Demand Parameters Research Articles

Manini Connect: IoT for integrated building monitoring

Constructions are conceived today following multi-risk scenarios encompassing natural and anthropic hazards, in the context of a rapid climate change. Nevertheless, currently the monitoring of local demand and/or performance on specific buildings is very poor due to the absence of a praxis towards the installation and the management of sensors, dedicated to the performance of the whole building. This makes the post-event field surveys and damage mapping extremely difficult, and retrofit intervention timespans very long, with negative reflection over the resilience of the whole built heritage. Manini Connect is an innovative patented system providing a response to this issue through integrated monitoring of precast structures. Through a set of interconnected sensors, the system monitors the static and dynamic behavior of the structures during critical events (earthquakes, strong winds, heavy rainfalls, collisions, blasts, etc.) and thermo-hygrometric parameters inside/outside the building. Moreover, it can be coupled with sensors devoted to the monitoring of the air quality inside the building, the local production of energy from renewable sources, and the consumptions in terms of electricity, water, gas, waste, etc. Taking advantage of the production of precast structures in offsite permanent plants, some sensors and utilities are easily inserted in the columns and cast within them during the production phase, whilst other typologies are collected into an external box installed on the roof throughout the building construction process. The data are received in real-time by the dedicated internal control center of Manini Prefabbricati SpA, and, after the occurrence of an exceptional event is revealed by the overcoming of predetermined thresholds of demand parameters, the system sends alerts for check. The user has himself constant access to the data through a dedicated platform accessible from PC and other devices. This allows to set predictive retrofit/maintenance works in response to anomalies or damages detected by the system, as a function of the parameters archived from the structural design of each specific building.

Seismic response prediction using a hybrid unsupervised and supervised machine learning in case of 3D RC frame buildings

The seismic vulnerability assessment represents an important step in monitoring the buildings’ capacity and checking their performance during and after earthquake events. The Nonlinear Time History Analysis (NL-THA) is considered the most reliable method that is used to calculate the exact structural behavior of any building. However, this sophisticated method is known for its complexity, the use of Finite Element (FE) software, and computational time consuming, especially in the case of tall buildings. For that reason, An Artificial Neural network (ANN) is used to develop a new model able to predict the essential Engineering Demand Parameters (EDPs), i.e., the Maximum Base Shear (MBS), the Maximum Inter-story Drift (MIDR) and the Maximum Roof Drift Ratio (RDR). Unsupervised algorithms such as the Principal Component Analysis PCA and the Autoencoder are coupled with the ANN to reduce the dimensionality, improve the dataset quality, and reduce the irrelevant features. More than 192,000 buildings are analyzed using the NL-THA and eighty artificial ground motions (GMs) to generate the dataset. The buildings’ characteristics are generated randomly from the selection range. The results showed that the Autoencoder-ANN model represents the highest performance compared to the PCA-ANN and ANN models. The Autoencoder-ANN model could quickly and accurately predict the seismic responses of unseen ground motions using only the building’s characteristics and the GM parameters without using any FE software.

Probabilistic seismic performance estimation through surrogate model and unbiased multi‐fidelity Monte Carlo predictor

AbstractThis study introduces an approach for probabilistic seismic performance estimation, which focuses on the probability of intensity measures exceeding a specified value based on engineering demand parameters. Conventional methods face challenges owing to the increase in computational costs associated with the uncertainties in earthquake scenarios. To address this, we use high‐fidelity (HF) and low‐fidelity (LF) model data to develop a multilevel hierarchy of surrogate models, which improves the simulation‐based probabilistic estimation. However, designing a reliable LF model and ensuring the accuracy of the surrogate model hierarchy remains challenging. Herein, we present a multi‐fidelity Monte Carlo (MFMC) predictor combined with a conventional surrogate model to improve probabilistic seismic performance estimation, thereby leveraging LF model efficiency and HF data accuracy for unbiased results. We addressed the challenge of constructing a suitable LF model by using a surrogate model trained from limited HF data. The MFMC predictor improves the accuracy of probabilistic analysis than the surrogate models trained from limited HF data. Further, the automatic relevance determination method is introduced to select the most appropriate inputs for the surrogate model. A case study featuring a special moment‐resistant frame, subject to uncertainties from both ground motion and structural properties, illustrates the efficiency of the method. A LF model is developed using the Kriging method, followed by the construction of the MFMC predictor for probabilistic analysis, thereby leveraging both limited HF and numerous LF data. Comparing the exceedance probability curves obtained from the MFMC predictor with those from direct Monte Carlo simulations and conventional Kriging showed that our proposed method offers a promising tool for probabilistic seismic performance estimation under uncertainty.

An optimization model for sustainable multi-product multi-echelon supply chain networks with U-shaped assembly line balancing under uncertainty

This study presents an integrated supply chain network with suppliers, manufacturers, assemblers, and customers. The proposed model considers a U-shaped assembly line with three sustainability objective functions. We consider assumptions considering different types of raw materials, multiple products, location selection of manufacturers, location selection of assemblers, and capacity of suppliers. The problem is formulated non-linear and then linearized as a multi-objective model. Some cost and demand parameters are considered uncertain and are represented by fuzzy sets and theory. The proposed uncertain model is first converted to a multi-objective crisp model by applying the modified robust possibilistic programming approach. Then, the obtained crisp multi-objective model is solved by an interactive-fuzzy optimization approach in the literature. For computational study, some test problems are generated and solved using an original deterministic formulation and the crisp form of the uncertain formulation. The obtained results are analyzed and compared according to the objective function values. Finally, an extensive sensitivity analysis is performed on the parameters of the models.

An integrated Optimization Model of Product Mix, Assortment Packing, and Distribution in A Fashion Footwear Company

Recognizing the paramount importance of operational effectiveness and resource management in supply chain management (SCM) of the fashion industry, this study addresses a specific challenge faced by a prominent Indonesian fashion footwear company. The inefficiency is due to repetitive sorting and packaging processes during product distribution, which significantly impact optimal production mixes and product distribution from the distribution center to the point of sale. A crucial aspect is also the optimization of the delivery route. To address these challenges and minimize the total cost of ownership, the study proposes an integrated optimization model. This model simultaneously determines the optimal production quantity, assortment packaging, and distribution channels, taking into account decision variables related to distribution in configuration boxes, overload and underload products, as well as production numbers that respond to store-specific demand fluctuations. A notable contribution of this research is the integration of product mix decisions into the assortment packaging and distribution model, which represents a novel approach. The optimal solution determined using the LINGO 18.0 software highlights the significant influence of product penalty costs and product demand parameters on the objective function, while shipping costs have no noticeable influence. By emphasizing the integration of product mix decisions into the optimization framework, this research contributes significantly to improving the understanding and practical application of efficient supply chain management in the fashion industry.

Сравнительный анализ транспортного спроса и предложения в моделях транспортных систем городских агломераций

Purpose: To analyze the methods of mathematical modeling used to determine the demand for urban transportation and predict the intensity of flow distribution in the public transport network. To determine the zones of effective use of network and pre-network methods for the formation of transport models of urban agglomerations. To conduct a comparative analysis of the parameters of transport demand and offer in the network and pre-network variants of urban transport systems modeling. Methods: Mathematical modeling, processing large amounts of data, geoinformation analysis. Results: The methods of determining transport demand and offer used in modern transport models are analyzed. A comparative analysis of pre-network and network methods in transport modeling is carried out, the zone of their effective use is defined. The approbation of the problem solution of determining the transport demand and offer is carried out on the example of the urban transport system model of the St.Petersburg agglomeration. Based on the modeling results, the dependencies of transport demand and offer on the input data and model limitations are analyzed. It is concluded that it is necessary to calibrate the value of each parameter when using transport modeling. Practical significance: The results obtained can be the basis for improving mathematical modeling methods used in urban transport planning. The proposed approaches to modeling transport demand and offer can be used in the creation of forecast models used to justify project decisions in the documentation of territorial and transport planning.

Deformation behavior of rectangular underground structures in liquefiable deposits correlated to ground motion intensity measures

Rectangular underground structures in liquefiable deposits are susceptible to larger deformation during earthquake events. The intensity of earthquake motions, as one of the critical factors that would induce large deformation of underground structures in liquefiable deposits, however, was not received enough recognitions. In this paper, nonlinear dynamic analyses with a probabilistic seismic demand model (PSDM) were conducted for a two-dimensional liquefied soil-structure system, considering a variable thickness of liquefiable layer below the structure. The nonlinear soil behavior was simulated by the nonlinear constitutive model PDMY02. The constitutive parameters of saturated sand were calibrated by a slope model in the centrifuge test from LEAP-2017. Interstory drift ratio (IDR) and uplift ratio (UR) of underground structures were selected as engineering demand parameters (EDP). There were totally 18 recorded earthquake motions and 8 intensity measures (IMs) included for the PSDM. Numerical results show that the uplift behavior of underground structures is more sensitive to the variable thickness of liquefiable deposits compared to the horizontal drift of the structure. According to the performance of correlation, efficiency, practicality and proficiency, the velocity-related IMs are more appropriate than the acceleration-related IMs for the evaluation of seismic deformation behavior of underground structures. The deformation response as well as the adaptability of velocity-related IMs are further discussed and evaluated by considering more general cases including different buried depths and height-width ratios for rectangular underground structures.

Effect of unreinforced masonry infills on seismic performance of reinforced concrete frame‐shear wall buildings

SummaryReinforced concrete (RC) shear wall buildings with unreinforced masonry (URM) infilled moment frames are common in India and neighboring countries. This study assesses the influence of the URM infills on their seismic performance. Fully infilled, open first‐storied, and bare frame versions of a 25‐story shear wall building are considered. Multiple stripe analysis is conducted at five return periods to estimate their performance. Fragility functions for the collapse prevention limit state, which is based on seven engineering demand parameter exceedance thresholds, are generated and compared. The presence of infills (full or partial) is observed to have an overall positive effect on the performance of the RC frame‐shear wall buildings. The performance of the open first‐story building was comparable to that of the fully infilled building. The ratio of story shear carried by the moment frames and shear walls is studied at all return periods to understand the variation in frame shear wall interaction with increased damage for each building. In the case of buildings with infills, the frames carry a higher proportion of story shear at lower return periods. For all three buildings, the fraction of story shear carried by moment frames increases along the height of the building.

Performance assessment of steel frame buildings with hybrid self-centering braces under extremely rare far-field earthquakes

This paper investigates the seismic performance enhancement of steel frame buildings using a novel hybrid self-centering braces (HSBs) under extremely rare earthquake events. The hybrid self-centering brace consists of shape memory alloy (SMA) cables and viscoelastic (VE) dampers. A prototype bracing system is designed and fabricated to explore its basic mechanical behavior and working mechanism under cyclic loading, with a focus on its failure modes under large deformation loading condition. A multi-material mechanical model is developed to capture the mechanical behavior and failure of the HSB. Furthermore, five steel frame buildings with different parameterized HSBs are designed and modeled in OpenSees. Nonlinear dynamic analyses and incremental dynamic analyses are conducted on the five case-study frames using 44 far-field ground motions. The risk-based seismic performances of steel buildings with HSB are evaluated to assess the performance of HSB during extremely rare seismic events. The results show that the hybrid self-centering brace exhibits excellent self-centering and energy dissipation capabilities with the maximum equivalent viscous damping ratio reaching 9.4 %. Even under large deformations, VE dampers continue to work effectively after the failure of SMA cables, demonstrating remarkable redundancy. Numerical simulations further reveal that the redundancy of HSB can improve the structural seismic resilience in terms of inter-story drift ratio, residual drift, and floor absolute acceleration. The higher the redundancy of HSB in the case-study frames, the smaller the seismic response and mean annual frequency of exceedance of the engineering demand parameters, thereby indicating a significant improvement in seismic performance.

Removal of Antibiotics From Hospital Wastewater Using Hybrid Chemical Purification and Batch Biological Reactor

Background: This study aimed to investigate the performance of tetracycline and amoxicillin antibiotics removal from hospital wastewater using a combination of chemical treatment and Batch biological reactor. Methods: In this study, the effect of PS/Fe2+/UV on tetracycline and amoxicillin removal was investigated. Different parameters including pH, different concentrations of iron, antibiotics and persulfate were investigated for removal efficiency. The remaining concentration of the solution was measured using a high performance liquid chromatography (HPLC) device. The degree of mineralization of the process was evaluated using the chemical oxygen demand (COD) parameter. Then, the removal of tetracycline, amoxicillin and COD from the pre-treated wastewater in the batch biological reactor was investigated. Results: The results demonstrate that the PS/Fe2+/UV process achieved complete removal of tetracycline and 97.3% removal of amoxicillin under laboratory conditions. In wastewater treatment, the process achieved a 69% reduction in tetracycline and a 67.2% reduction in amoxicillin within a 60-minute reaction time. Also, the amount of mineralization of tetracycline and amoxicillin antibiotics by PS/Fe2+/UV process was evaluated using COD index, which resulted in removal of more than 60% of COD for both antibiotics. Also, the combination of this process and the batch biological reactor succeeded in removing 99% of BOD5 from both antibiotics and 98% of COD from real wastewater, containing 10 mg of tetracycline and amoxicillin. Conclusion: The combined PS/Fe2+/UV process and batch biological reactor is an efficient method. It is effective for removing antibiotics and its mineralization for wastewater treatment containing tetracycline and amoxicillin antibiotics.

An efficient and accurate fragility approach for seismic performance assessment of structures

AbstractIn seismic risk assessment of bridges, developing fragility function is a fundamental step to characterize the structural vulnerability, which is usually derived based on the relationship between the engineering demand parameter (EDP) and intensity measure (IM). The EDP‐IM relationships are generally developed through three approaches, namely Cloud analysis (Cloud), incremental dynamic analysis (IDA), and multiple strip analysis (MSA). It is known that the Cloud method is computationally efficient while the IDA and MSA can provide the accurate fragility estimates. Thus, the present paper proposes an efficient and accurate fragility (EAF) approach which has similar computational demand as Cloud but keeps the same level of accuracy as IDA or MSA. In this proposed EAF procedure, the nonlinear time‐history responses at the intensifying duration of ground motions were used to develop the EDP‐IM curves. And these EDP‐IM curves are accurate enough to replace the IDA curves in developing fragility curves. To illustrate the efficiency and accuracy of the proposed EAF method, two typical bridges (a two‐span single‐frame bridge and a single‐pylon cable‐stayed bridge) were selected and modeled in OpenSees and employed as case studies. By comparing the fragility estimates of these bridges to IDA and MSA, it is demonstrated that the proposed EAF approach leads to reliable fragility results, while has similar computational time as Cloud.

Seismic design and performance evaluation of hybrid braced frames having buckling-restrained braces and self-centering viscous energy-dissipative braces

Hybrid braced frames (HBFs) emerge as an innovative seismic-resilient system, synergizing the strengths of buckling-restrained braces (BRBs) and self-centering viscous energy-dissipative braces (SCVDBs). This novel system has the potential to simultaneously manage three key seismic demand parameters: peak inter-story drift (PID), residual inter-story drift (RID), and peak absolute floor acceleration (PFA). Nevertheless, a dedicated seismic design method for HBFs is yet to be developed. This research proposes a performance-based seismic design (PBSD) method specifically tailored for HBFs. The method's core relies on energy decoupling in the HBFs using a proposed energy distribution factor (η). To validate the proposed design method, sets of 4-, 8-, and 12-story braced frames are designed using varied η. A comprehensive seismic performance evaluation is conducted, utilizing nonlinear static and nonlinear time-history analyses. The findings indicate that the HBFs, designed utilizing different values of η, consistently meet predefined performance objectives. Within the scope of this study, the η value of 0.5 is shown to be optimal, enhancing the structural resilience of HBFs against PIDs and PFAs while exhibiting excellent self-centering performance comparable to the self-centering viscous energy-dissipative braced frame (SCVDF). Additionally, the HBFs demonstrate superior control over PFA compared to pure buckling-restrained braced frame (BRBF) and SCVDF.

Recommendations regarding technology for making an well-grounded choice of enterprise development strategy

Introduction. Recently, more and more theorists and practitioners of management emphasize the importance of strategic planning, in particular, the formation of a development strategy, the main purpose of which is to determine directions for increasing competitiveness, which would ensure the long-term perspective of the successful functioning of the enterprise. The purpose of the paper is to study the process of making strategic management decisions; analyzing the criteria for choosing development strategies; development of the technology for the justified choice of a development strategy based on the parameters of demand and profit on the basis of the identification of selection criteria and the systematization of potentially possible types of strategies. Results. The recommended technology for the justified choice of a development strategy based on the parameters of demand and profit involves the implementation of certain stages: preparation of information support for further development of the development strategy; definition of strategic goals and tasks of development; strategic research and analysis of the competitive environment and development potential; formation of a justified set of criteria for choosing a development strategy based on demand and profit parameters; reasoned choice of strategic tools for developing a development strategy; formation of strategic development alternatives; formation of a justified development strategy and corresponding functional strategies; assessment of the level of implementation of the development strategy and strategic decisions according to performance criteria. Conclusion. The technology of formation of the development strategy is a priority element of the strategic planning system. Particular importance is attached to the methodological base, which ensures the processes of formation and implementation of planning technology, allows to achieve the goal of strategic planning in the formation of a sequence of defined justified actions, aimed at the implementation of effective functioning and long-term perspective of development.

Research on the operation of integrated energy microgrid based on cluster power sharing mechanism

This paper proposes a Nash bargaining cooperative game model for a microgrid cluster system with double re-energy-load delay considering electricity, heat and gas multi-energy synergies. With the minimization of the operating cost of each microgrid as the objective function, a low-carbon operation model of a multi-energy complementary integrated energy microgrid considering fuzzy opportunity constraints is developed, an optimal operation mechanism including carbon quota and carbon trading is assessed, and a carbon capture system and an electricity-gas conversion device are added to the improved cogeneration unit model. Source-load uncertainty in microgrids is described in terms of new fuzzy parameters of new energy and undefined parameters of load demand. Each microgrid plays a second game with the marginal contribution rate and carbon trading cost rate as the bargaining power. The model is solved in a distributed manner using the ADMM-RGE algorithm. Finally, the simulation results show that the proposed multi-microgrid power-sharing way maximizes the benefits of microgrid alliances; the cooperative help of microgrid alliances is pretty distributed according to the size of each microgrid's energy contribution; carbon capture joint power-gas systems and energy sharing methods between microgrids can effectively reduce carbon emissions during microgrid operation.

Reliable scheduling and routing in robust multiple cross-docking networks design

This study introduces a novel framework called Reliable Pollution Scheduling and Routing with Multi-Cross-Docking. The core idea behind this framework is to optimize the processing and transportation of products through each vehicle, ensuring that each vehicle serves its specified destinations only once before returning to the cross-dock. The objective of this research is to develop a multi-objective mixed integer programming model that efficiently manages scheduling and routing complexities in a multi-cross-docking system, taking into account uncertainties in demand. The primary goals of the model are to minimize the overall costs associated with pollution, loading/unloading, and transportation, while simultaneously reducing distribution and shipping durations. Additionally, the model aims to maximize the reliability of the supply chain for perishable products, contributing to sustainable development in the supply chain domain. To address the inherent complexity of the model, especially in dealing with demand uncertainties, we employ a robust optimization method. The multi-objective challenge is tackled using an innovative hybrid approach that combines goal programming and genetic algorithms. The effectiveness of our proposed solution strategies is rigorously assessed using a variety of metrics and subjected to comprehensive statistical testing. Furthermore, we validate the competence of our methodology by conducting a real-world case study, which includes sensitivity analysis of demand parameters and robustness analysis. Our findings confirm that our solution technique produces high-quality solutions. Notably, our approach optimizes route planning for delivery and pick-up phases, resulting in a significant 36.5% reduction in transportation time and a noteworthy 17.27% decrease in the overall system costs compared to existing conditions. Additionally, we observe a substantial 23.15% reduction in vehicle arrival times at cross-docks, contributing significantly to reduced product expenses.

Spatial and seasonal variations in surface water quality of the Lower Kinabatangan River Catchment, Sabah, Malaysia

Surface water quality was examined to determine spatial and seasonal variations in the Lower Kinabatangan River catchment, Sabah, Malaysia between October 2004 and June 2005, during the weak La Niña event. The study sought to distinguish between the quality in surface waters draining from an oil palm plantation (OP), a secondary forest (SF) and an oxbow lake (OB); and to identify its seasonal variability. A total of 45 samples were collected during fieldwork campaigns that spanned over the inter-monsoonal period, wet and dry seasons. The Water Quality Index (WQI) was calculated and analysed based on the Malaysia Interim National Water Quality Standard (INWQS). Results show that the quality of the river fall into Class II or moderate level. Discriminant analysis (DA) has been employed to classify independent variables into mutually-exclusive groups. Suspended sediment (SS) and chemical oxygen demand (COD) parameters were found higher during the wet season. COD was found dominant in stream located within the oil palm plantation, whilst SS was dominant in oxbow lake. Surface water quality variations could be influenced by weak La Niña event in 2005/2006, as precipitation anomalies have been observed during the sampling campaign.

Numerical Studies on Seismic Response of Structural Systems Using a Response-Spectra Based Intensity Measure

This paper proposes a novel intensity measure (IM) based on the geometric mean of acceleration response spectral ordinates to assess the probabilistic performance of structures subjected to seismic loading. Instead of relying solely on the fundamental period, the proposed IM is evaluated across a fixed period range for all structural systems, which allows consideration of higher mode effects and period changes due to nonlinearity. The proposed seismic IM is evaluated using two established indices sufficiency and efficiency. Sufficiency quantifies the independence of an engineering demand parameter at a specific intensity level with ground motion characteristics such as seismic magnitude [Formula: see text] and distance from site to fault plane [Formula: see text]. It is calculated by linear regression analysis, or using gradient-based relative sufficiency measures. On the other hand, efficiency is measured as dispersion across ground motions at a given intensity level for any physical response quantity. It helps to reduce computational demand for failure probability assessment by considering a smaller number of records compared to an inefficient IM for similar confidence levels. The effectiveness of the proposed IM along with 10 other IMs is demonstrated on single degree of freedom systems with various fundamental periods by performing nonlinear time history analysis using a far-field ground motion record set. The study is also extended to five degree of freedom lumped mass stick models, 2D models (4-, 8-, and 12-story archetype steel frames), and 3D reinforced concrete shear wall building model. The results indicate that the proposed IM limits dispersion to within 10% for long-time period structures, and demonstrates improved sufficiency across different structural systems. For example, gradient of the proposed IM with respect to magnitude [Formula: see text] and site-to-source distance [Formula: see text] for a 12-story steel frame is reduced by 42.9% and 94%, respectively, compared to spectral acceleration at fundamental time period. Potential application of this research lies in efficiently conducting seismic reliability assessment and design for structural systems.

Water Quality and Pollution Level in Plawangan Barat, Segara Anakan, Cilacap Based on Pollution Index Approach

Segara Anakan is a lagoon located in Cilacap, Central Java. It is characterized as a fragile ecosystem that is very susceptible to the impacts of alterations and land development. This region is susceptible to habitat degradation caused by human activity, resulting in alterations in water quality and pollution. The objective of this study was to provide a comprehensive description of water quality by analysing its physical and chemical properties. Additionally, the study intended to assess the level of water pollution by employing the Nemerow Sumitomo Pollution Index (PI) approach. The water quality sampling was conducted in the western region of Segara Anakan, namely Plawangan Barat. The obtained data were compared to the established standard quality for marine organisms, as outlined in the PP RI No. 22/2021. The classification of the water pollution level was determined according to Minister of Environment Decree No. 115/2003. The findings of this study indicate that the parameters of temperature, salinity, pH, dissolved oxygen (DO), and biological oxygen demand (BOD) in the water remain suitable for marine life throughout all study stations. However, it was observed that the levels of Total Suspended Solid (TSS), phosphate, and nitrate did not match the established safety thresholds. The pollution index indicated that the water quality in West Plawangan shows varying pollution levels, ranging from light to moderate pollution. Based on the findings obtained, it can be concluded that the Segara Anakan lagoon exhibits a diminished level of suitability for the life of marine organisms.Keywords: Water Quality, Index PI, Nemerow Sumitomo, Plawangan Barat, Marine Pollution

Scaling of earthquake ground motions for tri-directional nonlinear response history analyses of reinforced concrete rectangular bridge piers

In performance-based earthquake design (PBED), both the capacity of the structure and the demand from earthquake ground shaking are required to establish the desired performance levels. A range of possible demands can be estimated through nonlinear response history analyses (NRHA), which requires a suite of earthquake ground motions appropriately scaled to the target earthquake intensity for which the structure's performance is to be evaluated. The scaling is usually done for a particular earthquake intensity measure (IM) to get the associated dispersion in the engineering demand parameter (EDP). Several scaling strategies are available for uni-directional (Uni-NRHA) and bi-directional nonlinear response history analyses (Bi-NRHA). However, for tri-directional nonlinear response history analysis (Tri-NRHA), one literature suggests using the same scale factor (SF) for the vertical component, which is estimated for the Bi-NRHA. Therefore, in this study, three well-known scaling strategies, which are usually used for Uni-NRHA, are employed with 16 different methods for application in Tri-NRHA of a reinforced concrete (RC) single-column bridge pier modelled as a single-mass three-degree-of-freedom (3DoF) system. The absolute maximum drift is taken as the EDP, and a total of 1920 Tri-NRHA of the pier are performed using two suites of 20 far-fault and 20 near-fault ground motions, which are scaled to three levels of target earthquake intensity. The sufficiency and efficiency of all the scaling methods are checked statistically under all three target intensities. The study reports the effects of (i) vertical components in calculating the SF, (ii) earthquake intensity and structural nonlinearity, and (iii) far-fault and near-fault ground motion characteristics on the dispersion of the EDP. Out of 16 scaling methods, one is found to be acceptably efficient than the others for application in Tri-NRHA under both far-fault and near-fault ground motions at all target intensities.

Seismic performance of the temple of Aphaia in Aegina island, Greece

AbstractThe seismic performance assessment of the ancient Temple of Aphaia in Aegina island, Greece, is presented. The Temple of Aphaia was erected around 500BC using porous limestone and is one of the most characteristic examples of Doric architecture. The assessment is performed within a performance‐based framework using state‐of‐the‐art tools of earthquake engineering. In the first part, the seismic hazard of the site was calculated using the European Seismic Hazard Model and hazard‐consistent records were selected. Then, the Temple was scanned by drone and the point cloud was used to develop the numerical structural model. The Temple was analyzed using the discrete element method. Appropriate engineering demand parameters and limit state thresholds were defined. Fragility curves for the structural elements, namely, columns and architraves, of the Temple were computed via multi‐stripe analysis. Finally, the seismic risk of the Temple was evaluated using long‐term estimates in terms of return periods of exceeding limit states and total loss. The outcomes of the study offer valuable information to engineers, architects, and archaeologists regarding the current status of the monument in terms of identifying its most vulnerable elements and allowing the prioritization of short‐ and long‐term restoration actions.