Intensity Measurements Research Articles

Fragility and vulnerability models for poorly-detailed infilled buildings accounting for building-to-building and masonry infill variability

While in poorly-detailed masonry-infilled reinforced concrete (RC) buildings the significance of masonry infills is acknowledged, less attention has been paid to the variability surrounding their mechanical properties and its potential impact on fragility and, consequently, vulnerability models to be used in seismic risk estimation. This study addresses this gap by proposing updated fragility and vulnerability models of existing poorly-detailed masonry infilled and pilotis RC frames that consider the variability in building layout and infill properties. A large building portfolio, representative of those designed according to Italian codes between 1970 and 1980, is selected as case study, incorporating building-to-building variability through various geometrical configurations. Updated modelling uncertainty parameters, specifically derived for existing infilled RC frames, are used, including the variability surrounding the properties of different infill typologies and the occurrence of RC frame shear failure. The portfolio was analysed through multiple-stripe analyses, followed by the development of upgraded fragility models for buildings with different heights and geometrical configurations. Finally, the corresponding vulnerability models were derived using damage-to-loss models calibrated with post-earthquake observation damage data from the 2009 L'Aquila earthquake. The updated fragility and vulnerability curves can be used for more refined seismic risk estimates of large building portfolios, that account for building-to-building and infill-to-infill variability, revised modelling uncertainty estimates and a more robust intensity measure (AvgSa).

Interpretable machine learning models for displacement demand prediction in reinforced concrete buildings under pulse-like earthquakes

This work proposes a novel procedure to guide the development of machine learning models for estimating the seismic demand in existing reinforced concrete (RC) buildings. The proposed approach is organized across two scales. A large-scale (nonparametric) machine learning model is first obtained by means of Gaussian Process Regression (GPR) using all candidate building attributes and intensity measures. SHapley Additive exPlanations (SHAP) values are utilized to facilitate its interpretation and to assist the rational selection of a small subset of intensity measures, which is finally employed to develop a (symbolic) reduced-scale machine learning model by means of Genetic Programming (GP). Simplified models of archetype buildings are adopted to develop machine learning techniques at both scales, in such a way to alleviate the simulation time for preparing large datasets. Refined models representative of actual buildings are instead considered for the unbiased final assessment.The proposed approach is applied to develop predictive machine learning models for the maximum inter-storey drift in bare frames, pilotis frames and frames with infills under pulse-like seismic ground motions. Consequently, the critical examination of the SHAP values revealed the most significant intensity measures and unfolded interesting patterns depending on the occupancy rate of the infills. Moreover, the final assessment demonstrates that this approach allows the management of a non-homogeneous building stock consisting of very diverse structural systems (i.e., spanning from existing buildings designed against gravity loads only to buildings that comply with outdated seismic codes) while providing satisfactory predictions of the seismic demand with minimum computational effort.

Comprehensive measurement of carbonyls in Lhasa, Tibetan Plateau: Implications for strong atmospheric oxidation capacity

Carbonyls are ubiquitous in the troposphere and play a crucial role in atmospheric oxidation capacity (AOC), particularly in photochemistry-active regions such as the Tibetan Plateau (TP). However, the composition and evolution of carbonyls over the TP is still poorly understood due to a lack of comprehensive observations and modelling. Here, we conducted an intensive field measurement of 37 carbonyls and their precursors at a suburban site in Lhasa during summer 2022. Markedly higher levels of carbonyls (7.24 ± 3.83 ppbv) were found during ozone pollution episodes, with 36 % higher than those during non-episodes. Formaldehyde was the most abundant carbonyl (38 %), which primarily originating from photochemical secondary formations. Simulations using the Rapid adaptive Optimization Model for Atmospheric Chemistry (ROMAC) indicated strong AOC in Lhasa, with the daytime maximum of ·OH and ·HO2 of 9.8 × 106 and 4.2 × 108 molecules cm−3, respectively, which were even higher than that in most of the megacities in China. Notably, AOC significantly enhanced with the increasing carbonyls during the episodes, with the concentrations of ·OH and ·HO2 were boosted 21 % and 67 % than those during non-episodes, respectively. Budget analysis revealed that the ·HO2 + NO (88 %) and ·OH + VOC (74 %) pathways dominated the generation and loss of ·OH, respectively. And for ·HO2, they were ·RO2 + NO (67 %) and ·HO2 + NO (83 %). This study provides valuable insights into the strong AOC in the ecologically-fragile and climate-sensitive TP region, and highlighted the crucial role of anthropogenic–biogenic interactions in the active photochemistry of TP.

Minimum magnitude boundaries in probabilistic seismic hazard analysis: an insight from structural engineering

In order to systematically advance our understanding of the minimum magnitude limit (Mmin) in the probabilistic seismic hazard analysis (PSHA) calculations, a novel and useful approach utilising a broad range of Single-Degree-of-Freedom oscillators and hazard conditions is being developed and tested. We have determined the most reasonable Mmin value for a variety of structures by examining the impact of Mmin on the mean annual frequency (MAF) of various limit states (LSs) (including the collapse capacity). The originality of the suggested methodology in the current work, known as the MAF saturation strategy, is the recommended Mmin, which is the cut-off value at which lesser magnitude events do add to the hazard but do not significantly change the MAF. The current work is the first to offer the MAF saturation strategy methodology, which searches for the cut-off magnitude at which the MAF value essentially remains constant even when smaller values of this cut-off are utilised as Mmin for hazard assessments. Therefore, given a series of carefully chosen ground motions in each oscillator instance, an incremental dynamic analysis is carried out (by applying the Hunt and Fill algorithm), and the appropriate LS (including the collapse capacity defined as global instability) points are calculated. Thus, the relationship between the distribution of LSs and the Engineering Demand Parameter and intensity measure is found. A simple point source hazard curve is convoluted with this distribution, yielding the structure-specific MAF. In order to find the cut-off lower magnitude (Mmin), this convolution is repeated for several Mmin values. This cut-off is defined as the point at which, when lower values are utilised as Mmin in the PSHA computation, the MAF’s values do not change considerably (with a five per cent threshold). The acquired data were thoroughly discussed in relation to various structural features and seismic input factors. The primary findings showed that each of the structures under consideration requires a Mmin value in the range of 4–4.3. Put otherwise, the suggestions seen in technical literature, which range from 4.5 to 5, are not cautious, at least not when it comes to probabilistic structural limit state frequency. The derived Mmin value is mostly controlled by the natural period of the structure and is largely unaffected by other structural characteristics like ductility, damping ratio and overstrength factor.

Relation between the Dantu blood group variant and bacteraemia in Kenyan children: a population-based case control study.

The Dantu blood group variant protects against P. falciparum infections but its wider consequences have not been previously explored. Here, we investigate the impact of Dantu on susceptibility to bacteraemia. We conducted a case-control study in children presenting with community-acquired bacteraemia to Kilifi County Hospital in Kenya between 1998 and 2010. We used logistic regression to test for associations between the Dantu marker SNP rs186873296 A>G and both all-cause and pathogen-specific bacteraemia under an additive model. We used date of admission as a proxy measure of malaria transmission intensity, given known differences in malaria prevalence over the course of the study. Dantu was associated with protection from all-cause bacteraemia (OR=0.81, p=0.014), the association being greatest in homozygotes (OR=0.30, p=0.013). This protection was shared across the major bacterial pathogens but, notably, was only significant during the era of high malaria-transmission pre-2003 (OR=0.79, p=0.023). Consistent with previous studies showing the indirect impact on bacteraemia risk of other malaria-associated red cell variants, our study also shows that Dantu is protective against bacteraemia via its effect on malaria risk. Dantu does not appear to be under balancing selection through an increased risk of bacterial infections.

A Review of the Validity and Reliability of Accelerometer-Based Metrics From Upper Back-Mounted GNSS Player Tracking Systems for Athlete Training Load Monitoring.

Dawson, L, Beato, M, Devereux, G, and McErlain-Naylor, SA. A review of the validity and reliability of accelerometer-based metrics from upper back-mounted GNSS player tracking systems for athlete training load monitoring. J Strength Cond Res 38(8): e459-e474, 2024-Athlete load monitoring using upper back-mounted global navigation satellite system (GNSS) player tracking is common within many team sports. However, accelerometer-based load monitoring may provide information that cannot be achieved with GNSS alone. This review focuses on the accelerometer-based metrics quantifying the accumulation of accelerations as an estimation of athlete training load, appraising the validity and reliability of accelerometer use in upper back-mounted GNSS player tracking systems, the accelerometer-based metrics, and their potential for application within athlete monitoring. Reliability of GNSS-housed accelerometers and accelerometer-based metrics are dependent on the equipment model, signal processing methods, and the activity being monitored. Furthermore, GNSS unit placement on the upper back may be suboptimal for accelerometer-based estimation of mechanical load. Because there are currently no feasible gold standard comparisons for field-based whole-body biomechanical load, the validity of accelerometer-based load metrics has largely been considered in relation to other measures of training load and exercise intensity. In terms of convergent validity, accelerometer-based metrics (e.g., PlayerLoad, Dynamic Stress Load, Body Load) have correlated, albeit with varying magnitudes and certainty, with measures of internal physiological load, exercise intensity, total distance, collisions and impacts, fatigue, and injury risk and incidence. Currently, comparisons of these metrics should not be made between athletes because of mass or technique differences or between manufacturers because of processing variations. Notable areas for further study include the associations between accelerometer-based metrics and other parts of biomechanical load-adaptation pathways of interest, such as internal biomechanical loads or methods of manipulating these metrics through effective training design.

Study on the Effect of Burial Depth on Selection of Optimal Intensity Measures for Advanced Fragility Analysis of Horseshoe-Shaped Tunnels in Soft Soil

Seismic intensity measures (IMs) can directly affect the seismic risk assessment and the response characteristics of underground structures, especially when considering the key variable of burial depth. This means that the optimal seismic IMs must be selected to match the underground structure under different buried depth conditions. In the field of seismic engineering design, peak ground acceleration (PGA) is widely recognized as the optimal IM, especially in the seismic design code for aboveground structures. However, for the seismic evaluation of underground structures, the applicability and effectiveness still face certain doubts and discussions. In addition, the adverse effects of earthquakes on tunnels in soft soil are particularly prominent. This study aims to determine the optimal IMs applicable to different burial depths for horseshoe-shaped tunnels in soft soil using a nonlinear dynamic time history analysis method, and based on this, establish the seismic fragility curves that can accurately predict the probability of tunnel damage. The nonlinear finite element analysis model for the soil–tunnel interaction system was established. The effects of different burial depths on damage to horseshoe-shaped tunnels in soft soil were systematically studied. By adopting the incremental dynamic analysis (IDA) method and assessing the correlation, efficiency, practicality, and proficiency of the potential IMs, the optimal IMs were determined. The analysis indicates that PGA emerges as the optimal IM for shallow tunnels, whereas peak ground velocity (PGV) stands as the optimal IM for medium-depth tunnels. Furthermore, for deep tunnels, velocity spectral intensity (VSI) emerges as the optimal IM. Finally, the seismic fragility curves for horseshoe-shaped tunnels in soft soil were built. The proposed fragility curves can provide a quantitative tool for evaluating seismic disaster risk, and are of great significance for improving the overall seismic resistance and disaster resilience of society.

Water bodies as a stable reference for urban heat islands intensity measurements

Accurate measurement of urban heat islands (UHI) intensity is a necessary prerequisite for understanding UHI formation mechanisms and subsequently implementing effective prevention and control measures. The selection of a stable reference is a significant challenge in this process. In particular, rapid urbanization can lead to changes in land cover types. This process hinders the selection of a typical non-urban area as a stable reference for accurately measuring surface urban heat islands (SUHI) intensity. Among various land cover types, water bodies are widely distributed and stable during urban development. Nevertheless, the use of water bodies as a stable reference for SUHIs remains controversial. For 185 global cities, we first clustered the land cover transformation rates and then compared the interannual variations in SUHIW and SUHIR in these cities by using remote sensing data from MODIS. The trends of interannual intensities of the SUHIW and SUHIR in the stable group are similar, indicating that water bodies have the same effect on SUHI measurements as stable rural areas. However, the magnitude of the difference between the SUHIW and the SUHIR (SD) becomes more significant in cities with rapid changes in rural areas. As a stable reference, water bodies can be used to accurately measure the variation in the SUHI affected only by urbanization under the background climate, while the land cover transformation of rural areas changes the land surface temperature (LST) and thus affects the SUHI intensity. The findings of this study quantitatively demonstrate the feasibility of using water bodies as SUHI references from an urban dynamics perspective and provide direction for studying SUHIs under climate change.

Evaluation and clinical application of a bracketing calibration-based isotope dilution liquid chromatography-tandem mass spectrometry candidate reference measurement procedure for serum theophylline.

A candidate reference measurement procedure (RMP) for serum theophylline via isotope dilution liquid chromatography-tandem mass spectrometry (LC-MS/MS) was developed. With a single-step precipitation pretreatment and a 6-min gradient elution, the method achieved baseline separation of theophylline and its analogs on a C18-packed column. A bracketing calibration method was used to ensure repeatable signal intensity and high measurement precision. The intra-assay and inter-assay imprecisions were 1.06%, 0.84%, 0.72% and 0.47%, 0.41%, 0.25% at concentrations of 4.22 µg/mL (23.40 µmol/L), 8.45 µg/mL (46.90 µmol/L), and 15.21 µg/mL (84.43 µmol/L), respectively. Recoveries ranged from 99.35 to 102.34%. The limit of detection (LoD) was 2 ng/mL, and the lowest limit of quantification (LLoQ) was 5 ng/mL. The linearity range extended from 0.47 to 60 µg/mL (2.61-333.04 µmol/L). No ion suppression and carry-over (< 0.68%) were observed. The relative bias for this candidate RMP that participated in 2023 External Quality Control for Reference Laboratories (RELA) conducted by the International Federation of Clinical Chemistry (IFCC) was within a range of 0.17 to 0.93%. Furthermore, two clinical immunoassay systems were compared with this candidate RMP, demonstrating good correlations. The results of the Trueness Verification Plan indicate significant differences among routine systems, highlighting the need for standardization efforts. The developed candidate RMP for serum theophylline serves as a precise reference baseline for standardizing clinical systems and assigning values to reference materials.

Optimal intensity measure for seismic performance assessment of shield tunnels in liquefiable and non-liquefiable soils

Relating the ground motion intensity measure (IM) and the structural engineering demand parameter is a crucial step in the performance-based earthquake engineering framework. This study investigates the selection of IM for development of probabilistic seismic demand model of urban shield tunnels subjected to earthquake ground motions in liquefiable and non-liquefiable soils. Nonlinear dynamic effective stress analyses are conducted to develop a database of the intensity measures and structural seismic responses exposed to ground shaking and soil liquefaction. Two advanced soil constitutive models (i.e., Pressure DependMultiYield03 and PressureIndependMultiYield for liquefiable and non-liquefiable soils, respectively) are employed to capture the nonlinear behavior. A suite of 23ground motion intensity measures is selected and assessed based on the evaluation criteria of correlation, efficiency, practicality and proficiency. Eventually, the multi-level fuzzy comprehensive evaluation method is employed to comprehensively consider the four evaluation criteria and establish the optimal ground motion IM suitable for probabilistic seismic demand analysis of shield tunnel structures. The obtained results show that the sustained maximum acceleration is the optimal IM for evaluating the structural seismic response, followed by the peak ground acceleration in both liquefiable and non-liquefiable soils. Peak pseudo velocity spectrum, displacement square integral and Housner spectral intensity are found to be not suitable for the probabilistic seismic demand analysis of shield tunnel structures.

PDRs4All

Context. Mid-infrared emission features are important probes of the properties of ionized gas and hot or warm molecular gas, which are difficult to probe at other wavelengths. The Orion Bar photodissociation region (PDR) is a bright, nearby, and frequently studied target containing large amounts of gas under these conditions. Under the “PDRs4All” Early Release Science Program for JWST, a part of the Orion Bar was observed with MIRI integral field unit (IFU) spectroscopy, and these high-sensitivity IR spectroscopic images of very high angular resolution (0.2″) provide a rich observational inventory of the mid-infrared (MIR) emission lines, while resolving the H II region, the ionization front, and multiple dissociation fronts. Aims. We list, identify, and measure the most prominent gas emission lines in the Orion Bar using the new MIRI IFU data. An initial analysis summarizes the physical conditions of the gas and demonstrates the potential of these new data and future IFU observations with JWST. Methods. The MIRI IFU mosaic spatially resolves the substructure of the PDR, its footprint cutting perpendicularly across the ionization front and three dissociation fronts. We performed an up-to-date data reduction, and extracted five spectra that represent the ionized, atomic, and molecular gas layers. We identified the observed lines through a comparison with theoretical line lists derived from atomic data and simulated PDR models. The identified species and transitions are summarized in the main table of this work, with measurements of the line intensities and central wavelengths. Results. We identified around 100 lines and report an additional 18 lines that remain unidentified. The majority consists of H I recombination lines arising from the ionized gas layer bordering the PDR. The H I line ratios are well matched by emissivity coefficients from H recombination theory, but deviate by up to 10% because of contamination by He I lines. We report the observed emission lines of various ionization stages of Ne, P, S, Cl, Ar, Fe, and Ni. We show how the Ne III/Ne II, S IV/S III, and Ar III/Ar II ratios trace the conditions in the ionized layer bordering the PDR, while Fe III/Fe II and Ni III/Ni II exhibit a different behavior, as there are significant contributions to Fe II and Ni II from the neutral PDR gas. We observe the pure-rotational H2 lines in the vibrational ground state from 0–0 S(1) to 0–0 S (8), and in the first vibrationally excited state from 1–1 S (5) to 1–1 S(9). We derive H2 excitation diagrams, and for the three observed dissociation fronts, the rotational excitation can be approximated with one thermal (~700 K) component representative of an average gas temperature, and one nonthermal component (~2700 K) probing the effect of UV pumping. We compare these results to an existing model of the Orion Bar PDR, and find that the predicted excitation matches the data qualitatively, while adjustments to the parameters of the PDR model are required to reproduce the intensity of the 0–0 S (6) to S (8) lines.

Object alignment in spatially multiplexed holograms applied to polarization sensing.

The paper presents a new algorithm for object alignment in digital holography with multiple spherical reference waves. The algorithm was applied to polarization sensing with two orthogonally polarized reference waves. A novel holographic setup was built using a diffraction grating to generate two symmetric reference waves, keeping the setup simple and highly adjustable. The angles of rotation of the polarizing elements were calculated with mean absolute errors of 0.71° and 2.96° based on intensity and phase measurements, respectively. The same algorithm can be applied to any digital holographic measurement with multiple spherical reference waves.

Evidence for Spatially Distinct Galactic Dust Populations

We present an implementation of a Bayesian mixture model using Hamiltonian Monte Carlo techniques to search for the spatial separation of Galactic dust populations. Utilizing intensity measurements from the Planck High Frequency Instrument, we apply this model to high-latitude Galactic dust emission. Our analysis reveals a strong preference for a spatially varying two-population dust model over a one-population dust model, when the latter must capture the total variance in the sky. Each dust population is well characterized by a single-component spectral energy distribution (SED) and accommodates small variations. These populations could signify two distinct components or may originate from a one-component model with different temperatures resulting in different SED scalings. While no spatial information is built into the likelihood, our investigation unveils large-scale spatially coherent structures with high significance, pointing to a physical origin for the observed spatial variation. These results are robust to our choice of likelihood and input data. Furthermore, this spatially varying two-population model is the most favored from Bayesian evidence calculations. Incorporating IRAS 100 μm to constrain the Wein side of the blackbody function, we find the dust populations differ at the 2.5σ level in the spectral index (β d ) versus temperature (T d ) plane. The presence of multiple dust populations has implications for component separation techniques frequently employed in the recovery of the cosmic microwave background.

Photocapacitance discharge of LEDs applied in remote sensing detectors

Abstract This paper describes the application of light emitting diodes (LEDs) as light detectors for remote sensing systems, used for the measurement of normalized differential vegetation index, one of the most common parameters monitored by these systems. The light intensity measurement was carried out through correlation of discharge time of photocapacitance of LEDs, and the performance of this configuration was compared with the same LEDs used as detectors in photovoltaic mode. One measurement system was implemented for each configuration of LEDs, using the STM32F401CBU6 microcontroller. The normalized differential vegetation index was measured in samples of liquid suspensions of microalgae Spirulina platensis with different biomass concentrations. The measurements were taken at an outdoor location and under sunlight illumination. The results obtained with measurement of normalized differential vegetation index through photocapacitance discharge effect demonstrated that this is an effective technique with an improved repeatability in measurement, in comparison with photovoltaic mode of LEDs used as detectors.

“What’s yours is mine”: Partners’ everyday emotional experiences and cortisol in older adult couples

The existing literature consistently finds that emotional experiences and cortisol secretion are linked at the within-person level. Further, relationship partners tend to covary in emotional experience, and in cortisol secretion. However, we are only beginning to understand whether and how an individuals’ emotions are linked to their relationship partners’ cortisol secretion. In this project, we harmonized data from three intensive measurement studies originating from Canada and Germany to investigate the daily dynamics of emotions and cortisol within 321 older adult couples (age range=56–87 years). Three-level multilevel models accounted for the nested structure of the data (repeated assessments within individuals within couples). Actor-Partner Interdependence Models were used to examine the effect of own emotional experiences (actor effects) and partner emotional experiences (partner effects) on momentary and daily cortisol secretion. Adjusting for age, sex, education, comorbidities, assay version, diurnal cortisol rhythm, time spent together, medication, and time-varying behaviors that may increase cortisol secretion, results suggest that higher relationship partner’s positive emotions are linked with lower momentary cortisol and total daily cortisol. Further, this association was stronger for older participants and those who reported higher relationship satisfaction. We did not find within-couple links between negative emotions and cortisol. Overall, our results suggest that one’s relationship partner’s positive emotional experience may be a protective factor for their physiological responding, and that these more fleeting and day-to-day fluctuations may accumulate over time, contributing to overall relationship satisfaction.

Research on the Three-Level Integrated Environmental Evaluation Model for Multi-Greenhouse Potatoes

Aiming at the problems of large error and redundancy in the multi-node data acquisition of multi-greenhouse photo growth environmental information, a three-level fusion algorithm based on adaptive weighting, an LMBP network, and an improved D-S theory is proposed. The box-and-line graph method recognizes the original data and then replaces it based on the mean value method; the air temperature, humidity, and light intensity measurements are unbiased estimations of the true value to be estimated, so the first level of fusion chooses the adaptive weighted average algorithm to find the optimal weights of each sensor under the condition of minimizing the total mean-square error and obtains the optimal estimation of the weights of the homogeneous sensors of a greenhouse. The Levenberg–Marquardt algorithm was chosen for the second level of fusion to optimize the weight modification of the BP neural network, i.e., the LMBP network, and the three environmental factors corresponding to “suitable”, “uncertain” and “unsuitable” potato growth environments were trained for the three environmental factors in the reproductive periods. The output of the hidden layer was converted into probability by the Softmax function. The third level is based on the global fusion of evidence theory (also known as D-S theory), and the network output is used as evidence to obtain a consistent description of the multi-greenhouse potato cultivation environment and the overall scheduling of farming activities, which better solves the problem of the difficulty in obtaining basic probability assignments in the evidence theory; in the case of a conflict between the evidence, the BPA of the conflicting evidence is reallocated, i.e., the D-S theory is improved. Example validation shows that the total mean square error of the adaptive weighted fusion value is smaller than the variance of each sensor estimation, and sensors with lower variance are assigned lower weights, which makes the fusion result not have a large deviation due to the failure of individual sensors; when the fusion result of a greenhouse feature level is “unsuitable”, the fusion result of each data level is considered comprehensively, and the remote control agency makes a decision, which makes full use of the complementary nature of multi-sensor information resources and solves the problem of fusion of multi-source environmental information and the problem of combining conflicting environmental evaluation factors. Compared with the traditional D-S theory, the improved D-S theory reduces the probability of the “uncertainty” index in the fusion result again. The three-level fusion algorithm in this paper does not sacrifice data accuracy and greatly reduces the noise and redundancy of the original data, laying a foundation for big data analysis.

Mercury from Icelandic geothermal activity: High enrichments in soils, low emissions to the atmosphere

Geothermal activity is a natural source of mercury (Hg) to surface environments, but its contributions as part of the larger geogenic flux to the global Hg budget are poorly understood, in part due to large geographic gaps in emissions data where no measurements have been made. In this study we report the results of a field campaign over 2021 and 2022 on the highly active volcanic island country of Iceland. Six geothermal sites across the country were investigated for soil gaseous elemental mercury (GEM) and total Hg (THg) concentrations through a series of measurements made across the diffuse degassing surface. At 10 cm depth, soil GEM concentrations were often hundreds and in some cases thousands of times higher than ambient surface air concentrations. Geothermal soils were also highly enriched in THg due to the sorption of hydrothermal Hg on the characteristically fine, thermally-altered clays and silts. Soil “hotspots” displayed THg concentrations exceeding 100 µg g−1 comparable to levels in areas heavily contaminated by anthropogenic activity and in Hg-rich mineral soils. Strong correlations were observed between soil GEM, THg and soil temperature, and intensive measurements made at small spatial scales (∼1 m2) demonstrated the representativeness of individual sampling points. By adapting an active sampling gradient method for determining soil–air gas fluxes, we estimate an Icelandic geothermal GEM flux of 1.8 kg a−1 and a total Icelandic GEM flux, including non-geothermal areas, of ∼18 kg a−1. This work shows that Icelandic geothermal activity can generate high GEM and THg concentrations in the local soil environment, but its contribution to global Hg cycling appears to be minor.

Seismic Reliability Maps of Code-Compliant Italian Reinforced-Concrete Bare and Infilled Frame Buildings

The present study illustrates the main results of an extensive campaign of numerical simulations aimed at quantifying the seismic reliability of reinforced concrete (RC) bare and masonry-infilled frames compliant with the current Italian Building Code. For this purpose, a set of different residential-use archetype structures are considered, and a prototype seismic design-assessment tool is created to quantify their performance with respect to the relevant limit states, deriving fragility curves via the execution of several non-linear time-history analyses (NLTHAs). The fragilities are subsequently combined with the hazard curves derived for each of the over 8000 Italian municipalities based on the national seismic hazard model currently in force to obtain the respective seismic mean failure rates across Italy. The seismic reliability maps obtained for the investigated code-compliant designs highlight how the current Italian Building Code fails to provide uniform seismic safety across Italy, showing—on the contrary—a strong hazard-dependency. The results are finally used to calibrate regression laws able to correlate the seismic mean failure rates with an intensity measure representative of the seismic hazard.

Seismic fragility curves for concrete gravity retaining wall

Seismic fragility analysis plays a crucial role in performance-based seismic design (PBSD). The seismic fragility analyses for the concrete gravity retaining walls were performed in this study. Numerical models were developed for two concrete gravity retaining walls using OpenSees, considering two different backfill slope angles (0° and 12°). According to the probabilistic seismic demand models and comprehensive evaluation of intensity measures (IMs), the most suitable IM for concrete gravity retaining walls was determined. An approach for quantifying the limit state performance of concrete gravity retaining walls based on IDA was also proposed, and its reliability was verified based on observed damage during the 2008 Wenchuan earthquake. Seismic fragility curves for concrete gravity retaining walls were established under two backfill slope angles using three IMs. It is demonstrated to what extent a backfill slope angle can influence the damage probability under a specific seismic intensity level.

Seismic fragility analysis of girder bridges under mainshock‐aftershock sequences based on input‐output hidden Markov model

AbstractCurrent seismic design codes for bridge structures do not account for the influence of aftershock sequences, which, to some extent, overestimate the seismic performance for bridges subjected to mainshock‐aftershock (MS‐AS) scenarios. To address the great need for ground motion sequences tailored to specific research sites for fragility analysis, this study proposes a method for generating artificial MS‐AS ground motion sequences based on the evolutional bimodal Kanai–Tajimi model and the Epidemic–Type Aftershock Sequence model. We establish a framework for MS‐AS fragility analysis using an input–output Hidden Markov Model (IOHMM), where the damage states (DS) of bridge piers are considered unobservable and are inferred statistically through damage indices in an unsupervised manner. Model parameters are trained using intensity measure (IM) sequences and damage index (DI) sequences. Fragility curves for both the mainshock and state‐dependent aftershocks considering multiple aftershocks are formulated based on the initial state probability and state transition probabilities of the proposed IOHMM. The fragility analysis results reveal that as the initial seismic damage level increases, the probability of aftershocks causing higher damage levels in the structure also increases, highlighting the significant impact of aftershocks on structural damage increments. Furthermore, we extend the proposed model to a bivariate seismic intensity measure and develop fragility surfaces. The proposed framework provides a novel approach and insights for tackling seismic fragility under multiple aftershocks.