Complex Engineering Projects Research Articles

Verification, validation, and uncertainty quantification for electron-density diagnostics of polarimeter/interferometer system on experimental advanced superconducting tokamak

The verification, validation, and uncertainty quantification (VVUQ) analysis is a systematic method for identifying and quantifying uncertainties in complex engineering projects. This method has been used by the International Atomic Energy Agency as a critical assessment method in the field of high-precision plasma diagnostics in tokamaks. Starting from the basic theory to the final results, it assesses every process to obtain the uncertainties, system confidence level, and similarity between the model and experimental assessments. In this study, we evaluated the electron-density diagnosis of the polarimeter/interferometer system on an experimental advanced superconducting tokamak using a cylindrical simulation model. This study applied the VVUQ to an entire plasma diagnostic system for the first time, coupled with the statistical concepts of confidence and similarity. Through the VVUQ process, the uncertainty from the simulation code, diagnostic code, and engineering errors were identified, quantified, and minimized.

A Novel Hybrid Fuzzy Multiple-Criteria Decision-Making Model for the Selection of the Most Suitable Land Reclamation Variant at Open-Pit Coal Mines

The expansion of the open-pit exploitation of mineral raw materials, and especially the energy resources of fossil fuels, makes open-pit coal mines spatially dominant objects of large mining basins. Exploitation activities are accompanied by negative ecological impacts on the environment, which requires the integral planning, revitalization, reclamation, and rehabilitation of the disturbed area for human use in the post-exploitation period. The post-exploitation remediation and rehabilitation of open-pit mining areas and disposal sites, i.e., space disturbed by mining activities and accompanying facilities, are complex synthetic multidisciplinary multiphase engineering project tasks. In this paper, a hybrid fuzzy MCDM model (Multiple-Criteria Decision-Making) was developed for the selection of a reclamation solution for the Tamnava-West Field open-pit mine. IMF SWARA (Improved Fuzzy Stepwise Weight Assessment Ratio Analysis) was applied to define the weights of 12 criteria of different structures used in the evaluation of reclamation solutions. The Fuzzy ROV (Range of Value) method was applied to select the reclamation solution from a total of 11 solutions previously obtained using a process approach. The results of the hybrid IMF SWARA—Fuzzy ROV model show that forestry is the best solution for the Tamnava-West Field open-pit mine. After the results had been obtained, verification analyses of the proposed model were performed and the best stable proposed reclamation solution was determined.

A closed-loop human-computer interactive design method based on sequential human intention prediction and knowledge recommendation

Designers working on large-scale complex engineering projects may encounter design errors due to limited experience and expertise. Therefore, during the design process, accurately identifying the designer’s design intention and recommending relevant design knowledge can enhance design efficiency and reduce errors. In this paper, we propose a closed-loop human–computer interactive design method based on sequential human intention prediction and knowledge recommendation. This method leverages the Function-Behaviour-Structure (FBS) model to reduce the dimensionality of design action sequences, so as to facilitate the analysis of potential design patterns. The processed action sequences are used to train Transformer to predict design intentions. In different input sequences, Transformer achieved a highest prediction accuracy of 92.09%. We construct a Design Knowledge Recommendation Framework (DKRF) and its corresponding design knowledge matching algorithm. This framework accurately recommends design knowledge to designers, solving design stagnation and improving design efficiency. Finally, a case study of four types of mechanical model design is conducted to demonstrate the feasibility and wide applicability of the proposed closed-loop human–computer interactive design method.

Enhancing Robustness in Precast Modular Frame Optimization: Integrating NSGA-II, NSGA-III, and RVEA for Sustainable Infrastructure

The advancement toward sustainable infrastructure presents complex multi-objective optimization (MOO) challenges. This paper expands the current understanding of design frameworks that balance cost, environmental impacts, social factors, and structural integrity. Integrating MOO with multi-criteria decision-making (MCDM), the study targets enhancements in life cycle sustainability for complex engineering projects using precast modular road frames. Three advanced evolutionary algorithms—NSGA-II, NSGA-III, and RVEA—are optimized and deployed to address sustainability objectives under performance constraints. The efficacy of these algorithms is gauged through a comparative analysis, and a robust MCDM approach is applied to nine non-dominated solutions, employing SAW, FUCA, TOPSIS, PROMETHEE, and VIKOR decision-making techniques. An entropy theory-based method ensures systematic, unbiased criteria weighting, augmenting the framework’s capacity to pinpoint designs balancing life cycle sustainability. The results reveal that NSGA-III is the algorithm converging towards the most cost-effective solutions, surpassing NSGA-II and RVEA by 21.11% and 10.07%, respectively, while maintaining balanced environmental and social impacts. The RVEA achieves up to 15.94% greater environmental efficiency than its counterparts. The analysis of non-dominated solutions identifies the A4 design, utilizing 35 MPa concrete and B500S steel, as the most sustainable alternative across 80% of decision-making algorithms. The ranking correlation coefficients above 0.94 demonstrate consistency among decision-making techniques, underscoring the robustness of the integrated MOO and MCDM framework. The results in this paper expand the understanding of the applicability of novel techniques for enhancing engineering practices and advocate for a comprehensive strategy that employs advanced MOO algorithms and MCDM to enhance sustainable infrastructure development.

Research on Risk Management in International Engineering Project Contracting with Third World Countries in Africa

Risk management of international engineering project contracting with third world countries in Africa is a critical aspect that requires thorough investigation due to the unique challenges and complexities involved. The study delves into the various risk factors prevalent in international engineering projects with third world countries in Africa; different risk management strategy options and how they can be tailored to suit the specific context of international engineering projects with third world countries in Africa to enhance project success rates. The research will also investigate the application of the Analytic Hierarchy Process (AHP) method in prioritizing and selecting risk management strategies based on their importance and effectiveness in complex engineering projects.

A hybrid algorithm based on the proposed square strategy and NSGA-II for ship pipe route design

Ship pipe route design (SPRD) is a difficult and time-consuming job due to the complexity of the routing space and the large number of pipes. This paper introduces a hybrid optimization algorithm called SQNSGA-II based on the proposed Square strategy and NSGA-II to efficiently solve SPRD problems in complex situations. The details of the hybrid algorithm are introduced, including the principle of the Square strategy, genetic operators and pipe repair operators et al. Additionally, a new method called Intercept Search strategy is proposed for optimizing branch pipe design in complex scenarios. Finally, we conducted three cases of simulation experiments to demonstrate that the proposed algorithm and strategy can efficiently and accurately optimize the design of pipes, highlighting their pipe routing capabilities in complex engineering projects.

The Influence of Materials on the Mechanical Properties of Ultra-High-Performance Concrete (UHPC): A Literature Review.

Ultra-high-performance concrete (UHPC) is a cementitious composite combining high-strength concrete matrix and fiber reinforcement. Standing out for its excellent mechanical properties and durability, this material has been widely recognized as a viable choice for highly complex engineering projects. This paper proposes (i) the review of the influence exerted by the constituent materials on the mechanical properties of compressive strength, flexural tensile strength, and elastic modulus of UHPC and (ii) the determination of optimal quantities of the constituent materials based on simplified statistical analyses of the developed database. The data search was restricted to papers that produced UHPC with straight steel fibers at a content of 2% by volume. UHPC mixture models were proposed based on graphical analyses of the relationship of constituent materials versus mechanical properties, aiming to optimize the material's performance for each mechanical property. The results proved to be in accordance with the specifications present in the literature, characterized by high cement consumption, significant presence of fine materials, and low water-to-binder ratio. The divergences identified between the mixtures reflect how the constituent materials uniquely impact each mechanical property of the concrete. In general, fine materials were shown to play a significant role in increasing the compressive strength and flexural tensile strength of UHPC, while water and superplasticizers stood out for their influence on the material's workability.

Integrated alliance system architecture for lifecycle risk management in large-scale complex engineering projects

Integrated alliance system architecture for lifecycle risk management in large-scale complex engineering projects

Integrated alliance system architecture for lifecycle risk management in large-scale complex engineering projects

Integrated alliance system architecture for lifecycle risk management in large-scale complex engineering projects

RISK ASSESSMENT OF COMPLEX ENGINEERING PROJECT BASED ON FUZZY PETRI NET UNDER THE PERSPECTIVE OF VULNERABILITY

Traditional engineering risk management has been unable to adapt to the complexity and variability due to its constituent elements and dynamic nature of internal and external environments. Vulnerability, as a concept closely related to risk, has been neglected in the traditional risk management due to its hidden characteristics. This study attempts to quantify and evaluate vulnerabilities of complex engineering projects independently and explore the transmission mechanism between risk and vulnerability factors. Twenty different types of large-scale engineering projects in China were selected as case studies from the Mega Project Case Study Center (MPCSC) of Tongji University. Vulnerability and risk factors of each project were identified and analysed. A mechanism model was developed to explore the impacts of vulnerabilities and risks through ta Fuzzy Petri Net. Four main vulnerability-risk critical paths were identified through the reverse labelling method. The overall evaluation of engineering project risks considering the impacts of vulnerabilities is the highlight of this paper. This study interprets the cognition and evaluation of complex engineering risks from a new perspective, enriches the connotation of engineering risk management, and provides a reference for risk management and decisionmaking of complex engineering projects.

Analyzing Project Complexity, Its Dimensions and Their Impact on Project Success

Projects are undertaken in all science, engineering, and technology fields to achieve strategic and tactical goals. It is evident from the literature that projects are becoming more complex day by day, making project complexity a domain for current research. The objective of this study is to evaluate project complexity using a systematic, comprehensive, and widely accepted definition that can capture the multidimensional nature of project complexity and its impact on project success. Therefore, an integrative systemic framework has been selected to define project complexity considering seven key dimensions: context, size, diversity, autonomy, connectivity, emergence, and belonging. The study employed structural equation modeling to analyze project complexity, its dimensions and their relationship with project success for complex engineering projects. After an extensive literature review, a validated questionnaire was developed and used to obtain responses from different countries (Pakistan, China, UAE, UK, USA, and others) in the engineering fields of aerospace, design, manufacturing, oil and gas, IT, and construction. The work shows that project complexity has a negative impact on project success for complex engineering projects. Further, analyses examined the relationship between project success and the seven dimensions of project complexity. The significance of this study lies in its evaluation of project complexity using a systematic and comprehensive definition which is different from previous studies and brings more clarity and understanding of the underlying mechanisms and causal relationships between project complexity, project success and their related factors. The findings suggest that careful consideration of these dimensions and their factors can help project managers better understand and navigate project complexity and ultimately improve project success rates.

Editorial Innovation and Engineering Management in Emerging Economies

Over the past two decades, the development of emerging economies as drivers of global economic growth has been one of the most fundamental trends. Emerging economies account for more of the world's exports, including technology exports, while emerging country firms have heightened their profile in the global innovation landscape [1], [2], [3], [4]. Such changes required the building of substantial technological and engineering capabilities, but this is not the entire picture. To move up from basic to advanced innovation capabilities, firms in emerging economies have undergone a process of change and improvement in their managerial skills, by means of developing and adopting best practices of innovation and engineering management. Managerial skills are an enabling factor for dealing with systemic innovation processes and complex engineering projects. Nevertheless, while there has been substantial research on technological catching up in emerging economies, concern with how they are facing the challenges of adoption of innovation and engineering management practices have received little attention. The purpose of this Special Issue is to report on the state of the art of, and emerging trends in, research and practice of innovation and engineering management in emerging economies.

Research on Cooperative Evolutionary Game of Design and Construction Consortium of Green Building Project under Design Change

In recent years, with the country’s vigorous promotion of green buildings and the increasingly complex and large-scale engineering projects, the design-construction consortium model can better meet the needs of the organization and implementation of large-scale green projects and become a realistic choice for enterprises in project implementation. Therefore, the formation of a good and stable cooperative relationship between consortium members is increasingly important in improving project revenue and quality. The issue of maintaining the stability of consortium relationships is an urgent problem to be solved at this stage. As such, a three-party evolutionary game model, based on evolutionary game theory, comprising the developer unit, design unit, and construction unit, is constructed here. Then, strategies for ensuring evolutionary stability under different design modalities are discussed. Finally, the influence of relevant parameters under changing design conditions on the stability of the design and construction consortium of green building projects is analyzed through numerical simulation. The research results show the following: (1) If the additional revenue distribution coefficient within the consortium members is closer to 0.5, the influence on the stability of the design and construction consortium will be smaller; in contrast, if the influence on the design and construction consortium is increased, the cooperative relationship within the consortium will be more unstable. (2) The presence of additional revenue ∆π1 can increase the stability of the design and construction consortium. An increase in the additional revenue ∆π1 will inhibit the instability of the consortium on the one hand and strengthen the stability of the consortium on the other but will also lead to the occurrence of opportunistic behavior. (3) The construction unit’s payment of a subsidy to the cooperative members can help promote the stability of the design and construction consortium to a certain extent and can also weaken the effects of other factors on the stability of the consortium, but there is a threshold value for the amount of said subsidy. (4) On the one hand, the cooperation members actively cooperate with each other to maximize the cooperation benefits of the design and construction consortium, while on the other hand, the construction unit actively promotes the implementation of the green building project, strictly monitors the implementation of the green design and green construction approach by the design and construction units in the early and implementation stages of the project, prevents the design changes caused by the final product failing to meet the green building standard, and actively solves design change problems in a manner that benefits the sustainable development of the green building, so that the cooperative relationship among the members of the consortium can develop steadily, which is beneficial to the green and ecological development of architectural design and construction.

Preemptive multi-skill resource-constrained project scheduling of marine power equipment maintenance tasks1

The shipbuilding industry, characterized by its high complexity and remarkable comprehensiveness, deals with large-scale equipment construction, conversion, and maintenance. It contributes significantly to the development and national security of countries. The maintenance of large vessels is a complex management engineering project that presents a challenge in lowering maintenance time and enhancing maintenance efficiency during task scheduling. This paper investigates a preemptive multi-skill resource-constrained project scheduling problem and a task-oriented scheduling model for marine power equipment maintenance to address this challenge. Each task has a minimum capability level restriction during the scheduling process and can be preempted at discrete time instants. Each resource is multi-skilled, and only those who meet the required skill level can be assigned tasks. Based on the structural properties of the studied problem, we propose an improved Moth-flame optimization algorithm that integrates the opposition-based learning strategy and the mixed mutation operators. The Taguchi design of experiments (DOE) approach is used to calibrate the algorithm parameters. A series of computational experiments are carried out to validate the performance of the proposed algorithm. The experimental results demonstrate the effectiveness and validity of the proposed algorithm.

Risk Management as a Dynamic and Continuous Process in the Life Cycle of a Typical Major Civil Engineering Project

While many construction industries acknowledge the importance of risk management policies but hardly do they implement a defined technique in risk management. Many construction practitioners employ linear risk management process by applying risk mitigation process as and when risk occur. When project managers and practitioners ignore the application of risk management in real time projects, the implications are almost usually observed in the projects through forced variations, scope change and high uncertainties. In a complex and major civil engineering project, the risk exposure environment changes and shifts constantly due to external factors, changing objectives and other multiple dynamic variables. Quite often, initially planned risk mitigation targets do not generate intended outcome due to inadequate application of risk assessment process. For this reason, the risk and uncertainty management must be continuous, holistic and real time throughout the project life cycle from inception to completion. The ultimate goal of risk management plan is to achieve the project objectives in terms of cost, quality and time. Thus, risk management in complex and major civil engineering projects must be applied in real time, continuously and with utmost importance.

Cooperative negotiation in value-driven engineering and systems design: a technical note

The traditional practice of value-driven engineering and systems design is mainly based on net present values (NPVs). It is essentially enacted as a budgetary technique that neglects the future risk and strategic flexibility of a design project. Incorporating real options theory in value-driven decision models can improve the inability of NPV analysis in dealing with the upside potential of managerial flexibility and operational uncertainty over the design project life. This paper examines the critical issues and research opportunities for establishing a theoretical foundation of value-driven multiplayer game decision making in large complex engineering and systems design projects. This paper envisions a research framework for value-driven cooperative negotiation by synthesising the mathematical foundations of utility theory, real options theory and game theory into a coherent framework of design decision analysis. Fundamental issues and research directions are discussed to develop a variety of new methods for enhancing the formulation of value models for value-driven design with decision support to achieving equilibrium solutions with optimal value allocation among multiple decision agents involved in engineering and systems design.

Can product modularization approaches help address challenges in technical project portfolio management? – Laying the foundations for a methodology transfer

Formalized Project Portfolio Management (PPM) models struggle to provide comprehensive solutions to project selection, resource allocation and adaptability to dynamic technology project environments. In this article, we introduce a vision for a novel Modular Project Portfolio Management (MPPM) approach by drawing on well-established engineering methods for designing modular product architectures. We show how systems theory can be used to enable a transfer of methods from the area of engineering design and manufacturing to the area of PPM and how the concept of product modularity could help address challenges of existing PPM approaches. This lays the groundwork for the possible development of MPPM as a new and innovative methodology for managing complex technology and engineering project landscapes.

A Conceptual Model‐Based Systems Engineering Method for Creating Secure Cyber‐Physical Systems

AbstractThe Air Traffic Control industry is being increasingly exposed to rising levels of risk, as criminals and cyber‐attackers look to exploit system vulnerabilities. Air Navigation Service Providers become more demanding regarding cybersecurity concerns in the products they acquire. Consequently, systems engineers need to consider cyber security concerns early in their system's development life cycle. Model‐Based Systems Engineering methodologies are widely used to manage complex engineering projects in terms of system requirements, design, analysis, verification, and validation activities, leaving cyber security aspects aside. This paper presents a conceptual solution of a model‐based security method that aims to enable systems engineers to perform threat modeling analysis of cyber‐physical systems early and incorporate mitigation strategies into the system design, thereby reducing the cyber‐physical system's overall security‐related risks. Based on a real‐life case study the method will be validated later during execution period from Jan. – May 2022.

Research on the Water Pollution Control Mechanism of Xiangjiang River Basin Based on Machine Learning

Due to the complexity of water pollution treatment and the impact of external factors, precise regulation of water pollution has always been one of the problems in the environmental field. Traditional methods cannot meet the increasingly complex engineering project requirements. Machine learning methods developed in recent years provide a series of effective solutions for such problems. Taking the Xiangjiang River basin as an example, this paper introduces the characteristics of machine learning methods such as artificial neural network, support vector machine and random forest, and expounds the application of machine learning methods in the field of water pollution control in the Xiangjiang River basin from three aspects of water quality prediction and early warning, fault diagnosis of sewage treatment system and intelligent control, and analyzes the advantages of machine learning methods compared with traditional methods and the problems existing in the application of machine learning methods in water pollution control in the Xiangjiang River basin, the prospect and trend of the application of machine learning methods in the field of water pollution control in the Xiangjiang River basin are forecasted.

Project-based Learning for Control Education during COVID-19 Pandemic

The paper presents a project-based learning approach for the undergraduate level first course on control systems in the context of electrical and computer engineering program. We share the experience of a complex engineering project model that assumes no access to lab facility due to the COVID-19 pandemic but targets learning outcomes of a fundamental control system course, i.e., system modeling, performance investigation, analysis, design of analog or digital controller for a selected open-loop unstable system. The project utilizes Tinkercad Circuits which is a free online circuit simulator. The approach provides a solution to one of the challenges of remote or virtual engineering labs, i.e., a requirement of having high-performance expensive hardware and resource-intensive software support. Results are presented in terms of student samples and learning outcomes achieved at the end of the project.