During the operation phase, energy conservation of buildings gets much attention. controlling methods are often based on physical parameters, ignoring the specific needs of different groups of people for the environme...
During the operation phase, energy conservation of buildings gets much attention. controlling methods are often based on physical parameters, ignoring the specific needs of different groups of people for the environment. To evaluate the current status, the questionnaire is used to investigate the relationship between personnel comfortability and various factors. This article aims to introduce the method of personnel portraits, balance the personality and common conflicts of the crowd, and solve the control problem of comfort that varies from person to person. Finally, combined with the analysis of the results of the questionnaire, a multi-faceted study of personnel satisfaction was provided to provide a reference for methods that can achieve energy-saving and satisfaction control at the same time.
In view of the inaccuracy of the existing cellular automata (CA) technique in predicting failure patterns of masonry wall panels, this paper proposed a refined CA method which contains two measures to promote the prec...
In view of the inaccuracy of the existing cellular automata (CA) technique in predicting failure patterns of masonry wall panels, this paper proposed a refined CA method which contains two measures to promote the precision of results. The optimization of matching criterion based on Taylor expansion updates the definition of state values for the CA model of wall panels and improves the accuracy of predicting the failure patterns of wall panels with opening. Besides, the post-processing of noise reduction explains the discontinuity of cracks in wall panels from the perspective of noise based on two proposed theorems, which improves the prediction of the failure patterns in appearance, continuity and clarity of cracks. Meanwhile, the difference functions and similarity of wall panels are introduced to evaluate the predicting results. Moreover, the combination of two measures shows the brilliant capacity in enhancing the accuracy and efficiency of prediction.
It has become a mainstream to use physical models to quantify expected energy savings from alternative retrofit methods and technologies. However, they are not suitable for predicting energy use of buildings when deta...
It has become a mainstream to use physical models to quantify expected energy savings from alternative retrofit methods and technologies. However, they are not suitable for predicting energy use of buildings when detailed and specified input parameters are unavailable. The overall purpose of the research is to support the stakeholders in taking decisions on refurbishments options when not all of physical information is available, in order to achieve the Swedish Energy Agency's measurements of near-zero energy buildings. The research will transfer big data from Swedish Energy Performance Certificates for building retrofitting. A Support Vector Machines and Fuzzy C-means clustering (SVM-FCM) integrated machine learning algorithm is used directly to extract the case-specific knowledge from EPC big data regarding building characteristics and energy saving of retrofit measures. It enables to prioritize retrofit measures and compute their expected energy savings for buildings. This proposed data driven method is an attempt of taking advantage of big data for practical building retrofit selection.
Recently, there are many papers report the development of some new buckling-restrained braced (BRB) frames and the evaluation of its characteristics. At the same time self-centering buckling-restrained braced (SCBRB) ...
Recently, there are many papers report the development of some new buckling-restrained braced (BRB) frames and the evaluation of its characteristics. At the same time self-centering buckling-restrained braced (SCBRB) frames are considered as new solutions for the increasing of the structural resilience. In this thesis, the seismic performance of structures is analyzed subjected to earthquake main shock-aftershock sequences. There is comparison of two types of the additional BRB elements, and also there is comparison between them and original steel frame to show the effect of using BRB and SCBRB elements. To compare the seismic performance of BRBF and SCBRBF, the same main shock-aftershock sequences were used in this part. Because of the flag-shaped hysteretic curve of the SCBRB elements, big amount of the energy was dissipated during the motion. Compared to steel frame, smaller seismic responses and residual deformation occurred the structure. BRBF and SCBRBF can control the seismic responses effectively due to the energy dissipation of BRB, and SCBRB can also reduce the structural residual deformation. The earthquake aftershock after earthquake main shock can increase the structural damage and enlarge the structural seismic responses.
Modeling and control are primary domains in bridge wind engineering. The natural wind field characteristics (e.g., non-stationary, non-uniform, spatial-temporal changing characteristics) and the wind-bridge interactio...
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Modeling and control are primary domains in bridge wind engineering. The natural wind field characteristics (e.g., non-stationary, non-uniform, spatial-temporal changing characteristics) and the wind-bridge interaction processes are physically complex and exhibit strong nonlinearity. The lack of analyzing these complex physical processes based on first principles makes it difficult for traditional modeling and control methods to accurately characterize or control wind field and wind-induced vibration of bridges. Data-driven automatic modeling and control is a new expansion direction in bridge wind engineering due to the extensive valuable historical data available and the complex, high-dimensional character of the state space and action space of the agent in active control. Machine Learning (ML) has been shown versatile for various modeling and control tasks in bridge wind engineering due to its excellent ability to automatically extract space features efficiently and make wonderful decisions facing complicated tasks without manual interval. Starting from an overview of the basic concepts and methods of ML, this review will comprehensively analyze and summarize the application of ML methods in various aspects of bridge wind engineering, including wind fields, static aerodynamic reconstruction, wind-induced vibrations and control based on reinforcement learning, in order to enable readers to have a full knowledge of the potential of ML in various subfields. The essence of these tasks is to rely on data-driven minds to solve tricky problems that cannot be solved based on first principles. ML will continue to integrate and coexist with wind engineering of bridges and generate new revolutions in both theories and applications owing to its powerful information-processing and modeling-learning ability.
During the long service period of the transmission tower, the severe environment, material aging and fatigue effects result in the damage accumulation and resistance fading of the transmission tower, which even lead t...
During the long service period of the transmission tower, the severe environment, material aging and fatigue effects result in the damage accumulation and resistance fading of the transmission tower, which even lead to the structural failure. In this paper, a stochastic subspace-based damage detection algorithm combined with statistical model is proposed for the damage identification of transmission tower structures through processing and analysing its vibration signals. Based on the structural modal parameters identified from the structural vibration response, the nominal modal parameters are defined. Considering that the Hankel matrixes constructed by the system observability matrix and the system output covariance matrix have the same kernel space, the damage index sensitive to the modal parameters is constructed. In the manuscript, firstly, the damage index establishment method and process of the algorithm are presented; and then the vibration data of transmission tower structure simulation under different damage conditions are obtained through numerical simulations; finally, above data are analysed to obtain the damage identification results of transmission tower. The results show that the method proposed in this work can effectively identify the local damage of transmission tower structure.
Carbonation may potentially lead to corrosion of steel bars in reinforced concrete. This concern presents a major barrier against the implementation of sustainable low-clinker cementitious materials in the design of r...
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Carbonation may potentially lead to corrosion of steel bars in reinforced concrete. This concern presents a major barrier against the implementation of sustainable low-clinker cementitious materials in the design of reinforced concrete structures. Various studies have documented the relationship between different equilibrium moisture states in carbonated concrete and the corrosion rate of the embedded steel. However, limited attempts were focused on visually observing the dynamic (time-dependent) behavior of moisture penetration into concrete and the related corrosion state and rate. Moreover, there is a lack of data on the local moisture state in the cementitious matrix in the steel-concrete interfacial zone. In this study, liquid water uptake in carbonated mortar was in-situ and over time monitored by neutron imaging. The corrosion state of embedded steel was monitored by means of electrochemical measurements. This combined experiment revealed that the arrival of the waterfront at the steel surface led to a sharp decrease of the steel potential. The corrosion rate increased from negligibly low values (<1 µm/year) to about 31 µm/year within a couple of minutes. Based on the neutron images, it is concluded that the moisture ingress through the concrete cover is locally affected by the heterogeneity of projected (depth-averaged) porosity distribution, and that large obstacles such as entrapped air have an effect. These observations were further confirmed by numerical simulation results of water transport, which also showed that liquid water permeability of the studied carbonated mortar determined by the inverse analysis is much higher than reported values in the literature. Overall, this study highlights the importance of considering the dynamic and coupled corrosion and moisture transport behavior during the periods which active corrosion can occur in carbonated concrete exposed to cyclic wetting/drying conditions.
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