic seismic demand model (PSDM, i.e., conditional distribution of an engineering demand parameter [EDP] given a ground-motion intensity measure [IM]). These metamodels allow the rapid derivation of fragility curves of SDoF representation of structures. Gaussian Process (GP) regression is selected as the metamodelling approach because of their flexibility in implementation, the resulting accuracy and computational efficiency. The metamodel training dataset includes 10,000 SDoF systems analysed via cloud-based non-linear time-history analysis (NLTHA) using recorded ground motions. The proposed GP regressions are tested in predicting the PSDM of both the SDoF database (through ten-fold cross validation) and eight realistic reinforced concrete (RC) frames, benchmarking the results against NLTHA. An application is conducted to propagate such modelling uncertainty to both fragility and vulnerability/loss estimations. Error levels are deemed satisfactory for practical applications, especially considering the low required modelling effort and analysis time. Regarding single-building applications enabled by the proposed metamodel, this paper presents a first attempt at a direct loss-based design procedure, which allows setting a target loss level for the designed structure (shown for a realistic RC frame). An earthquake risk model involving dynamic exposure and vulnerability modules is illustrated as an example of building portfolio applications. Specifically, the proposed application considers a retrofit-based seismic risk-reduction policy for a synthetic building portfolio, for which it is possible estimating the loss evolution over time
Optimal retrofit selection for seismically-deficient RC buildings based on simplified performance assessment
This study deals with the selection of optimal retrofit solutions for seismically-deficient Reinforced Concrete (RC) buildings. To this aim, Multi-Criteria Decision-Making (MCDM) analysis is used. A discussion on the retrofit design strategy is first presented, recommending
designing each retrofit solution for the same expected damage state under the design-level
earthquake-induced ground-motion spectrum. Secondly, it is argued to explicitly consider seismic economic losses as a decision criterion. To this aim, seismic fragility/vulnerability relationships are derived for the structure of interest retrofitted with different techniques and
considering a large suite of ground-motion records. Simplified-yet-accurate non-linear static
procedures are used as an alternative to non-linear time-history analysis to reduce the challenges in building detailed numerical models, computational demand, and results interpretation. Specifically, three increasingly-refined structural analysis methods are adopted to derive
fragility/vulnerability curves: the Simple Lateral Mechanism Analysis (SLaMA), which is an
analytical approach; numerical pushover; and non-linear time-history analysis. A seismicallydeficient RC school index building, with construction details typical of developing countries, is
used for illustrative purposes. The case-study structure is retrofitted through concrete jacketing, addition of concrete walls, and addition of steel braces, all designed through Direct Displacement-Based Design. The MCDM analysis is performed adopting, among other criteria,
intensity-based losses derived with the three considered analysis methods, using state-of-theart, advanced ground-motion intensity measures. The results show that the ranking of the retrofit alternatives is rather insensitive to the adopted analysis method, even if the considered
weight for the seismic loss criterion is relatively high (30% in this example). Findings from this
study suggest that simplified analysis methods can be effectively employed in the preliminary/conceptual design of retrofit solutions for seismically-deficient buildings
Hysteretic energy-based state-dependent fragility for ground-motion sequences
A framework to derive state‐dependent fragility relationships of structures subjected to ground‐motion sequences (e.g. mainshock‐aftershock (MS‐AS) or triggered earthquakes) is proposed. The hysteretic energy dissipated in the sequence is adopted as the main demand parameter, as it is a cumulative measure monotonically increasing with the length of the excitation. For a structure subjected to earthquake‐induced ground motions, it is not possible to define a closed‐form representation of the hysteretic energy as a function of the peak deformation. However, based on theoretical considerations, the hysteretic energy‐peak deformation trend is discussed, highlighting that (a) the significant duration of the ground motion explains the variability of the hysteretic energy for a given peak deformation; (b) the hysteretic energy dissipated in an AS decreases (for a given AS peak displacement) if the peak displacement in the MS increases. A vector‐valued probabilistic seismic demand model consistent with these considerations is proposed in the form of a surface relating the hysteretic energy in the sequence to the peak deformation in the MS and a ground‐motion intensity measure of the AS. This is calibrated via sequential cloud‐based time‐history analyses. The framework is demonstrated for 14 reinforced concrete frame buildings with different height, plastic mechanisms, and infill distributions. The results show the feasibility of the proposed approach, effectively capturing damage accumulation without inconsistencies in the obtained statistical model. The framework may be used for risk‐assessment applications explicitly incorporating ground‐motion sequences. The hysteretic energy versus peak deformation relationship may also be exploited in problems involving long‐duration ground motions or soft soils
Simplicity versus accuracy trade-off in estimating seismic fragility of existing reinforced concrete buildings
This paper investigates the trade-off between simplicity (modelling effort and computational time) and result accuracy in seismic fragility analysis of reinforced concrete (RC) frames. For many applications, simplified methods focusing on “archetype” structural models are often the state-of-practice. These simplified approaches may provide a rapid-yet-accurate estimation of seismic fragility, requiring a relatively small amount of input data and computational resources. However, such approaches often fail to capture specific structural deficiencies and/or failure mechanisms that might significantly affect the final assessment outcomes (e.g. shear failure in beam-column joints, in-plane and out-of-plane failure of infill walls, among others). To overcome these shortcomings, the alternative response analysis methods considered in this paper are all characterised by a mechanics-based approach and the explicit consideration of record-to-record variability in modelling seismic input/demands. Specifically, this paper compares three different seismic response analysis approaches, each characterised by a different refinement: 1) low refinement - non-linear static analysis (either analytical SLaMA or pushover analysis), coupled with the capacity spectrum method; 2) medium refinement - non-linear time-history analysis of equivalent single degree of freedom (SDoF) systems calibrated based on either the SLaMA-based or the pushover-based force-displacement curves; 3) high refinement - non-linear time-history analysis of multi-degree of freedom (MDoF) numerical models. In all cases, fragility curves are derived through a cloud-based approach employing unscaled real (i.e. recorded) ground motions. 14 four- or eight-storey RC frames showing different plastic mechanisms and distribution of the infills are analysed using each method. The results show that non-linear time-history analysis of equivalent SDoF systems is not substantially superior with respect to a non-linear static analysis coupled with the capacity spectrum method. The estimated median fragility (for different damage states) of the simplified methods generally falls within ±20% (generally as an under-estimation) of the corresponding estimates from the MDoF non-linear time-history analysis, with slightly-higher errors for the uniformly-infilled frames. In this latter cases, such error range increases up to ±32%. The fragility dispersion is generally over-estimated up to 30%. Although such bias levels are generally non-negligible, their rigorous characterisation can potentially guide an analyst to select/use a specific fragility derivation approach, depending on their needs and context, or to calibrate appropriate correction factors for the more simplified methods
Simplified seismic loss assessment for optimal structural retrofit of RC buildings
This study deals with selecting optimal seismic retrofit solutions for reinforced concrete (RC) buildings. To this aim, multi-criteria decision-making (MCDM) is implemented explicitly considering earthquake-induced economic loss as a decision criterion. Fragility (i.e. likelihood of damage levels vs intensity measure (IM) levels) and vulnerability (i.e. likelihood of loss levels vs IM levels) relationships are derived by using three increasingly refined analysis methods: Simple Lateral Mechanism Analysis; numerical pushover; time-history analysis. A seismically deficient RC school index building, with construction details typical of developing countries, is used for illustrative purposes. Concrete jacketing, addition of concrete walls, and addition of steel braces are the considered retrofit alternatives. Intensity-based expected loss and expected annual loss are adopted in the MCDM, among other criteria, independently derived with the three analysis methods. It is shown that, given the adopted loss-analysis methodology, the ranking of the retrofit alternatives is insensitive to both analysis methods and loss metrics, even when the weight for the seismic loss criterion is high. These findings suggest that simplified methods can be effectively employed in the conceptual/preliminary design of retrofit alternatives
A computational framework for selecting the optimal combination of seismic retrofit and insurance coverage
Economic earthquake losses can be mitigated through either building retrofit strategies and/or, to some extent, risk-transfer to the (re)insurance market. This paper proposes a computational framework to select the optimal combination of seismic retrofit and insurance policy parameters for buildings. First, a designer selects a suitable retrofit strategy. This is implemented incrementally to define interventions with increasing retrofit performance levels. The cost of each intervention is calculated, along with the cost of property rental while the retrofit is implemented. Alternative insurance options are considered. For each retrofit-insurance combination, the insured and uninsured economic losses within a given time horizon are estimated. The optimal retrofit and insurance combination minimizes the tail value at risk of the life cycle cost. The selected confidence level for this metric depends on the homeowner's risk aversion. The proposed framework is illustrated for a case-study archetype Italian reinforced concrete frame building retrofitted with concrete jacketing, also considering the Italian retrofit tax incentives/rebates called “Sismabonus.
A multi-fidelity Bayesian framework for robust seismic fragility analysis
Fragility analysis of structures via numerical methods involves a complex trade-off between the desired accuracy, the explicit consideration of uncertainties (both epistemic and aleatory) related to the numerical structural model and the available computational performance. This paper introduces a framework for deriving numerical fragility relationships based on multi-fidelity non-linear models of the structure under investigation and response-analysis types. The proposed framework aims to reduce the computational burden while achieving a desired accuracy of the fragility estimates without neglecting aleatory and epistemic uncertainties. The proposed approach is an extension of the well-known robust fragility (RF) analysis framework. Different model classes, each characterised by increasing refinement, are used to define multi-fidelity polynomial expansions of the fragility model parameters. Each analysis result is then considered as a ‘new observation’ in a Bayesian framework and used to update the coefficients of the polynomial expansions. An adaptive sampling algorithm is also proposed to futher improve the performance of the multi-fidelity framework. Specifically, such an adaptive sampling algorithm relies on partitioning the sample space and the Kullback–Leibler divergence to find the optimal sampling path. The sample space partitioning allows an analyst to specify different criteria and parameters of the algorithm for different regions, thus further improving the performance of the procedure. The proposed approach is illustrated for an archetype reinforced concrete (RC) frame for which two model classes are developed/analysed: the simple lateral mechanism analysis (SLaMA), coupled with the capacity spectrum method, and non-linear dynamic analysis. Both model classes involve a cloud-based approach employing unscaled real (i.e. recorded) ground motions. The fragility relationships derived with the proposed procedure are finally compared to those calculated by using only the most advanced/high-fidelity (HF) model class, thus quantifying the performance of the proposed approach and highlighting further research needs
Simulating interacting multiple natural-hazard events for lifecycle consequence analysis
Among different types of natural-hazard interactions (simply multi-hazard interactions hereinafter), some occur through the nature of the hazards themselves, regardless of the presence of any physical assets: they are often called モLevel Iヤ (or occurrence) interactions. In such cases, one hazard event triggers or modifies the occurrence of another (e.g., severe wind and flooding; liquefaction and landslides triggered by an earthquake), thus creating a dependency between the parameters characterising such hazard events. They differ from モLevel IIヤ (or consequence) interactions, which instead occur through impacts/consequences on physical assets/components and systems (e.g., accumulation of physical damage or social impact due to earthquake sequences, landslides due to the earthquake-induced collapse of a retaining structure). Multi-hazard Life Cycle Analysis (LCA) aims to quantify the consequences (e.g., repair costs, downtime, and casualty rates) expected throughout a systemメs service life, accounting for both Level I and Level II interactions. Nevertheless, the available literature generally considers these interactions mainly defining relevant taxonomies, often qualitatively, without providing a computational framework to simulate a sequence of hazard events in terms of their occurrence times and features and resulting consequences. This paper aims to partly fill this gap by identifying modelling approaches associated with different Level I interactions. It describes a simulation-based approach for generating multi-hazard scenarios (i.e., a sequence of hazard events and associated features through the systemメs life cycle) based on the theory of competing Poisson processes. The proposed approach incorporates the different types of interactions in a sequential Monte Carlo sampling method. The method outputs potential sequences of events throughout a systemメs life cycle, which can be integrated into LCA frameworks to quantify interacting hazard consequences. A simple application is presented to illustrate the potential of the proposed method.
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