Construction Method Research Articles

Computer vision-based real-time monitoring for swivel construction of bridges: from laboratory study to a pilot application

PurposeThe swivel construction method is a specially designed process used to build bridges that cross rivers, valleys, railroads and other obstacles. To carry out this construction method safely, real-time monitoring of the bridge rotation process is required to ensure a smooth swivel operation without collisions. However, the traditional means of monitoring using Electronic Total Station tools cannot realize real-time monitoring, and monitoring using motion sensors or GPS is cumbersome to use.Design/methodology/approachThis study proposes a monitoring method based on a series of computer vision (CV) technologies, which can monitor the rotation angle, velocity and inclination angle of the swivel construction in real-time. First, three proposed CV algorithms was developed in a laboratory environment. The experimental tests were carried out on a bridge scale model to select the outperformed algorithms for rotation, velocity and inclination monitor, respectively, as the final monitoring method in proposed method. Then, the selected method was implemented to monitor an actual bridge during its swivel construction to verify the applicability.FindingsIn the laboratory study, the monitoring data measured with the selected monitoring algorithms was compared with those measured by an Electronic Total Station and the errors in terms of rotation angle, velocity and inclination angle, were 0.040%, 0.040%, and −0.454%, respectively, thus validating the accuracy of the proposed method. In the pilot actual application, the method was shown to be feasible in a real construction application.Originality/valueIn a well-controlled laboratory the optimal algorithms for bridge swivel construction are identified and in an actual project the proposed method is verified. The proposed CV method is complementary to the use of Electronic Total Station tools, motion sensors, and GPS for safety monitoring of swivel construction of bridges. It also contributes to being a possible approach without data-driven model training. Its principal advantages are that it both provides real-time monitoring and is easy to deploy in real construction applications.

Curves that allow the motion of a regular polygon

AbstractThis paper characterizes curves where a regular polygon of either a variable side length or a constant side length is allowed to rotate during k full revolutions while having its vertices on the curve during the motion. A constructive method to generate these curves is given based on the curve described by the polygon centers (centroids) during the motion and some examples are shown. Moreover, if the regular polygon divides the curve perimeter into parts of equal length, it is proved that the curve is either a rotational symmetric curve in the case of a variable side length or a circle otherwise. Finally, in the case of a regular polygon of constant side length rotating along a curve, a simple relation between the algebraic areas of such a curve and the curve of polygon centers is revisited.

Assessment for shallow and large tunnel construction in weak ground conditions: Application of tunnel boring machines

AbstractWith recent technological advancements, tunnel boring machines (TBM) have developed and exhibited high performance in large diameters and weak ground conditions. Tunnels are crucial structures that significantly influence the timelines of highway and railway projects. Therefore, the construction of tunnels with TBMs becomes a preferred option. In this study, a comparative analysis between TBM and the New Austrian Tunneling Method (NATM) for tunnel construction is performed in the construction of the T1 tunnel with a diameter of 13 m, which is the longest tunnel in the Eşme‐Salihli section of Ankara‐İzmir High‐Speed Railway Project (Türkiye). The selection of TBM type, measures taken in problematic sections, and application issues of TBM are discussed. The impact of correct description of geological and geotechnical conditions on both selection and performance of TBM is presented. An earth pressure balanced type TBM is chosen for the construction of the T1 tunnel. Because of the additional engineering measures taken before excavation in problematic areas, the tunnel was completed with great success within the initially planned timeframe. From this point of view, this study is an important case and may contribute to worldwide tunneling literature.

Novel long-span cable-stayed deck arch bridge: Concept and structural characteristics

To explore a cost-efficient bridge structure system and expand the options for long-span bridges in mountainous regions, we propose an innovative cable-stayed deck arch (CSDA) bridge with significant potential benefits. This paper discusses the conceptualization, structural design considerations, and implementable construction methods of this bridge-type. We trial designed two CSDA bridges with span arrangements of 268 + 350 + 268 m and 280 + 3 × 380 + 280 m to demonstrate the versatility of our proposal in different topographic situations and its ability to accommodate both single and multiple main spans. The finite element analysis confirms the mechanical properties and structural feasibility of the conceptual designs. A comprehensive comparison with other types of bridges under identical conditions reveals that this new hybrid bridge is not only lightweight in structure, excellent in performance, and elegant in form, but also cost savings and with minor environmental impact. The preliminary study indicates that the CSDA bridges are suitable for the construction demand of high-rise pier and long-span bridges in mountainous terrain, and also an economical option for the main span between 350 to 400 m.

Appraising the Feasibility of 3D Printing Construction in New Zealand Housing

The construction industry in New Zealand is significantly impacted by the importance of housing, particularly as urbanisation continues to grow in major cities. Modern construction methods, such as offsite construction and building automation, evolving into digital manufacturing and construction in the industry, have become prominent. Despite the global recognition of 3D printing technology, its adoption in the construction industry in New Zealand is still relatively limited. This study aims to examine the feasibility of 3D printing construction in response to current market challenges, innovation, and the 2050 net-zero carbon goal. Utilising Building Information Modelling (BIM) and Life Cycle Assessment (LCA) approaches, this study investigated the environmental impacts of three housing types: 3D printing (3DP), light steel framed (LSF), and timber. This study used cradle-to-cradle as the system boundary. The results indicate that the 3DP house emits 20% fewer carbon emissions than the traditional timber house and 25% less than the LSF house. Additionally, the 3DP house exhibits a 19% lower annual electric energy consumption than the timber house. Therefore, in response to the growing housing demand in New Zealand, the construction industry must innovate and embrace digital and advanced construction methods, including the adoption of 3D printing.

Leveraging YouTube to aid Construction Hazard Prevention through Design (CHPtD)

Construction Hazard Prevention through Design (CHPtD) is widely recognized as a key approach for preventing injuries in construction workplaces. It prioritizes the safety of construction workers by explicitly tackling potential hazards during the design development phase. This involves proactively incorporating design features aimed at minimizing the risk of workplace injuries. Despite the theoretical promise of CHPtD, practical implementation has faced significant challenges. Notably, prior research has emphasized issues such as designers’ unfamiliarity with construction means and methods, along with their inability to anticipate safety hazards that may arise in the field due to their design choices. In response, proponents of CHPtD have advocated for educational interventions aimed at equipping designers with the essential skills needed for effective implementation of CHPtD. This investigation assessed the effectiveness of YouTube as an educational resource for enhancing hazard recognition in simulated CHPtD review sessions among civil engineering students. YouTube was expected to aid hazard recognition due to its extensive collection of videos featuring various construction operations and related safety hazards. The study utilized a randomized controlled experiment to evaluate treatment effects. The results indicate that YouTube can serve as a valuable tool in supporting CHPtD efforts. Furthermore, the benefits derived from using YouTube were more pronounced when examining specific building elements (e.g. interior upper-level drywall) compared to other elements.

Scoring probability model based on service landing location and ranking points in men’s professional tennis matches

Service is regarded as the most crucial shot in tennis matches, and hence affects the outcome. This study aims to construct a mathematical model that expresses the scoring probability of service shots. Here, “scoring” means that the server wins points in subsequent rallies after a service. The explanatory variables are the service landing location and the ranking points of the players (logarithms of ranking points for the two players). The model construction method is a stepwise regression of the generalized linear model. The model is constructed using more than 110,000 service shots from Association of Tennis Professionals Tour tournaments of 2019. The model comprises four service situations: first/second and ad/deuce sides. The developed model reveals the following facts: in the first service, advantageous locations for the servers are not symmetric between the advantage and deuce sides. Higher-ranked players can win more points than lower-ranked players even if their shots land in easy locations, that is, in the middle of the service court.

Design and Test of Intelligent Farm Machinery Operation Control Platform for Unmanned Farms

The unmanned farm control platform is of great significance in promoting the supervision of farm production with less manpower or autonomous operation of farm machinery and the construction of farm informatization. Addressing the existing control platform for farm location information acquisition is time-consuming, labor-intensive, and lacks the whole process control of multiple types of farm machinery. In this paper, we propose an Internet of Things (IoT) control scheme for intelligent farm machinery operation of unmanned farms and design the access standards for multiple types of farm machinery, as well as realize the remote control of intelligent farm machinery operation by constructing a remote control model. A high-precision map construction method is designed to improve the DeepLabV3+ algorithm to identify fields and roads. The control models of path planning, remote task, remote control, and safety system are built to achieve the remote control of intelligent agricultural machinery operation. The proposed technology is implemented in the platform integration and application tests are carried out. The error of the constructed high-precision map is less than 3 cm, the completeness rate of the automatic boundary extraction rate is 96.71%, and the correctness rate is 95.63%, which can be used to obtain the boundary instead of manual labeling or on-site point picking. The use of the platform for the simultaneous control of three farm machinery operations reduces the number of people in operation and production and reduces the professional requirements of the personnel, which will promote the management of the entire farm by one person or even by no one in the future.

Study of nonlinear gas transport in double-porous and double-permeable coal rocks based on the increasing fractal construction method

Study of nonlinear gas transport in double-porous and double-permeable coal rocks based on the increasing fractal construction method

An open source knowledge graph ecosystem for the life sciences.

Translational research requires data at multiple scales of biological organization. Advancements in sequencing and multi-omics technologies have increased the availability of these data, but researchers face significant integration challenges. Knowledge graphs (KGs) are used to model complex phenomena, and methods exist to construct them automatically. However, tackling complex biomedical integration problems requires flexibility in the way knowledge is modeled. Moreover, existing KG construction methods provide robust tooling at the cost of fixed or limited choices among knowledge representation models. PheKnowLator (Phenotype Knowledge Translator) is a semantic ecosystem for automating the FAIR (Findable, Accessible, Interoperable, and Reusable) construction of ontologically grounded KGs with fully customizable knowledge representation. The ecosystem includes KG construction resources (e.g., data preparation APIs), analysis tools (e.g., SPARQL endpoint resources and abstraction algorithms), and benchmarks (e.g., prebuilt KGs). We evaluated the ecosystem by systematically comparing it to existing open-source KG construction methods and by analyzing its computational performance when used to construct 12 different large-scale KGs. With flexible knowledge representation, PheKnowLator enables fully customizable KGs without compromising performance or usability.

SICK BUILDING SYNDROME: IMPACT OF IDEAL ROOFING ON OCCUPANTS HEALTH

Sick Building Syndrome (SBS) has been defined as a “set of adverse health or discomfort symptoms that individuals experience when they spend time indoors, particularly in office buildings, and that lessen while away from the building” Apte et al. (2000). Various construction elements such as windows, floors, roof designs and construction methods can substantially increase or reduce health and safety levels. This can affect internal and external environments in workplaces. Therefore, the more sustainable the construction elements, the less hazardous or negative impacts on the building construction, the workforce, the environment, the occupants and vice versa. This study aims to use existing building construction elements and designs in North Cyprus to create a framework for developing and evaluating suitable roofing structures for adequate insulation in the North Cyprus residential buildings. This was achieved through research experiments on the construction of building elements, that is, roofing. Most SBS buildings in Cyprus have no roof structure or adequate insulation. Therefore, this experiment was carried out to prove that wrong roof systems contribute to SBS formation in buildings and the rate of SBS effects on the end users.

Mechanical terracing regulates soil physicochemical properties and infiltration processes in the Loess Hilly Region of China

AbstractThe widespread adoption of large‐scale machines has led to a significant shift in terrace construction methods, transitioning from manual labor to mechanical processes. Mechanical terracing, by deeply disturbing the surface and compaction of the soil, has resulted in significant variations in both the soil physicochemical properties (SPCs) and soil infiltration properties (SIPs). However, few studies have been carried out to investigate the impact mechanisms of mechanical terracing on soils. In this study, we conducted detailed field experiments to determine the effects of mechanical terracing on SPCs and SIPs. The results showed that mechanical terracing increased soil compaction and decreased soil porosity and organic matter compared to manual terracing. Moreover, mechanical terracing had lower initial and steady infiltration rates than manual terracing (decreasing by 2.60% and 18.59%, respectively). However, initial and steady infiltration rates significantly improved compared to sloped land, increasing by 20.82% and 54.68%, respectively. The partial least squares path model indicated that bulk weight, organic matter content, and soil texture were the dominant influencing factors of SIPs. The results underscore the critical need to incorporate distinctions between various terrace construction methods into hydrological models for more accurate predictions.

Operation of a Pilot-Scale Biogas Plant Made of Textile Materials and Application of Its Results to a Full-Sized Demonstration Plant

In small German farms, there is a technically usable potential of cattle manure and pig manure ranging from 153 to 187 million tons of fresh matter per year. Since 2021 and 2023, new incentives under the Renewable Energy Sources Act (EEG) have been promoting biogas production in small farms. These incentives, applicable to biogas plants up to 150 kWel, include direct compensations for plants up to 100 kWel and market premiums for those up to 150 kWel. A small biogas plant made of textile materials was designed for both pilot and full-scale applications. Compared to conventional concrete biogas reactors, these textile-based reactors offer a simplified construction and operation, eliminating the need for specialized civil engineering. The primary objective of this research is to demonstrate the process engineering feasibility of biogas reactors based on textile materials for small farm biogas plants (30 to 75 kWel). Another goal is to design the construction method in such a way that this type of system can be built by farmers themselves after type testing on site. Operational insights were gathered from the laboratory plant with a 300-L digester volume, using cattle manure and clover grass silage. To adapt the system to the biogas reactor made of textile materials, the reactor was designed without a stirrer. These insights were considered in the design and approval procedure of the full-sized demonstration biogas plant made of textile materials. The full-size demonstration plant digesters underwent an approval procedure from local authorities, featuring treatment volumes of 120 m3 for the main biogas reactor and 550 m3 for the digestate reactor in an earth basin style. This new type of biogas plant could be built in small farms for self-sufficiency in electrical and thermal energy or for treating sewage sludge in small-scale communal wastewater treatment and biogas plants.

Constructing eRNA-mediated gene regulatory networks to explore the genetic basis of muscle and fat-relevant traits in pigs

BackgroundEnhancer RNAs (eRNAs) play a crucial role in transcriptional regulation. While significant progress has been made in understanding epigenetic regulation mediated by eRNAs, research on the construction of eRNA-mediated gene regulatory networks (eGRN) and the identification of critical network components that influence complex traits is lacking.ResultsHere, employing the pig as a model, we conducted a comprehensive study using H3K27ac histone ChIP-seq and RNA-seq data to construct eRNA expression profiles from multiple tissues of two distinct pig breeds, namely Enshi Black (ES) and Duroc. In addition to revealing the regulatory landscape of eRNAs at the tissue level, we developed an innovative network construction and refinement method by integrating RNA-seq, ChIP-seq, genome-wide association study (GWAS) signals and enhancer-modulating effects of single nucleotide polymorphisms (SNPs) measured by self-transcribing active regulatory region sequencing (STARR-seq) experiments. Using this approach, we unraveled eGRN that significantly influence the growth and development of muscle and fat tissues, and identified several novel genes that affect adipocyte differentiation in a cell line model.ConclusionsOur work not only provides novel insights into the genetic basis of economic pig traits, but also offers a generalizable approach to elucidate the eRNA-mediated transcriptional regulation underlying a wide spectrum of complex traits for diverse organisms.

Regionalization of primary health care units: An iterated greedy algorithm for large-scale instances

In this paper, we study the problem of multi-institutional regionalization of primary health care units. The problem consists of deciding where to place new facilities, capacity expansions for existing facilities, and demand allocation in a multi-institutional system to minimize the total travel distance from demand points to health care units. It is known that traditional exact methods as branch-and-bound are limited to solving small- to medium-size instances of the problem. Given that real world-instances can be large, in this paper we propose an iterated greedy algorithm with variable neighborhood descent search for handling large-scale instances. Within this solution framework, several methods are developed. A greedy constructive method and two deconstruction strategies are developed. Another interesting component is the exact optimization of a demand allocation subproblem that is obtained when the location of facilities is previously fixed. An empirical assessment using real-world data from the State of Mexico’s Public Health Care System is carried out. The results demonstrate the effectiveness of the proposed metaheuristic in handling large-scale instances.

Research on the Construction and Application of an Intelligent Education Learner Model Based on the UTAUT Theory

With the rapid development of computer technology, a new educational model, the innovative education learner model, has emerged as a product of the deep integration of technology and education. In this paper, we will begin by organizing the theories and models related to technology acceptance. We will select the UTAUT model, known for its high explanatory power, as the theoretical framework. Subsequently, we will comprehensively analyze the dataset and conduct in-depth habit mining. The effectiveness of applying K-means concepts to address the classification of clusters of learners’ learning habits is confirmed. The feasibility of the LSTM algorithm in predicting learners for exercise responses is also demonstrated. Next, a learning cluster construction method based on intelligent learner clustering is proposed. The methods of MDS+K-means and spectral clustering are selected for clustering. Learning clusters are constructed, and the performance of the two types of algorithms is compared and analyzed. Finally, the enhanced text feature extraction algorithm is utilized to design and implement the corresponding system for the practical application of the innovative educational learner model. The final experiment proves that the text features extracted by the model are effective, with an error rate of only about 2.8%, thus demonstrating that the intelligent educational learning model in this paper is reasonable.

Enhancing Thermal Performance of Thermodynamic Cycle through Zeotropic Mixture Composition Regulation: An Overview

Composition regulation of zeotropic mixture working fluid for a thermodynamic cycle is an effective way to improve energy conversion efficiency, which offers the potential to construct efficient, flexible and intelligent cycles. Current research on cycle construction of zeotropic mixture composition regulation still heavily relies on construction methods using pure working fluids, where the characteristics of flexible composition variations fail to be utilized. In this paper, the research progress of cycle construction methods and composition regulated structures are comprehensively reviewed, aiming to clarify the potential for enhancing a thermodynamic cycle based on composition regulation. The characteristics of different cycle construction methods are firstly summarized and compared. Then, the composition-regulated structures of a physical-based method and chemical-based method are introduced, and the composition regulation performance are also concluded. Finally, a future outlook on the cycle design and structure design is provided. The review results show that the combination of 3D construction method and superstructure/intelligences construction method has the potential to maximize the cycle performance, where the improvement of each thermal process and the optimization of complex cycles can be considered simultaneously. The composition regulation based on a passive physical method has the advantage of being readily applicable; however, the composition regulation range is limited. In addition, the distillation and hydrate method have a wider regulation range through extra energy input, where the trade-off between energy consumption and cycle performance improvement should be considered in the future. This study greatly assists in the design of thermodynamic cycles involving zeotropic mixture composition regulation and the corresponding composition regulation structures.

Performance of Eco-Friendly Zero-Cement Particle Board under Harsh Environment

The increasing scarcity of virgin natural resources and the need for sustainable waste management in densely populated urban areas have heightened the importance of developing new recycling technologies. One promising approach involves recycling agricultural waste in construction applications and transforming it into secondary products. This is anticipated to reduce the demand for new resources and lower the environmental impact, aligning with industrial ecology principles. Combined with a low carbon emission binder (i.e., alkali-activated), utilizing agro-waste to produce zero-cement particle boards is a promising method for green construction. Traditionally, particle boards are engineered from wood or agricultural waste products that are pressed and bonded with a binder, such as cement or synthetic resins. However, alternative binders replace cement in zero-cement particle boards to address environmental concerns, such as the carbon dioxide emissions associated with cement production. This study investigated the effects of accelerated aging on the performance of alkali-activated agro-waste particle boards. Accelerated aging conditions simulate natural aging phenomena. Repeated wetting–drying and freezing–thawing cycles increased water absorption and thickness swelling and reduced flexural strength. The thermal performance of the alkali-activated particle boards did not exhibit significant changes. Hence, it was confirmed that agro-waste has a high potential for utilization in producing particle boards provided that the working environment is carefully selected to optimize performance.

Development of a Method for Preservation Appraisal of Historic Transportation Structures and Its Application for the Masonry Bridges of Mimar Sinan

Social history is closely related to the history of transportation. Since the establishment of the first settlements, bridges have been fundamental elements along established land routes, providing mobility, accessibility, reliability, safety, and comfort to their users over the many elements that act as obstacles along these routes. Supporting commerce, trade, and unfortunately wars, these bridges were instrumental in the efficient use of time, enhancing the possibilities of development and progress through interaction between the groups of people using them. Although quite variable in type and dimensions, bridges are unique elements of civil engineering. The effort required to construct them was and remains very demanding in the time spent, techniques used, and resources consumed. Before the advances in construction methods beginning with the use of iron and steam engines following the Industrial Revolution, stone masonry arch construction with the use of timber false-works, masonry blocks, masonry piers, and timber piles, mechanisms of pulleys and levers provided the fundamental materials and techniques used to construct lasting bridges. Along the many examples of masonry arch bridges from far back in history, there is a unique group of stone masonry bridges dating back to the 16th century and constructed by a single polymath, Mimar Sinan. This article will investigate the characteristics of the bridges built by Sinan and their evaluation for preservation and implementation in contemporary urban life through a proposed preservation appraisal method.

An Approach to Distributed Systems from Orderings and Representability

In the present paper, we propose a new approach on ‘distributed systems’: the processes are represented through total orders and the communications are characterized by means of biorders. The resulting distributed systems capture situations met in various fields (such as computer science, economics and decision theory). We investigate questions associated to the numerical representability of order structures, relating concepts of economics and computing to each other. The concept of ‘quasi-finite partial orders’ is introduced as a finite family of chains with a communication between them. The representability of this kind of structure is studied, achieving a construction method for a finite (continuous) Richter–Peleg multi-utility representation.