Construction Defect Research Articles

Study on seismic behavior of prefabricated shear wall with pressed cone sleeves (PCSs)

Current prefabricated shear walls predominantly utilize grouting sleeves for connection, whereas an in-depth review and summary of the current state of research have indicated a 26.7 % construction defect rate in these sleeves due to present construction techniques. To solve the problem of defects, this study introduced a novel prefabricated shear wall design using vertical rebars connected via pressed cone sleeves (PCSs). Three reinforced concrete (RC) prefabricated shear walls with different vertical rebars connected and tested under cyclic horizontal load and constant vertical load to study the seismic performance, including cast-in-situ shear wall (specimen SW1), partial sleeve grouting defects shear wall (specimen SW2) and shear wall with vertical rebars connected via PCSs (PCSs-SW, specimen SW3). Key performance indicators such as failure modes, hysteresis curves, shear capacity, stiffness, ductility, energy dissipation capacity and stress characteristics were evaluated. The results of the tests revealed that SW1 and SW3 failures resulted from a combination of bending moment and shear force, whereas SW2 failure in the area of grout sleeve defects connection. Compared to the specimen SW2, the SW3 owns better shear bearing capacity, ductility, stiffness, energy dissipating capacity and reliable seismic performance. Meanwhile, SW3 and SW1 exhibited the similar seismic performance, can primarily achieve the effect of “equivalent cast-in-situ”. Finite element (FE) model of specimen SW3 were developed by using software ABAQUS, and the precision and utility of FE models verified by testing data. Using proposed FE models, an extensive parametric study was conducted to investigate the influencing factors on the seismic performance of precast fabricated RC shear wall, including axial compression ratio, concrete strength, vertical rebar strengths and vertical rebar diameters.

IMPLEMENTING VIRTUAL REALITY TO FOSTER CONSTRUCTION DEFECTS CHECKING AND REPORTING

The scarce human workforce during the economic downturn and the COVID lockdown measures exposed the need for more reliance on in-person construction site visits. During the pandemic, the research team conducted a systematic review to investigate how virtual reality (VR) techniques can be applied to foster more effective construction defect checking and reporting. The findings indicate that VR technologies can be applied in marker-based inspection, which is crucial for developing the automatic defect recording and tracking system. Built on these findings, this paper reports a case study conducted in Melbourne, Australia, demonstrating how VR techniques can be applied to develop practical solutions for enhancing defect checking and reporting in an actual construction project. The solutions focused on reducing the time-consuming and inefficient manual tracking process. This study shows a step forward in assisting human judgment by resolving the in-person marker-based inspections and manual defect tracking encountered in traditional defect checking and reporting practices.

IMPLEMENTING VIRTUAL REALITY TO FOSTER CONSTRUCTION DEFECTS CHECKING AND REPORTING

The scarce human workforce during the economic downturn and the COVID lockdown measures exposed the need for more reliance on in-person construction site visits. During the pandemic, the research team conducted a systematic review to investigate how virtual reality (VR) techniques can be applied to foster more effective construction defect checking and reporting. The findings indicate that VR technologies can be applied in marker-based inspection, which is crucial for developing the automatic defect recording and tracking system. Built on these findings, this paper reports a case study conducted in Melbourne, Australia, demonstrating how VR techniques can be applied to develop practical solutions for enhancing defect checking and reporting in an actual construction project. The solutions focused on reducing the time-consuming and inefficient manual tracking process. This study shows a step forward in assisting human judgment by resolving the in-person marker-based inspections and manual defect tracking encountered in traditional defect checking and reporting practices.

The Causal Factors of Building Construction Defects

Defects are something that must be identified in the implementation of quality management. Defects can potentially lead to construction failures and injury. This study aims to identify and analyse the causal factors of building construction defects based on the perspective’s project stakeholders. This research is quantitative-descriptive research conducted through questionnaires distributed to the purposive respondents. Then, conduct statistical analysis and evaluate the causal factors of construction defect using Failure Mode and Effect Analysis (FMEA). Based on the results, the critical causal factors of building construction defects are lack of communication within the project environment with a value of 33.6; poor performance of the project management team with a value of 30.3; improper design and specification with a value of 27.88; lack of supervision in the site with the value of 24.60 and lack of competency of the construction labour with the value of 23.04. Project stakeholders are expected to pay more attention to critical causal factors as preventive measures to prevent structural failure and injury.

Experimental investigation on mechanical performance of kerf anchorage of stone cladding considering construction defects

Because of its good deformation performance, easy installation and replacement, the kerf anchorage technology is widely used in the stone cladding. The current reports of accidents related to the kerf anchorage of stone claddings are most often caused by construction defects. However, current studies on the impact of construction defects on the failure of kerf anchorage of stone claddings are still limited. In order to investigate the mechanical performance of kerf anchorage of stone cladding with construction defects, anchorage strength tests under monotonic load were conducted on seven groups of specimens based on ASTM C1354-15. The results indicate that, compared with the specimens without adhesive, the filling of adhesive in the slot directly affects the failure characteristics of kerf anchorage of stone cladding, and greatly enhances the ultimate load of anchorage systems. The failure modes of specimens with and without adhesive are flexural failure and punch-shear failure, respectively. The average ultimate load of specimens with epoxy resin and unsaturated polyester resin is increased by 321 % and 289 % compared to the specimens without adhesive. For the specimens with adhesive, the position deviation of the anchor, which is a common construction defect, can cause changes in the thickness of the adhesive between the loading surface of panel and the anchor. As the thickness of adhesive between the loading surface of panel and the anchor increases, the ultimate load of specimens with adhesive increase accordingly. Based on the strength criteria and mechanical analysis, a calculation model for predicting the ultimate load of kerfed stone cladding with slot adhesive is proposed.

A Simplified Approach to Determine Shear Strength for Corroded RC Beams

Corrosion damage, which can be considered as a construction or usage defect during the life of the structure, is an important parameter for the structural elements. Strength loss is observed in reinforced concrete (RC) elements due to corrosion, which is an important parameter affecting the performance of the building. Determining the shear strength of beams with corroded reinforcement is important in terms of strength loss, design, and reinforcement criteria in the structural element. In this context, the data of the corroded RC beam experimental tests carried out in the literature were collected and the ultimate shear strength values of the beams were determined depending on the test parameters. Strength estimation was performed with machine learning regression algorithms XGBoost and AdaBoost. The results obtained were evaluated with R2, RMSE and MAE performance metrics and high estimation success was achieved. The study shows that with these systems, which can perform learning based on experimental data, it is possible to estimate the shear strength values of corroded beams with known production parameters without the need for experimental measurements.

Automated hand-marked semantic text recognition from photographs

Automated text recognition techniques have made significant advancements; however, certain tasks still present challenges. This study is motivated by the need to automatically recognize hand-marked text on construction defect tags among millions of photographs. To address this challenge, we investigated three methods for automating hand-marked semantic text recognition (HMSTR)—a modified scene text recognition-based (STR) approach, a two-step HMSTR approach, and a lumped approach. The STR approach involves locating marked text using an object detection model and recognizing it using a competition-winning STR model. Similarly, the two-step HMSTR approach first localizes the marked text and then recognizes the semantic text using an image classification model. By contrast, the lumped approach performs both localization and identification of marked semantic text in a single step using object detection. Among these approaches, the two-step HMSTR approach achieved the highest F1 score (0.92) for recognizing circled text, followed by the STR approach (0.87) and the lumped approach (0.78). To validate the generalizability of the two-step HMSTR approach, subsequent experiments were conducted using check-marked text, resulting in an F1 score of 0.88. Although the proposed methods have been tested specifically with tags, they can be extended to recognize marked text in reports or books.

A Decision Support System for Organizing Quality Control of Buildings Construction during the Rebuilding of Destroyed Cities

Natural disasters and warfare lead to the destruction of city buildings and infrastructure, leaving large numbers of people homeless. The rebuilding of destroyed cities needs to be carried out promptly while maintaining a balance between construction quality and duration. Rework due to defects and the lengthy approval of non-conformances significantly increases the duration of construction. This study aimed to develop a decision support system to fix or negotiate strategies to address construction defects, depending on their level of risk. The paper addresses the following objectives: classifying defects by the quality of construction that they affect; building a tree of construction defect risks; and developing an artificial neural network (ANN) to assess the defect risk. The weights of the links are represented by posterior probabilities of damage calculated using the Bayes’ theorem in the pre-training stage. The ANN has been adapted to cast-in-place reinforced concrete structures. When training the resulting ANN on a sample of precedents, the test sample demonstrated convergence and low errors. The resulting model will accelerate construction by automating assessments of defect severity and reducing the time spent on reworking defects with low quality risk.

Construction defect identification for structural sealant by statistical driving-point accelerance

Accidental defects occur often during the construction of the structural sealant in a glass curtain wall structure. However, there are tens of thousands of glass panel units in a building, and the baseline models of different panel units are different from each other. In this paper, a two-stage construction defect identification method is proposed to identify a few units with structural sealant defect from a large number of units. In the first stage, the average driving-point accelerance (DA) was used as statistical baseline DA to calculate the accumulative difference of driving-point accelerance (ADDA). Then, the abnormal panel units are identified by the quantile estimation method. In the second stage, structural sealant construction defects are detected further by comparing the peak frequency difference between the statistical baseline DA and the abnormal DA. Several numerical examples and on-site experiments indicated that the probability density function of ADDA is agreement with the Weibull distribution, and the proposed method can effectively detect the structural sealant construction defects from many units without baseline model.

Numerical modeling for evaluation of the thermal resistance of reflective airspaces with and without defects

The thermal resistances (R-values) of airspaces depends on the emittance of all surfaces around an airspace, dimensions, heat-flow direction, and the temperatures of the bounding surfaces. Assessing the energy performance of building envelope components and fenestration systems requires accurate results for the R-values of any enclosed spaces. The evaluation of reflective insulation R-values has evolved to include use of computational fluid dynamics and surface-to-surface radiation to quantify convective and radiative contributions to the heat transfer across airspaces of all types. This paper compares an advanced and validated model for calculating enclosed airspace R-values with the widely-used ISO 6946 and airspace R-values in the ASHRAE Handbook-Fundamentals. The impact of construction and installation defects on the thermal performance of reflective insulation has not been previously evaluated. In this research, an advanced model was used to evaluate a construction defect and dimensional aspect ratios that one-dimensional methods do not address. Imperfect installation and defects that result in air movement into or through a reflective insulation assembly reduces the thermal resistance of the assembly. Additionally, the amount of thermal resistance reduction depends on the amount and temperature of invasive air or the size of internal defects that allows natural convection inside the reflective airspace. In this study, these performance issues are evaluated quantitatively using computer simulation techniques. The differences in results obtained using methods that are currently being used to evaluate the R-value and the advantages of the advanced method for evaluating the reflective insulation performance for different applications are discussed. For the case considered in this study, the results showed that the failure to achieve parallel surfaces results in less than a 5% decrease in thermal resistance. Also, the results showed that internal air gaps between airspaces result in negligible loss in R-value unless air gaps that allow circulation between airspaces are created.

Defect Repair Deposit and Insurance Premium for a New Home Warranty in Korea

Disputes due to defects in newly built houses are increasing worldwide. A house builder is responsible for repairing any defects in a newly built house. However, since house builders’ risk of closure and bankruptcy are increasing due to aggravated disputes and economic crises, builders may become insolvent and fail to perform defect repairs. In preparation for this, many countries have established defect repair deposit or guaranty insurance systems; however, the standards for these systems are not based an objective evidence since the current standards were arbitrarily established during industrialization. It has been pointed out that Korea’s housing defect repair deposit has been set excessively high and is being abused in disputes. Based on dispute cases in Korea, this study analyzed housing construction costs, deposits, and defect repair costs, resulting from lawsuits due to defects. The results confirmed that the defect repair deposit has been set too high compared to incurred defect repair costs. In addition, it was found that the guaranty insurance premium in lieu of the housing defect repair deposit was excessive compared to the damage caused by builder insolvency. In order to improve this, in this study, we proposed two alternative plans in which the housing defect repair deposit was set at a certain percentage of the construction cost based on the current Korean standard. In addition, based on the concept of different deposit levels using the scale of housing construction, such as in Australia and Canada, two additional alternative plans with different deposit ratios for each scale of housing construction were presented. The comparison results for housing defect repair deposits and guaranty insurance premiums based on the four presented alternative plans accompanied by actual cases showed that all the alternative plan deposits were higher than the actual defect repair costs. Even in the case of a guaranty insurance premium, the level was at least twice as high as the damage caused by builder insolvency. Therefore, all the alternative plans can fulfill their original role of protecting homeowners in the case of builder insolvency. At the same time, reducing the guaranty insurance premium to reflect the cost of housing construction is possible, and would benefit both house builders and home buyers. The results of this study are valuable as a reference for other countries considering establishing or revising a housing defect repair deposit system. Specifically, these findings, which analyzed the case of Korea’s socioeconomic changes as it transitioned from a developing country to a developed country, can provide important information for many developing countries operating housing defect repair deposit policies and systems.

Analysis of damp in the substructure of a multi-family residential building – case study

This paper discusses dampness in an underground garage of a multi-family residential building on the basis of a case study. Due to high groundwater levels, the building substructure was constructed using W8 watertight concrete. This applies to both the foundation slab and substructure walls. However, leaks have occurred even though the used solutions were in theory designed to protect the building substructure from rainwater ingress. Macroscopic in situ tests, boreholes in the garage hall floor and foundation slab as well as laboratory test to determine the watertightness of the concrete were carried out to determine the cause of this construction defect, manifesting itself as damp in the structural elements in question.

Named entity recognition of building construction defect information from text with linguistic noise

Neither traditional rule-based named entity recognition (NER) nor the latest language models perform well in information extraction from noisy text—the text that contains linguistic errors, slang, loanwords, and jargon. Building defect complaints filed by residents via online systems is a representative example of such noisy text. This paper proposes an NER method for automatically extracting defect information from noisy text using a defect thesaurus and transfer learning. The thesaurus built herein included 1097 defect named entities in 23 categories. The NER performance was tested using 69,750 defect complaints through transfer learning of three representative pre-trained language models: Multilingual Bidirectional Encoder Representations from Transformers (BERT), Korean BERT (KoBERT), and Korean Efficiently Learning an Encoder that Classifies Token Replacements Accurately (KoELECTRA). The proposed method achieved an average F1 score of 91.0% using KoBERT. This NER performance was higher than that of the open benchmark NER performance for clean text (86.1%).

Behavior of axially loaded L-shaped RC columns strengthened using steel jacketing

Other than rectangular and circular columns, the most commonly used sections in reinforced concrete (RC) buildings in Saudi Arabia are L-shaped columns with a re-entrant angle of 90° or more. The structural designers are using L-shaped columns to meet the architectural and functional constraints of the building without obstructing the movement. Strengthening of such L-shaped RC columns is required to increase their load capacity for a number of reasons, such as an increase in the number of stories, the change of building use, design error(s), or construction defect(s). This research studied experimentally and analytically the behavior of strengthened L-shaped RC columns. The test matrix comprised two groups of six half-scale L-shaped RC columns. In the first and second groups, respectively, columns had 90° and 135° re-entrant corners. Each group had three columns: one unstrengthened control specimen used as a baseline for comparison and two steel-jacketed columns. In the first strengthened specimen, there was a 25 mm gap at the interface of the steel jacket with the ends (bottom base and top box), whereas, in the second specimen, the jacket was connected with the ends. The column specimens were concentrically loaded in compression until failure. It is demonstrated that strengthening of L-shaped columns with disconnected steel jackets had limited improvement in the axial load capacity ranging from 26% to 29% over the unstrengthened ones, while upgrading the columns with connected steel jackets had major enhancement in the axial load capacity varying from 68% to 79% over the control specimens. Furthermore, an analytical model that considers concrete confinement and axial load contributed by connected steel jacket was developed for assessing the axial capacity of tested specimens. Good agreement was achieved between the experimental and analytical peak loads with errors in prediction ranging from 1% to 6%.

CorDet: Corner-Aware 3D Object Detection Networks for Automated Scan-to-BIM

The use of automatic building information modeling (BIM) based on point cloud scans is in increasing demand in many engineering applications, such as construction progress monitoring, building renovation, project management, energy simulation, and defect detection. Segmentation-based three-dimensional (3D) modeling approaches using deep learning have been extensively investigated and achieved great performance in recent years. However, segmentation-based methods represent an object as a cluster of points and require further handcrafted steps to convert those points into 3D models. This paper aims to achieve a fully automatic, high-precision method of scan-to-BIM by exploring new 3D object detection networks. CorDet, a corner-aware detector, is proposed for the reconstruction of 3D objects in BIM. Each building object is represented as a class-specific, oriented, and symmetric 3D bounding box. The local features around the corners of an object are incorporated in order to decompose the object location precisely. CorDet can simultaneously learn both object-level and corner-level features through corner-based supervision using deformable convolutions. In experiments on the S3DIS data set, CorDet outperforms state-of-the-art benchmarks with a detection accuracy of 80.5% and a mean intersection of union (mIoU) of 88.9%. The average time spent in modeling a single room is 0.53 s, and this scheme therefore has great potential for many real-time engineering applications.

Feasibility of active and passive thermal control application for defect identification of building materials and products, enclosures of construction objects

This paper considers one of the most promising and modern methods of non-destructive testing - thermal control. The possibilities and advantages of thermal control for identifying defects of various building materials and products, enclosures of buildings and structures are presented. Brief characteristics of the main defects of building materials, products, and structures are presented. The basic principles of identifying hidden (invisible) and explicit (visible) defects are briefly considered and the practical results of construction defect identification of objects for various purposes using thermal imaging equipment are presented. The zones of thermal temperature anomalies are localized during qualitative analysis of thermograms (the method of active thermal control). The considered example is a fragment of a building enclosure made ceramic bricks with artificially created technical defects. For some enclosures of building structures and constructions, explicit thermal defects were identified from thermal imaging, their qualitative analysis was carried out, and recommendations for their elimination were proposed (method of passive thermal control).

A statistical analysis of temperature compensation for piezoelectric sensor bonded to AISI-1080 material

Electromechanical impedance (EMI) method has been widely used to evaluate structural health in recent years. In this method inexpensive, small, easy to apply, lightweight piezoelectric sensors are used to observe the changes in the structures. Different environmental conditions affect the piezoelectric sensor and the structure significantly. If the environmental impact is neglected, it causes misinterpretations as if it were present, although there is no construction defect. Therefore, it is necessary to compensate for the environmental effect. In this study, the EMI method was performed for AISI 1080 specimen at different environmental conditions. Impedance measurements were carried out between –45°C and –10°C. It has been observed that as the temperature decreases, the frequency shifts to the right and the amplitude increases. Temperature compensation was carried out to prevent these shifts. RMSD, MAPD, and CCDM were used as damage metrics. The effective frequency shift (EFS) algorithm was applied, and temperature compensation was performed according to the CCDM. As a result, damage metric values decrease after temperature compensation. Considering the change of damage metric values as a result of the compensation process, CCDM is a useful metric to detect changes. In the final stage, statistical tests (Pearson/Spearman and paired t-tests) were performed to compare non-compensated/compensated test results. Generally, damage metrics produce successful results in terms of statistical tests.

A novel silver-loaded graphitic carbon nitride with structural defect assisted by ascorbic acid for the fast and efficient degradation of sulfamethoxazole

The heterojunction construction and structural defect engineering both can effectively improve the catalytic performance of semiconductor photocatalysts. In this work, a novel composite photocatalyst consisted of the porous graphitic carbon nitride with two structural defects of oxygen atom and cyano group (COCN) and silver nanoparticles (AgNPs) decorated to COCN plane has been successfully prepared. And the morphology, structure, chemical composition and photoelectrical properties of this composite photocatalyst (Ag/COCN) were further characterized. Due to the synergistic effect of the heterojunction, surface plasmon resonance effect of AgNP and structural defects, Ag/COCN showed the narrow bandgap, high light absorption and fast charge separation so as to achieve a fast and efficient degradation of sulfamethoxazole (SMX). Through further optimization of AgNPs-loaded content, Ag/COCN presented the excellent photocatalytic activity on SMX degradation under simulated solar irradiation that more than 99.9% of SMX was removed within 20 min, which is among the best results reported thus far for SMX degradation rate via photocatalysis.

Site Civil Issues within Construction Defect Litigation

Across the United States, increased development continues to lead to an increase in construction defect litigation, particularly for multifamily for-sale projects. This research builds on previous research that identified common construction defects and suggested the majority of common construction defects generally relate to keeping water out of or flowing away from a building or structure. This research, therefore, focused its analysis on defects related to site civil engineering. The authors analyzed 43 construction defect cases litigated between 2012 and 2019, which include issues related to site civil design and construction in and around buildings. New findings begin to quantify the economic impact of site civil issues and alleged construction defects on commercial and residential projects. The contribution of this research is (1) identification and characterization of civil engineering–related defects, and (2) quantification of potential financial impacts related to site civil issues with the goal of helping to reduce future construction defect litigation.

Experimental study on post-fire performance of half grouted sleeve connection with construction defect

Half grouted sleeve connection (HGSC) is widely used in joining rebars in precast concrete structures. Construction defects and fires are inevitable in practical projects. However, the mechanical behaviors of post-fire HGSC with construction defect remain to be a topic with little research. The present work presents experimental results of 66 post-fire HGSC specimens with construction defect under static tension at room temperatures. Results show that the tensile properties of post-fire HGSC are directly affected by the peak temperature and the construction defect, and some properties are different from that of the rebar. Post-fire HGSC exhibited two main types of failure mode: rebar fracture and bonding failure. The protruded rebar in some post-fire specimens obviously slides before the rebar fractured and the ultimate elongation becomes larger. Different type of construction defect has a different effect on the behavior of the specimens, and the effect depends on the weakening of the effective bond area between rebar and grout. The peak temperature and construction defect may make reliable HGSC be unreliable and not acceptable, once the corresponding peak temperature is near 600 °C. Results also show that the proposed method to simulate the construction defects of HGSC is feasible and the X-ray method is an effective way to detect the defects in HGSC.