Controllable thermal rectification design for buildings based on phase change composites

Phase-change material(PCM)is widely used in thermal management due to their unique thermal behavior.However,related research in thermal rectifier is mainly focused on exploring the principles at the fundamental device level,which results in a gap to real applications.Here,we propose a controllable thermal rectification design towards building applications through the direct adhesion of composite thermal rectification material(TRM)based on PCM and reduced graphene oxide(rGO)aerogel to ordinary concrete walls(CWs).The design is evaluated in detail by combining experiments and finite element analysis.It is found that,TRM can regulate the temperature difference on both sides of the TRM/CWs system by thermal rectification.The difference in two directions reaches to 13.8 K at the heat flow of 80 W/m^(2).In addition,the larger the change of thermal conductivity before and after phase change of TRM is,the more effective it is for regulating temperature difference in two directions.The stated technology has a wide range of applications for the thermal energy control in buildings with specific temperature requirements.

A Stroke-Limitation AMD Control System with Variable Gain and Limited Area for High-Rise Buildings

Collisions between a moving mass and an anti-collision device increase structural responses and threaten structural safety.An active mass damper(AMD)with stroke limitations is often used to avoid collisions.However,a strokelimited AMD control system with a fixed limited area shortens the available AMD stroke and leads to significant control power.To solve this problem,the design approach with variable gain and limited area(VGLA)is proposed in this study.First,the boundary of variable-limited areas is calculated based on the real-time status of the moving mass.The variable gain(VG)expression at the variable limited area is deduced by considering the saturation of AMD stroke.Then,numerical simulations of a stroke-limited AMD control system with VGLA are conducted on a high-rise building structure.These numerical simulations show that the proposed approach has superior strokelimitation performance compared with a stroke-limited AMD control system with a fixed limited area.Finally,the proposed approach is validated through experiments on a four-story steel frame.

A novel control strategy for reproducing the floor motions of high-rise buildings by earthquake-simulating shake tables

To enable the experimental assessment of the seismic performance of full-scale nonstructural elements with multiple engineering parameters(EDPs),a three-layer testbed named Nonstructural Element Simulator on Shake Table(NEST)has been developed.The testbed consists of three consecutive floors of steel structure.The bottom two floors provide a space to accommodate a full-scale room.To fully explore the flexibility of NEST,we propose a novel control strategy to generate the required shake table input time histories for the testbed to track the target floor motions of the buildings of interest with high accuracy.The control strategy contains two parts:an inverse dynamic compensation via simulation of feedback control systems(IDCS)algorithm and an offline iteration procedure based on a refined nonlinear numerical model of the testbed.The key aspects of the control strategy were introduced in this paper.Experimental tests were conducted to simulate the seismic responses of a full-scale office room on the 21^(st)floor of a 42-story high-rise building.The test results show that the proposed control strategy can reproduce the target floor motions of the building of interest with less than 20%errors within the specified frequency range.

Low-Cost Insulation for Energy Efficient Buildings in Terai Region of Nepal

There is a huge amount of energy savings potential in public building sector that has yet to be realized.By prioritizing energy efficiency in its own buildings and thus promoting the development of required knowledge in terms of new technology and construction methods,the public sector will lead the way in efforts to increase the rate of renovations.The low-cost insulation strategies and a comparison of cost with existing insulation materials has been described in this study.We have repeatedly faced energy crises and will continue to do so in the future if appropriate action is not taken in a timely manner.Properly implementing energy-saving initiatives in for achieving thermal comfort in buildings as well as reducing the energy costs would undoubtedly inspire the residential sector,resulting in significant reductions in energy usage.Simulations were carried out to study insulation layers on various building components like exterior walls,floor and roofs,generating different scenarios for a building as a base model,which were then compared and analysed to verify the literature used to develop the cases.The proposed recommendations,which have been validated,are certain to increase building energy efficiency,achieve thermal comfort in low cost than what is currently being used.

The Effect of Core Eccentricity on the Structural Behavior of Concrete Tall Buildings

The main purpose of this paper is to investigate the effect of core eccentricity on the structural behavior of concrete tall buildings.Concrete buildings of 55 floors with plan dimensions 48.0×48.0 m2 were investigated.Three cases of main core locations are studied:centric(A),eccentric by one sixth(B)and one third(C)of building width.The three-dimensional finite element method has been used in conducting structural analysis through ETABS software.Gravity and lateral(wind and seismic)loadings are applied to all building cases.It has been concluded that the core location is the prime parameter governing the structural behavior of tall buildings.Although the first two cases(A,B)have acceptable and similar structural behaviors conforming to code limits,in the third case(C),the building behavior came beyond code limits.The author introduced remedial action by adding two secondary cores in the opposite direction of the main core(C-R)to restore the building behavior to the code limits.The results of this action were satisfactory.

Post-war Sustainability-Driven School Buildings: A Review of the Literature

The Safe Schools Declaration of 2015 is an inter-governmental political agreement signed by several countries designed to protect the schooling of the school-aged population during armed conflicts.Yet,in countries where civil war erupted,schools were demolished.Several school-aged children were either forcibly recruited by governments or coerced by rebel groups to serve in armed fights.As a result,several children were deprived of their education and have remained suffering from deep psychological scars.The central question of the study is:What kind of sustainability-driven school buildings can be initiated in countries that are now enduring peace so that the learning environments are more comfortable and improve the well-being of the war-impacted children and school employees?After reviewing the literature,a strategic conceptual framework that incorporated the synergistic relationship between economic,social,and environmental aspects of sustainability was initiated to map out sustainable school buildings.In short,the conceptual framework proposed to construct school buildings in some of the war-affected developing countries includes assembling cost-efficiency and eco-effectiveness inputs,using renewable energy sources powered by natural sunlight,collecting rainwater in mud cisterns,reducing emissions of carbon oxides,and empowering the local community to be the main actors to design sustainable buildings during the preconstruction,construction,and post-construction stages to serve as learning spaces for the war-affected occupants and their neighborhoods.

Research and Application of Deep Learning Technology in Prefabricated Buildings

Prefabricated buildings have become an important development trend in the field of modern architecture because of their high efficiency and environmental friendliness. Artificial intelligence and deep learning technology have been increasingly applied in prefabricated buildings. Deep learning technology provides comprehensive optimization of building design, construction, quality control, and cost and schedule management through the learning and analysis of large amounts of data. This paper aims to explore the application of deep learning technology in prefabricated buildings, analyze the revolutionary changes it brings in different stages, and discuss the problems faced when implementing this technology.

Research and Application of Recycled Concrete Technology in Prefabricated Buildings

The utilization of waste concrete as a raw material for recycled concrete in the domain of prefabricated components is garnering greater interest.This paper delineates and examines the concept,categorization,methodologies of preparation,applicable sectors,and evaluative metrics of recycled concrete technology,highlighting its prospective benefits.Nonetheless,for the successful integration of recycled concrete technology into prefabricated component applications,it is imperative to systematically enhance its physical,mechanical,and attributes,as well as its environmental efficacy.Moreover,to foster the continued advancement of recycled concrete technology,innovative initiatives,standardization,educational programs,demonstration projects,and collaborative efforts are crucial to promote broader adoption and realize improved outcomes within the realm of prefabricated components.In conclusion,recycled concrete technology is poised to play a pivotal role in prefabricated construction,offering robust support for propelling the construction industry towards a sustainable future.

Weathering Characterization and Degradation Analysis of Landscape Wooden Buildings in Semi-Arid and Sandy Area

Wooden buildings play a very important role in China’s construction and landscape architecture industry.In order to explore the weathering characteristics of the surface layer of landscape wooden buildings,the main causes of weathering were analyzed on the basis of summarizing the common types of weathering characterization.The results showed that the weathering characterization was mainly reflected in the surface defects of wood structures,such as cracking,discoloration,peeling,wind erosion wear,and so on.The coating technology on the surface of constructions was the main artificial factor affecting the surface defects of constructions.In the case of similar surface decoration conditions,sunlight and moisture were the main natural factors affecting the weathering of wooden buildings,which will promote the process of weathering.

A Review of Innovative Design Strategies for Prefabricated Green Buildings

Prefabricated green buildings are becoming a trend in the construction industry of China.The prefabricated components are made using modern technologies like green materials,artificial intelligence,and low-carbon and energy-saving techniques.This makes them an important aspect of the development of the construction industry in China,representing modernization and sustainable development.This article presents a study on the innovative design of prefabricated green buildings.This article serves to promote sustainable development on a macro level.

Investigation the Correlation between Thermal Bridging and Geometries in Concrete Buildings

This article focuses on the investigation of the correlation between thermal bridging and various geometric configurations. The article employs QuickField software for conducting three-dimensional steady-state heat transfer simulations to investigate the thermal behaviors of diverse geometric shapes. Significantly, this study involves the simulation of four distinct geometries including concrete circular, square, rectangular, and triangular column through an insulated concrete layer while all geometries maintain the consistent surface areas. The simulations yield findings indicating that circular thermal bridging has the best thermal performance, while rectangular thermal bridging displays comparatively the lowest thermal efficiency. Furthermore, the results indicate that alterations in the perimeter of thermal bridge interfaces, while maintaining a constant area, exert a more pronounced influence on the thermal performance of the geometries compared to proportional changes in area while preserving the perimeter. The study’s findings aid building designers and architects in creating more energy-efficient structural and architectural elements by incorporating thermally efficient geometries and forms. .

Plus Energy Buildings:A Numerical Case Study

The feasibility of Plus Energy Building for a sample relevant case is investigated.After a literature review aimed to identify key aspects of this type of buildings,a preliminary evaluation of the thermal performance of a building constructed using conventional material is presented together with a parametric analysis of the impact of typical influential parameters.Solar domestic hot water(SDHW)and photovoltaic systems(PV)are considered in the study.Numerical simulations indicate that for the examined sample case(Beirut in Lebanon)the total annual energy need of conventional building is 87.1 kWh/y.m^(2).About 49%of energy savings can be achieved by improving the building envelope and installing energy efficient technologies.Moreover,about 90%of energy savings in domestic hot water production can be achieved by installing a SDHW system composed of two solar collectors connected in series.Finally,the addition of a grid connected PV array system can significantly mitigate the energy needs of the building leading to an annual excess of energy.

Performance of RC buildings after Kahramanmaraş Earthquakes: lessons toward performance based design

Two simultaneous earthquakes occurred in the Kahramanmaraş-Pazarcık and Kahramanmaraş-Elbistan districts of Turkey on February 6,2023,and with magnitudes of 7.7 and 7.6,respectively.These events caused the highest estimated loss recorded in Turkey within the last century from natural disasters.The key reason for the extensive loss was the proximity of eleven cities to the earthquake epicenters.Middle East Technical University teams investigated the building sites in Gaziantep,Kahramanmaras,Hatay,Adiyaman and Adana.The ground motion recordings revealed that in certain locations of Gaziantep,Kahramanmaraşand Hatay,the ground motion levels exceeded the maximum credible earthquake level defined for a return period of 2,475 years in the Turkish Earthquake Code.Residential building performance was investigated with respect to the construction year,which is a good indicator of compliance with modern seismic codes and inspection procedures.About 97%of the collapsed buildings were constructed prior to 2000,whereas over 5,000 buildings,which were built after 2000,collapsed or required urgent demolition.Most of the buildings with minor or greater structural damage sustained heavy infill wall damage rendering occupancy impossible.Aside from damage in older construction with significant structural deficiencies,the damage in some of the more recent and better constructed buildings was observed to be surprisingly poor.This can be attributed to the level of ground motion,significant ductility demands,poor material and workmanship and damage to non-structural elements.With the estimated total loss of above 100 billion dollars and over 50,000 casualties,the current seismic design criterion based on ductility and acceptance of structural damage should be re-evaluated to ensure a more resilient urban environment in high seismic regions.

Towards rapid and automated vulnerability classification of concrete buildings

With the overwhelming number of older reinforced concrete buildings that need to be assessed for seismic vulnerability in a city,local governments face the question of how to assess their building inventory.By leveraging engineering drawings that are stored in a digital format,a well-established method for classification reinforced concrete buildings with respect to seismic vulnerability,and machine learning techniques,we have developed a technique to automatically extract quantitative information from the drawings to classify vulnerability.Using this technique,stakeholders will be able to rapidly classify buildings according to their seismic vulnerability and have access to information they need to prioritize a large building inventory.The approach has the potential to have significant impact on our ability to rapidly make decisions related to retrofit and improvements in our communities.In the Los Angeles County alone it is estimated that several thousand buildings of this type exist.The Hassan index is adopted here as the method for automation due to its simple application during the classification of the vulnerable reinforced concrete buildings.This paper will present the technique used for automating information extraction to compute the Hassan index for a large building inventory.

Analysis of the Performances of a New Type of Alumina Nanocomposite Structural Material Designed for the Thermal Insulation of High-Rise Buildings

The sol-gel method is used to prepare a new nano-alumina aerogel structure and the thermal properties of this nanomaterial are investigated comprehensively using electron microscope scanning,thermal analysis,X-ray and infrared spectrometer analysis methods.It is found that the composite aerogel alumina material has a multi-level porous nano-network structure.When employed for the thermal insulation of high-rise buildings,the alumina nanocomposite aerogel material can lead to effective energy savings in winter.However,it has almost no energy-saving effect on buildings where energy is consumed for cooling in summer.

Analysis of Remotely Sensed Imagery and Architecture Environment for Modelling 3D Detailed Buildings Using Geospatial Techniques

The use of three-dimensional maps is more effective than two-dimensional maps in representing the Earth’s surface. However, the traditional methods used to create digital surface models are not efficient for capturing the details of Earth’s features. This is because they represent only three-dimensional objects in a single texture and do not provide a realistic representation of the real world. Additionally, there is a growing demand for up-to-date and accurate geo-information, particularly in urban areas. To address this challenge, a new technique is proposed in this study that involves integrating remote sensing, Geographic Information System, and Architecture Environment software to generate a highly-detailed three-dimensional model. The method described in this study includes several steps such as acquiring high-resolution satellite imagery, gathering ground truth data, performing radiometric and geometric corrections during image preprocessing, producing a 2D map of the region of interest, constructing a digital surface model by extending the building outlines, and transforming the model into multi-patch layers to create a 3D model for each object individually. The research findings indicate that the digital surface model obtained with comprehensive information is suitable for different purposes, such as environmental research, urban development and expansion planning, and shape recognition tasks.

Integrating Highly Spatial Satellite Image for 3D Buildings Modelling Using Geospatial Algorithms and Architecture Environment

The growing demand for current and precise geographic information that pertains to urban areas has given rise to a significant interest in digital surface models that exhibit a high level of detail. Traditional methods for creating digital surface models are insufficient to reflect the details of earth’s features. These models only represent three-dimensional objects in a single texture and fail to offer a realistic depiction of the real world. Furthermore, the need for current and precise geographic information regarding urban areas has been increasing significantly. This study proposes a new technique to address this problem, which involves integrating remote sensing, Geographic Information Systems (GIS), and Architecture Environment software environments to generate a detailed three-dimensional model. The processing of this study starts with: 1) Downloading high-resolution satellite imagery; 2) Collecting ground truth datasets from fieldwork; 3) Imaging nose removing; 4) Generating a Two-dimensional Model to create a digital surface model in GIS using the extracted building outlines; 5) Converting the model into multi-patch layers to construct a 3D model for each object separately. The results show that the 3D model obtained through this method is highly detailed and effective for various applications, including environmental studies, urban development, expansion planning, and shape understanding tasks.

Intelligent Risk-Identification Algorithm with Vision and 3D LiDAR Patterns at Damaged Buildings

Existingfirefighting robots are focused on simple storage orfire sup-pression outside buildings rather than detection or recognition.Utilizing a large number of robots using expensive equipment is challenging.This study aims to increase the efficiency of search and rescue operations and the safety offirefigh-ters by detecting and identifying the disaster site by recognizing collapsed areas,obstacles,and rescuers on-site.A fusion algorithm combining a camera and three-dimension light detection and ranging(3D LiDAR)is proposed to detect and loca-lize the interiors of disaster sites.The algorithm detects obstacles by analyzingfloor segmentation and edge patterns using a mask regional convolutional neural network(mask R-CNN)features model based on the visual data collected from a parallelly connected camera and 3D LiDAR.People as objects are detected using you only look once version 4(YOLOv4)in the image data to localize persons requiring rescue.The point cloud data based on 3D LiDAR cluster the objects using the density-based spatial clustering of applications with noise(DBSCAN)clustering algorithm and estimate the distance to the actual object using the center point of the clustering result.The proposed artificial intelligence(AI)algorithm was verified based on individual sensors using a sensor-mounted robot in an actual building to detectfloor surfaces,atypical obstacles,and persons requiring rescue.Accordingly,the fused AI algorithm was comparatively verified.

Correg-Yolov3:a Method for Dense Buildings Detection in High-resolution Remote Sensing Images

The exploration of building detection plays an important role in urban planning,smart city and military.Aiming at the problem of high overlapping ratio of detection frames for dense building detection in high resolution remote sensing images,we present an effective YOLOv3 framework,corner regression-based YOLOv3(Correg-YOLOv3),to localize dense building accurately.This improved YOLOv3 algorithm establishes a vertex regression mechanism and an additional loss item about building vertex offsets relative to the center point of bounding box.By extending output dimensions,the trained model is able to output the rectangular bounding boxes and the building vertices meanwhile.Finally,we evaluate the performance of the Correg-YOLOv3 on our self-produced data set and provide a comparative analysis qualitatively and quantitatively.The experimental results achieve high performance in precision(96.45%),recall rate(95.75%),F1 score(96.10%)and average precision(98.05%),which were 2.73%,5.4%,4.1%and 4.73%higher than that of YOLOv3.Therefore,our proposed algorithm effectively tackles the problem of dense building detection in high resolution images.

Determination of Effectiveness of Energy Management System in Buildings

Building Energy Management Systems(BEMS)are computer-based systems that aid in managing,controlling,and monitoring the building technical services and energy consumption by equipment used in the building.The effectiveness of BEMS is dependent upon numerous factors,among which the operational characteristics of the building and the BEMS control parameters also play an essential role.This research develops a user-driven simulation tool where users can input the building parameters and BEMS controls to determine the effectiveness of their BEMS.The simulation tool gives the user the flexibility to understand the potential energy savings by employing specific BEMS control and help in making intelligent decisions.The simulation is developed using Visual Basic Application(VBA)in Microsoft Excel,based on discrete-event Monte Carlo Simulation(MCS).The simulation works by initially calculating the energy required for space cooling and heating based on current building parameters input by the user in the model.Further,during the second simulation,the user selects all the BEMS controls and improved building envelope to determine the energy required for space cooling and heating during that case.The model compares the energy consumption from the first simulation and the second simulation.Then the simulation model will provide the rating of the effectiveness of BEMS on a continuous scale of 1 to 5(1 being poor effectiveness and 5 being excellent effectiveness of BEMS).This work is intended to facilitate building owner/energy managers to analyze the building energy performance concerning the efficacy of their energy management system.