Engineering Projects Research Articles

The Performance and Qualitative Evaluation of Scientific Work at Research Universities: A Focus on the Types of University and Research

The successful implementation of scientific research is one of the key factors for sustainable development, including the development of tertiary education. A leading or “world-class university”, today, transfers knowledge to innovation, bearing the concept of “academic excellence”, and features of “research” and “entrepreneurial” universities highly match the SDGs. This article presents an analysis for scientific quality-assessing indicators at research universities. It also studies university science models in different countries, the features of university types—engineering (technical or technological) and comprehensive (multidisciplinary)—and the arising problems with their possible solutions for university science on the whole. The authors suggested a composition of indicators for assessing the quality of the fundamental scientific research and engineering project results and the performances of universities’ specialized scientific units. The respondents of the survey weighed the significance of the indicators. The research used methods of analysis, brainstorming, Ishikawa diagram building, and a survey of specialists. The results obtained can be useful for the improvement of quality management systems (QMSs) at research universities. Some implications of this study could be extended to improve QMS and management processes of specialized scientific organizations that belong to the state, business, and non-profit sectors of science.

Failure analysis of Nehbandan granite under various stress states and strain rates using a calibrated Riedel–Hiermaier–Thoma constitutive model

This study presents a comprehensive procedure for determining, calibrating, and validating the Riedel–Hiermaier–Thoma (RHT) material model parameters for granite. The process involves collecting a comprehensive dataset of conventional mechanical tests conducted on various types of granite worldwide. Based on this dataset, one set of RHT material model parameters is determined. Additionally, a specific granite sample from Iran, known as Nehbandan granite, is characterized through physical and mechanical testing to obtain another set of parameters. The challenging task of determining the third set of parameters, which are difficult to obtain analytically and experimentally, is accomplished through a calibration process that iteratively adjusts the parameters based on comparisons between numerical simulation results and experimental data. To validate the determined parameters, a series of tests, including uniaxial compressive strength (UCS), triaxial compressive strength (TCS), Brazilian tensile strength, and dynamic Brazilian using split Hopkinson pressure bar (SHPB) tests, are conducted on the Nehbandan granite. These tests are also simulated using LS-Dyna software, and the numerical simulation results are compared with the corresponding experimental test results. The comparison between the numerical and experimental data serves as a means of validating and verifying the accuracy and reliability of the determined RHT material model parameters for granite. The results demonstrate the successful determination and calibration of the RHT material model parameters for granite. The model exhibits effectiveness in predicting the behavior of granite under various loading conditions. The validation process confirms the accuracy and reliability of the determined parameters through a close agreement between numerical simulations and experimental data. The findings contribute to a better understanding of granite's mechanical response and provide a reliable tool for simulating and predicting its behavior in engineering applications. The validated RHT material model parameters offer a robust framework for accurate numerical simulations, enabling engineers to make informed decisions in rock engineering projects.

Supporting strategy for investment evaluation of photovoltaic power generation engineering projects using multi-criteria decision analysis methods

This scientific study examines the evaluation of photovoltaic power generation projects through the application of multi-criteria decision analysis methods. Two groups of large-scale grid-connected PV power generation system projects with a nominal power of 50 MW and 500 MW respectively were analyzed and evaluated. These systems were designed to be installed in the same wider geographical area in northern Greece, but they were differentiated in the part of the PV circuit. Twelve systems were analyzed in which either monocrystalline silicon panels or poly-crystalline silicon panels or bifacial photovoltaic panels were to be installed. In these systems either central photovoltaic inverters or photovoltaic string inverters were considered for installation. The following criteria were used to evaluate the investment in these projects. These criteria were related to the profitability, the financial cost, the technical level, and the electrical energy production of the systems and these were the initial investment cost, the operation and maintenance cost, the levelized cost of electricity, the net present value, the internal rate of return, the capital recovery or payback period, the technical level of the photovoltaic circuit, the technical maturity of the photovoltaic circuit, and the annual electricity production. The evaluation of these criteria was initially conducted with fixed weighting coefficients followed by a sensitivity analysis of these weighting coefficients. The results of the evaluation using the PROMETHEE, AHP and TOPSIS multi-criteria decision analysis methods showed that the PV power generation systems which should be preferred are those with increased nominal power, where monocrystalline silicon technology panels are employed following the central inverter topology.

Incentivizing green building technology: A financial perspective on sustainable development in India

Future viability depends on ensuring a sustainable society because green energy methods may efficiently reduce greenhouse gas emissions. Nevertheless, stakeholders, consumers, and developers continue to be notably ignorant of the financial incentives connected to green technology. Moreover, there is still a dearth of studies on the range of financial incentives offered by different authorities in India. Monetary incentives, such as tax breaks, indirect tax exemptions, and refunds, are crucial in encouraging the use of green technology in the modern world. This study explores the importance of financial incentives for green building technologies in India, which also looks at the wide range of incentives provided by federal, state, and local governments. Furthermore, the study highlights various state government programs such as goods subsidies, exemptions from local taxes, and fee waivers. Notably, several incentives aimed at consumers, developers, and other stakeholders have been implemented by the Indian Green Building Council (IGBC). This review study emphasizes the effectiveness of financial incentives in green construction projects and draws attention to a clear knowledge gap regarding the adoption of green technology. This study also provides insights into potential future directions. Studies and research results emphasize the importance of spreading the word about financial incentives as a key factor in determining the adoption of green technologies. Many parties, including governmental organizations, municipal governments, developers, and clients engaged in green building technology projects, stand to gain increased awareness.

Improved determination of the S-wave velocity of rocks in dry and saturated conditions: Application of machine-learning algorithms

The determination of S-wave velocity (Vs) is of significant importance in various engineering disciplines, including mining, civil, and geotechnical engineering. It is beneficial to indirectly determine Vs under both dry and saturated conditions and to understand its relationship with influencing input variables: coring depth (H), durability index (DI), water content (Wa), dry density (ρd), saturated density (ρs), and porosity (n). In this study, we evaluate these relationships using three multiple machine-learning algorithms (MLAs): artificial neural network (ANN), fuzzy inference system (FIS), and gene expression programming (GEP), alongside a linear regression method (LRM) and predict both dry S-wave velocity (Vs-dry) and saturated S-wave velocity (Vs-sat) of rocks. The research involves the analysis of 90 datasets derived from samples of schist, phyllite, and sandstone rocks collected from Azad and Bakhtiari dam sites in Iran. The diversity of these datasets is a key advantage of this study, providing a solid foundation for models training and testing while enhancing the models’ generalizability. Model optimization techniques are employed in the Python, MATLAB, GenXProTools, and SPSS environments to identify the most effective versions of ANN, FIS, GEP, and LRM models, respectively. The prediction performance analysis reveals that all applied models yield acceptable levels of accuracy for predicting Vs-dry and Vs-sat. However, GEP emerges as the best model for predicting both Vs-dry and Vs-sat. The ANN and FIS models also achieve high levels of accuracy, while LRM performs comparatively less well. Additionally, sensitivity analysis conducted using the cosine amplitude method (CAM) highlights the influence of different variables on Vs-dry and Vs-sat. The ρd is found to be the most influential parameter on Vs-dry, whereas DI exhibits the least impact. Conversely, the ρs significantly affects Vs-sat, while Wa shows the lowest impact. The exceptional performance of these proposed MLAs confirms their applicability in real-world rock engineering and geotechnics projects, offering precise determination of Vs. The diversity of studied rock types and datasets, along with the use of cost-effective and easy measurable inputs, the determination of Vs in both dry and saturated status, and the application of robust MLAs for Vs determination are the main novelties of this study. However, further researches involving additional datasets and more rock types are required to validate these findings.

Performance evaluation of bamboo species for structural applications using TOPSIS and VIKOR: A comparative study

This study focuses on and investigates bamboo as a workable building material for civil engineering projects. The various bamboo species suitable for the building are identified and their intrinsic mechanical and physical properties are investigated to get a thorough understanding. A detailed methodology is proposed that presents all the steps performed from sample size collection to investigating the characteristics of the bamboo species and demonstrating bamboo's structural capabilities. The study provides insightful and technical knowledge that will be extremely helpful in advancing the sustainable incorporation of bamboo into civil engineering construction methods. The findings have proven that varieties of bamboo with higher density and lower shrinkage rates, such as Thyrsostachys Oliveri (Oliveri), perform superior in structural applications. Multi-criteria decision-making techniques (TOPSIS and VIKOR) revealed Dendrocalamus strictus (Manvel) and Thyrsostachys Oliveri (Oliveri) as top-performing species, making them suitable for structural applications.

Investment in CCUS under technical uncertainty considering investor's risk aversion: An exotic compound real-options approach

Carbon capture, utilization, and storage (CCUS) technology is effective and value-adding solution for reducing emissions. However, the development and commercialization of these technologies are challenging due to high investment costs and several uncertainties. This study develops a novel comprehensive real-options-based model to evaluate investment in CCUS projects considering the technical risk and the investor's risk aversion. This study proposed an exotic compound real options model that combines American and barrier options. First, applying the Poison process, the technical risk is explicitly modeled. Secondly, the investor's risk aversion is defined as a barrier level for the barrier option part of the proposed model. Thirdly, the value of the project is evaluated through the exotic compound real option. Finally, we assess the economic viability of the project under multiple scenarios. The results of implementing the model for a real case show that the integrated technical risk assessment and the barrier option appropriately address investors' risk aversion. Furthermore, the comparison indicates that the proposed compound real options model is more effective than the traditional NPV (Net Present Value). Regarding policymaking, the results reveal that setting an appropriate carbon tax that considers the costs of carbon capture would be more beneficial. Further, the model provides investors helpful guidance to make proper investment decisions for CCUS technology projects under uncertainties.

Hydraulic fracturing in cement mortar subjected to seepage-sulfate coupled attack under varying pH levels

Cement-based structures are prone to hydraulic fracturing in acidic sulfate and seepage environments, posing a significant safety threat to engineering projects. To investigate the impact of pH levels on hydraulic fracturing in cement-based materials under seepage-sulfate coupled attack, hydraulic fracturing test and splitting tensile strength test have been conducted on cement mortar specimens permeated with Na2SO4 solution. A mathematical model is developed to establish the relationship between the critical water pressure of hydraulic fracturing and the splitting tensile strength at varying pH levels. The results show that the critical water pressure and splitting tensile strength initially increase and then decrease with the increase in erosion duration under pH levels of 7 and 3, while they continuously decrease with the increase in erosion duration under pH level of 1. Furthermore, the peak values of the critical water pressure and splitting tensile strength gradually diminish, which indicates an increased deterioration in hydraulic fracturing resistance with the decrease in pH value. The relationship between critical water pressure damage coefficient and erosion duration can be accurately described by a quadratic polynomial. Overall, the findings of this study can serve as a useful reference for enhancing the structural performance of cement mortar subjected to seepage-sulfate coupled attack at varying pH levels.

A method for selecting the type of energy storage for power systems with high penetration of renewable energy with multi-application scenarios

Energy storage (ES) configurations effectively relieve regulatory pressure on power systems with a high penetration of renewable energy. However, it is difficult for a single ES type to satisfy the complex regulatory demands of a power system. There has been little research on the selection methods for multiple types of ES that meet the demands of multiple application scenarios of power systems. This study introduces a method for the selection of ES types for power systems with a high penetration of renewable energy to determine the optimal ES types for multi-application scenarios. First, a generation method for ES schemes is proposed based on K-means clustering and combination theory. Then, considering the demands of peak shaving, frequency regulation and reserve of power systems with high penetration of renewable energy, an optimisation model of the expected indices of the ES is constructed to meet the demands of multi-application scenarios. Finally, the comprehensive evaluation method for ES schemes based on the error mean and the selection method for optimal ES types based on projection technology are proposed. Numerical studies show that for the power system in the example whose demand coefficients for peak shaving, frequency regulation and reserve are 30.59 %, 26.29 % and 43.11 %, respectively, a combination of pumped storage and colloidal battery, lithium iron phosphate battery, or lithium titanate battery is the most suitable ES type for the power system. This study offers a reference for the selection of ES types when an ES is configured.

Simulating cross-scale flow dynamics around offshore monopile foundations with a GFD-CFD coupled model

Flow dynamics are complex and undergo significant impact from offshore engineering infrastructures, such as wind turbines, involving interactions across different temporal and spatial scales. Individual numerical models of geophysical fluid dynamics (GFD) or computational fluid dynamics (CFD) face challenges in accurately representing these dynamics. To effectively capture the three-dimensional cross-scale flow around offshore infrastructures, we propose a generalized coupling framework that integrates the unstructured-grid Finite-Volume Community Ocean Model (FVCOM) for GFD and the Open Field Operation and Manipulation (OpenFOAM) for CFD. With the validation against the flume experiment, the common-boundary nesting method was developed to allow an accurate representation of flow dynamics around offshore hydraulic infrastructures. Idealized monopile foundation experiments demonstrate the model's capability to capture the formation of Karman vortex street, rotating horseshoe vortex under realistic astronomical tidal conditions. Application of this coupling framework to the offshore wind farm in Yangjiang, China, reveals flow direction lagging of 15° in the wake of a monopile under diurnal tide. This coupling approach, leveraging the strengths of both CFD and GFD models, provides a universal downscaling methodology in geophysical conditions, for a better understanding of the impact of offshore hydraulic infrastructures on the surrounding environment and further planning offshore engineering projects.

A complete experimental study on hard granites: Microstructural characterization, mechanical response, and failure criterion

This study, performed during the ORCHYD European project, devoted to drilling deep geothermal boreholes, has many potential applications to mechanical studies. It gathers geological descriptions of three outcropping granites from Scandinavia (Kuru Grey and Red Bohus) and from the South of France (Sidobre). Microstructural investigations include optical microscopy and X-ray tomography. The three granites chosen contain grain sizes that cover all the common ranges for granites: fine, medium and coarse. As the mineral phase volume fractions are similar in each, the grain defects and grain boundaries are carefully studied in an attempt to understand the physical and mechanical properties of the three granite rock samples measured at laboratory specimen scale. The rocks are tested for UCS, BTS and triaxial compressive strength with confining pressures up to 225 MPa or/and high strain-rates up to 103/s. The micro-structural parameters influencing the mechanical behaviour are highlighted. Test results show that the effect of confining pressure and strain-rate on compressive strength are uncoupled. These effects are then estimated independently, and a fracture criterion in compression accounting for both variables is proposed for the family of very hard granites. This criterion takes as a single reference strength measure for each rock the deviatoric stress at failure under 20 MPa confining stress in the quasi-static regime. It is then compared with existing datasets for which both quasi-static and dynamic regime data are available. This complete data set on these three very hard granites (UCS ∼ 200 MPa), together with a synthesis for failure prediction, has the potential to inform numerous rock engineering projects and be of value to the scientific community.

Challenges and Facilitators in the Clinical Adoption of Traditional Chinese Medicine Technology

Objective: This study aims to analyze the challenges and facilitators in the clinical adoption of traditional Chinese medicine (TCM) technology. It proposes practical recommendations to provide evidence-based support and guidance for medical institutions at various levels in effectively integrating and advancing TCM technology. Methods: A descriptive phenomenological approach was employed to facilitate semi-structured interviews with doctors, nursing managers, and nurses. The collected data were subsequently analyzed using NVivo software. Results: In a study involving interviews with 17 doctors, nursing managers, and nurses, researchers identified three main themes and ten sub-themes. These included factors that promote the use of traditional Chinese medicine (TCM), such as the development of a comprehensive training curriculum, support from leadership, and strategies for integrating TCM technology. Conversely, hindering factors were also identified, including low awareness of TCM among some healthcare professionals and patients, as well as challenges related to medical costs and insurance. Recommendations for promoting TCM technology in Grade A hospitals include the creation of operation manuals, establishment of platforms for learning and communication, provision of dedicated spaces for teaching and discussion, and empowerment of nurses to assume leadership roles in clinical decision-making. Conclusion: The development of Traditional Chinese Medicine (TCM) appropriate technology projects in general hospitals in Northwest China faces both obstacles and promoting factors. It is essential to address these challenges through targeted training and the implementation of a standardized management system to enhance the capabilities of TCM nursing services. Additionally, establishing a distinctive platform for TCM nursing services, fostering collaboration and exchange across various regions, and encouraging the inheritance and innovation of TCM nursing characteristics are critical steps in advancing TCM practices.

A FDEM study on the mechanical properties and failure behavior of soft-hard interbedded rocks considering the size effect

Soft–hard interbedded rocks are widely distributed at the Earth’s surface, and their mechanical properties and failure behavior directly affect the stability of local tunnel and slope engineering projects. Previous studies have rarely considered the influence of size effects on the mechanical properties and failure behavior of such rocks. Therefore, this paper used the combined finite–discrete element numerical method (FDEM) to study the mechanical properties and failure behavior of soft–hard interbedded rock samples considering the size effect. First, appropriate input parameters were calibrated and verified by using a new parameter calibration method. Second, the effects of the element size and loading rate were studied to obtain appropriate model parameters. Finally, the effects of the layer number, sample size, and height–diameter ratio of composite rock samples on their mechanical properties and failure behavior at different layer dip angles and layer thickness ratios were investigated. The results support the following findings: (1) For the composite rock samples with a layer thickness of 10 mm, reliable simulation results can be obtained by using a 2.2 mm element size, and the loading rate should not exceed 0.2 m/s in FDEM numerical modeling. (2) The number of layers in the sample should be at least 5, and when the height–diameter ratio is a constant 2.0, the height of the sample should not be less than 110 mm. (3) As the height–diameter ratio of the composite rock samples increases, both the compressive strength and elastic modulus decrease for all layer dip angles considered, but the rock failure mode changes for layer dip angles of 15–75°; in addition, the sample size effect is most significant for layer dip angles of 60° and 75°. (4) Taking horizontally layered composite rock samples as examples, both the compressive strength and elastic modulus of samples with different layer thickness ratios decrease with increasing height–diameter ratio and their failure modes also depend on the height–diameter ratio.

Can Your Leadership Increase Mine? Enabling IT Self-Leadership Through Transformational IT Leadership

Despite substantial investments by companies in technology projects, these resources are often not utilized to their maximum capability. People can enhance their use of technology by taking leadership in their IT use, i.e., by exhibiting IT self-leadership. This way, they may contribute to applying technology in ways that boost the innovativeness of their team. Therefore, the more IT self-leadership employees exhibit, the better the IT-utilization of the organization is. This study investigates the connection between the team leaders’ transformational IT leadership and team members’ IT self-leadership. Findings from diverse European teams in various industries indicate a positive relationship between the two.

Neural network classification of technological development projects in Russian companies: Perspectives of extreme project management

To achieve the goals of sustainable socio-economic development and ensure the technological sovereignty of the Russian Federation, it is critically important to choose effective methods of technological project management. The article develops a novel toolkit for neural network classification of technological development projects in Russian companies and justifies the use of extreme project management to such endeavors. The methodological framework resides in the concepts of project lifecycle management and data mining. The study employed the following research methods: textual analysis of project documentation using large language models, and intelligent project classification based on two-dimensional projection of multidimensional clusters using Orange Data Mining. The research draws upon regulatory documents in the field of Russia’s scientific and technological development and open databases on Russian companies’ projects. The work proposes a new neural network classification toolkit based on a large language model. We have found that most development projects related to critical and end-to-end technologies are characterized by low certainty of goals and solutions, which necessitates applying extreme approaches to manage them. The findings can be used by Russian companies for reasoning the choice of a project management model, as well as by experts when evaluating technological development projects.

Do Technical Implementations Help Physicians: An Evaluation of a New Procedure Documentation Tool on Provider Efficiency in the Electronic Health Record

Introduction. Provider time spent in the electronic health record (EHR) continues to increase, adding stress to an already demanding field. This study quantified the impact of a new EHR procedure documentation tool designed to reduce charting burden. Methods. This retrospective cohort study was conducted at the University of Kansas Health System and involved ambulatory physicians from all hospitals who were granted access to a new procedural documentation tool. Data on time spent per chart and clicks per chart per office visit were gathered from the hospital's EHR system. The cohort also completed a survey regarding their self-perceived efficiency in the EHR and charting burden. Results. The procedure documentation tool was used for 68% (25/37) of eligible procedures at one-month post-implementation. There was no significant difference in minutes per chart between the group that used the tool and the group that did not, although the group using the tool had lower charting time (median difference [MD] = 5.517; 95% CI, -0.283 to 13.317; p = 0.066). A similar trend was seen with clicks per chart, with an MD of 4 (95% CI, -3 to 11; p = 0.25). Conclusions. While the difference was not significant, this study achieved its goal of quantifying the impact of a health information technology (HIT) project and indicates the need for further examination of how to quantify future projects. It lays the groundwork for future evaluation of similar tools and studies.

Digital Twins and Civil Engineering Phases: Reorienting Adoption Strategies

Abstract Digital twin (DT) technology has received immense attention over the years due to the promises it presents to various stakeholders in science and engineering. As a result, different thematic areas of DT have been explored. This is no different in specific fields such as manufacturing, automation, oil and gas, and civil engineering, leading to fragmented approaches for field-specific applications. The civil engineering industry is further disadvantaged in this regard as it relies on external techniques by other engineering fields for its DT adoption. A rising consequence of these extensions is a concentrated application of DT to the operations and maintenance phase. On another spectrum, building information modeling (BIM) is pervasively utilized in the planning/design phase, and the transient nature of the construction phase remains a challenge for its DT adoption. In this article, we present a phase-based development of DT in the architecture, engineering, and construction industry. We commence by presenting succinct expositions on DT as a concept and as a service, and establish a five-level scale system. Furthermore, we present separately a systematic literature review of the conventional techniques employed at each civil engineering phase. In this regard, we identified enabling technologies such as computer vision for extended sensing and the Internet of things for reliable integration. Ultimately, we attempt to reveal DT as an important tool across the entire life cycle of civil engineering projects, and nudge researchers to think more holistically in their quest for the integration of DT for civil engineering applications.

Development of a Prediction Model for Construction Project Cost in India: an Analytical Approach A Review

The fundamental problem in the construction industry is that building projects are completed attaken a tolls significantly higher than estimated venture taken a tolls consequently, it is fundamental todevelop a taken a toll forecast show that detain all components influencing the extend taken a toll bymeans of relapse examination. Development costs are continuously inclined to vacillations, with a longtermdesign of expanding, making the estimating prepare a difficult errand. Vacillations within the fetchedof building materials have a noteworthy affect on foreseeing the esteem of a venture and, as a result, onthe project's great conclusion It is well known that civil engineering projects are prone to cost overrunsand schedule delays. Lack of project scope and frequent changes leads to a negotiation process interms of cost and time between the first partyowner and the second partycontractors. In the project lifecycle, cost forecast is a precursor to budget prices and resource allocation, thus it is critical for anyorganization. The following objectives are framed based on the literature study identify the constructioncost predictability of various tools, identify the various influencing factors to predict the material price ofcement and steel, model the Construction Cost Index (CCI), predict the construction duration (Especiallyfor highway projects, as compared to other kind of projects. They are having more obstacles to completethe task), predict the land value, Regarding this issue this paper find the best methodology for thePrediction Model for Construction Project Cost by analysising the different researchers papersresearch.

Demonstrating clean energy transition scenarios in sector-coupled and renewable-based energy communities.

Energy communities facilitate several advantages, including energy autonomy, reduced greenhouse gas emissions, poverty mitigation, and regional economic development. They also empower citizens with decision-making and co-ownership prospects in community renewable projects. Integrating renewable energy sources and sector coupling is a crucial strategy for flexible energy systems. However, demonstrating clean energy transition scenarios in these communities presents challenges, including technology integration, flexibility activation, load reduction, grid resilience, and business case development. Based on the system of systems approach, this paper introduces a 4-step funnel approach and a 4-step reverse funnel approach to systematically specify and detail demonstration scenarios for energy community projects. The funnel approach involves four steps. First, it selects demonstration scenarios promoting energy-efficient state-of-the-art renewable technologies and storage systems, flexibility through demand side management techniques, reduced grid dependence, and economic viability. Second, it lists all existing and planned project technologies, analysing energy flows. Third, it plans actions at different levels to implement the demonstration scenarios. Fourth, it validates the strategies using key performance indicators (KPI) to quantify the effectiveness of the planned measures. Furthermore, the reverse funnel approach delves deeper into the demonstration scenarios. The four steps involve identifying stakeholder perspectives, describing scenario scopes, listing conditions for realisation, and outlining business models, including value chains and economic assumptions. This approach provides a detailed analysis of the demonstration scenarios, considering actors, objectives, boundary conditions, and business assumptions. The methodologies are exemplified in three diverse European energy communities extending across residential, commercial, tertiary, and industrial establishments, allowing power-to-x and sector coupling opportunities. The paper also suggested thirteen KPIs for validating renewable-focused energy community projects. Finally, the paper recommends increased collaboration between energy communities, knowledge sharing, stakeholder engagement, transparent data collection and analysis, continuous feedback, and method improvement to mitigate policy, technology, business, and market uncertainties.

Exploring the influence of linear infrastructure projects 4.0 technologies to promote sustainable development in smart cities

Industry 4.0 technologies have a high potential to improve the planning and execution of linear projects such as roads, bridges and railroads. These technologies can help reduce emissions, enhance operations' efficiency, and improve users' quality of life. Despite their potential to promote sustainability in smart cities, there is a lack of research focused on analysing their impact. Therefore, this paper aims to identify 4.0 technologies related to linear projects and examine their influence on smart cities' sustainable development. The research method involved four main stages: identification of 4.0 technologies in linear projects, questionnaire design and application, influence analysis, and factor analysis. A systematic literature review identified a set of 4.0 technologies that favour smart cities' sustainable development. Subsequently, 66 experts were consulted to determine which of these technologies have the most significant influence on smart cities' sustainable development, highlighting data analysis and management, intelligent traffic control systems, and artificial intelligence. This study makes three main contributions: (1) it identifies thirty-seven 4.0 technologies associated with linear projects that promote sustainable development in smart cities; (2) it characterises the 4.0 technologies with the most significant influence on the sustainability of smart cities; and (3) it proposes nine principal components into which interrelated 4.0 technologies that promote sustainable development can be grouped. This study provides valuable evidence for smart city managers and offers guidance for the efficient adoption of 4.0 technologies in linear projects.