Journal of Performance of Constructed Facilities

The use of nondestructive testing (NDT) methods for the condition assessment of reinforced concrete structures is increasing due to the various advantages of NDT compared to traditional approaches, such as qualitative visual inspections and destructive testing protocols. Nevertheless, there remains some uncertainty over how to develop appropriate and cost-effective assessment procedures that account for the inherent advantages and disadvantages of various available NDT tools and technologies. In this study, a new wireless impact echo (IE) prototype system is presented. The system consists of a handheld device that connects via Bluetooth to a user-friendly software interface optimized for tablet computers. The wireless IE system was validated using a series of three reinforced concrete slabs containing artificial defects intended to simulate geometric discontinuities, delamination, internal voids, cracks, and a hollow conduit. The IE prototype was compared with other common NDT devices used for similar purposes, namely ground-penetrating radar (GPR) and ultrasonic pulse echo (UPE). GPR was the quickest method by far, although the results gathered were significantly influenced by the presence of steel reinforcement and failed to locate certain defects. UPE was slower than GPR but was generally able to identify the locations of the artificial defects more accurately; UPE readings were also affected by the presence of steel reinforcement. The IE method was not as rapid as the other two approaches but was able to locate most of the artificial defects and was less significantly affected by the presence of steel reinforcing bars than the other two methods. Based on these results, a general framework for the condition assessment of reinforced concrete slabs is presented.

Resilience is defined as the enduring capacity of a system or infrastructure system against natural disasters such as floods, hurricanes, and earthquakes and to restore to stipulated performance limits after the occurrence of disasters. Quantifying the flood resilience of infrastructure is of utmost importance for stakeholders, policymakers and concerned government bodies. It is essential to develop strategies in devising mechanisms to make communities resilient. Creating a community resilient involves the accumulation of factors associated with social as well as physical infrastructure. In this study, a flood resilience modeling and quantifying scheme is proposed for the housing infrastructure system. Quantifying resilience consisted of engulfing evidence/data in a community through a rigorous field survey and experts’ opinions. The information collected from different sources understandably suffers from uncertainty, incompleteness, and subjectiveness; consequently, their credibility level cannot be assured. To address these problems, the Dempster–Shafer theory is adopted in this study to address the inherent uncertainty, vagueness, and subjectivity with lack of information. The research proposes a framework to compute the “belief of resilience” over the desired frame and the belief propagation at different hierarchy levels to subsequently quantify resilience. A case study is implemented using the developed flood resilience modeling framework facilitating informed decision making.

Predictive modeling of deterioration is typically done based on visually inspected condition ratings of building components. This paper presents the concept of a cumulative lost value ratio (CLVR) for component groups to track their deterioration with time. The CLVR is computed through the estimated nominal replacement costs and times for the components that form the group in a given building. This eliminates the need for condition surveys and enables a much larger proportion of building assets to be modeled. Data from the City of Melbourne indicated that eight building component groups encapsulated 87% of building value. The similarities observed in their deterioration patterns were used to allocate them into four categories: (1) superstructure; (2) finishes; (3) fittings, plumbing, and water; and (4) air-conditioning, fire, and electrical. Next, for each year, the proportions of buildings with a given component group in each of five CLVR ranges (C1–C5) were established and fitted with Markov deterioration models. The best fits were obtained for the superstructure and finishes groups and also for Conditions C1 and C5.

This paper presents the durability performance criteria for precast reinforced concrete (RC) box units for long-term durability against corrosion deterioration. This paper also presents the condition evaluation of precast RC box units constructed (at site) for road under bridge (RUB) that were exposed to open atmosphere for a period of about seven to eight years. This warranted the evaluation of the quality, integrity, strength, and durability of precast RC box units. Nondestructive testing and evaluation (NDT&E) reveal that some portions of RC box units are found to be of poor quality showing voids, honeycombing, and very low cover thickness to the rebar. The study shows that satisfying the minimum compressive strength criteria will not be sufficient for ensuring quality, integrity, and long-term durability of an RC structure since the deficiency in terms of poor quality and insufficient rebar cover thickness initiated corrosion deterioration at some portions in the selected RC box units. The detailed comprehensive investigation emphasizes the urgent need for the implementation of ‘durability performance’ criteria, in addition to the strength criteria for ensuring the long-term durability of the as-built structure. Necessary repair measures are suggested to enhance the long-term durability of RUB.

To investigate the causes of cracks in wet joints of continuous concrete box girders, we performed in situ analysis of the temperature and strain field of wet-joint concrete for a sea-crossing bridge under construction in China after casting. We developed a numerical model to compare with the field tests. The numerical results agree well with those measured in the field. Thermal stress due to the heat of hydration in concrete is the main factor causing cracks, followed by concrete shrinkage. Furthermore, we investigated some measures to minimize and control the occurrence of cracks, such as optimizing the concrete mix ratio and lowering the casting temperature of wet concrete.

Numerous studies have highlighted the importance of condition forecasting and service life estimation for building components, but many previous approaches do not account for the uncertainty inherent in failure processes where similar components may have differing degradation paths. This study focuses on incorporating a probabilistic approach to more accurately model independent component failures and mitigate this deficiency found in other methods by expanding upon existing research to develop a Weibull model through Monte Carlo simulation to characterize a failure process. The study institutes a different gradient descent approach than previous methods by modifying an algorithm designed for unconstrained optimization in order to be suitable for the constraints of the problem. Comparisons were drawn between the proposed method and a traditional Markov process model where the proposal improved accuracy across all studies to a $p<0.01$ level of significance. Results show that an optimized characteristic Markov transition matrix utilizing variable inspection frequencies improves condition forecasting accuracy across multiple time-series intervals and generalizes well across different classification schemes. The analysis on data partitioning demonstrates that the method is applicable to smaller data sets than may be necessary for other approaches, such as machine learning algorithms, and results in a two-parameter Weibull model that can be used to predict equipment degradation.

Bridge deterioration is inevitable in service, and the inspection and maintenance of bridges are needed to ensure structural integrity. To make cost-effective inspection plans, bridge management departments need degradation models to predict future condition ratings of bridges. Although there have been studies on bridge degradation, the input features of models are selected mostly based on engineering experience, and no effective method has been proposed. Meanwhile, most models based on machine learning (ML) and deep learning (DL) only predict the degradation of bridges in a single year and cannot cover a complete inspection cycle (usually 2 years), providing limited decision support for the transportation departments. Besides, more accurate models are needed to predict the degradation trend of bridges. In response to these problems, an improved ReliefF algorithm is proposed to select features of bridges in the paper. Meanwhile, a new degradation model combining recurrent neural network (RNN) and convolutional neural network (CNN) is established. Historical data of bridges in the US state of Texas from 1992 to 2019 are employed to verify the proposed methods. The result shows that the improved ReliefF algorithm selects the appropriate feature set as the input of the prediction model, and the model accurately predicts the future condition ratings of bridges in the next 3–4 years. The research is beneficial to infrastructure management departments in allocating bridge inspection and maintenance resources reasonably.

Long-term exposure to a harsh environment leads to irreversible degradation of mechanical properties of fiber-reinforced polymer (FRP) profiles. Understanding the aging effects on pultruded FRP composites due to long-term exposure is essential. The moisture diffusion process plays a significant role in understanding material degradation of E-glass/polyester-reinforced polymer composite laminates exposed to hygrothermal environments. In this paper, the moisture diffusion process in pultruded (GFRP) composite bridge members is numerically simulated using the finite-element method. The moisture diffusion parameters were calibrated by gravimetric tests of pultruded composite thin plates. Gravimetric tests of three different rectangular specimens were conducted to investigate three-dimensional moisture diffusion at different temperatures and environments. The calibrated mass diffusion parameters were validated by comparing the average time-dependent moisture concentration obtained from non-Fick finite-element (FE) simulation with experimental results.

In the past several years, the high frequency of cave-in failures of urban roadways has posed a serious threat to the safety of traffic, pedestrians, and existing structures and facilities in China, and they have often led to fatalities, injuries, and significant economic losses. First, this study collates 379 cases to characterize roadway cave-in failures. Then the major causes associated with these events are classified, which includes damage and defects on preexisting underground structures and facilities, washout and erosion of roadway subgrade by seepage water, underground construction, loose subgrade, excessive lateral wall movement and through-wall leaking of deep excavations adjacent to roadways, and rapid decline in water table levels. Then four enormously influential failure cases are described as typical examples. Finally, the primary characteristics of the cave-in failures are discussed, including their temporal and spatial distributions, sizes, and morphologies, as well as the number of casualties and injuries involved. This review concludes that it is of paramount importance to inspect healthy conditions of aging underground structures and pipelines and to adopt or develop reliable measures to check unseen loose zones, voids, and cavities underneath urban roadways, in particular those adjacent to construction sites, with erodible subsurface conditions, or frequently subject to disturbing forces (seepage flow and vibration).

Subway tunnels in Nanchang, China, may pass through one or several weathered argillaceous siltstones in the construction process. To reveal the influence of weathered argillaceous siltstone on the long-term settlement of subway tunnels, dynamic triaxial tests of intensely and moderately weathered argillaceous siltstone were carried out. Based on these tests results, the evolution law of cumulative plastic dynamic strain was analyzed and a prediction model of cumulative plastic strain was established. Finally, an actual subway tunnel with weathered argillaceous siltstone was selected for long-term settlement prediction analysis. The results of settlement prediction indicate that the sedimentation value of this tunnel is approximately 20.87 mm under 100 years of operation (service life). Research results show that the dynamic strain of weathered argillaceous siltstone under cyclic vibration load is mainly affected by dynamic stress and static deviatoric stress. When the static deviatoric stress increased from 0 to 200 kPa, the dynamic strain of intensely and moderately weathered argillaceous siltstone increased by 8.53 and 5.97 times, respectively. Therefore, the intensely weathered argillaceous siltstone (IWAS) is more susceptible to static deviatoric stress than moderately weathered argillaceous siltstone (MWAS). In addition, increasing the confining pressure will accelerate the expansion of fissures in intensely weathered argillaceous siltstone, while the fissures in moderately weathered argillaceous siltstone will be inhibited, and the effect is completely opposite.

Shield tunnel structures are commonly found to be overdeformed in Eastern China soft ground due to adjacent engineering activities. Grouting treatment could serve as a viable solution to actively reduce the excessive diametrical expansion of tunnel linings. However, understanding the grouting-induced effects on adjacent tunnel structures remains preliminary due to the scarcity of well-documented case histories. In this study, a field experiment was conducted to explore a shield metro tunnel’s real performance during grouting treatments. An extensive monitoring scheme was deployed while varied geometrical grouting arrangements were carried out. The tests provided a comprehensive database of the tunnel responses in multiple temporal resolution levels, both during the entire course of the grouting treatment and within single grouting operations. Investigations are carried out over the influencing factors of the grouting efficiency. The experimental observations suggest that grouting efficiency tends to evolve with time and can be affected by various geometrical grouting parameters. Observations are also presented and discussed in detail for the influence of grouting history on the convergence distribution and the tunnel’s performance after the termination of all grouting operations. Time-variant behaviors of the tunnel are depicted in detail, such as the convergence recovery and rebound during the grouting process. Overall, this case study brings new insights into understanding the grouting-induced tunnel lining response. It can also serve as a benchmark for further theoretical and numerical studies.

Graphene has been proven to have a wide range of applications in transportation intelligence and green infrastructure development. In view of a series of distresses in the use of epoxy asphalt, we used graphene nanoplatelets (GNPs) to modify epoxy asphalt to further increase the strength and toughness of epoxy asphalt. The one-pot method was employed to form GNPs modified epoxy asphalt, and GNPs were dispersed by high-speed shear mixing emulsifier. Then we conducted macro-micro comparison tests between epoxy asphalt and GNPs modified epoxy asphalt. Macroscopic testing, including tensile testing with epoxy asphalt dumbbell specimens, showed that adding GNPs into epoxy asphalt can increase the fracture toughness more than three times. According to the fluorescence microscopy in microanalysis, the main reason for the improvement of tensile properties is that GNPs can build a bridge between epoxy resin and asphalt, which makes the matrix asphalt distribute in epoxy resin continuously with smaller particle size and forming a denser network structure. This dense network can enhance epoxy asphalt’s cohesion and flexibility and improve the tensile properties of the epoxy asphalt modified by GNPs. Thermal analysis showed that adding GNPs can improve the high- and low-temperature performance of epoxy asphalt. Infrared spectroscopy revealed the position of functional groups in epoxy asphalt. This research can provide new material for long-life pavement, which promises to extend the highway infrastructure’s service life.

Welded steel connections have been extensively used in practical engineering for the superiority of welding. However, many welded structures under complex disaster conditions have exhibited significant low-cycle fatigue damage, resulting in catastrophic accidents and tremendous economic losses. In this study, the low-cycle fatigue performance of steel welded connections was experimentally investigated based on full-field strain collected by a 3D-digital image correlation (DIC) system. Analysis of fatigue life, failure mode, force-displacement hysteresis curve, strain-time curve, and strain distribution of butt-welded steel connections under low-cycle fatigue loading was implemented. The failure process under low-cycle fatigue was investigated based on the strain distribution and variation of the weld zone and heat-affected zone and further explained from the point of micromechanisms. Results reveal that the strains of the weld zone were higher with the increase of loading cycles than that of other positions. Hence, the final failure of the specimens had a preference for the weld zone where the weld metal exhibited tensile and compressive plastic strain asymmetry and cyclic softening characteristics. The plastic strain accumulation of the weld zones and heat-affected zones should be the main reason for the failure of specimens under low-cycle fatigue.

Because of its high historical, cultural, and scientific value, wooden architectural heritage in East Asia requires comprehensive protection. The dou-gong (bracket set) is an essential member in ancient Chinese wooden architecture. The hysteresis behaviors of dou-gongs are critical to the abilities of structures to resist external dynamic loads, mainly including wind and earthquakes. It is crucial to develop an effective and convenient method to investigate the hysteresis performance of dou-gongs quantitatively. This study developed a simplified finite element model of dou-gongs using Euler beam and link elements. The types of Song-style dou-gongs and the experimental hysteresis characteristics were reviewed. Eight parameters of the skeleton and hysteresis curves were determined, and their suggested value ranges were proposed. The hysteresis behaviors, predicted using the proposed simplified simulation method, were compared with the experimental results, and the accuracy and rationality were validated. Finally, the applicability of the proposed simplified model was verified based on single and cooperative dou-gong performance. This study extends the simplified model of dou-gongs and provides useful guidelines to investigate their hysteresis performance.

This work arises from the evidences of recent collapses of historical urban walls. These events, mainly occurred after severe rainfalls, recalled the attention on the vulnerability of these infrastructures. Specific evaluation models which take into account the role of moisture inside the walls are not frequent in the literature. The problem is difficult to treat in many practical cases due to the extension of the urban walls and the variability of their geometry and of their mechanical features. The integrity of the urban walls is investigated throughout the analysis of a set of vertical sections. Risk scenarios of rainfall events are analyzed. At this scope, four limit states are proposed and investigated to determine both collapse and serviceability conditions. The combined risk analysis is obtained by treating the single-risk analysis. The results from the limit analysis are compared with those from the finite element method models. The method is applied to the relevant case study of the Volterra historical urban walls with a retrospective analysis of the section that collapsed in January 2014 and the analysis of other relevant sections.

One method of bridge construction consists of simply supported precast, prestressed concrete girders made continuous for live load through individual continuity joints connecting the two girder ends from adjacent spans. However, creep, shrinkage, and thermal effects can create large positive moments in the joints, leading to severe cracking and potential loss of moment transfer. A bridge in Fort Supply, Oklahoma, utilizing this type of connection was slated for joint replacement, and the Oklahoma DOT elected to use ultra-high-performance concrete (UHPC) for the replacement. To evaluate the effectiveness of the UHPC joint, a load test was conducted before and after joint replacement. The bridge was tested by systematically placing dump trucks filled with crushed stone at the midspan of each continuous span. Deflections were monitored for each test, and strains were monitored in two joints using strain gauges embedded in the UHPC joints during construction. While the measured deflections were small, the strain readings from the postrepair test showed that the UHPC joint was able to effectively provide continuity.

Coastal transportation systems are extremely vulnerable due to the coupled impacts of storm surge, waves, and inundation. Existing literature has developed coastal fragility models for bridges. However, to date, flood fragility models for coastal roadways are lacking. For this purpose, the current study proposes a data-driven fragility model based on logistic regression for coastal roadways, with failure probability conditioned on distance to shoreline and inundation duration, using hindcast data for Hurricane Ike. In addition, the effect of bridge and roadway damage on transportation network performance is investigated through a case study on Galveston Island, Texas. The results indicate the spatial distribution of storm impacts on the transportation network, with select roads highly vulnerable if they are located within a couple of hundred meters of the shoreline. In addition, considering roadway damage in addition to bridge damage alone, which is the current state of the art, can have a significant impact on decreasing the performance of the transportation network. Such analyses shed light on potential policy or risk mitigation practices that are expected to be increasingly important in the future as sea level rise further reduces roadway distance to the shoreline or as storm intensity and frequency changes.

Penetrating sealers have been applied to some concrete pavement joints to reduce moisture movement and provide additional durability in Wisconsin since 1999. In these projects, contractors were asked to first pressure-wash all saw slurry from sawed joints and allow them to dry thoroughly, then apply a silane sealer directly to the interior of the sawed joint. The objective of this study was to evaluate the effectiveness of penetrating sealer in protecting pavement joints through field investigation of three projects in Wisconsin. Site visit surveys along with sample evaluation of field cores were completed. Although there was no visual detection of the presence of sealers in in-service pavements, laboratory tests proved the presence and functionality through contact angle, absorption, and penetration depth. The depth of penetration ranged from 1.46 to 11.75 mm, with an average of 5.14 mm. Penetration was correlated with concrete strength where less penetration was associated with high-performance concrete. When compared with the samples without sealer, more than half of the joints with sealer were still performing better in terms of contact angle and absorption after 8.2 years of service.

Due to the importance of civil structures and infrastructures, structural safety assessment or structural health monitoring has become a basic necessity for every society. Recent developments of sensing and data acquisition systems enable civil engineers to exploit machine learning methods based on data-driven strategies for structural safety assessment and damage detection. However, the choice of an appropriate machine learning method may be problematic, particularly under some challenging issues such as the negative effects of environmental and/or operational variability (EOV), and the necessity of estimating some influential unknown elements of parametric machine learning methods called hyperparameters. Accordingly, this article focuses on three main aspects: (1) comparing various machine learning methods, (2) developing semiparametric algorithms, and (3) proposing automated algorithms for hyperparameter optimization of semiparametric and parametric machine learning methods. An innovative automated output-only approach is proposed to qualitatively and relatively predict the levels of EOV in terms of strong or weak variability. The main contributions of this article include comparing various machine learning methods, which will enable civil engineers to choose the most appropriate technique, and proposing automated approaches to hyperparameter optimization and variability level prediction. Dynamic and statistical features extracted from measured vibration data of two full-scale bridges were considered to perform the comparative studies and investigate the proposed methods. The results demonstrated that the semiparametric methods provide the best performance when their unknown parameters are determined appropriately.

Modal parameters are widely recognized as valuable indicators for evaluating the performance of railway bridges in structural health monitoring. A major challenge in the mode-based performance assessment is to obtain modal parameters reliably because operational factors may cause significant identification errors or reduce modal identifiability. To reduce the operational effects on mode-based assessment, vibration responses are divided according to excitation types, and then two subspace identification techniques are developed for identifying modal parameters of the railway bridge. If the bridge is only acted on by the ambient excitation, the stochastic subspace identification (SSI) is taken in this paper. If the bridge is mainly acted on by the train excitation, modal parameters are difficult to identify due to the regularly spaced and highly energetic axle loads. In this case, a deterministic stochastic subspace identification (DSSI) method is developed for improving the modal identifiability of the railway bridge under train action. The monitoring responses of a high-speed railway bridge are analyzed in this paper to track long-term modal parameters. Besides, variations of modal parameters that are related to environmental factors, operational conditions, modal orders, vibration directions, and member types are extensively compared. The results show that modal parameters can be well-identified even though the nonwhite noise excitation exists, and the performance assessment can be well achieved through determining the optimal modal parameters.

This paper presents an accurate and stable method for object and defect detection and visualization on building and infrastructural facilities. This method uses drones and cameras to collect three-dimensional (3D) point clouds via photogrammetry, and uses orthographic or arbitrary views of the target objects to generate the feature images of points’ spectral, elevation, and normal features. U-Net is implemented in the pixelwise segmentation for object and defect detection using multiple feature images. This method was validated on four applications, including on-site path detection, pavement cracking detection, highway slope detection, and building facade window detection. The comparative experimental results confirmed that U-Net with multiple features has a better pixelwise segmentation performance than separately using each single feature. The developed method can implement object and defect detection with different shapes, including striped objects, thin objects, recurring and regularly shaped objects, and bulky objects, which will improve the accuracy and efficiency of inspection, assessment, and management of buildings and infrastructural facilities.

To reduce the reflection cracking and interlayer bonding degree of cement concrete pavement, an isolation layer was set up between the water-stabilized base layer and the cement surface layer. Finite-element analysis was used to analyze the mechanical properties of the cement concrete pavement structure and the wax isolation layer. By changing the cohesive strength and internal friction angle of interlaminar structures, the effects of different friction coefficients on the pavement deflection, the maximum tensile stress of surface course, the maximum interlaminar shear stress, and the maximum tensile stress of base course were analyzed. Results showed that when the internal friction angle was 0°, the maximum tensile stress of surface course of cement concrete in the upper warpage state was 4.6 times of that in the lower warpage state; the change of internal friction angle had more influence on the concrete stress than did the change of cohesive force; and the internal friction angle needs to be controlled at 30° to 50° when the cohesion is less than 0.01 MPa. The mechanical property parameters of cement concrete pavement were obtained, which could provide a scientific basis for the pavement structure design with wax isolation layer.

Because of the relatively low accuracy of the current asphalt pavement performance prediction, a new pavement performance prediction model was established based on the particle swarm optimization (PSO) algorithm and support vector machine regression (SVR) algorithm. First, the SVR algorithm was introduced into the model to deal with the nonlinear regression. Then the PSO algorithm was applied to improve the searching efficiency and parameter continuity of the SVR algorithm. The pavement inspection data of an expressway in eastern China from 2006 to 2015 were used to verify the results, proving the feasibility of the PSO-SVR prediction model. The research results show that the model using particle swarm optimization has a fast convergence speed, and the optimized support vector machine has better rutting prediction performance and perfect generalization, and the prediction accuracy and reliability are higher than those of unoptimized support vector machine model.

A super-large-scale foundation pit ($\mathrm{74,000}{\mathrm{m}}^2$ in plane) adjacent to an existing historic building on three sides was constructed by the technique of a deep foundation pit group in downtown Shanghai, China. Through extensive and long-term field monitoring, this study investigated structural responses of the building during the construction process as well as effectiveness of corresponding protective measures on controlling the deformation of foundation pit and building settlement. The analysis of field data indicated that by taking advantage of the construction technology of the foundation pit group, the wall deflection close to the protection building was controlled within 0.09% final excavation depth, which was less than the limit of relevant specifications. The control effect of prestressed steel support on wall deflection did not surpass that of reinforced concrete supports when the excavation depth was less than 12 m but rose significantly after the excavation entered the soft clay layer. The construction of diaphragm wall panels resulted in significant settlement of the historic building. However, more importantly, the lateral stress relief of soils on both sides of it caused by trenching would lead to hogging deformation of the bearing wall and horizontal tensile stress in the building’s foundation, which aggravated the crack propagation and structural damage. Underpinning for the historic building was verified to be an effective method to resist the impact of ground movement caused by the excavation in soft soils. The maximum settlement of the historic building during the excavation stages stabilized between 10 and 18 mm, accounting for 20%–40% of the total settlement, far less than the settlement of ground surface around the building.

Detection of potential damage is of great significance for aging railway bridges. In this paper, a damage location method for beam railway bridges based on the rotation response to operational train loading is presented. The method is based on deformation area analysis of the operational rotation response of bridges to the passage of trains. The theoretical basis of this method is elaborated. The calculated deformation curvature area difference ratio (CADR) change is used to identify damage in bridges. To obtain the curvature area, a technique is proposed for the curvature area calculation. The results are presented in terms of the damage condition extracted from each ratio, which was obtained by dividing the deformation area from the current interval to the sum of the areas from all the intervals. The location of damage was identified by observing the magnitude of the changes in the CADR. Finite element models were utilized to verify the method. The influences of train-track-bridge interaction and environmental temperature changes were considered. The calculation process is given for the application of the proposed method to the damage location of railway bridges. Thereafter, vehicle-bridge models with different parameters are investigated. The results show the capability of the method.

Fragility curves are useful tools for presenting the risk of structural damage from earthquakes as a function of a ground-motion parameter. Seismic hazard analysis for an area precedes the fragility analysis for structures built in that area. Many studies are available in the literature regarding probabilistic seismic hazard analysis (PSHA) and fragility estimation. However, a practical approach to integrate the hazard curve from PSHA and using the ground motion of that level to estimate fragility can be an area to explore further. In this study, an effort has been made to obtain peak ground acceleration (PGA) level at design-based earthquake (DBE) from PSHA. Based on this PGA value obtained, a fragility assessment has been performed. This study aims to obtain a fragility curve for a midrise RC frame building for DBE hazard level using PSHA. Three 6-story RC frame buildings are considered in this study for a seismically active zone in India. The buildings have been designed with the following performance objectives: (1) immediate occupancy (IO) with 1% drift, (2) life safety (LS) with 2% drift, and (3) collapse prevention (CP) with 3% drift. Incremental dynamic analysis (IDA) is performed using 22 numbers of far-field ground motions as prescribed by a strong ground-motion database to obtain the capacity of exceeding the respective drift limit states. Fragility curves for the three buildings are generated based on those capacities. The present study is a practical approach to capture the consequence of seismic hazard for an area and predicting the seismic risk.

Water seepage is the primary cause of corrosion of stone carvings in caverns. At present, grouting is commonly accepted by conservators as an effective technique to reduce leakage and help preserve carvings. However, because cracks are often narrow and deep, there can be attachments on the surface of rocks that affect the bonding between the grouting materials and rocks and that cannot be cleared completely. This will eventually cause the failure of accepted techniques to seal against leakage. In this work, four kinds of modifiers were applied to improve the bonding between the grouting material and rock under laboratory conditions. The results show that dried moss and dried fungus will significantly increase the hydrophobicity of rock and inhibit the spread of grouting material on the surface of rock. Mud and calcium sulfate will immensely increase the water absorption of rock and cause the grouting material to lose fluidity. All four kinds of modifiers tested improved the diffusion and penetration depth of grouting materials on the surfaces of specimens. Among these, the 3-glycidoxypropyl trimethoxy silane (KH560) had the best overall effect. It could help to increase by 40%–55% the diffusion and penetration depth of grouting materials on the four kinds of mimic surfaces.

This paper presents research concerning new fireproof construction guidelines for protection of dwellings against wildfires. The main subject of this study are newly-built houses, using current building materials and methods to maintain the integrity of the overall structure for an extended time during an ongoing fire exposure. This study also presents possibilities for use of these new construction techniques to rehabilitate existing houses located in highly endangered wildland fire areas. The scope of this study are traditional dwellings situated mainly in the south of Europe, such as Portugal, Spain, France, Italy, and Greece, located in high risk wildfire zones in the wildland-urban interface. In recent years, wildfires have had a major impact on the forest areas in Portugal, mostly due to the high combustibility of the wildland and to climate change, causing severe lasting damage to, or even the destruction of, dwellings. The dwellings have often been rebuilt with similar characteristics to the original ones, disregarding interventions with new techniques that would make them fire protected, thus making them likely to burn again. As a result of these analyses, this study provides new fireproof construction guidelines for new and old dwellings, using traditional materials found in the construction industry of Europe. Finally, as a future reference, the situation of isolated villages surrounded by forests is also investigated and solutions are proposed to protect the inhabitants.

Closed-cell aluminum foams of density 0.3 to $0.46\mathrm{g}/\mathrm{cc}$ ($1\mathrm{g}/\mathrm{cc}=\mathrm{1,000}\mathrm{kg}/{\mathrm{m}}^3$) were exposed to incident shock waves of 10–11 bar ($1\mathrm{bar}=1.01325\times {10}^5\mathrm{N}/{\mathrm{m}}^2$) pressure in a shock tube to study the shock-induced stress on the end wall, which was measured using a fast-response polyvinylidene difluoride (PVDF) sensor. The experimental results revealed amplification of the end-wall stress by 2.5 to 4 times compared to pressure exerted on the front surface of the foams. Shock compression of foams is discussed based on the stress history output of the PVDF. The properties of the densified foam samples, the particle and plastic wave speeds in foams, based on theory, are presented. A numerical analysis of loading the foams with shocks was conducted using Abaqus software to complement the experimental results. The numerical prediction of the end-wall stress also suggests stress amplification by a factor of 2.6 to 3.4. The information can be useful to designers of shock attenuators and defense shields using aluminum foams.