Bayesian Updating of Solar Panel Fragility Curves and Implications of Higher Panel Strength for Solar Generation Resilience

Solar generation can become a major and global source of clean energy by 2050. Nevertheless, few studies have assessed its resilience to extreme events, and none have used empirical data to characterize the fragility of solar panels. This paper develops fragility functions for rooftop and ground-mounted solar panels calibrated with solar panel structural performance data in the Caribbean for Hurricanes Irma and Maria in 2017 and Hurricane Dorian in 2019. After estimating hurricane wind fields, we follow a Bayesian approach to estimate fragility functions for rooftop and ground-mounted panels based on observations supplemented with existing numerical studies on solar panel vulnerability. Next, we apply the developed fragility functions to assess failure rates due to hurricane hazards in Miami-Dade, Florida, highlighting that panels perform below the code requirements, especially rooftop panels. We also illustrate that strength increases can improve the panels' structural performance effectively. However, strength increases by a factor of two still cannot meet the reliability stated in the code. Our results advocate reducing existing panel vulnerabilities to enhance resilience but also acknowledge that other strategies, e.g., using storage or deploying other generation sources, will likely be needed for energy security during storms.

Seismic Collapse Probability and Life Cycle Cost Assessment of Isolated Structures Subjected to Pounding With Smart Hybrid Isolation System Using a Modified Fuzzy Based Controller

The possibility of pounding on isolated structures with surrounding moat walls is one of the concerns in the design of isolation systems, especially in pulse-type near-field earthquakes. This paper puts forward the seismic probability assessment of structures equipped with passive and smart hybrid isolation systems by considering pounding possibilities. This investigation is performed on isolated structures equipped with a high damper rubber bearing (HDRB) considering stiff moat walls around the structure. In the Hybrid isolation system, magnetorheological dampers (MR) are considered an adaptive dissipation energy device along with isolators using an optimized novel interval Type-2 fuzzy logic controller with adaptive red-zone function (IT2FS+RZF) to reduce pounding possibilities. The fragility curves of the building for various cases are determined using IDA analysis, and possible damage costs are evaluated by using exceedance probability in each damage level. This study concludes that the collapse probability of the isolated structures with restrains at the code-based distance is over the acceptable limit of ASCE 7-22. The smart additional damping system with the proposed controller reduces the possible damage cost of the building by about 64% compared to the uncontrolled system and puts the collapse probability of the structure in the acceptable range.

Fragility Analysis of Structural Pounding Between Adjacent Structures Arranged in Series With Various Alignment Configurations Under Near-field Earthquakes

A major cause of local to total damages is related to structural pounding in a large number of past earthquakes. In general, these collisions take place as a result of differences in the dynamic characteristics of the colliding structures. To acquire a better perception of the behavior of structures, in this paper, three structures featuring different heights are modeled in series and with various configurations next to each other in OpenSees. To determine the collision effects of the structures, three different configurations of 4-, 8- and 12-story adjacent reinforced concrete special moment resisting frames were considered. Then, by conducting an incremental dynamic analysis, their structural seismic limit state capacities were assessed via 20 near-field record subsets recommended by FEMA-P695. At last, for the above adjacent buildings with various separation distances and configurations, the fragility curves were determined, and the probability of exceedance from the primary Hazus-MH failure criteria was estimated. In addition, the results were compared with those obtained when this phenomenon did not take place for buildings to have a better perception of the pounding phenomenon. The results of the analyses show that arranging adjacent structures in series greatly affects the collapse capacities of the colliding structures. In addition, in the case when the shorter structure is placed in the middle of two taller structures, it results in the most critical situation among all configurations, and in this case, a higher reduction is observed in the structural performance levels.

The Role of Soil Structure Interaction in the Fragility Assessment of HP/HT Unburied Subsea Pipelines

Subsea high pressure/high temperature (HP/HT) pipelines may be significantly affected by the effects of soil structure interaction (SSI) when subjected to earthquakes. Numerical simulations are herein applied to assess the role of soil deformability on the seismic vulnerability of an unburied pipeline. Overcoming most of the contributions existing in the literature, this paper proposes a comprehensive 3D model of the system (soil + pipeline) by performing OpenSees that allows the representation of non-linear mechanisms of the soil and may realistically assess the induced damage caused by the mutual interaction of buckling and seismic loads. Analytical fragility curves are herein derived to evaluate the role of soil structure interaction in the assessment of the vulnerability of a benchmark HP/HT unburied subsea pipeline. The probability of exceeding selected limit states was based on the definition of credited failure criteria.

New insights into the relationship between seismic intensity measures and nonlinear structural response

This paper focuses on the probabilistic analysis of Intensity Measures (IMs) and Engineering Demand Parameters (EDPs) in the context of earthquake-induced ground motions. Several statistical properties, which are desirable in IMs when they are used to predict EDPs, have been analysed. Specifically, efficiency, sufficiency and steadfastness have been quantified for a set of IMs with respect to two EDPs: the maximum inter-storey drift ratio, MIDR, and the maximum floor acceleration, MFA. Steadfastness is a new statistical property proposed in this article, which is related to the ability of IMs to forecast EDPs for large building suites. In other words, this means that efficiency does not significantly vary when different types of buildings are simultanously considered in the statistical analyses. This property allows reducing the number of calculations when performing seismic risk estimations at urban level since, for instance, a large variety of fragility curves, representing specific building typologies, can be grouped together within a more generic one. The main sources of uncertainty involved in the calculation of the seismic risk have been considered in the analysis. To do so, the nonlinear dynamic responses of probabilistic multi-degree-of-freedom building models, subjected to a large data set of ground motion records, have been calculated. These models have been generated to simulate the dynamic behavior of reinforced concrete buildings whose number of stories vary from 3 to 13. 18 spectrum-, energy- and direct-accelerogram-based IMs have been considered herein. Then, from clouds of IM-EDP points, efficiency, sufficiency and steadfastness have been quantified. For MIDR, results show that IMs based on spectral velocity are more efficient and steadfast than the ones based on spectral acceleration; spectral velocity averaged in a range of periods, AvSv, has shown to be the most efficient IM with an adequate level of steadfastness. For MFA, spectral acceleration-based-IMs are more efficient than velocity-based ones. A comparison is also presented on the use of linear vs quadratic regression models, and their implications on the derivation of fragility functions. Concerning sufficiency, most of the 18 IMs analysed do not have this property. Nonetheless, multi-regression models have been employed to address this lack of sufficiency allowing to obtain a so-called ‘ideal’ IM.