Outdoor Construction Research Articles

Effect of shrinkage-mitigating additive and curing condition on flexural and fracture behavior of ultra-high-performance concrete (UHPC) unnotched beam

The study aims to examine how the flexural and fracture behavior of UHPC is impacted when shrinkage is mitigated by adding shrinkage-mitigating additives. Furthermore, due to the consistent use of UHPC for structural repair and reinforcement throughout the year, including emergency construction in winter, it is necessary to carry out construction operations in winter conditions. Thus, this study adopts the natural cold curing condition of UHPC specimens to mimic real-world outdoor construction settings, while also using the standard curing condition as a comparison. The bending test was performed on three different types of UHPC materials: material 1 without a shrinkage-reducing agent (SRA) or expansive agent (EA), material 2 with 1 % SRA, and material 3 with 1 % SRA and 7.5 % EA. Fracture and flexural behavior of UHPC beams were studied, and Spearman's correlation between shrinkage and flexural/fracture toughness was evaluated. The study revealed that adding SRA/EA decreased the mean flexural tensile strength of specimens cured in standard conditions. Additionally, specimens cured in natural conditions showed less flexural tensile strength when SRA/EA was added. Furthermore, when compared to material 1, the addition of SRA and EA greatly reduced the fracture energy of UHPC, resulting in reductions of 21.9 % and 26.6 %, respectively, for materials 2 and 3. The fracture toughness showed a modest correlation with the shrinkage behavior, and the fracture energy exhibited a high association with the shrinkage behavior. The research findings can provide references for UHPC applications in natural winter conditions when the material contains shrinkage-mitigating additives.

Airborne particulate matter and diesel engine exhaust on infrastructure construction sites in the Copenhagen metropolitan area.

Diesel engine exhaust (DEE) is carcinogenic and potentially hazardous for those working in close proximity to diesel-powered machines. This study characterizes workplace exposure to DEE and its associated particulate matter (PM) during outdoor construction activities. We sampled at 4 construction sites in the Copenhagen metropolitan area. We used portable constant-flow pumps and quartz-fiber filters to quantify personal exposure to elemental carbon (EC), and used real-time instruments to collect activity-based information about particle number and size distribution, as well as black carbon (BC) concentration. Full-shift measurements of EC concentration ranged from < 0.3 to 6.4 µg/m3. Geometric mean (GM) EC exposure was highest for ground workers (3.4 µg/m3 EC; geometric standard deviation, GSD = 1.3), followed by drilling rig operators (2.6 µg/m3 EC; GSD = 1.4). Exposure for non-drilling-rig machine operators (1.2 µg/m3 EC; GSD = 2.9) did not differ significantly from background (0.9 µg/m3 EC; GSD = 1.7). The maximum 15-min moving average concentration of BC was 17 µg/m3, and the highest recorded peak concentration was 44 µg/m3. In numbers, the particle size distributions were dominated by ultrafine particles ascribed to DEE and occasional welding activities at the sites. The average total particle number concentrations (PNCs) measured in near-field and far-field positions across all worksites were 10,600 (GSD = 3.0) and 6,000 (GSD = 2.8)/cm3, respectively. Sites with active drilling rigs saw significantly higher average total PNCs at their near-field stations (13,600, 32,000, and 9,700/cm3; GSD = 2.4, 3.4, and 2.4) than sites without (4,700/cm3; GSD = 1.6). Overall, the DEE exposures at these outdoor construction sites were below current occupational exposure limits for EC (10 µg/m3 in Denmark; 50 µg/m3 in the European Union), but extended durations of exposure to the observed DEE levels may still be a health risk.

Content annotation in images from outdoor construction jobsites using YOLO V8 and Swin transformer

Digital visual data, such as images and videos, are valuable sources of information for various construction engineering and management purposes. Advances in low-cost image-capturing and storing technologies, along with the emergence of artificial intelligence methods have resulted in a considerable increase in using digital imaging in construction sites. Despite these advances, these rich data sources are not typically used to their full potential because they are processed and documented subjectively, and several valuable contents could be overlooked. Semantic content analysis and annotation of the images could enhance retrieval and application of the relevant instances in large databases. This research proposes an ensemble approach to use deep learning-based object recognition, pixel-level segmentation, and text classification for medium-level (ongoing activities) and high-level (project type) annotation of still images from various outdoor construction scenes. The proposed method can annotate images with and without construction actors, i.e. equipment and workers. The experimental results have shown the potential of this approach in annotating construction activities with an 82% overall recall rate.

Improving the mechanical properties of heat-treated wood bonding interphase via plasma treatment

Plasma treatment is an eco-friendly and effective way to improve the chemical reactivity of wood surface. This study explores the improvemnet of bonding properties of heat-treated wood for outdoor construction applications through plasma treatment. In this work, the low temperature atmospheric barrier discharge (DBD) plasma was used to modify the surface of heat-treated wood, and then phenol-formaldehyde (PF) resin adhesive and modified wood were applied to prepare bonded wood. The in-situ chemical structure and mechanical properties of the bonding interphase were characterized by Raman spectrum, nanoindentation and digital image correlation technology (DIC) to indicate the effect of DBD modification on the bonding properties of heat-treated wood. Results showed that after plasma treatment, the hydrophilic functional groups in the cell wall were increased and the PF adhesive molecules had chemical interaction with the cell wall. The elastic modulus (Er) and hardness (H) of wood cell wall gradually decreased along the bonding interphase towards wood with the decrease of PF penetration depth, which resulted in the reduction of the mechanical properties difference between the cell wall and PF adhesive at the bonding interphase. As a result, the shear strain was distributed homogeneously due to the effective stress transmission more at the bonding interphase. The shear strength of the control bonded wood decreased by about 35 % after heat treatment at 215 °C for 2 h, while the shear strength of heat-treated wood was increased by up to 34 % after plasma treatment.

From biowaste to BioPave: Biological pathways for sequestration of anthropogenic CO2 and enhancing durability of roadway infrastructures

Biomass-derived bio-oils are emerging as sustainable, low-carbon alternatives for construction materials, particularly in innovative pavement applications, 'BioPave'. This study evaluates bio-oils from various sources, including algae and wastewater biomass, revealing variations in carbon, nitrogen, and sulfur contents, along with viscosity. We focused on their application in outdoor construction, assessing their resistance to thermal and solar radiation, and moisture. The study also examines their interaction with siliceous surfaces and their influence on asphalt adhesion in BioPave systems under moisture conditions. Laboratory experiments and computational modeling demonstrated molecular composition significantly influenced bio-oils' responses to thermal and UV exposure. Bio-oils rich in polar groups showed hardening upon thermal treatment, while those with higher concentrations of saturated aliphatics remained more stable. Furthermore, our findings highlight the significance of dosage control in maximizing beneficial effects of bio-oils in intermolecular interactions at bitumen-aggregate interface in BioPave applications. These findings offer insights into the potential of bio-oils in sustainable construction and the need for dosage control to optimize pavement performance.

Detection method of the seat belt for workers at height based on UAV image and YOLO algorithm

In the domain of outdoor construction within the power industry, working at significant heights is common, requiring stringent safety measures. Workers are mandated to wear hard hats and secure themselves with seat belts to prevent potential falls, ensuring their safety and reducing the risk of injuries. Detecting seat belt usage holds immense significance in safety inspections within the power industry. This study introduces detection method of the seat belt for workers at height based on UAV Image and YOLO Algorithm. The YOLOv5 approach involves integrating CSPNet into the Darknet53 backbone, incorporating the Focus layer into CSP-Darknet53, replacing the SPPF block in the SPP model, and implementing the CSPNet strategy in the PANet model. Experimental results demonstrate that the YOLOv5 algorithm achieves an elevated average accuracy of 99.2%, surpassing benchmarks set by FastRcnn, SSD, YOLOX-m, and YOLOv7. It also demonstrates superior adaptability in scenarios involving smaller objects, validated using a UAV-collected dataset of seat belt images. These findings confirm the algorithm's compliance with performance criteria for seat belt detection at power construction sites, making a significant contribution to enhancing safety measures within the power industry's construction practices.

Potential of fibre reinforced and cement stabilized fibre reinforced soil blocks as sustainable building units

The alarming pollution level and its consequences on the environment owing to the use of conventional building materials have resulted in a renewed interest in earth-based materials for construction. The soil used in the production of earth blocks requires a specific composition of granular and clay soil, which is of limited availability. This study attempts to use locally available granular soil with limited fines content for block making and investigates the choice of reinforcing soil blocks for optimal performance with minimum cement content. Natural fibres– areca, coir and flax were selected for reinforcing the soil blocks, and 2.5% cement was used for stabilizing the blocks. Fibre reinforcement improved the mechanical properties of the soil blocks, but their durability was limited. Coir-reinforced soil blocks showed an increase of 3.56 times in strength compared to unreinforced soil blocks at the optimum fibre content of 1%. Similarly, coir-reinforced cement stabilized blocks showed nearly 1.70 times strength improvement when compared to unreinforced cement-stabilized blocks. A minimal addition of 2.5% cement improved the durability properties like erosion resistance, linear shrinkage, water absorption and abrasion resistance of the blocks. Flax fibre-reinforced blocks showed better durability properties. The minimum quantity of cement improved both mechanical and durability properties qualifying the blocks for indoor and outdoor construction use, as observed from wallette tests.

Predictive worker safety assessment through on-site correspondence using multi-layer fuzzy logic in outdoor construction environments

Construction sites remain highly perilous work environments globally, exposing employees to numerous hazards that can result in severe injuries or fatalities. To resolve this several solutions based on quantitative approaches have been developed. However the wide adoption of preexisting solutions is hindered by lack of accuracy. To this aim the development of an efficient fuzzy inference system has become a de-facto necessity. In this paper, we propose an edge inference framework based on multi-layered fuzzy logic for safety of construction workers. The proposed system employs an edge computing-based framework where IoT devices collect, store, and manage data to offer safety services. Multi-layer fuzzy logic is applied to infer the worker safety index based on rules that consist of construction environment factors. The multi-layer fuzzy logic is fed with weather, building and worker data collected from IoT nodes as inputs. The safety risk assessment process involves analyzing various factors. Weather information, such as temperature, humidity, and rainfall data, is considered to assess the risk to safety. The condition of the building is evaluated by analyzing load, strain, and inclination data. Additionally, the safety risk to workers is analyzed by taking into account their heart rate and location information. The initial layer's outputs are utilized as inputs for the subsequent layer, where an integrated safety index is inferred. Ultimately, the safety index is generated as the final outcome. The system's results are conveyed through warnings and an error measurement on a safety scale ranging from 1 to 10. Furthermore, web service is developed to allow the construction management to check the worker safety condition of the construction site in real-time, while also monitoring the operational status of the IoT devices, allowing for the early detection of sensor malfunction and the subsequent guarantee of worker safety. Extensive evaluations conducted to test the performance of the developed framework verify its efficiency to provide improved risk assessment, real-time monitoring, and proactive safety actions, encouraging a safer and more productive work environment.

Design of New LED Curtain Wall Controller and Its Effect in Architectural Decoration

In recent years, LED with high brightness or ultra-high brightness has appeared. Because of its low production cost, it has been widely used. Compared with other display media, LED has the advantages of rich display content, wide dynamic range, vivid picture, no pollution, long life, etc., so it is used in building curtain wall facade decoration. This research designs LED curtain wall control system, the use of SD600 chip dimming control of LED, the use of absorbing current mode LED drive, further design of single SD600 chip application circuit, multi-SD600 chip application circuit. LED curtain wall display text need to design the corresponding graphic processing hardware, the hardware is composed of ARM microprocessor LPC2210 and its related peripheral circuits. The core chip of the LPC2210 processor chip needs 1.8 V working voltage, and the I/O interface voltage is 3.3 V, so it is necessary to design the corresponding power circuit; The system clock is adjusted through the internal PLL circuit to make the system run faster and design its crystal oscillator circuit; The power monitoring chip CAT1025JI-30 is adopted to build reset circuit, 20-pin interface type JTAG interface circuit; It is considered that the UARTO interface can’t be directly connected with the RS232 interface of PC, the MAX3232 chip is introduced for level conversion, and the serial interface circuit based on LPC2210 is designed. In the experiment, the new technology is used for outdoor lighting LED curtain wall construction, and the development tool uses the ADS1.2 provided by ARM company. The μC/OS-II embedded operating system is introduced to control the graphic processing hardware resources, reading the file from the SD card, and writing the text file and BMP file into the three-dimensional array, the corresponding text and pattern effect are displayed in the LED curtain wall.

Superhydrophobic Wood Surfaces: Recent Developments and Future Perspectives

Wood is a renewable material that has been widely utilized as indoor and outdoor construction and decoration material in our daily life. Although wood has many advantages (i.e., light weight, high strength, low price and easy machinability), it has some drawbacks that influence dimensional stability, cracking and decay resistance in real practical applications. To mitigate these issues, superhydrophobic surfaces have been introduced to wood substrates, creating superhydrophobic wood surfaces (SHWSs) that can improve stability, water resistance, ultraviolet radiation resistance and flame retardancy. Herein, the recent developments and future perspectives of SHWSs are reviewed. Firstly, the preparation methods of SHWSs are summarized and discussed in terms of immersion, spray-coating, hydrothermal synthesis, dip-coating, deposition, sol-gel process and other methods, respectively. Due to the characteristics of the above preparation methods and the special properties of wood substrates, multiple methods are suggested to be combined to prepare SHWSs rather than each individual method. Secondly, the versatile practical applications of SHWSs are introduced, including anti-fungi/anti-bacteria, oil/water separation, fire-resistance, anti-ultraviolet irradiation, electromagnetic interference shielding, photocatalytic performance, and anti-icing. When discussing these practical applications, the advantages of SHWSs and the reason why SHWSs can be used in such applications are also mentioned. Finally, we provide with perspectives and outlooks for the future developments and applications of SHWSs, expecting to extend the utilization of SHWSs in our daily life and industry.

High-performance wood scrimber prepared by a roller-pressing impregnation method

Wood scrimber is a wood-based composite material with high mechanical strength and large size, which can potentially replace the use of steel and cement in various fields. However, its poor dimensional stability and low flame retardancy limit its use in outdoor construction projects and fire-prone areas. To solve this, here we report a roller-pressing impregnation method to realize the deep penetration of resin using mechanical compression and low-pressure adsorption. Microstructural imaging by SEM and 3D ultra-deep field microscopy shows the phenol formaldehyde(PF) resin distribution of the roller-pressed wood scrimber (R-WS) is deeper and more uniform, which increases the flatness and crystallinity. The R-WS showed greatly improved dimensional stability, with 63 % and 35 % lower thickness swelling rate (TSR) and width swelling rate (WSR) compared with the traditional wood scrimber (T-WS). In terms of flame retardancy, the smoke production rate (SPR) and heat release rate (HRR) of R-WS decreased by 32.7 % and 52 %, respectively. The R-WS at 800 °C formed a dense char that content increased by 20 %, helping to inhibits combustion. The mechanical properties of R-WS were also improved, and the modulus of rupture (MOR), modulus of elasticity (MOE) and short-beam strength (SS) of R-WS increased by 31.2 %, 7.4 %and 26.7 %, respectively. The R-WS suffer toughness failure and wood-to-wood failure under bending and shear scenarios, respectively, indicating that the roller-pressing impregnation treatment enhanced toughness and bonding strength. In addition, the use of a rotating roller is expected to realize the continuous production of the dipping link, saving drying energy consumption and improving production efficiency. These properties are expected to promote the outdoor utilization and continuous production of wood scrimber.

Collaborative Worker Safety Prediction Mechanism Using Federated Learning Assisted Edge Intelligence in Outdoor Construction Environment

Collaborative Worker Safety Prediction Mechanism Using Federated Learning Assisted Edge Intelligence in Outdoor Construction Environment

Durability Evaluation of Outdoor Scrimbers Fabricated from Superheated Steam-Treated Bamboo Fibrous Mats

With natural texture and high performance, bamboo scrimber is one of the artificial lignocellulosic composites widely used in construction, furniture and other structural applications. However, it is vulnerable to the actions of water, ultraviolet radiation and fungus, which affect its durability, especially in the open. Here, bamboo was treated with superheated steam in an attempt to improve the durability of bamboo scrimbers. The chemical composition, mechanical properties, dimensional stability, aging resistance, decay resistance and anti-mildew properties were investigated at different temperatures (160~200 °C). After superheated steam treatment, the relative contents of holocellulose and α-cellulose in bamboo decreased. The bending strength and short-beam shearing strength slightly decreased as the temperature was raised while the modulus was essentially retained. The aging resistance in terms of thickness swelling rate (≤9.38%) was substantially improved. The decay resistance reached to the level of Grade I and can be dramatically enhanced by elevating temperature. The anti-mildew properties were also improved. To take together, superheated steam treatment remarkably improves the resistance of bamboo scrimbers to water, ultraviolet radiation, rot fungi and mildew with some concomitant reduction in mechanical properties. The results will permit outdoor construction using bamboo scrimbers more resistant to environmental damage.

A self-priming air filtration system based on triboelectric nanogenerator for active air purification

Air pollution is becoming more and more serious, which has a huge impact on human production and life. Dust particulate matter (PM) is one of the main pollutants in the air, threatening human life and health. In this work, a triboelectric air filtration system (TAFS) based on triboelectric nanogenerators (TENGs) was developed for active removal of outdoor PM2.5 and harmful bacteria. The TAFS consists of a layer of industrial filter media (filter cotton or sponge) and a layer of polytetrafluoroethylene (PTFE). Due to frictional electrification effect of these two layers, the filtration efficiency of the low-efficiency and low-resistance filter material for particulate matter is greatly improved. The filtration efficiencies of PM1.0 and PM2.5 are increased by 20 %-40 %. Moreover, the frictional positive charge also greatly improves the interception efficiency of the material against Staphylococcus aureus. A self-priming air filtration system composed of an air pump and TENG are used to remove PM2.5 up to 99 % in a confined space filled with cigarettes for 30 min. In addition, the wind cup design makes the system take full advantage of the wind energy in the environment, realizing self-power supply, zero carbon emission and high efficiency and environmental protection. The self-powered TAFS can be used in outdoor dusty construction sites, dust factories, sand and haze weather and other places to remove particulate pollution. This work also provides a novel self-powered air purification strategy.

Water resistance and mechanical properties of bamboo scrimber composite made from different units of Bambusa chungii as a function of resin content

Bamboo units form basic components of bamboo scrimber composite (BSC), directly affecting the composite’s characteristics and performance. In this study, the water resistance and mechanical properties of BSCs containing different resin percentages were investigated. BSCs were made from bamboo bundles (BSC-I) and oriented bamboo fiber mat (BSC-II) of Bambusa chungii via mechanical decomposition followed by molding recombination. Water resistance of BSCs increased with rising resin content, specifically, with increased thickness swelling rate. BSC-II with a resin content of 25% met the level for high-class outdoor-use bamboo scrimber flooring products. Notably, the resin content and mechanical properties of BSCs were marginally correlated. In addition, BSC-II was more water resistant but had lower mechanical strength compared to BSC-I. The bending strength and modulus of all BSCs were greater than 200 MPa and 22 GPa, respectively. With the selection of appropriate bamboo unit processing methods and resin content for outdoor flooring and building construction, B. chungii is an attractive option for BSC products owing to its properties of water resistance and mechanical strength.

Quaternary Ammonium Based Compound Improves Interfacial Bond and Hydrophobicity of Coirpith-Cement Composite

Coir pith is a coconut waste derived from the extraction of coconut fiber that accounts for 70% of total husk. With an estimated 6.7 million husks produced in the Philippines annually, a large fraction of waste known as coir pith is left to rot, thrown or burned. Coir pith in cement board composite is applicable as insulation and a light indoor construction material due to its high-water absorption properties and less strength. The study sought to solve the high-water absorption problem while aiming at improving the strength and durability of the composite that will meet the needs for indoor and outdoor construction materials. According to the study's findings, QUAC increases the hydrophobicity of coir pith-cement composites, improves interfacial bonds, and has the potential for light indoor and outdoor construction.

Stimulating Sunscreen Use Among Outdoor Construction Workers: A Pilot Study.

BackgroundOutdoor workers (OW) receive a higher dose of ultraviolet radiation (UVR) compared to indoor workers (IW) which increases the risk of non-melanoma skin cancer (NMSC). Regular sunscreen use reduces the NMSC risk, however, adequate sun-safety behavior among OW is poor. The main objective was to conduct method- and intervention-related elements of a future intervention trial among OW, based on providing sunscreen and assessing sunscreen use on group- and individual level.MethodsThis pilot study was conducted at a construction site in the Netherlands from May-August 2021. Nine dispensers with sunscreen (SPF 50+) were installed at the worksite. OW (n = 67) were invited to complete two (cross-sectional) questionnaires on sun-safety behavior, before and after providing sunscreen. Stratum corneum (SC) samples for the assessment of UV-biomarkers were collected from the forehead and behind the ear from 15 OW and 15 IW. The feasibility of the following elements was investigated: recruitment, (loss to) follow-up, outcome measures, data collection, and acceptability of the intervention.ResultsThe first questionnaire was completed by 27 OW, the second by 17 OW. More than 75 percent of the OW were aware of the risks of sun exposure, and 63% (n = 17) found sunscreen use during worktime important. The proportion of OW never applying sunscreen in the past month was 44.4% (n = 12) before, and 35.3% (n = 6) after providing sunscreen. A majority of OW (59.3%, n = 16) found sunscreen provision encouraging for sunscreen use, the dispensers easy to use (64.7%, n = 17) and placed in practical spots (58.8%, n = 18). Collecting SC-samples was fast and easy, and several UV-biomarkers showed higher levels for sun-exposed compared to less exposed body parts. There was no significant difference in UV-biomarker levels between OW and IW.ConclusionsThis pilot study revealed low sunscreen use among OW despite providing sunscreen, overall satisfaction with the sunscreen, and the sufficient awareness of the risks of UVR-exposure. Collecting SC-samples at the workplace is feasible and several UV-biomarkers showed to be promising in assessing UVR-exposure. The low participation rate and high loss to follow-up poses a challenge for future intervention studies.

Vision-Based UAV-UGV Collaboration for Autonomous Construction Site Preparation

Construction site preparation tasks rely on experienced operators and heavy machinery for clearing debris, earthmoving, leveling, and soil stabilization. These actions require complex collaboration between human teams to survey the site, estimate the material condition, and guide the operators accordingly. In recent years there has been a critical labor shortage due to increasing demands in construction. Integrating autonomous systems can mitigate this gap by replacing traditional methods with robotic solutions. However, while ideal conditions for automatic systems are static and highly controlled, construction sites are dynamic and unstructured environments. The ability of autonomous systems to overcome these conditions during outdoor construction site preparation tasks relies on their capacity to map the material on-site and continuously perform localization. This study suggests a solution to these problems by collaborating between an Unmanned Aerial Vehicle (UAV) and an Unmanned Ground Vehicle (UGV). In this method, the UAV produces a material map and monitors the UGV’s location relative to known static landmarks. These measurements are then sent to the ground vehicle and are added to the onboard sensors using the Extended Kalman Filter (EKF) approach. Thus, the UAV enhances the operation of the UGV by providing an accurate localization and mapping from the air and allowing it to perform a site-preparation task beyond mere sensing. This approach is examined with simulation and validated by outdoor experiments. Additionally, this method is integrated within Shepherd, a custom-developed plugin for computer-aided design applications.

Protection against solar ultraviolet radiation in outdoor construction workers in The Netherlands: a feasibility study

Protection against solar ultraviolet radiation in outdoor construction workers in The Netherlands: a feasibility study

A Smart Helmet-Based PLS-BPNN Error Compensation Model for Infrared Body Temperature Measurement of Construction Workers during COVID-19

In the context of the long-term coexistence between COVID-19 and human society, the implementation of personnel health monitoring in construction sites has become one of the urgent needs of current construction management. The installation of infrared temperature sensors on the helmets required to be worn by construction personnel to track and monitor their body temperature has become a relatively inexpensive and reliable means of epidemic prevention and control, but the accuracy of measuring body temperature has always been a problem. This study developed a smart helmet equipped with an infrared temperature sensor and conducted a simulated construction experiment to collect data of temperature and its influencing factors in indoor and outdoor construction operation environments. Then, a Partial Least Square–Back Propagation Neural Network (PLS-BPNN) temperature error compensation model was established to correct the temperature measurement results of the smart helmet. The temperature compensation effects of different models were also compared, including PLS-BPNN with Least Square Regression (LSR), Partial Least Square Regression (PLSR), and single Back Propagation Neural Network (BPNN) models. The results showed that the PLS-BPNN model had higher accuracy and reliability, and the determination coefficient of the model was 0.99377. After using PLS-BPNN model for compensation, the relative average error of infrared body temperature was reduced by 2.745 °C and RMSE was reduced by 0.9849. The relative error range of infrared body temperature detection was only 0.005~0.143 °C.