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- OA-Publikationsfonds2022 (23) (remove)
Paper-based data acquisition and manual transfer between incompatible software or data formats during inspections of bridges, as done currently, are time-consuming, error-prone, cumbersome, and lead to information loss. A fully digitized workflow using open data formats would reduce data loss, efforts, and the costs of future inspections. On the one hand, existing studies proposed methods to automatize data acquisition and visualization for inspections. These studies lack an open standard to make the gathered data available for other processes. On the other hand, several studies discuss data structures for exchanging damage information among different stakeholders. However, those studies do not cover the process of automatic data acquisition and transfer. This study focuses on a framework that incorporates automatic damage data acquisition, transfer, and a damage information model for data exchange. This enables inspectors to use damage data for subsequent analyses and simulations. The proposed framework shows the potentials for a comprehensive damage information model and related (semi-)automatic data acquisition and processing.
Determining the earthquake hazard of any settlement is one of the primary studies for reducing earthquake damage. Therefore, earthquake hazard maps used for this purpose must be renewed over time. Turkey Earthquake Hazard Map has been used instead of Turkey Earthquake Zones Map since 2019. A probabilistic seismic hazard was performed by using these last two maps and different attenuation relationships for Bitlis Province (Eastern Turkey) were located in the Lake Van Basin, which has a high seismic risk. The earthquake parameters were determined by considering all districts and neighborhoods in the province. Probabilistic seismic hazard analyses were carried out for these settlements using seismic sources and four different attenuation relationships. The obtained values are compared with the design spectrum stated in the last two earthquake maps. Significant differences exist between the design spectrum obtained according to the different exceedance probabilities. In this study, adaptive pushover analyses of sample-reinforced concrete buildings were performed using the design ground motion level. Structural analyses were carried out using three different design spectra, as given in the last two seismic design codes and the mean spectrum obtained from attenuation relationships. Different design spectra significantly change the target displacements predicted for the performance levels of the buildings.
For the safe and efficient operation of dams, frequent monitoring and maintenance are required. These are usually expensive, time consuming, and cumbersome. To alleviate these issues, we propose applying a wave-based scheme for the location and quantification of damages in dams.
To obtain high-resolution “interpretable” images of the damaged regions, we drew inspiration from non-linear full-multigrid methods for inverse problems and applied a new cyclic multi-stage full-waveform inversion (FWI) scheme. Our approach is less susceptible to the stability issues faced by the standard FWI scheme when dealing with ill-posed problems. In this paper, we first selected an optimal acquisition setup and then applied synthetic data to demonstrate the capability of our approach in identifying a series of anomalies in dams by a mixture of reflection and transmission tomography. The results had sufficient robustness, showing the prospects of application in the field of non-destructive testing of dams.
The goal of architecture is changing in response to the expanding role of cities, rapid urbanization, and transformation under changing economic, environmental, social, and demographic factors. As cities increased in the early modern era, overcrowding, urbanization, and pollution conditions led reformers to consider the future shape of the cities. One of the most critical topics in contemporary architecture is the subject of the future concepts of living. In most cases, domed cities, as a future concept of living, are rarely considered, and they are used chiefly as “utopian” visions in the discourse of future ways of living. This paper highlights the reviews of domed cities to deepen the understanding of the idea in practice, like its approach in terms of architecture. The main aim of this paper is to provide a broad overview for domed cities in the face of pollution as one of the main concerns in many European cities. As a result, the significance of the reviews of the existing projects is focused on their conceptual quality. This review will pave the way for further studies in terms of future developments in the realm of domed cities. In this paper, the city of Celje, one of the most polluted cities in Slovenia, is taken as a case study for considering the concept of Dome incorporated due to the lack of accessible literature on the topic. This review’s primary contribution is to allow architects to explore a broad spectrum of innovation by comparing today’s achievable statuses against the possibilities generated by domed cities. As a result of this study, the concept of living under the Dome remains to be developed in theory and practice. The current challenging climatic situation will accelerate the evolution of these concepts, resulting in the formation of new typologies, which are a requirement for humanity.
It is widely accepted that most people spend the majority of their lives indoors. Most individuals do not realize that while indoors, roughly half of heat exchange affecting their thermal comfort is in the form of thermal infrared radiation. We show that while researchers have been aware of its thermal comfort significance over the past century, systemic error has crept into the most common evaluation techniques, preventing adequate characterization of the radiant environment. Measuring and characterizing radiant heat transfer is a critical component of both building energy efficiency and occupant thermal comfort and productivity. Globe thermometers are typically used to measure mean radiant temperature (MRT), a commonly used metric for accounting for the radiant effects of an environment at a point in space. In this paper we extend previous field work to a controlled laboratory setting to (1) rigorously demonstrate that existing correction factors used in the American Society of Heating Ventilation and Air-conditioning Engineers (ASHRAE) Standard 55 or ISO7726 for using globe thermometers to quantify MRT are not sufficient; (2) develop a correction to improve the use of globe thermometers to address problems in the current standards; and (3) show that mean radiant temperature measured with ping-pong ball-sized globe thermometers is not reliable due to a stochastic convective bias. We also provide an analysis of the maximum precision of globe sensors themselves, a piece missing from the domain in contemporary literature.
The fracture of microcapsules is an important issue to release the healing agent for healing the cracks in encapsulation-based self-healing concrete. The capsular clustering generated from the concrete mixing process is considered one of the critical factors in the fracture mechanism. Since there is a lack of studies in the literature regarding this issue, the design of self-healing concrete cannot be made without an appropriate modelling strategy. In this paper, the effects of microcapsule size and clustering on the fractured microcapsules are studied computationally. A simple 2D computational modelling approach is developed based on the eXtended Finite Element Method (XFEM) and cohesive surface technique. The proposed model shows that the microcapsule size and clustering have significant roles in governing the load-carrying capacity and the crack propagation pattern and determines whether the microcapsule will be fractured or debonded from the concrete matrix. The higher the microcapsule circumferential contact length, the higher the load-carrying capacity. When it is lower than 25% of the microcapsule circumference, it will result in a greater possibility for the debonding of the microcapsule from the concrete. The greater the core/shell ratio (smaller shell thickness), the greater the likelihood of microcapsules being fractured.
One of the most important renewable energy technologies used nowadays are wind power turbines. In this paper, we are interested in identifying the operating status of wind turbines, especially rotor blades, by means of multiphysical models. It is a state-of-the-art technology to test mechanical structures with ultrasonic-based methods. However, due to the density and the required high resolution, the testing is performed with high-frequency waves, which cannot penetrate the structure in depth. Therefore, there is a need to adopt techniques in the fields of multiphysical model-based inversion schemes or data-driven structural health monitoring. Before investing effort in the development of such approaches, further insights and approaches are necessary to make the techniques applicable to structures such as wind power plants (blades). Among the expected developments, further accelerations of the so-called “forward codes” for a more efficient implementation of the wave equation could be envisaged. Here, we employ electromagnetic waves for the early detection of cracks. Because in many practical situations, it is not possible to apply techniques from tomography (characterized by multiple sources and sensor pairs), we focus here on the question of whether the existence of cracks can be determined by using only one source for the sent waves.
Design-related reassessment of structures integrating Bayesian updating of model safety factors
(2022)
In the semi-probabilistic approach of structural design, the partial safety factors are defined by considering some degree of uncertainties to actions and resistance, associated with the parameters’ stochastic nature. However, uncertainties for individual structures can be better examined by incorporating measurement data provided by sensors from an installed health monitoring scheme. In this context, the current study proposes an approach to revise the partial safety factor for existing structures on the action side, γE by integrating Bayesian model updating. A simple numerical example of a beam-like structure with artificially generated measurement data is used such that the influence of different sensor setups and data uncertainties on revising the safety factors can be investigated. It is revealed that the health monitoring system can reassess the current capacity reserve of the structure by updating the design safety factors, resulting in a better life cycle assessment of structures. The outcome is furthermore verified by analysing a real life small railway steel bridge ensuring the applicability of the proposed method to practical applications.
This dataset consists mainly of two subsets. The first subset includes measurements and simulation data conducted to validate the simulation tool ENVI-met. The measurements were conducted at the campus of the Bauhaus-University Weimar in Weimar, Germany and consisted of recording exterior air temperature, globe temperature, relative humidity, and wind velocity at 1.5 m at four points on four different days. After the measurements, the geometry of the campus was modelled and meshed; the simulations were conducted using the weather data of the measurements days with the aim of investigating the accuracy of the model.
The second data subset consists of ENVI-met simulation data of the potential of facade greening in improving the outdoor environment and the indoor air temperature during heatwaves in Central European cities. The data consist of the boundary conditions and the simulation output of two simulation models: with and without facade greening. The geometry of the models corresponded to a residential buildings district in Stuttgart, Germany. The simulation output consisted of exterior air temperature, mean radiant temperature, relative humidity, and wind velocity at 12 different probe points in the model in addition to the indoor air temperature of an exemplary building. The dataset presents both vertical profiles of the probed parameters as well as the time series output of the five-day simulation duration. Both data subsets correspond to the investigations presented in the co-submitted article [1].
The seismic vulnerability assessment of existing reinforced concrete (RC) buildings is a significant source of disaster mitigation plans and rescue services. Different countries evolved various Rapid Visual Screening (RVS) techniques and methodologies to deal with the devastating consequences of earthquakes on the structural characteristics of buildings and human casualties. Artificial intelligence (AI) methods, such as machine learning (ML) algorithm-based methods, are increasingly used in various scientific and technical applications. The investigation toward using these techniques in civil engineering applications has shown encouraging results and reduced human intervention, including uncertainties and biased judgment. In this study, several known non-parametric algorithms are investigated toward RVS using a dataset employing different earthquakes. Moreover, the methodology encourages the possibility of examining the buildings’ vulnerability based on the factors related to the buildings’ importance and exposure. In addition, a web-based application built on Django is introduced. The interface is designed with the idea to ease the seismic vulnerability investigation in real-time. The concept was validated using two case studies, and the achieved results showed the proposed approach’s potential efficiency