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Heat gain in buildings occurs due to heat transfer through the building fabric or envelope, especially the walls and roof. The purpose of this paper is to identify and recommend the suitable wall materials for better thermal performance in buildings in warm and hot climatic zones of India. As India lies between the tropic of cancer and the equator, the solar radiation from the sun falls more on the walls than the roofs of the buildings. Thus, it is imperative to protect the walls from heat gain to promote thermal comfort in naturally ventilated buildings and reduce the energy loads due to artificial cooling systems in air-conditioned buildings.

In this paper, an investigation of heat flow characteristics in steady-state and the transient state for five different uninsulated wall structures using computational fluid dynamics (CFD) software has been carried out. The climate conditions at Madurai, India have been considered for this study.

The findings of the study revealed that aerated autoclaved concrete (AAC) and hollow clay blocks (HCB) for external walls in naturally ventilated buildings in warm climatic regions could improve the building’s thermal performance index and reduce peak indoor operative temperature by about 6°C–7°C. The results of steady-state and transient state analysis were found to be in good agreement with the results of the reviewed literature.

Over the past few decades, only very few architects and builders have been successful in influencing their clients to accept alternate materials such as AAC blocks, HCB, stabilized earth blocks, adobe blocks, fly-ash bricks as an alternate to conventional bricks in an attempt of highlighting their benefits, such as; materials that are easily available, more energy-efficient, can withstand the extreme weather conditions, promote thermal comfort and cost-effective. This paper provides strong evidence that AAC and HCB blocks are the most appropriate materials for improving the thermal performance of envelope walls in regions where the outdoor temperatures are above 40°C.

This paper has made an attempt to identify the appropriate wall materials for effective thermal performance in warm and hot climates. A comparative analysis between five different wall types under the existing solar conditions has been analyzed using CFD simulation study in steady-state and transient conditions under summer conditions and the appropriate wall materials have been suggested. There has been no attempt carried out so far to analyze the thermal performance of different walls using 24 h transient approach in CFD.

To present a new constitutive model for capturing inelastic behavior of brittle materials.

The multi‐surface plasticity theory is employed to describe the damage‐induced mechanisms. An original feature in that respect concerns the multi‐surface criterion which limits the principle values of elastic strains, which is equivalent to Saint‐Venant plasticity model. The latter allows to represent the damage both in tension and in compression.

Provides a quite realistic description of cracking phenomena in brittle materials, with a very few parameters, leading to a very useful tool for analyzing practical engineering problems.

The model is recast in terms of stress resultants and employed within a flat shell elements in order to provide a very efficient tool for analysis of cellular structures. Moreover, a detailed description of the numerical implementation is given.

This paper aims to propose a new deep learning technique to detect the type of material to improve automated construction quality monitoring.

A new data augmentation approach that has improved the model robustness against different illumination conditions and overfitting is proposed. This study uses data augmentation at test time and adds outlier samples to training set to prevent over-fitted network training. For data augmentation at test time, five segments are extracted from each sample image and fed to the network. For these images, the network outputting average values is used as the final prediction. Then, the proposed approach is evaluated on multiple deep networks used as material classifiers. The fully connected layers are removed from the end of the networks, and only convolutional layers are retained.

The proposed method is evaluated on recognizing 11 types of building materials which include 1,231 images taken from several construction sites. Each image resolution is 4,000 × 3,000. The images are captured with different illumination and camera positions. Different illumination conditions lead to trained networks that are more robust against various environmental conditions. Using VGG16 model, an accuracy of 97.35% is achieved outperforming existing approaches.

It is believed that the proposed method presents a new and robust tool for detecting and classifying different material types. The automated detection of material will aid to monitor the quality and see whether the right type of material has been used in the project based on contract specifications. In addition, the proposed model can be used as a guideline for performing quality control (QC) in construction projects based on project quality plan. It can also be used as an input for automated progress monitoring because the material type detection will provide a critical input for object detection.

Several studies have been conducted to perform quality management, but there are some issues that need to be addressed. In most previous studies, a very limited number of material types were examined. In addition, although some studies have reported high accuracy to detect material types (Bunrit et al., 2020), their accuracy is dramatically reduced when they are used to detect materials with similar texture and color. In this research, the authors propose a new method to solve the mentioned shortcomings.

The purpose of this paper is to study the partitioned solution procedure for thermomechanical coupling, where each sub‐problem is solved by a separate time integration scheme.

In particular, the solution which guarantees that the coupling condition will preserve the stability of computations for the coupled problem is studied. The consideration is further generalized for the case where each sub‐problem will possess its particular time scale which requires different time step to be selected for each sub‐problem.

Several numerical simulations are presented to illustrate very satisfying performance of the proposed solution procedure and confirm the theoretical speed‐up of computations which follow from the adequate choice of the time step for each sub‐problem.

The paper confirms that one can make the most appropriate selection of the time step and carry out the separate computations for each sub‐problem, and then enforce the coupling which will preserve the stability of computations with such an operator split procedure.

The purpose of this study is to quantify the energy heating performance of apartment buildings in Kosovo built after 2003 and compare it against the energy heating performance of buildings in member states of EU and selected European countries.

This paper takes a case study approach focussed on the assessment of the heating energy performance of the building. This approach facilitated a detailed calculation of the selected materials’ energy performance used in a representative building structure in Kosovo comparing with passive buildings standard and energy heating performance of buildings in member states of EU and selected European countries.

Results of quantitative research find that the energy heating performance of apartment buildings in Kosovo built after 2003 is far higher than that of passive buildings standard and is better than the average annual energy heating performance of apartment buildings in member states of the EU and selected European countries.

The research provides new knowledge regarding energy heating performance in new residential buildings in Kosovo and compares the findings with earlier research and energy consumption in other selected European countries. The research provides great benefits for researchers and practitioners working in the field of energy management as it compares the energy performance of residential buildings across Europe.

This paper provides a perspective on investigating the energy performance of a building structure of a residential apartment building in Prishtina, Kosovo. By unveiling the level of energy consumption of a residential apartment building in Kosovo representative of the new construction period can help the facility managers to acknowledge the standards they must achieve to refurbish the old building stock to achieve at least the same standard as the buildings in the new construction period.

The purpose of this paper is to quantify the carbon emissions emitted by two different typical apartment units representative of two different construction periods in Kosovo due to main construction materials as a consequence of embodied energy.

The present study uses a three-step (bottom-up) process-based life cycle analysis of the construction material set for two different apartment units. The current study uses material analysis. Embodied CO₂ is estimated by multiplying material masses with the corresponding ECO₂ coefficients (kg CO₂/kg). Due to the lack of a comprehensive Kosovo database, data from an international database are utilized. The results provide practical baseline indicators for the contribution of each material in terms of mass and embodied CO₂.

Results of quantitative research find that apartment unit representative of the old communist-era construction produces 50 percent more embodied CO₂ emissions than an apartment unit that is representative of modern construction in Kosovo. The study finds that this difference comes mainly because of the utilization of larger quantities of steel, concrete, and precast fabricated concrete in the apartment unit that is representative of the old communist era.

The calculation of embodied CO₂ emissions for major construction materials in typical apartments in Kosovo can help in the development of national databases in the future. The availability of such databases could help the construction industry in Kosovo to open up to new sustainable design approaches since such databases and evaluations performed in the national context in Kosovo could help the builders in selecting, assessing and using environmentally friendly materials during the design or refurbishment stage of a building.

This paper is the first investigation of the embodied carbon emission in two different typical apartment building structures in Kosovo.

The purpose of this paper is to present information on the construction technology used to build Dublin City Council’s (DCC’s) housing stock, with an emphasis on wall construction.

The methodology applied was a mix of literature review and archival research. The research was undertaken as part of PhD research exploring the energy upgrade of a housing stock.

The research uncovered details of the construction technology used in the construction of DCC’s housing stock, especially wall construction. These details disprove perceptions and assumptions made on the evolution of construction technology in Dublin and Ireland.

The research is limited in that it primarily focused on the period between 1887 to the introduction of the 1991 Building Regulations. Further research is required on both DCC’s housing stock and the Irish housing stock to identify the specific changes in construction technology.

It is hoped this research will be a foundation for further research on the evolution of house construction technology, and housing stock asset intelligence in Ireland.

This research provides information for researchers and professionals with an interest in the evolution of Irish house construction technology. This is an area which has not received significant attention in Irish built-environment research.

This paper aims to investigate the pile group efficiency based on the load-settlement response in soft clay conditions, considering several pile configurations using a variable number of piles and pile spacing. The overall objective of the present paper is to provide further insight into the mechanical response of the pile group and aim at helping the engineers in taking a logical path in an iterative design process for pile group efficiency.

To investigate the pile group efficiency, three-dimensional (3D) numerical simulations were performed using the finite-difference code FLAC3D.

The obtained numerical results are validated by comparing them to those of similar subgrade structure and in comparable geological conditions provided within the literature. The results indicated that although the bearing capacity of the pile group increases with increasing number of piles, the efficiency of the pile group is very important for a small number of piles. However, increasing of pile spacing has a positive effect on pile group efficiency depending on piles number and settlement level. The pertinence of the 3D numerical results of efficiency coefficient is judged by comparison with those obtained from the most popular formulas available in the literature.

A predicted model is also proposed which is validated with the obtained numerical results to a better goodness of fit.

Cuba has recently endured the impact of hurricanes Lili (1996), George (1998), Irene (1999), Michelle (2001), Isidore (2002), Lili (2002), Charlie and Ivan (2004). The provinces of Villa Clara, Matanzas and Pinar del Río have suffered the major damage, basically in coastal towns where thousands of houses have been destroyed, and families displaced from their homes.

Tackling this problem proves to be complicated. Decision-makers face two choices: (a) to concentrate the scarce resources - including post disaster aid - on emergency actions to reduce only the damages caused by the hurricane, or (b) to improve in a sustainable way existing houses through better and more efficient material supply. In both cases, the possibility of local production of building materials becomes a crucial factor.

The Centre for Investigation and Development of Structures and Materials (CIDEM) has been involved in disaster-response projects in the area since 1996. The thrust has been the manufacture of ecomaterials such as micro concrete roofing (MCR) tiles, pozzolanic cement CP-40 and hollow concrete blocks, which provide the means to build affordable and hurricane safe houses. These materials are produced on the basis of local raw materials and labour in small workshops based directly in the communities.

The widespread use of ecomaterials on the northern coast of Villa Clara province has been a key aspect in decreasing the vulnerability of the houses against hurricanes. The fact that these materials have withstood the impact of various hurricanes without significant damage has drawn the attention of local governments, communities and donors. The presentation of case studies in this paper will illustrate this experience.

This study aims to elucidate the machining properties of low-cost expanded clay-reinforced syntactic foams by using different neural network models for the first time in the literature. The main goal of this endeavor is to create a casting machining-neural network modeling flow-line for real-time foam manufacturing in the industry.

Samples were manufactured via an industry-based die-casting technology. For the slot milling tests performed with different cutting speeds, depth of cut and lubrication conditions, a 3-axis computer numerical control (CNC) machine was used and the force data were collected through a digital dynamometer. These signals were used as input parameters in neural network modelings.

Among the algorithms, the scaled-conjugated-gradient (SCG) methodology was the weakest average results, whereas the Levenberg–Marquard (LM) approach was highly successful in foreseeing the cutting forces. As for the input variables, an increase in the depth of cut entailed the cutting forces, and this circumstance was more obvious at the higher cutting speeds.

The effect of milling parameters on the cutting forces of low-cost clay-filled metallic syntactics was examined, and the correct detection of these impacts is considerably prominent in this paper. On the other side, tool life and wear analyses can be studied in future investigations.

It was indicated that the milling forces of the clay-added AA7075 syntactic foams, depending on the cutting parameters, can be anticipated through artificial neural network modeling.

It is hoped that analyzing the influence of the cutting parameters using neural network models on the slot milling forces of metallic syntactic foams (MSFs) will be notably useful for research and development (R&D) researchers and design engineers.

This work is the first investigation that focuses on the estimation of slot milling forces of the expanded clay-added AA7075 syntactic foams by using different artificial neural network modeling approaches.