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1 – 10 of over 1000
Article
Publication date: 26 March 2024

Keyu Chen, Beiyu You, Yanbo Zhang and Zhengyi Chen

Prefabricated building has been widely applied in the construction industry all over the world, which can significantly reduce labor consumption and improve construction…

Abstract

Purpose

Prefabricated building has been widely applied in the construction industry all over the world, which can significantly reduce labor consumption and improve construction efficiency compared with conventional approaches. During the construction of prefabricated buildings, the overall efficiency largely depends on the lifting sequence and path of each prefabricated component. To improve the efficiency and safety of the lifting process, this study proposes a framework for automatically optimizing the lifting path of prefabricated building components using building information modeling (BIM), improved 3D-A* and a physic-informed genetic algorithm (GA).

Design/methodology/approach

Firstly, the industry foundation class (IFC) schema for prefabricated buildings is established to enrich the semantic information of BIM. After extracting corresponding component attributes from BIM, the models of typical prefabricated components and their slings are simplified. Further, the slings and elements’ rotations are considered to build a safety bounding box. Secondly, an efficient 3D-A* is proposed for element path planning by integrating both safety factors and variable step size. Finally, an efficient GA is designed to obtain the optimal lifting sequence that satisfies physical constraints.

Findings

The proposed optimization framework is validated in a physics engine with a pilot project, which enables better understanding. The results show that the framework can intuitively and automatically generate the optimal lifting path for each type of prefabricated building component. Compared with traditional algorithms, the improved path planning algorithm significantly reduces the number of nodes computed by 91.48%, resulting in a notable decrease in search time by 75.68%.

Originality/value

In this study, a prefabricated component path planning framework based on the improved A* algorithm and GA is proposed for the first time. In addition, this study proposes a safety-bounding box that considers the effects of torsion and slinging of components during lifting. The semantic information of IFC for component lifting is enriched by taking into account lifting data such as binding positions, lifting methods, lifting angles and lifting offsets.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

Abstract

Details

Understanding Intercultural Interaction: An Analysis of Key Concepts, 2nd Edition
Type: Book
ISBN: 978-1-83753-438-8

Open Access
Article
Publication date: 15 February 2024

Di Kang, Steven W. Kirkpatrick, Zhipeng Zhang, Xiang Liu and Zheyong Bian

Accurately estimating the severity of derailment is a crucial step in quantifying train derailment consequences and, thereby, mitigating its impacts. The purpose of this paper is…

Abstract

Purpose

Accurately estimating the severity of derailment is a crucial step in quantifying train derailment consequences and, thereby, mitigating its impacts. The purpose of this paper is to propose a simplified approach aimed at addressing this research gap by developing a physics-informed 1-D model. The model is used to simulate train dynamics through a time-stepping algorithm, incorporating derailment data after the point of derailment.

Design/methodology/approach

In this study, a simplified approach is adopted that applies a 1-D kinematic analysis with data obtained from various derailments. These include the length and weight of the rail cars behind the point of derailment, the train braking effects, derailment blockage forces, the grade of the track and the train rolling and aerodynamic resistance. Since train braking/blockage effects and derailment blockage forces are not always available for historical or potential train derailment, it is also necessary to fit the historical data and find optimal parameters to estimate these two variables. Using these fitted parameters, a detailed comparison can be performed between the physics-informed 1-D model and previous statistical models to predict the derailment severity.

Findings

The results show that the proposed model outperforms the Truncated Geometric model (the latest statistical model used in prior research) in estimating derailment severity. The proposed model contributes to the understanding and prevention of train derailments and hazmat release consequences, offering improved accuracy for certain scenarios and train types

Originality/value

This paper presents a simplified physics-informed 1-D model, which could help understand the derailment mechanism and, thus, is expected to estimate train derailment severity more accurately for certain scenarios and train types compared with the latest statistical model. The performance of the braking response and the 1-D model is verified by comparing known ride-down profiles with estimated ones. This validation process ensures that both the braking response and the 1-D model accurately represent the expected behavior.

Details

Smart and Resilient Transportation, vol. 6 no. 1
Type: Research Article
ISSN: 2632-0487

Keywords

Article
Publication date: 6 February 2024

Andrea Lucherini and Donatella de Silva

Intumescent coatings are nowadays a dominant passive system used to protect structural materials in case of fire. Due to their reactive swelling behaviour, intumescent coatings…

Abstract

Purpose

Intumescent coatings are nowadays a dominant passive system used to protect structural materials in case of fire. Due to their reactive swelling behaviour, intumescent coatings are particularly complex materials to be modelled and predicted, which can be extremely useful especially for performance-based fire safety designs. In addition, many parameters influence their performance, and this challenges the definition and quantification of their material properties. Several approaches and models of various complexities are proposed in the literature, and they are reviewed and analysed in a critical literature review.

Design/methodology/approach

Analytical, finite-difference and finite-element methods for modelling intumescent coatings are compared, followed by the definition and quantification of the main physical, thermal, and optical properties of intumescent coatings: swelled thickness, thermal conductivity and resistance, density, specific heat capacity, and emissivity/absorptivity.

Findings

The study highlights the scarce consideration of key influencing factors on the material properties, and the tendency to simplify the problem into effective thermo-physical properties, such as effective thermal conductivity. As a conclusion, the literature review underlines the lack of homogenisation of modelling approaches and material properties, as well as the need for a universal modelling method that can generally simulate the performance of intumescent coatings, combine the large amount of published experimental data, and reliably produce fire-safe performance-based designs.

Research limitations/implications

Due to their limited applicability, high complexity and little comparability, the presented literature review does not focus on analysing and comparing different multi-component models, constituted of many model-specific input parameters. On the contrary, the presented literature review compares various approaches, models and thermo-physical properties which primarily focusses on solving the heat transfer problem through swelling intumescent systems.

Originality/value

The presented literature review analyses and discusses the various modelling approaches to describe and predict the behaviour of swelling intumescent coatings as fire protection for structural materials. Due to the vast variety of available commercial products and potential testing conditions, these data are rarely compared and combined to achieve an overall understanding on the response of intumescent coatings as fire protection measure. The study highlights the lack of information and homogenisation of various modelling approaches, and it underlines the research needs about several aspects related to the intumescent coating behaviour modelling, also providing some useful suggestions for future studies.

Details

Journal of Structural Fire Engineering, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2040-2317

Keywords

Article
Publication date: 5 January 2024

Hongqiang Sang, Fang Huang, Wei Lu, Rui Han and Fen Liu

The patient-side manipulator (PSM) achieves high torque capability by combining harmonic servo system with high reduction ratio and low torque motor. However, high reduction ratio…

Abstract

Purpose

The patient-side manipulator (PSM) achieves high torque capability by combining harmonic servo system with high reduction ratio and low torque motor. However, high reduction ratio can increase inertia and decrease compliance of the manipulator. To enhance the backdrivability of the minimally invasive surgical robot, this paper aims to propose a resistance torque compensation algorithm.

Design/methodology/approach

A resistance torque compensation algorithm based on dynamics and Luenberger observer is proposed. The dynamics are established, considering joint flexibility and an improved Stribeck friction model. The dynamic parameters are experimentally identified by using the least squares method. With the advantages of clear structure, simple implementation and fast solution speed, the Luenberger observer is selected to estimate the unmeasured dynamic information of PSM and realize the resistance torque compensation.

Findings

For low-speed surgical robots, the centrifugal force term in the dynamic model can be simplified to reduce computational complexity. Joint flexibility and an improved Stribeck friction model can be considered to improve the accuracy of the dynamic model. Experiment results show that parameter identification and estimated results of the Luenberger observer are accurate. The backdrivability of the PSM is enhanced in ease and smoothness.

Originality/value

This algorithm provides potential application prospects for surgical robots to maintain high torque while remaining compliant. Meanwhile, the enhanced backdrivability of the manipulator helps to improve the safety of the preoperative manual adjustment.

Details

Industrial Robot: the international journal of robotics research and application, vol. 51 no. 1
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 13 February 2024

Wenqi Mao, Kexin Ran, Ting-Kwei Wang, Anyuan Yu, Hongyue Lv and Jieh-Haur Chen

Although extensive research has been conducted on precast production, irregular component loading constraints have received little attention, resulting in limitations for…

Abstract

Purpose

Although extensive research has been conducted on precast production, irregular component loading constraints have received little attention, resulting in limitations for transportation cost optimization. Traditional irregular component loading methods are based on past performance, which frequently wastes vehicle space. Additionally, real-time road conditions, precast component assembly times, and delivery vehicle waiting times due to equipment constraints at the construction site affect transportation time and overall transportation costs. Therefore, this paper aims to provide an optimization model for Just-In-Time (JIT) delivery of precast components considering 3D loading constraints, real-time road conditions and assembly time.

Design/methodology/approach

In order to propose a JIT (just-in-time) delivery optimization model, the effects of the sizes of irregular precast components, the assembly time, and the loading methods are considered in the 3D loading constraint model. In addition, for JIT delivery, incorporating real-time road conditions in the transportation process is essential to mitigate delays in the delivery of precast components. The 3D precast component loading problem is solved by using a hybrid genetic algorithm which mixes the genetic algorithm and the simulated annealing algorithm.

Findings

A real case study was used to validate the JIT delivery optimization model. The results indicated this study contributes to the optimization of strategies for loading irregular precast components and the reduction of transportation costs by 5.38%.

Originality/value

This study establishes a JIT delivery optimization model with the aim of reducing transportation costs by considering 3D loading constraints, real-time road conditions and assembly time. The irregular precast component is simplified into 3D bounding box and loaded with three-space division heuristic packing algorithm. In addition, the hybrid algorithm mixing the genetic algorithm and the simulated annealing algorithm is to solve the 3D container loading problem, which provides both global search capability and the ability to perform local searching. The JIT delivery optimization model can provide decision-makers with a more comprehensive and economical strategy for loading and transporting irregular precast components.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

Article
Publication date: 6 March 2024

George Okello Candiya Bongomin, Pierre Yourougou, Rebecca Balinda and Joseph Baleke Yiga Lubega

Currently, consumers of financial products and services have become more vulnerable to predatory financial institutions, especially in the aftermath of Covid-19 pandemic…

Abstract

Purpose

Currently, consumers of financial products and services have become more vulnerable to predatory financial institutions, especially in the aftermath of Covid-19 pandemic. Therefore, financial consumers like the persons with disabilities (PWDs) should be equipped with knowledge and skills to help them to evaluate complex financial products on offer in financial markets, especially in developing countries to avoid being victims of fraudulent lending. The purpose of this study is to establish whether customized financial literacy mediates the relationship between financial consumer protection and financial inclusion of PWDs’ owned MSMEs in rural Uganda post Covid-19 pandemic.

Design/methodology/approach

SmartPLS 4.0 was used to construct the measurement and structural equation models to test whether customized financial literacy significantly mediates the relationship between financial consumer protection and financial inclusion of PWDs’ owned MSMEs in rural Uganda post Covid-19 pandemic.

Findings

The results revealed a partial mediating effect of customized financial literacy in the relationship between financial consumer protection and financial inclusion of PWDs’ owned MSMEs in rural Uganda post Covid-19 pandemic. Conducting customized financial literacy increases financial consumer protection by 12 percentage points to promote financial inclusion of PWDs’ owned MSMEs in rural Uganda post Covid-19 pandemic.

Research limitations/implications

This study focused only on customized financial literacy and financial consumer protection to promote universal financial inclusion of PWDs’ owned MSMEs post Covid-19 pandemic. Future studies may use data collected from other vulnerable groups amongst the unbanked population in developing countries, Uganda inclusive. In addition, this study also collected only quantitative data from the selected population. Further studies can be conducted using key informant interviews and focused group discussion to get the perceptions of the PWDs on being protected from exploitation by unscrupulous financial institutions.

Practical implications

The findings from this study can help policymakers in developing countries like Uganda to revise the existing consumer protection law to include strong clauses on protection of people with special needs like the PWDs. The law must ensure that they are not exploited by financial institutions because of their conditions. The law ought to make sure that the PWDs are educated about their rights in the financial market place and all information on financial products offered by financial institutions should be simplified and interpreted to them before they make consumption decisions.

Originality/value

To the best of the authors’ knowledge, the present study is amongst the first few studies to provide a meticulous and unique discourse on the ever increasing role of financial literacy combined with consumer protection to reduce consumption risks within the financial markets, especially in developing countries in the aftermath of global pandemic shocks. This study uses the social learning theory, theory of reasoned action and theory of planned behaviour to elucidate how customized financial literacy can enhance consumer protection to increase financial inclusion of groups with special needs like the PWDs who have become more susceptible to exploitation by unscrupulous financial institutions in under-developed financial markets, especially in post Covid-19 pandemic.

Details

Journal of Financial Regulation and Compliance, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1358-1988

Keywords

Content available
Article
Publication date: 1 February 2024

Ismael Gómez-Talal, Lydia González-Serrano, José Luis Rojo-Álvarez and Pilar Talón-Ballestero

This study aims to address the global food waste problem in restaurants by analyzing customer sales information provided by restaurant tickets to gain valuable insights into…

Abstract

Purpose

This study aims to address the global food waste problem in restaurants by analyzing customer sales information provided by restaurant tickets to gain valuable insights into directing sales of perishable products and optimizing product purchases according to customer demand.

Design/methodology/approach

A system based on unsupervised machine learning (ML) data models was created to provide a simple and interpretable management tool. This system performs analysis based on two elements: first, it consolidates and visualizes mutual and nontrivial relationships between information features extracted from tickets using multicomponent analysis, bootstrap resampling and ML domain description. Second, it presents statistically relevant relationships in color-coded tables that provide food waste-related recommendations to restaurant managers.

Findings

The study identified relationships between products and customer sales in specific months. Other ticket elements have been related, such as products with days, hours or functional areas and products with products (cross-selling). Big data (BD) technology helped analyze restaurant tickets and obtain information on product sales behavior.

Research limitations/implications

This study addresses food waste in restaurants using BD and unsupervised ML models. Despite limitations in ticket information and lack of product detail, it opens up research opportunities in relationship analysis, cross-selling, productivity and deep learning applications.

Originality/value

The value and originality of this work lie in the application of BD and unsupervised ML technologies to analyze restaurant tickets and obtain information on product sales behavior. Better sales projection can adjust product purchases to customer demand, reducing food waste and optimizing profits.

Book part
Publication date: 5 April 2024

Luis Orea, Inmaculada Álvarez-Ayuso and Luis Servén

This chapter provides an empirical assessment of the effects of infrastructure provision on structural change and aggregate productivity using industrylevel data for a set of…

Abstract

This chapter provides an empirical assessment of the effects of infrastructure provision on structural change and aggregate productivity using industrylevel data for a set of developed and developing countries over 1995–2010. A distinctive feature of the empirical strategy followed is that it allows the measurement of the resource reallocation directly attributable to infrastructure provision. To achieve this, a two-level top-down decomposition of aggregate productivity that combines and extends several strands of the literature is proposed. The empirical application reveals significant production losses attributable to misallocation of inputs across firms, especially among African countries. Also, the results show that infrastructure provision has stimulated aggregate total factor productivity growth through both within and between industry productivity gains.

Article
Publication date: 7 November 2023

Islam Abdeljawad, Muiz Abu Alia and Muhannad Demaidi

Existing theories on the determining factors of corporate investment decisions raise the importance of financial market imperfections in explaining investment behavior. Many…

Abstract

Purpose

Existing theories on the determining factors of corporate investment decisions raise the importance of financial market imperfections in explaining investment behavior. Many factors have been proposed as drivers of investment, mainly in developed economies, while emerging countries have almost been neglected. The main purpose of this study is to examine the effect of financing constraints on the investment behavior of a small context, namely, Jordan, with an imperfect environment.

Design/methodology/approach

This study considers panel data regressions from the industrial companies traded at the Amman Stock Exchange with a total of 1,058 firm-year observations.

Findings

The results are able to demonstrate that business size, tangibility, market-to-book ratio, profitability, financial slack and leverage are major drivers of investment choices. The results support the importance of information asymmetry in explaining the investment behavior of firms. Nonetheless, the Q-theory is in place, as is firm agility.

Practical implications

Policies to reduce information asymmetry are immediately needed to help firms increase investments by providing them with access to training, technology and market information. They also should enhance the firms’ opportunities for growth. Moreover, they should make it easier for businesses to access financial slack, such as by improving access to credit and financial institutions. They also can work to improve the financial infrastructure to meet the financing needs of businesses. Finally, smaller businesses should be assisted by improving their ability to invest and grow.

Originality/value

To the best of the authors’ knowledge, this is one of the first studies, if any, to investigate this issue in a distinct environment. Despite the unique characteristics of Jordan, the findings are applicable to other countries that experience comparable political and economic circumstances because Jordan has traits common to many emerging nations.

Details

Competitiveness Review: An International Business Journal , vol. 34 no. 1
Type: Research Article
ISSN: 1059-5422

Keywords

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