Methodology For Construction Research Articles

Chemical Stability of Metal Halide Perovskite Detectors

Metal halide perovskite (MHP) detectors are highly esteemed for their outstanding photoelectric properties and versatility in applications. However, they are unfortunately prone to degradation, which constitutes a significant barrier to their sustained performance. This review meticulously delves into the causes leading to their instability, predominantly attributable to factors such as humidity, temperature, and electric fields and, notably, to various radiation factors such as X-rays, γ-rays, electron beams, and proton beams. Furthermore, it outlines recent advancements in strategies aimed at mitigating these detrimental effects, emphasizing breakthroughs in composition engineering, heterostructure construction, and encapsulation methodologies. At last, this review underscores the needs for future improvements in theoretical studies, material design, and standard testing protocols. In the pursuit of optimizing the chemical stability of MHP detectors, collaborative efforts are in an imperative need. In this way, broad industrial applications of MHP detectors could be achieved.

Editorial: Innovative materials and optimization methodologies for green building design and construction

Editorial: Innovative materials and optimization methodologies for green building design and construction

Ray Tracing Meets Terahertz: Challenges and Opportunities

It is very likely that the terahertz (THz) spectrum will be used for the operation of the upcoming 6th-generation (6G) wireless communication systems. This article presents a study for the application of ray tracing (RT) for THz channel modeling. Because of the extremely short wavelengths of THz signals, we argue that signal propagation in the THz spectrum can be precisely modeled by employing RT techniques and thus accurate channel models can be obtained in an efficient manner. We first review recent research and standardization activities related with RT-assisted channel modeling which mainly deal with millimeter-wave (mmWave) applications and to a much lesser extent have been applied the THz spectrum. Then, we present the basic THz wave propagation characteristics, including reflection, scattering, penetration, shadowing as well as signal absorption by atmospheric molecules and tiny particles under different weather conditions. The methodologies for the appropriate construction of target scenarios are presented as well as efficient computational methods for the effective RT operation. Finally, various research and development (R&D) challenges related to RT-based channels for future THz communication systems are identified and possible solutions are highlighted.

Capacitive Bionic Magnetic Sensors Based on One-Step Biointerface Preparation.

Magnetic biomolecule-based bionic magnetic field sensors are anticipated to open up novel pathways for magnetic field detection. The detection range and accuracy of current bionic magnetic field sensors are limited, and little work is based on the capacitive response principle. We successfully developed a biochemical interface with an extralarge target-receptor size ratio, which can be manufactured in a single step for weak magnetic field detection across a wide frequency range, and we used electrochemical capacitance as a magnetic field change conduction strategy. The thickness-controllable nanoscale bovine serum albumin/graphene layer on an indium tin oxide working electrode combines with the one-step preparation method to immobilize the MagR/Cry4 complex. This capacitive bionic magnetic sensor can achieve the detection range of 0-120 mT. This biointerface design strategy obtains the further improvement of the performance of this bionic magnetic field sensor. Furthermore, the biointerface construction and optimization methodology in this proposal has potential applications in the design of other medical biosensors.

ANALYSIS OF ENVIRONMENTALLY SUSTAINABLE PROJECTS IN THE FIELD OF GREEN ARCHITECTURE: USE OF NATURAL MATERIALS AND RENEWABLE ENERGY SOURCES

The article explores contemporary architectural trends focused on the establishment of sustainable and ecologically responsible environments. It scrutinizes projects incorporating natural building materials and renewable energy sources, evaluating their environmental impact and discerning their role in fostering sustainable development. Additionally, the article delves into alternative approaches for the utilization of materials during both the construction and operational phases of green buildings. A comprehensive analysis is presented, elucidating the intricacies of the "green building" concept, notable for its pronounced benefits in curtailing energy consumption for heating purposes. The salient characteristic of such structures lies in the integration of green design strategies and cutting-edge building materials. The article meticulously examines the efficacy of energy utilization within the context of a "green" architectural paradigm. Emphasis is placed on technologies and solutions conducive to diminishing energy expenditure, particularly in the domain of heating. This encompasses the deployment of renewable energy sources, optimal architectural configurations, and innovative engineering systems. The investigation reveals that the integration of green methodologies in construction is contingent not solely upon the reduction of energy consumption but also on the adoption of environmentally friendly and sustainable materials. Such materials not only serve to ameliorate the structural quality but also enhance the comfort of indoor spaces. The findings proffered by the analysis hold the potential to unveil novel avenues for the progressive refinement of green architecture and its application in construction.

Structural Performance Evaluation of Cross Dapped Connection for Vertical Wall to Wall Connection of Precast Wall Panel

In the context of Industrialised Building Systems (IBS), precast concrete buildings are composed of multiple structural members that are interconnected through different techniques. The adoption of precast concrete wall panels has gained significant traction in contemporary construction methodologies. Nevertheless, the utilization of dapped connections specifically designed for non-load bearing applications in precast walls incorporating recycled concrete aggregate (RCA) remains largely unexplored and limited in practice. This research proposes a new wall-to-wall connection for precast wall panels to enhance the constructability of IBS for non-load bearing walls. The novel Cross Dapped (CD) design enables horizontal panel installation in confined areas with existing structural frames, while ensuring the connection’s strength as a non-load bearing wall to prevent failure. Uniformly distributed loads are applied until sample failure, recording compressive load patterns, deflection, stress-strain patterns, and crack patterns on the wall surface. The CD connection demonstrates applicability for precast wall-towall connections, improving IBS constructability with its innovative design and locking system. Overall, this research explores and proposes an efficient and structurally sound wall-to-wall connection design for precast wall panels of non-load bearing system, facilitating the adoption of IBS methods, and improving the overall quality and constructability of building systems.

Reporting on the Development of a Web-Based Prototype Dashboard for Construction Design Managers, Achieved through Design Science Research Methodology (DSRM)

Construction Design Management (DM) involves the coordination of design processes and activities to ensure quality project design, yet it involves many challenges. This study reports on a collaborative Knowledge Transfer Partnership (KTP) project with a Case Study Organization (CSO) that tackled several issues faced by construction design managers. Employing a design science research methodology (DSRM), qualitative analysis of semi-structured interviews with purposefully identified design managers uncovered real-world concerns around design co-ordination and performance monitoring. To address these concerns, a web-based design management prototype dashboard was developed using typical project data to aid in the management of design coordination, task prioritization, and reporting functionalities. The web-based Design Management prototype dashboard enhances design management productivity in construction firms by monitoring design production, assessing designer performance trends, and focusing on Technical Queries (TQs) and Requests for Information (RFIs). Digitalizing selected design management processes improves efficiency and productivity. The visual reporting of the dashboard enables design production monitoring at project and portfolio levels, assesses trends in designer performance, and maintains focus on TQs and RFIs. Demonstrating how web-based Design Management dashboards can enhance productivity, this study emphasizes practical solutions derived from employing a design science research methodology. The development and application of the web-based dashboard contribute to the growing evidence that employing design science research methodology in construction can yield tangible solutions to address real-world construction concerns.

The role of BIM as a lean tool in design phase

In the architectural, engineering, and construction industry, poor visualization of construction processes and lack of information exchange between different work teams can lead to poor performance. To address these challenges, lean construction methodologies aim to reduce and eliminate waste in construction processes, while BIM technology aims to enhance collaboration between project team members. In general, these technologies can be used together to improve project management and cost reduction. This can be achieved through improving workflow and coordination, enhancing interaction among project members, and using available tools to analyze and improve work. Many aspects of the integration between LC and BIM have been studied, and researchers have come up with some findings and recommendations. Most studies previously demonstrated theoretically that cost reductions using BIM techniques are significant compared to the traditional approach of project management. This is what this study proved practically by applying BIM in the design of a building which is quite successful in construction as it identifies the main causes of construction waste such as reducing waiting time and reducing non-value-added work by using Dynamo to develop these designs. So, the research problem comes, which is how to keep up with development in the field of construction by applying different BIM programs, which results in reducing the time and cost used in design. BIM is a technology that aims to enhance project management and cut costs. A digital representation of the project that contains all the data required for planning, managing, and carrying out the project is created using BIM.

An empirical approach and practical framework for a decentralized Ethereum Ecosystem Index (EEI).

Stock market indices are pivotal tools for establishing market benchmarks, enabling investors to navigate risk and volatility while capitalizing on the stock market's prospects through index funds. For participants in decentralized finance (DeFi), the formulation of a token index emerges as a vital resource. Nevertheless, this endeavor is complex, encompassing challenges such as transaction fees and the variable availability of tokens, attributed to their brief history or limited liquidity. This research introduces an index tailored for the Ethereum ecosystem, the leading smart contract platform, and conducts a comparative analysis of capitalization-weighted (CW) and equal-weighted (EW) index performances. The article delineates exhaustive criteria for token eligibility, intending to serve as a comprehensive guide for fellow researchers. The results indicate a consistent superior performance of CW indices over EW indices in terms of return and risk metrics, with a 30-constituent CW index outshining its counterparts with varied constituent numbers. The recommended CW30 index demonstrates substantial advantages in comparison to established benchmarks, including prominent indices like DeFi Pulse Index (DPI) and CRypto IndeX (CRIX). Additionally, the article explores the practicality of implementing the CW30 in Layer 2 networks of the Ethereum Ecosystem, advocating for the Arbitrum infrastructure as the optimal choice for the decentralized crypto index protocol herein referred to as the Ethereum Ecosystem Index (EEI). The study's insights aspire to enrich the DeFi ecosystem, offering a nuanced understanding of network selection and a strategic framework for implementation. This research significantly enhances the existing literature on index construction and performance within the Ethereum ecosystem. To our knowledge, it represents a pioneering comprehensive analysis of an index that accurately mirrors the Ethereum market, advancing our comprehension of its intricacies and wider ramifications. Moreover, this study stands as one of the initial thorough examinations of index construction methodologies within the nascent asset class of crypto. The insights gleaned provide a pragmatic approach to index construction and introduce an index poised to serve as a benchmark for index products. In illuminating the unique facets of the Ethereum ecosystem, this research makes a substantial contribution to the current discourse on crypto, offering valuable perspectives for investors, market stakeholders, and the ongoing exploration of digital assets.

3D printed concrete using Portland pozzolana cement - fly ash based

This project investigates the feasibility and properties of 3D printed concrete using Portland Pozzolana Cement (PPC). The increasing demand for construction materials, particularly ordinary Portland cement (OPC), has led to a surge in its usage. Consequently, Portland Pozzolana Cement (PPC) has gained popularity as an alternative due to its advantageous properties. PPC, characterized by its enhanced durability and sustainability, has become a preferred choice in the construction industry, offering versatility and reliability in various construction applications. The main focus of the project is economical printing of concrete structures through 3D printing technology. With sustainability and cost-effectiveness as paramount considerations, the study delves into refining the mix proportions ideal for 3D printing applications. By harnessing the potential of Portland Pozzolana Cement (PPC) with a 35% fly ash content, the aim is to strike a balance between structural integrity, workability, and affordability. It examines various key properties essential for successful 3D printing, such as extrudability, printability, flowability, buildability, setting time and thixotropic open time. Furthermore, the project examines the strength of 3D printed concrete mixes. Through testing and studying these properties, the research aims to contribute to the advancement of eco-friendly and efficient construction practices by using 3D printing and innovative cementitious materials. The findings from this study provide valuable insights to enhance the efficiency of 3D printing and the strength of printed concrete structures, including beams, walls, and other structural elements. By implementing these ideas, potential advancements in construction methodologies could be realized, facilitating more robust and cost-effective building practices. This research aims to contribute to the ongoing evolution of 3D printing technology in construction, ultimately fostering innovation and sustainability in the built environment.

Analysis of the application of neural network technologies in predicting equipment failure in production

The relevance. The article considers the solution to the problem of analyzing and predicting changes in the dynamics of measuring instrument readings and identifying patterns describing the course and possible periods of failures of technological process equipment by constructing a predictive time series model. A critically important infrastructure facility of a thermal power plant was selected as the studied one – a water pump for pumping process water into neutralizer tanks (the first stage of chemical water purification) located in the chemical workshop of the Krasnoyarsk CHP-3. The general methodology of model construction, requirements for input data arrays, preprocessing algorithms for the formation of samples used for training and testing models are described. To build a predictive model, the work used elements such as recurrent layers of long-term short- term memory LSTM, MinMaxScaler regularization, Dropout layer to reduce the effect of retraining, the ‘Adam’ optimizer using error back propagation methods and optimization using the steepest descent method using conjugate gradients, the learning error function is the average root of the error (Root Mean Squared Error, RMSE), as well as plot_predictions visualization. The algorithms are implemented in Python, in the Anaconda Jupyter Nootebook core. Based on the results of testing the training, the model showed sufficient performance of this method, since the time spent on creating the model and obtaining a forecast plays an important role when launching the model in real production conditions. In conclusion, recommendations are given to improve the accuracy of the forecast, the developed interface of the production system is presented and the directions of future research in this area are outlined.

Experimental models for preclinical research in kidney disease.

Acute kidney injury (AKI) and chronic kidney disease (CKD) are significant public health issues associated with a long-term increase in mortality risk, resulting from various etiologies including renal ischemia, sepsis, drug toxicity, and diabetes mellitus. Numerous preclinical models have been developed to deepen our understanding of the pathophysiological mechanisms and therapeutic approaches for kidney diseases. Among these, rodent models have proven to be powerful tools in the discovery of novel therapeutics, while the development of kidney organoids has emerged as a promising advancement in the field. This review provides a comprehensive analysis of the construction methodologies, underlying biological mechanisms, and recent therapeutic developments across different AKI and CKD models. Additionally, this review summarizes the advantages, limitations, and challenges inherent in these preclinical models, thereby contributing robust evidence to support the development of effective therapeutic strategies.

Approaches for Benchmarking Single-Cell Gene Regulatory Network Methods.

Gene regulatory networks are powerful tools for modeling genetic interactions that control the expression of genes driving cell differentiation, and single-cell sequencing offers a unique opportunity to build these networks with high-resolution genomic data. There are many proposed computational methods to build these networks using single-cell data, and different approaches are used to benchmark these methods. However, a comprehensive discussion specifically focusing on benchmarking approaches is missing. In this article, we lay the GRN terminology, present an overview of common gold-standard studies and data sets, and define the performance metrics for benchmarking network construction methodologies. We also point out the advantages and limitations of different benchmarking approaches, suggest alternative ground truth data sets that can be used for benchmarking, and specify additional considerations in this context.

Development and Validation of a Farmer’s Focused Digital Literacy Scale

The research aimed to develop a tool for assessing the digital literacy of farmers towards ICT-led agriculture in India. The study identified three dimensions namely digital knowledge, attitude, and digital competency, for a farmer-focused digital literacy scale. Digital competency consisted of seven sub-dimensions viz device setup, digital communication and collaboration, digital content creation and sharing, digital safety, problem-solving, digital marketing, and digital payment. The digital literacy scale was developed with Likert scale construction methodology. An overall mean relevancy score of 5.693 was obtained. A pilot study was conducted with 60 farmers in a non-sampled area. The t value was calculated, and the cutoff value for item selection was set at > 1.75. For assessing internal consistency reliability using the Spearman-Brown formula, a reliability coefficient of 0.850 was found. The calculation of Cronbach’s alpha gave a value of 0.743, indicating that the scale shows a high level of consistency in its measurement. The standard farmers-focused digital literacy scale comprised of 30 items, and its content validity was determined with expert opinions.

A Novel Perspective in Construction: Analysing the Effects of 3-D Printing Innovation

The sector of production has witnessed a transformative shift with the combination of 3-D printing technologies, providing novel strategies to design, production, and constructing practices. This investigation explores three primary 3D printing techniques: Extrusion-type techniques, Powder Bonding, and Spray Methodologies, each contributing uniquely to the sustainable development of the construction industry. We delve into the usage of revolutionary materials, including gelatin-based composites and geopolymers, and verify their effect on performance, sustainability, and structural integrity. The research underscores the importance of each approach's technique to diminishing material waste, improving durability, and facilitating complex architectural designs. Although by analysing latest improvements and experimental findings, the study gives insights into the evolving perspectives of construction methodologies, highlighting the potential for advanced environmental compatibility, cost-effectiveness, and architectural flexibility.Construction industry, 3D printing, extrusion, spray, powder bonding, environmentally friendly.

Study of the construction techniques, materials and architectural prospectives of ancient monumental structures in Allahabad City, India

This research examines the construction methodologies, materials, and architectural principles employed in creating ancient monumental structures in Allahabad (now Prayagraj), India. Despite being erected over 600 years ago, these structures stand resiliently among the evolution of modern construction techniques and seismic safety standards. The history of Prayagraj can be traced back to ancient times. The city was initially referenced in the ancient Hindu scriptures, known as the Vedas, as a sacred destination. Further, established by the Mughal Empire under Akbar’s reign in 1583, Allahabad City witnessed the construction of numerous monumental structures using robust techniques involving stone, brick masonry, and timber materials bonded together with thin mortar and plaster. Many of these ancient edifices, erected during this period, continue to serve various functions today, reflecting the enduring craftsmanship of their builders. In this study, we have identified prestigious monuments for examination, utilizing visual inspection to gain deeper insights into the emphasized construction materials and techniques. Notably, mortar is a critical component in construction and structural connections. Furthermore, our investigation reveals the diverse range of materials utilized for binding, plastering, painting, and other decorative purposes during construction. However, it is evident that some of these monuments have endured significant wear and tear over time, resulting in major cracks and damage to their structural elements and construction materials. Through this exploration, we aim to unveil the intricate craftsmanship and architectural brilliance that characterize Allahabad’s ancient monumental structures, while also highlighting the preservation challenges posed by ageing and environmental factors.

Data‐Driven Decision Algorithm for Open Caisson Foundation Construction

The accuracy of instructions for the extraction of large open caissons directly affects the construction quality and safety. This study is focused on developing a smart construction methodology for predicting open caisson excavation instructions. The proposed approach aims to reduce the errors in excavation instructions attributable to the subjective and varying experiences of decision‐makers. The multilabel classification task of predicting the instructions of large open caisson excavation is accomplished through the problem analysis. The study conducted a comparative analysis of a multilayer perceptron model, a classifier chain model, and a multilabel K‐nearest neighbor model (MLKNN) based on Hamming loss and accuracy. The results revealed that MLKNN exhibits significant differences from the other models and is most suitable for predicting open caisson excavation instructions. Furthermore, the traditional MLKNN model was improved by refining the normalization and distance measurement methods for the open caisson scenario. The prediction accuracy of the improved MLKNN model is 89.04% for the excavation instructions and 98.63% for the nonexcavation decisions. The successful prediction of excavation instructions for a large open caisson can compensate for the lack of data mining capability of the existing monitoring system. This can reduce construction risks. Finally, this study discussed the robustness of the improved MLKNN in a real project, highlighting the model’s high accuracy during the midstage of open caisson construction.

Framework and construction methodology of underground engineering domain knowledge large language model: UndergrGPT

Framework and construction methodology of underground engineering domain knowledge large language model: UndergrGPT

Standard Datasets for Autonomous Navigation and Mapping: A Full-Stack Construction Methodology

Standard Datasets for Autonomous Navigation and Mapping: A Full-Stack Construction Methodology

Bond strength of substrate with repair material for masonry structures

Masonry infrastructure repair is a daunting challenge. The short intervention and limited resources have led to the loss of novel rendering and finishing materials. In the present study, the bibliometric analysis is conducted for period 2003 to 2022. Co-cited reference analysis, keywords, cluster, and temporal evolution were used for analysis using Citespace software. Additionally, summary of suitable content showed that major challenges in this field are disparities in the properties of old mortar and new materials and the lack of documents to understand nature and methodology of construction. Based on the analysis and content review, a suggestive technique is proposed inculcating four aspects: Finite element analysis, preparing numerical models, improvised techniques for bonding mechanisms and understanding mechanical attributes.