An Assessment to Benchmark the Seismic Performance of a Code-Conforming Reinforced-Concrete Moment-Frame Building

This report describes a state-of-the-art performance-based earthquake engineering methodology that is used to assess the seismic performance of a four-story reinforced concrete (RC) office building that is generally representative of low-rise office buildings constructed in highly seismic regions of California. This “benchmark” building is considered to be located at a site in the Los Angeles basin, and it was designed with a ductile RC special moment-resisting frame as its seismic lateral system that was designed according to modern building codes and standards. The building’s performance is quantified in terms of structural behavior up to collapse, structural and nonstructural damage and associated repair costs, and the risk of fatalities and their associated economic costs. To account for different building configurations that may be designed in practice to meet requirements of building size and use, eight structural design alternatives are used in the performance assessments. Our performance assessments account for important sources of uncertainty in the ground motion hazard, the structural response, structural and nonstructural damage, repair costs, and life-safety risk. The ground motion hazard characterization employs a site-specific probabilistic seismic hazard analysis and the evaluation of controlling seismic sources (through disaggregation) at seven ground motion levels (encompassing return periods ranging from 7 to 2475 years). Innovative procedures for ground motion selection and scaling are used to develop acceleration time history suites corresponding to each of the seven ground motion levels. Structural modeling utilizes both “fiber” models and “plastic hinge” models. Structural modeling uncertainties are investigated through comparison of these two modeling approaches, and through variations in structural component modeling parameters (stiffness, deformation capacity, degradation, etc.). Structural and nonstructural damage (fragility) models are based on a combination of test data, observations from post-earthquake reconnaissance, and expert opinion. Structural damage and repair costs are modeled for the RC beams, columns, and slabcolumn connections. Damage and associated repair costs are considered for some nonstructural building components, including wallboard partitions, interior paint, exterior glazing, ceilings, sprinkler systems, and elevators. The risk of casualties and the associated economic costs are evaluated based on the risk of structural collapse, combined with recent models on earthquake fatalities in collapsed buildings and accepted economic modeling guidelines for the value of human life in loss and cost-benefit studies. The principal results of this work pertain to the building collapse risk, damage and repair cost, and life-safety risk. These are discussed successively as follows. When accounting for uncertainties in structural modeling and record-to-record variability (i.e., conditional on a specified ground shaking intensity), the structural collapse probabilities of the various designs range from 2% to 7% for earthquake ground motions that have a 2% probability of exceedance in 50 years (2475 years return period). When integrated with the ground motion hazard for the southern California site, the collapse probabilities result in mean annual frequencies of collapse in the range of [0.4 to 1.4]x10 -4 for the various benchmark building designs. In the development of these results, we made the following observations that are expected to be broadly applicable: (1) The ground motions selected for performance simulations must consider spectral shape (e.g., through use of the epsilon parameter) and should appropriately account for correlations between motions in both horizontal directions; (2) Lower-bound component models, which are commonly used in performance-based assessment procedures such as FEMA 356, can significantly bias collapse analysis results; it is more appropriate to use median component behavior, including all aspects of the component model (strength, stiffness, deformation capacity, cyclic deterioration, etc.); (3) Structural modeling uncertainties related to component deformation capacity and post-peak degrading stiffness can impact the variability of calculated collapse probabilities and mean annual rates to a similar degree as record-to-record variability of ground motions. Therefore, including the effects of such structural modeling uncertainties significantly increases the mean annual collapse rates. We found this increase to be roughly four to eight times relative to rates evaluated for the median structural model; (4) Nonlinear response analyses revealed at least six distinct collapse mechanisms, the most common of which was a story mechanism in the third story (differing from the multi-story mechanism predicted by nonlinear static pushover analysis); (5) Soil-foundation-structure interaction effects did not significantly affect the structural response, which was expected given the relatively flexible superstructure and stiff soils. The potential for financial loss is considerable. Overall, the calculated expected annual losses (EAL) are in the range of $52,000 to$97,000 for the various code-conforming benchmark building designs, or roughly 1% of the replacement cost of the building ($8.8M). These losses are dominated by the expected repair costs of the wallboard partitions (including interior paint) and by the structural members. Loss estimates are sensitive to details of the structural models, especially the initial stiffness of the structural elements. Losses are also found to be sensitive to structural modeling choices, such as ignoring the tensile strength of the concrete (40 EAL) or the contribution of the gravity frames to overall building stiffness and strength (15 change in EAL). Although there are a number of factors identified in the literature as likely to affect the risk of human injury during seismic events, the casualty modeling in this study focuses on those factors (building collapse, building occupancy, and spatial location of building occupants) that directly inform the building design process. The expected annual number of fatalities is calculated for the benchmark building, assuming that an earthquake can occur at any time of any day with equal probability and using fatality probabilities conditioned on structural collapse and based on empirical data. The expected annual number of fatalities for the code-conforming buildings ranges between 0.05*10 -2 and 0.21*10 -2 , and is equal to 2.30*10 -2 for a non-code conforming design. The expected loss of life during a seismic event is perhaps the decision variable that owners and policy makers will be most interested in mitigating. The fatality estimation carried out for the benchmark building provides a methodology for comparing this important value for various building designs, and enables informed decision making during the design process. The expected annual loss associated with fatalities caused by building earthquake damage is estimated by converting the expected annual number of fatalities into economic terms. Assuming the value of a human life is$3.5M, the fatality rate translates to an EAL due to fatalities of $3,500 to$5,600 for the code-conforming designs, and $79,800 for the non-code conforming design. Compared to the EAL due to repair costs of the code-conforming designs, which are on the order of$66,000, the monetary value associated with life loss is small, suggesting that the governing factor in this respect will be the maximum permissible life-safety risk deemed by the public (or its representative government) to be appropriate for buildings. Although the focus of this report is on one specific building, it can be used as a reference for other types of structures. This report is organized in such a way that the individual core chapters (4, 5, and 6) can be read independently. Chapter 1 provides background on the performance-based earthquake engineering (PBEE) approach. Chapter 2 presents the implementation of the PBEE methodology of the PEER framework, as applied to the benchmark building. Chapter 3 sets the stage for the choices of location and basic structural design. The subsequent core chapters focus on the hazard analysis (Chapter 4), the structural analysis (Chapter 5), and the damage and loss analyses (Chapter 6). Although the report is self-contained, readers interested in additional details can find them in the appendices

The Association Between Maternal Glucose Concentration and Child BMI at Age 3 Years

OBJECTIVE—The objective of the study was to determine the association between child BMI at age 3 years and maternal glucose concentration among women without pre-existing diabetes or a gestational diabetes mellitus (GDM) diagnosis. RESEARCH DESIGN AND METHODS—Data are from the Pregnancy Infection and Nutrition and Postpartum studies and include 263 mother-child pairs. Measured weights and heights at 3 years were used to calculate age- and sex-specific BMIz scores and percentiles. Multivariable linear regression models were used to examine associations of continuous BMI z scores with maternal glucose concentration. Modified Poisson regression estimated risk ratios of child overweight/obesity (BMI $85th percentile). RESULTS—The mean (SD) maternal glucose concentration and prepregnancy BMI were 103.8 (23.7) mg/dL and 24.3 (5.9) kg/m 2, respectively. At 3 years, the mean (SD) child BMI z score was 0.29 (0.99), 20.9$130 mg/dL was associated with significantly higher child BMI z score at 3 years (estimated z scoredifferenceof0.39[95

Exposures to phthalates and bisphenols in pregnancy and postpartum weight gain in a population-based longitudinal birth cohort

Background: Experimental evidence suggests that exposures to phthalates and bisphenols may interfere with processes related to glucose and lipid metabolism, insulin sensitivity, and body weight. Few studies have considered the possible influence of chemical exposures during pregnancy on maternal weight gain or metabolic health outcomes postpartum. Objective: To examine the associations of early and mid-pregnancy bisphenol and phthalate urine concentrations with maternal weight gain 6 years postpartum. Methods: We analyzed urine samples for bisphenol, phthalate and creatinine concentrations from early and mid-pregnancy in 1192 women in a large, population-based birth cohort in Rotterdam, the Netherlands, and examined postpartum weight gain using maternal anthropometrics before pregnancy and 6 years postpartum. We have used covariate-adjusted linear regressions to evaluate associations of early and mid-pregnancy bisphenols and phthalate metabolites with weight change. Mediator and interaction models have been used to assess the role of gestational weight gain and breastfeeding, respectively. Sensitivity analysis is performed among women without subsequent pregnancies. Results: Among all 1192 mothers included in the analysis, each log unit increase in the average bisphenol A and all assessed phthalate groupings were associated with increased maternal weight gain. As a proxy for phthalate exposure, each log unit increase in averaged phthalic acid was associated with 734 g weight gain (95% CI 273–1196 g) between pre-pregnancy and 6 years postpartum. Mediation by gestational weight gain was not present. Breastfeeding and ethnicity did not modify the effects. Stratification revealed these associations to be strongest among overweight and obese women. Among women without subsequent pregnancies (n = 373) associations of bisphenols, HMW phthalate metabolites and di-2-ethylhexylphthalate metabolites attenuated. For phthalic acid, LMW phthalate metabolites and di-n-octylphthalate metabolites associations increased. Similarly to the whole group, stratification yielded significant results among overweight and obese women. Discussion: In a large population-based birth cohort, early and mid-pregnancy phthalate exposures are associated with weight gain 6 years postpartum, particularly among overweight and obese women. These data support ongoing action to replace phthalates with safer alternatives

Exposures to phthalates and bisphenols in pregnancy and postpartum weight gain in a population-based longitudinal birth cohort

BACKGROUND: Experimental evidence suggests that exposures to phthalates and bisphenols may interfere with processes related to glucose and lipid metabolism, insulin sensitivity, and body weight. Few studies have considered the possible influence of chemical exposures during pregnancy on maternal weight gain or metabolic health outcomes postpartum. OBJECTIVE: To examine the associations of early and mid-pregnancy bisphenol and phthalate urine concentrations with maternal weight gain 6 years postpartum. METHODS: We analyzed urine samples for bisphenol, phthalate and creatinine concentrations from early and mid-pregnancy in 1,192 women in a large, population-based birth cohort in Rotterdam, the Netherlands, and examined postpartum weight gain using maternal anthropometrics before pregnancy and 6 years postpartum. We have used covariate-adjusted linear regressions to evaluate associations of early and mid-pregnancy bisphenols and phthalate metabolites with weight change. Mediator and interaction models have been used to assess the role of gestational weight gain and breastfeeding, respectively. Sensitivity analysis is performed among women without subsequent pregnancies. RESULTS: Among all 1,192 mothers included in the analysis, each log unit increase in the average bisphenol A and all assessed phthalate groupings were associated with increased maternal weight gain. As a proxy for phthalate exposure, each log unit increase in averaged phthalic acid was associated with 734 g weight gain (95% CI 273-1196 g) between pre-pregnancy and 6 years postpartum. Mediation by gestational weight gain was not present. Breastfeeding and ethnicity did not modify the effects. Stratification revealed these associations to be strongest among overweight and obese women. Among women without subsequent pregnancies (n=373) associations of bisphenols, HMW phthalate metabolites and di-2-ethylhexylphthalate metabolites attenuated. For phthalic acid, LMW phthalate metabolites and di-n-octylphthalate metabolites associations increased. Similarly to the whole group, stratification yielded significant results among overweight and obese women. DISCUSSION: In a large population-based birth cohort, early and mid-pregnancy phthalate exposures are associated with weight gain 6 years postpartum, particularly among overweight and obese women. These data support ongoing action to replace phthalates with safer alternatives

Evaluation of the seismic performance of a code-conforming reinforced-concrete frame building—from seismic hazard to collapse safety and economic losses

A state-of-the-art seismic performance assessment is illustrated through application to a reinforcedconcrete moment-frame building designed per current (2003) building code provisions. Performance is quantified in terms of economic losses and collapse safety. The assessment includes site-specific seismic hazard analyses, nonlinear dynamic structural response simulations to collapse, damage analyses, and loss estimation. When selecting ground motion records for nonlinear dynamic analyses that are consistent with a target hazard level expressed in terms of a response spectral value at the building’s fundamental period, it is important to consider the response spectral shape, especially when considering higher hazard levels. This was done through the parameter commonly denoted by ε. Neglecting these effects during record selection is shown to lead to a factor of 5–10 overestimation of mean annual collapse rate. Structural response simulations, which properly account for uncertainties in ground motions and structural modelling, indicate a 2–7% probability of collapse for buildings subjected to motions scaled to a hazard level equivalent to a 2% probability of exceedance in 50 years. The probabilities of component damage and the means and coefficients of variation of the repair costs are calculated using fragility functions and repair-cost probability distributions. The calculated expected annual losses for various building design variants range from 0.6 to 1.1% of the replacement value, where the smaller losses are for above-code design variants and the larger losses are for buildings designed with minimum-code compliance. Sensitivity studies highlight the impact of key modelling assumptions on the accurate calculation of damage and the associated repair costs