Whole System Research Articles

Assessing the innovative skills and competencies required of construction management graduates

Abstract The construction industry has been experiencing high waves of revolutionised innovative technologies globally. These resulted from the highly innovative demands of the 4th industrial revolution (IR), which does not exclude the construction industry. These technologies do not rely on traditional design and build principles, and they require sophisticated skills and competencies. Currently, the construction industry is still struggling to find professionals with innovative competencies and the skills needed to manage the building lifecycle process. These have been a major concern in developing countries’ construction industry sector. Employers in the construction industry are now looking for construction management graduates (CMG) who are academically qualified and also possess considerable construction-related innovative skills and competencies in related technological software or tools. This study investigates the expected core skills and competence required by CMG. The methodology entails a well-structured systematic literature review, wherein 13 expected core competencies and 27 expected core skills were identified. Based on these, primary data were elicited through an online Google Forms survey distributed to professionals in the Nigerian construction industry. A total of 330 valid responses were obtained. Relative Important Index (RII) and principal component analysis (PCA) were carried out and presented. The result reveals the industry’s expectations and provides guidance to CMG seeking employment in the construction industry. Understanding the industry expectations and possessing the required core competencies will enable the CMG to remain relevant in the dynamic built environments. This study contributes to building information modelling (BIM) knowledge and the current innovative competencies and skills required in the built environment.

Academic libraries and research data management

Purpose. Open Science entails research reproducibility, with an emphasis on data sharing and reuse. Hence, research data management (RDM) is an essential asset in research institutions for supporting open science. This study offers a systematic review of the landscape of research data management in academic libraries. It further examines the influence academic libraries can have if they are involved in the research lifecycle process, and how this benefits research institutions that have started implementing research data management, especially in the data-intensive disciplines.
 Methodology. In this study, the authors analysed Web of Science and Scopus databases, searching for papers connecting research data management and academic libraries. The authors found a total of N=387 articles. After removing duplicates and applying the exclusion and inclusion criteria process, the authors finally analysed N=32 articles, n=20 case studies, and n=12 research papers at both national and international levels.
 Limitations. This study has some limitations. Although the authors retrieved as many papers as possible for the analysis, it should not be considered as an exhaustive analysis, as varying studies may also be missing from the sample. The authors observed that there are more case studies focused on one institution rather than research papers involving different institutions at the international or national level. Therefore, more research studies would enrich the literature and show best practices in RDM.
 Results. The results show that research data management has some services implemented in different countries at the local or the international level. The authors argue that research data management generates new opportunities for academic libraries and librarians to acquire new skills as a part of the research data lifecycle.
 Originality/value. This study reports the current state of research data management at the international level in academic libraries and the influence libraries can have if they are involved in the research lifecycle process.

Agile Functional Requirements Modeling from Goal-Oriented Requirements Engineering: A Systematic Mapping Study

During the last two decades, the application of Goal-Oriented Requirements Engineering has increased in software projects, mainly because this approach is useful during the requirements analysis process and supports the realization of tasks such as requirements elaboration, validation, and planning, and can be used as part of the system life cycle, e.g. architecture and design of behavioral processes, coding, testing, monitoring, adaptation and evolution. Several approaches addressing goal-oriented requirements have already been proposed. Currently, there are several concerns about how to correctly adopt and implement it in current industrial contexts, such as agile approaches and, more specifically, its integration with user stories and acceptance criteria. This study presents a compilation of the current knowledge on adopting GORE in agile requirements specification through user stories and their acceptance criteria. A systematic mapping study guided by ten research questions was conducted, and nine primary studies were selected considering the selection criteria. The results obtained show some initiatives as goal-oriented modelling languages in different proposals for transforming goal-oriented models into user stories, among them: i* (i-star), Tropos, KAOS, GRL, AOM, and Goal Net. This study provides a solid basis for classifying existing and future approaches in the application of GORE. Researchers and practitioners can use this mapping to identify existing technical/research gaps to better address and assess their own contributions or understand existing ones.

Process design and environmental analysis for catalytic production of gamma-valerolactone from Kenaf

Previous studies have suggested to report the effectiveness in an economically viable insight of generation of gamma-valerolactone (GVL) from non-food biomass resources, but the environmental performance has less been conducted. When a new biorefinery process is presented for production of GVL from non-food biomass resources, environmental performances including carbon dioxide emission will be improved compared to the conventional production approaches. This study designs the more environmentally-friendly GVL process and expands to a LCA framework for the use of non-food biomass derived GVL as a product and solvent. To examine Kenaf utilization as a non-food biomass on GVL prodcution, this study focuses on process design and life cycle assessment (LCA) to indentify the global warming potentials (GWP) and fossil resource scarcity (FRS) of GVL production. The GWP and FRS results of Kenaf-based GVL were estimated to −1.326 kg CO2 eq. and −0.513 kg oil eq. of pure GVL. The LCA has been conducted in consideration of Kenaf growth farmland and biorefinery construction site located in Jeollabuk-do in South Korea.

A Commentary on Towards autonomous artificial agents with an active self: Modeling sense of control in situated action

Kahl et al., (2022) present a computational model of an autonomous agent implemented with an active self. With ideas based on the Free Energy Principle (Friston and Kiebel, 2009), their model tackles the challenge to unify higher-level cognitive activities and lower-level sensorimotor control as the autonomous agent maintains situational awareness while interacting with the environment. While Kahl et al., (2022) focus on modeling a single agent, we argue that this challenge similarly appears in modeling human–robot interaction (HRI). In this commentary, we discuss how the conceptual framework from Kahl et al., (2022) could inspire unified models of physical and cognitive HRI and how the modeling approach from Kahl et al., (2022) can potentially be applied to anticipatory thinking in robotics to support the human in daily life.

Cleaner technologies to minimise the environmental footprint of the footwear bonding process

Advances in cleaner technologies have a critical role in reaching Europe’s climate and environmental goals. More precisely, in the case of the footwear bonding process its environmental impact is mainly related to the VOCs emissions resulting from the use of organic solvents in the most common adhesives used, as well as during the application of some surface treatments such as halogenation. Moreover, the use of raw materials of fossil origin also contributes to its carbon footprint. The aim of this work is to deploy cleaner technologies to minimise the environmental footprint of the footwear bonding process through several approaches at different steps of the process life cycle, also to contribute to footwear circularity. This work focuses on the synthesis and application of reactive hot melt polyurethanes from CO2-based polyols as biobased adhesives, and the study of plasma-based surface treatments (low-pressure plasma and atmospheric pressure plasma) to improve adhesion properties, using styrene-butadiene vulcanised (SBR) rubber as a representative footwear soling material. The influence of CO2-based polyols on the polyurethane structure and the physicochemical effects of the plasma treatments on the rubber surface, as well as the final adhesion properties have been evaluated by means of different experimental techniques. The results showed that the values obtained for the T-peel strength of the adhesive joints studied, with the combination of the application of the plasma surface treatments and the biobased reactive hotmelt, exceed the minimum quality requirements for footwear according to the standardised tests. As a result, the deployment of such cleaner technologies regarding adhesives and surface treatments in the footwear bonding process will contribute to improving footwear carbon footprint and its circularity.

Benchmarking sidestream shortcut nitrogen removal processes against nitrous oxide recovery from a life cycle perspective

Anaerobic digestion effluent adds significantly to nutrient loading, energy consumption, and emissions of wastewater treatment plants. Sustainably treating this ammonia-rich sidestream requires systematic analysis on environmental impacts of shortcut nitrogen removal processes. Coupled Aerobic–Anoxic Nitrous Decomposition Operation (CANDO) is a novel biotechnology for sidestream nitrogen removal with energy recovery potential from N2O. Nevertheless, the environmental impacts of CANDO remain unknown after initial scale-up studies. In this study, three sidestream treatment processes, namely, nitritation-denitritation, nitritation-anammox, and CANDO, integrated with mainstream anaerobic-anoxic-oxic (A2O) treatment routes, are assessed by process simulation and life cycle assessment (LCA). The results show that the nitritation-anammox process has the smallest effect on human health, ecosystem quality, and resource availability among the three routes. Furthermore, the global warming potential generated from the CANDO-A2O process is 157 kg CO2 eq per cubic meter of anaerobic digestion liquid treated, which is slightly higher than nitritation-anammox-A2O (132 kg CO2 eq) but remarkably lower than nitritation-denitritation-A2O (248 kg CO2 eq). With low carbon emission and promising alternatives for carbon source, the CANDO-A2O route exhibits great potential in achieving carbon neutrality. This work is the first to quantitatively evaluate the potential environmental impacts of CANDO from a life cycle perspective, providing insights on the adoption and optimization of shortcut nitrogen removal processes in sidestream treatment.

EVALUATION OF 3D MODEL OF REBAR FOR QUANTITATIVE PARAMETERS

Abstract. The construction industry practices and processes are evolving constantly, and with the emergence of Industry 4.0, the use of technologies is expanding. Construction progress monitoring is an essential project lifecycle process; project success and timely completion are linked with effective progress monitoring operations and adopted tools. In the domain of automated construction progress monitoring, 3D modeling techniques have been studied a lot, with laser scanning and photogrammetry as two main methods. Although laser scanning provides precise and detailed 3D models, it is an expensive technology. Moreover, the literature reveals that for digitized construction progress monitoring, the major focus has been given to primary reinforced concrete (RC) structures compared to rebar. In contrast, rebar is a key element in RC structures, as structural integrity is dependent on steel reinforcement design, which makes rebar monitoring an essential activity. This study aimed to devise an automated monitoring digital-based methodology for effective and efficient onsite rebar monitoring considering quantitative parameters e.g., rebar length and rebar spacing. The developed module successfully interpreted photogrammetry-based 3D point cloud rebar model for the aforementioned parameters with an overall achieved accuracy ≥ 98%.

Digital twin-based life-cycle seismic performance assessment of a long-span cable-stayed bridge

Long-span cable-stayed bridges often have a design service life of more than a hundred years, during which they may experience multiple earthquake events and accumulate seismic damage if they are located in seismic-prone regions. Earthquake occurrence is discretely and randomly distributed over the life cycle of a long-span cable-stayed bridge and often causes sudden drops in the structural performance instead of yearly fixed seismic performance degradation. This study thus proposes a digital twin-based life-cycle seismic performance assessment method for long-span cable-stayed bridges. The major components of this method include: (1) a seismic hazard analysis-based generation method of earthquake occurrence sequence; (2) a digital twin-based structural response prediction method considering lifetime earthquake occurrence and sequence; and (3) a service life quantification method. The proposed method is applied to a scaled long-span cable-stayed bridge with a series of shake table tests. The results show that the digital twin can closely reproduce the life-cycle seismic response of the bridge under sequential earthquakes. The proposed assessment method provides a more intuitive presentation of the life-cycle seismic damage accumulation process and a more accurate estimation of the service life of a long-span cable-stayed bridge.

Cumulative exergy analysis of lignocellulosic biomass to bio-jet fuel through aqueous-phase conversion with different lignin conversion pathways

Lignocellulosic biomass conversion to bio-jet fuel is beneficial for reducing the depletion of fossil fuel. This study presented and compared the two different pathways of lignin in corn stalk to bio-jet fuel via aqueous-phase conversion based on the process simulation approach and life cycle cumulative exergy analysis. The results show that the pathway of lignin one-step conversion (LJA) can obtain a higher bio-jet fuel yield and cumulative exergy efficiency than lignin two-step conversion (LJC). Moreover, biomass conversion to bio-jet fuel with self-supplied hydrogen is beneficial to the conversion of low-quality biomass into high-quality bio-jet fuel and the decrease in fossil fuel consumption. Under the optimal parameters, corn stalk aqueous-phase conversion to bio-jet fuel with external-supplied hydrogen can achieve the largest bio-jet fuel yield (142.7 kg/t-bio) and cumulative exergy efficiency of system (29.3%). The sensitivity analyses show that the hydrolysis efficiency of lignin has the most influence on the cumulative exergy efficiency of bio-jet fuel, while the furfural yield from hemicellulose has the lowest impact. When the consumption of chemicals and steam is considered, it is significant to reduce the stripping steam to furfural ratio for the cumulative exergy efficiency and reduce the consumption of methanol and sulfuric acid for the renewability.

Guideline for software life cycle in health informatics.

The long-lasting trend of medical informatics is to adapt novel technologies in the medical context. In particular, incorporating artificial intelligence to support clinical decision-making can significantly improve monitoring, diagnostics, and prognostics for the patient's and medic's sake. However, obstacles hinder a timely technology transfer from research to the clinic. Due to the pressure for novelty in the research context, projects rarely implement quality standards. Here, we propose a guideline for academic software life cycle processes tailored to the needs and capabilities of research organizations. While the complete implementation of a software life cycle according to commercial standards is not feasible in scientific work, we propose a subset of elements that we are convinced will provide a significant benefit while keeping the effort within a feasible range. Ultimately, the emerging quality checks for academic software development can pave the way for an accelerated deployment of academic advances in clinical practice.

Workflow for health-related and brain data lifecycle.

Poor lifestyle leads potentially to chronic diseases and low-grade physical and mental fitness. However, ahead of time, we can measure and analyze multiple aspects of physical and mental health, such as body parameters, health risk factors, degrees of motivation, and the overall willingness to change the current lifestyle. In conjunction with data representing human brain activity, we can obtain and identify human health problems resulting from a long-term lifestyle more precisely and, where appropriate, improve the quality and length of human life. Currently, brain and physical health-related data are not commonly collected and evaluated together. However, doing that is supposed to be an interesting and viable concept, especially when followed by a more detailed definition and description of their whole processing lifecycle. Moreover, when best practices are used to store, annotate, analyze, and evaluate such data collections, the necessary infrastructure development and more intense cooperation among scientific teams and laboratories are facilitated. This approach also improves the reproducibility of experimental work. As a result, large collections of physical and brain health-related data could provide a robust basis for better interpretation of a person's overall health. This work aims to overview and reflect some best practices used within global communities to ensure the reproducibility of experiments, collected datasets and related workflows. These best practices concern, e.g., data lifecycle models, FAIR principles, and definitions and implementations of terminologies and ontologies. Then, an example of how an automated workflow system could be created to support the collection, annotation, storage, analysis, and publication of findings is shown. The Body in Numbers pilot system, also utilizing software engineering best practices, was developed to implement the concept of such an automated workflow system. It is unique just due to the combination of the processing and evaluation of physical and brain (electrophysiological) data. Its implementation is explored in greater detail, and opportunities to use the gained findings and results throughout various application domains are discussed.

Process Simulation and Life Cycle Assessment of Waste Plastics: A Comparison of Pyrolysis and Hydrocracking.

Pyrolysis and hydrocracking of plastic waste can produce valuable products with manageable effects on the environment as compared to landfilling and incineration. This research focused on the process simulation and life cycle assessment of the pyrolysis and hydrocracking of high-density polyethylene. Aspen Plus was used as the simulator and the Peng-Robinson thermodynamic model was employed as a fluid package. Additionally, sensitivity analysis was conducted in order to optimize product distribution. Based on the simulation, the hydrocracking process produced value-added fuels, i.e., gasoline and natural gas. In contrast, pyrolysis generated a significant quantity of pyrolysis oil with a high number of cyclo-compounds and char, which are the least important to be utilized as fuels. Moreover, in the later part of the study, life cycle assessment (LCA) was adopted in order to investigate and quantify their impact upon the environment using simulation inventory data, which facilitates finding a sustainable process. Simapro was used as a tool for LCA of the processes and materials used. The results demonstrate that hydrocracking is a better process in terms of environmental impact in 10 out of the 11 impact categories. Overall, the present study proposed a promising comparison based on energy demands, product distribution, and potential environmental impacts, which will help to improve plastic waste management.

Strengthening the Role of the Young Generation as the Influencers to Accelerate the Implementation of Green Economy: A Co-Creation Value Perspective

The role of the green economy is very important, where the fulfillment of needs does not sacrifice the goals of sustainable consumption and production as well as resource efficiency. Indonesia has made a National Action Plan (RAN) to implement the 12th principle in the Sustainable Development Goals, known as Responsible Consumption and Production (RCP) aimed at improving production processes and consumption practices to reduce resource consumption, waste generation, and emissions throughout the life cycle of processes and products. RCP requires citizen involvement about community, increased awareness, willingness to pay, and environmental-friendly lifestyle. This research is intended to analyze the role of the Young Generation to become Influencers (through co-creation of values) so that they can encourage the implementation of good practices as green consumers. To gain insights on people’s willingness to participate in green economy, preliminary research has been conducted involving 229 respondents. A model was constructed to identify the antecedents of willingness to participate. The antecedents were Attitude, Perceived Behavioral Control and Behavior. Descriptively, the field findings can explain the behavior and willingness to participate of the younger generation in green economy practices. The findings of the preliminary research can be used as the basis for proposing a more predictive model using the role of influencers as a moderating variable that intervene in the influence of behavioral intention on willingness to participate. Keywords: Behavior, Willingness to participate, SDG, Influencers, Co-creation of Value.

Targeting climate‐neutral hydrogen production: Integrating brown and blue pathways with green hydrogen infrastructure via a novel superstructure and simulation‐based life cycle optimization

AbstractThis article addresses the sustainable design of hydrogen (H2) production systems that integrate brown and blue pathways with green hydrogen infrastructure. We develop a systematic framework to simultaneously optimize the process superstructure and operating conditions of steam methane reforming (SMR)‐based hydrogen production systems. A comprehensive superstructure that integrates SMR with multiple carbon dioxide capture technologies, electrolyzers, fuel cells, and working fluids in the organic rankine cycle is proposed under varying operating conditions. A life cycle optimization model is then developed by integrating superstructure optimization, life cycle assessment approach, techno‐economic assessment, and process optimization using extensive process simulation models and formulated as a mixed‐integer nonlinear program. We find that the optimal unit‐levelized cost of hydrogen ranges from $1.49 to $3.18 per kg H2. Moreover, the most environmentally friendly process attains net‐zero life cycle greenhouse gas emissions compared to 10.55 kg CO2‐eq per kg H2 for the most economically competitive process design.

Conceptual carbon-reduction process design and quantitative sustainable assessment for concentrating high purity ethylene from wasted refinery gas

The direct emission of waste refinery gas after combustion will cause a severe greenhouse effect. Recovering high-value-added ethylene from wasted refinery gas has fundamental economic and environmental significance. Due to the complexity of the composition of refinery waste gas, designing and optimizing the whole recovery process is still a challenging task. Herein, a novel process (SCOAS) was proposed to obtain polymer-grade ethylene from wasted refinery gas through a direct separation process, and heat pump-assisted thermal integration optimization (HPSCOAS) was carried out. The unique feature of the novel approach is that a new stripper and ethylene reabsorber follow the dry gas absorber to ensure ethylene recovery and methane content. An industrial model, shallow cooling oil absorption (SCOA), and concentration combined cold separation system of ethylene unit using wasted refinery gas was established to analyze the technology and environment. Based on the detailed process modeling and simulation results, the quantitative sustainability assessment of economy and environment based on product life cycle process is carried out. The results show that compared with the traditional process when the same product is obtained, the total annual cost of the HPSCOAS process is the lowest, which is 15.4% lower than that of the SCOA process and 6.1% lower than that of the SCOAS process. In addition, compared with the SCOA process and the HPSCOAS process, the SCOAS process has more environmental advantages. The non-renewable energy consumed by SCOAS is reduced by about 24.8% and 6.1%, respectively. The CO2 equivalent is reduced by about 38.6% and 23.7%.

Toward Sustainable and Cost‐Effective CO2 Conversion Processes to Propylene Carbonate Based on Ionic Liquids

AbstractThe use of ionic liquids (ILs) for CO2 capture and utilization into a valuable product is attracting interest even though literature evaluating their sustainability is scarce. A liquid–liquid extraction (LLE)‐based separation is recently proposed as an alternative to the high energy‐consuming distillation‐based reference approach to produce propylene carbonate (PC). In this work, the environmental impacts associated to the distillation‐based reference and two proposed LLE‐based approaches to produce PC are evaluated by means of process modeling and life cycle impact assessment tools. Simulations prove that tuning operating variables in terms of environmental benefits also improves the cost‐effectiveness of the process. In addition, sustainability of the processes is nearly not altered by the IL selection when an effective recovery is designed. The emissions associated to the proposed approaches vary between 0.12 and 0.22 kg CO2 equiv. per kgPC, while the operational costs range from 3 to 8 $ per tPC. The water‐mediated LLE‐based approach imposes the best environmental, capital expenditures, and operating expenses performance.

Social sustainability indicators for road infrastructure projects: A systematic literature review

Australia’s population is predicted to grow to 31.4 million by 2034, according to Infrastructure Australia Audit 2019, resulting in additional demand for road infrastructure. Although road infrastructure projects have a significant positive impact at the regional level regarding reduced travel time, improved accessibility, and amenities, they may also have negative social impacts at the local level. However, road infrastructure projects are often seen as key drivers of economic development. Social aspects are generally less considered in the decision-making process of the project lifecycle. The existing sustainability assessment models focus on economic and environmental aspects and lack social considerations. To bridge the gap, this paper aims to examine the existing literature on social sustainability in the construction industry and identify the social aspects and relevant indicators to be considered in assessing the social sustainability performance of road infrastructure projects. Through systematic literature review, using Scopus, Web of Science, EBSCO and google search databases from an initial set of 1178 journals, conference papers, books, book chapters and other relevant industry reports, 80 articles related to social sustainability in the construction industry were selected for the study. Based on the analysis, nine social sustainability criteria such as quality of life, equity, employment, health and safety, stakeholder participation, culture and heritage, compensation strategies, governance, macro-social activities and 78 respective indicators were identified. The findings of this study may assist policymakers and industry practitioners in developing comprehensive assessment models for benchmarking social sustainability in Australian road infrastructure projects.

Threat modeling in application security planning citizen service complaints

The mobile-based service complaint application is one way to implement good governance today. Public facilitated to make complaints without going through a complicated process. Security aspects must be considered to protect user privacy. The security design must be considered so that no one is harmed by the application's users damaged in the application's use. This study used threat modeling during the planning stage of developing a citizen service complaint application to obtain information about vulnerabilities. The researcher uses the threat modeling process that the open web application security project (OWASP) organization has formulated as a framework. The researchers took steps to describe application information, determine and rank threats, countermeasures, and mitigation. In the final stage, the spoofing, tampering, repudiation, information disclosure, denial of service and elevation of privilege (STRIDE) threat modeling methodology is used to analyze and assess mitigation actions against threats in the application. The researcher gets a defense strategy to reduce the danger based on the threat analysis results. Threat modeling in the early phase software development life cycle process is constructive in ensuring that software is developed with adequate security based on threat mitigation from the beginning.

Urban life cycle and long-run violence: Colombia 1938–2018

ABSTRACT This paper revisits and improves upon the traditional urban life cycle theory, using it as a long-term conceptual baseline model to assess the effect of the Colombian internal armed conflict on urbanization during 1938–2018. The paper makes three innovations: (1) It uses a third-degree autoregressive panel estimation to detect the underlying Data Generating Process of the urban life cycle, a feature that eluded original scholarship in the field; (2) It uses the baseline urban life cycle model to assess the impact of long-term violence in Colombia; and (3) It produces an inductive conceptual approach to the relationship between urbanization and economic development. Our third-degree autoregressive panel models adequately explain the urban concentration cycles experienced by Colombia’s 20 largest metropolitan areas, regardless of using different specification structures. It also correctly controls the long-term trends of the demographic transition that the country experienced during that period: its rate of urbanization increased from 31 to 68% between 1938 and 2018; the largest 20 metro areas increased their participation in the total population from 17 to 54%; and yearly total population growth increased from 2.12% in the 1940s to its peak 3.19% in the 1970s, decreasing to 1.18% in the 2010s. The homicide rate had a controlling effect on the increasing parts of the urban life cycle, acting as a deterrent of urban concentration per metropolitan area.