Phases Of Life Cycle Research Articles

Knowledge Graphs underpinning ship digital twins for decarbonisation options assessment

We propose the concept of a Knowledge Graph as a data management and inference machinery that underpins digital twins of ships. The Knowledge Graph is a directed graph connecting dependent and independent model variables of interest in the digital twin, where the correlations between variables are continuously updated based on data received from the physical ship. The paper outlines a methodology for constructing the Knowledge Graph and proposes metrics that help to calculate the effectiveness of decarbonization solutions based on changes to the strength of data correlations. The proposed methodology allows for the extrapolation of decarbonization technology potential across specific vessels, fleets, operational patterns, and lifecycle phases.

Sustainability in Project Management Practices

The intersection between sustainability and project management has received significant attention as organizations recognize the criticality of incorporating sustainability practices into their projects. However, incorporating sustainability considerations presents some challenges, requiring the development and adoption of methods, tools and techniques tailored to address sustainability at the project level. Against this backdrop, this study endeavors to develop an understanding of the effective incorporation of sustainability within projects through the micro-level perspective of practices. An online survey was developed based on a comprehensive literature review of which a total of 107 valid responses were collected and analyzed. The results show the most useful sustainable project management practices perceived by experienced project professionals, including ‘Sustainability team management’, ‘Lessons learned towards sustainability’ and ‘Sustainability risk register’, among others. However, a data analysis reveals a prevailing trend marked by the limited perceived usefulness of sustainability practices in the context of project management. Furthermore, through exploratory factor analysis, a clear classification of sustainable project management practices was identified, according to the specific phases of the common project management lifecycle: ‘Initiation and planning’, ‘Execution, monitoring, controlling and replanning’ and ‘Closure’. By providing a set of sustainable project management practices and identifying the underlying factors that elucidate the incorporation of sustainable project management practices across the project management lifecycle, this study extends a guiding hand to practitioners in pursuing successful sustainability integration in their projects. It vividly illustrates that sustainability can be readily incorporated into project-management processes, delivering sustainable products and/or services in a sustainable way, combining both the ‘sustainability of the project’ and ‘sustainability by the project’ perspectives.

Polyhexamethylene Biguanide Reduces High-Risk Human Papilloma Virus Viral Load in Cervical Cell Samples Derived from ThinPrep Pap Test.

Human papilloma virus (HPV) infection and its progression still represent a great medical challenge worldwide. Clinical evidence has demonstrated the beneficial effects of polyhexamethylene biguanide (PHMB) on HPV clinical manifestations; however, evidence of the effect of this molecule on HPV viral load is still lacking. In this in vitro study, 13 ThinPrep Papanicolaou (Pap) tests were treated with a PHMB solution (0.10 g/100 mL) for 2 h. We observed no cytological changes but a significant reduction in the viral load of high-risk (HR) HPV after PHMB treatment, also revealing a dose-dependent antiviral effect. In addition, by stratifying the obtained results according to HR-HPV genotype, we observed a significant reduction in the viral load of HPV 16, P2 (56, 59, 66), 31, and P3 (35, 39, 68) and a strong decrease in the viral load of HPV 45, 52, and P1 (33, 58). Overall, 85% of the analyzed cervical cell samples exhibited an improvement in HPV viral load after PHMB exposure, while only 15% remain unchanged. For the first time, the data from this pilot study support the activity of PHMB on a specific phase of the HPV viral lifecycle, the one regarding the newly generated virions, reducing viral load and thus blocking the infection of other cervical cells.

Transforming offshore field developments with Pivotree™: an innovative technology solution for fast, cost effective, and low footprint projects

Pivotree™ represents a technology paradigm shift in offshore oil field development, reducing cost and providing a route to market for the operators of stranded resources. Conventional standalone projects, characterised by substantial upfront capital expenditures with complex equipment and high installation costs, are juxtaposed against the Pivotree™ solution, with a markedly reduced capital outlay that retains all the requisite safety and operational features associated with larger systems. A comparative study of activities, materials, and risks concomitant with different field development concepts are analysed for a range of reservoir characteristics, highlighting the financial advantages of the Pivotree™ technology using Multiple-Criteria Decision Analysis (MCDA). MCDA allows a systematic assessment and comparison of a broad spectrum of qualitative factors including safety, environmental impact, operability, maintainability, time to deploy, water depth, independence, and abandonment burden and development of a set of economic scenarios with the costs of different development concepts compared over the lifecycle phases from Drilling to Abandonment, and the Net Present Value (NPV) and Internal Rate of Return (IRR) calculated against a range of oil prices, and operating expenditures. A case study ‘Concept Select’ activity is performed using MCDA to evaluate the range of development options against the listed set of project and technology attributes. A set of weightings is provided for the purpose of analysis by the author equating to the corporate values and strategy of a fictional energy company. The MCDA analysis demonstrates that the Pivotree™ technology can unlock production from the global store of stranded offshore discovered resources.

Requalification of pipelines for CO2 transport – giving new life to the Bayu-Undan and Reindeer pipelines

Australia has in the order of 3500 km of offshore pipelines currently operating in Commonwealth waters which will require either re-use or decommissioning at the end of hydrocarbon service. Santos are currently developing the Bayu-Undan and Reindeer CCS (carbon, capture and storage) Projects, to make use of the depleted hydrocarbon reservoirs to store carbon dioxide (CO2) via existing offshore infrastructure. A key aspect of these projects is the requalification of existing offshore hydrocarbon pipelines to transport CO2, both of which have been in operation for 10–20 years. The Bayu-Undan and Reindeer pipelines were designed and operated for (a) distinctly different hydrocarbon services and (b) with no initial consideration for future CO2 service. This presents two unique technical starting points in the delivery of safe and robust conversion to CO2 service. Using knowledge gained from this, the paper provides an outline of the key technical considerations to requalification of pipelines unique to the combination of life extension and CO2 service. These are framed in the context of existing industry codes and technical challenges with CO2 pipelines. The outcomes are structured against typical phases in the project lifecycle and opportunities for optimisation of future CO2 re-purposing projects are proposed.

Hindrance or facilitator? The economic consequences of national demonstration eco-industrial parks in China.

Many countries attach great importance to the green, low-carbon, and circular development of industrial parks. China is one of them and has entered an exploration journey of national demonstration eco-industrial parks (NDEIPs). However, the impact of the transformation of industrial parks into NDEIPs on local economic development still remains a mystery. To address this issue, we develop an empirical study using a combination of the multi-period difference-in-differences method and the propensity score matching method based on the panel data for 266 cities in China from 2001 to 2021. The results show that industrial parks becoming NDEIPs promotes cities' economic development. This conclusion still holds after a series of robustness tests, such as the reverse causality test and the placebo test. Moreover, the park heterogeneity tests show that the economic consequences vary according to differences in levels, industry types, life cycle phases, and the degree of foreign firm agglomeration. The city heterogeneity tests show that the economic consequences differ based on administrative levels, innovation capabilities, technology industrialization, and environmental friendliness. The spatial heterogeneity tests show that the economic consequences differ according to geographical location and whether situated in the Yangtze River Economic Belt. The policy upgrading heterogeneity tests show that the economic consequences differ during the process of policy upgrading and transformation. In addition, the mechanism tests reveal that green innovation, human capital level, and firm attractiveness mediate the relationship between industrial parks becoming NDEIPs and cities' economic development. This study provides a new perspective for understanding the economic effects of the transformation of industrial parks into NDEIPs, and provides a reference for the government on how to maximize these economic effects.

Digital twins in aircraft production and MRO: challenges and opportunities

The digital twin (DT) concept, value-adding connecting the real and digital world, has been a rising trend in recent years, while the implementation and observation of challenges are still subject to research. Implementations of holistic Digital Twins of tangible and intangible assets of complex products or processes are often ideal-theoretic; instead, only subsystems and processes are replicated, which digital representations serve specific, meaningful applications. Specifically, with its distinct characteristics, the aviation industry and its production show various future application scenarios, which we use case-driven outline in this work. Therefore, we first summarize common, industry-neutral challenges of implementing Digital Twins and give an overview of aircraft production characteristics. Then, we will outline different fields of utilizing the Digital Twin concept and highlight integrational, organizational, and compliance-related challenges as well as opportunities in the context of aircraft production and Maintenance, Repair, and Overhaul (MRO). The use cases are located at different aircraft life cycle phases, from production system development, production supplying logistics, and Quality Assurance (QA) up to retrofit.

Use cases of a digital twin bridge in operation

AbstractThe digital twin bridge makes an important contribution on the way to predictive life cycle management. The potentials are many, especially in the life cycle phase “operation.” There, the digital twin bridge can serve as an efficient tool in terms of analyses, predictions, control, and monitoring. The goal is optimized maintenance, the importance of which continues to grow in view of the current challenges for civil engineering structures. It is therefore particularly important that relevant stakeholders with their needs and requirements are involved in the conception of the digital twin bridge at an early stage. This approach is being pursued by the German Federal Highway Research Institute (BASt) in various research projects that already cover partial aspects of the digital twin and is also being continued in an ongoing project to develop an overall concept for the digital twin bridge. Possible use cases were collected and assigned to the topics of “operational processes,” “maintenance planning and implementation,” and “strategic life cycle management.” In a workshop, the use cases were discussed and initially ranked by and with stakeholders. The results form an important basis for the elaboration of the modular overall concept of the digital twin bridge and the way into practice.

Advances in Understanding the Envelope Protein in Coronavirus Infection

The COVID-19 pandemic continues to impart devastating effects on human health, healthcare systems, and the economy. Vaccination, monoclonal antibodies, and antiviral therapies prevent and limit early infection. Unfortunately, few strategies exist to mitigate the disease burden in the vast number of individuals who seek medical attention with established infection and severe disease. While we have a limited understanding of the mechanistic basis by which SARS-CoV-2 causes critical illness, increasing evidence suggests that host-pathogen interactions shape immune responses that drive the pathogenesis of COVID-19. Therefore, it is imperative to understand the roles of the viral proteins and how they shape the course of infection. One interesting protein is the envelope (E) protein of SARS-CoV-2; this tiny structural protein has been implicated in many phases of the viral life cycle. Importantly, the E protein facilitates viral packaging and replication, and its deletion reduces viral pathogenicity. The E protein also possesses ion channel functions, interacts with host proteins, and has the potential to have various structural topologies. This review aims to establish an updated understanding by highlighting recent developments in the investigation of the SARS-CoV-2 E protein, particularly in comparison to the envelope protein of SARS-CoV. thorough knowledge of this protein will enable targeted studies in hopes of tailored efficacious treatments.

Carbon Footprint of Seawater Desalination Technologies: A Review

Abstract As an important and effective way of mitigating water shortages, desalination has steadily and rapidly increased its global capacity over the decades. This raises concern about its environmental impacts, especially its carbon footprint (CF). Although the CF of desalination has been extensively studied, the existing literature lacks reviews exclusively for it. To help fill the research gap, this study presents a comprehensive and up-to-date review of the CF of seawater desalination technologies, including the conventional reverse osmosis (RO), multi-stage flash (MSF), multi-effect distillation (MED), electrodialysis (ED), and mechanical vapor compression (MVC), and the emerging membrane distillation (MD) and humidification–dehumidification (HDH). To our knowledge, this is the first review that focuses on the CF of seawater desalination. A general procedure for assessing the CF of a desalination system is discussed. The CF data of 211 scenarios from 34 studies published from 2004 to 2023 are reviewed and analyzed, with special focuses on the CF of different technologies, the roles of different life-cycle phases and material/energy flows, and the mitigation measures. The results highlight the CF advantage of RO and low-carbon heat-driven MSF, MED, and MD, and emphasize the dominant role of the operational energy consumption (the amount, the form, and especially the source of the energy) in the CF of desalination. This review improves the understanding of the CF of seawater desalination technologies and of the ways to reduce it.

DeepAVP-TPPred: identification of antiviral peptides using transformed image-based localized descriptors and binary tree growth algorithm.

Despite the extensive manufacturing of antiviral drugs and vaccination, viral infections continue to be a major human ailment. Antiviral peptides (AVPs) have emerged as potential candidates in the pursuit of novel antiviral drugs. These peptides show vigorous antiviral activity against a diverse range of viruses by targeting different phases of the viral life cycle. Therefore, the accurate prediction of AVPs is an essential yet challenging task. Lately, many machine learning-based approaches have developed for this purpose; however, their limited capabilities in terms of feature engineering, accuracy, and generalization make these methods restricted. In the present study, we aim to develop an efficient machine learning-based approach for the identification of AVPs, referred to as DeepAVP-TPPred, to address the aforementioned problems. First, we extract two new transformed feature sets using our designed image-based feature extraction algorithms and integrate them with an evolutionary information-based feature. Next, these feature sets were optimized using a novel feature selection approach called binary tree growth Algorithm. Finally, the optimal feature space from the training dataset was fed to the deep neural network to build the final classification model. The proposed model DeepAVP-TPPred was tested using stringent 5-fold cross-validation and two independent dataset testing methods, which achieved the maximum performance and showed enhanced efficiency over existing predictors in terms of both accuracy and generalization capabilities. https://github.com/MateeullahKhan/DeepAVP-TPPred.

The digital thread for system lifecycle management with a native graph database in a polyglot architecture

AbstractThe Digital Thread is a system that connects different phases of the product lifecycle and the related data across one or more companies in the supply chain. This work aims to develop a graph data model of the Digital Thread, in the context of the vision of polyglot persistence, that interconnects the different phases of the lifecycle and their corresponding data models, processes, and IT systems. This work proposes a Digital Thread Graph that integrates a Digital Model and a derived Digital Twin, using object and relation attributes for view creation and filtering while minimizing redundancy.

Predictive sustainability analysis applied to an automotive design case study.

The paper deals with a predictive sustainability analysis applied to the design of automotive components in lightweight perspective. The analysis is conducted through the integration of the traditional Life Cycle Assessment (LCA) methodology with tailored forecasting algorithms able to provide a predictive evaluation of Climate Change (CC) by elaboration data contained in commercial environmental datasets. The comparison is referred to the entire Life Cycle (LC) of the system (including production, use and End-of-Life) according to a “from cradle to grave approach”.A medium-class car rear crash management system is used as case study, assessing the potential benefits related to the substitution of conventional steel with 6000/7000 series aluminium alloys, along with other minor design changes. Particularly, the study compares the environmental profile of the two solutions based on the CC impact category in application to both an Internal Combustion Engine Vehicle (ICEV) and a Battery Electric Vehicle (BEV).The results show the potentiality of the proposed methodology, highlighting possible improvements/worsenings: new materials and manufacturing technologies adopted in the lightweight rear crash management system entail contrasting environmental effects depending on LC phases, that is, increased CO2eq in production (around 125% - mainly due to the strong energy intensity of aluminium supply chain) and reduced burdens in use and EoL (primarily provided by component mass reduction). That said, the influence of different boundary conditions on the predictive models is significant only for the electricity produced to energize the BEV configuration, leading to an overall variability of comparison results ranging within 3-30% for the BEV case study.

A novel STPA approach to software safety and security in autonomous maritime systems

With higher autonomy in maritime systems, tasks and responsibilities are moved from the human operator to software, increasing the complexity and the importance of safe and reliable functionality. Software failures, however, may be introduced from the early life cycle phases intentionally or unintentionally, and these must therefore be mitigated by safe and secure design approaches. A challenge is that existing methods are not particularly well-suited for analyzing software risks. Thus, the objective of this paper is to propose a systematic and efficient software failure identification approach by extending the Systems-Theoretic Process Analysis (STPA) with a software failure taxonomy and the System Modeling Language (SysML). This enables the control structure in STPA to cover both the dynamic and static aspects of the software functions. Combined with an implementation platform independent questionnaire, this gives a more systematic and guided search for potential software failures than existing approaches. To demonstrate the proposed approach, a case study on a ferry's navigation system that operates in manual control or semi-autonomous mode is performed. In the case study, the focus is on creating an avoidance map data structure, including both moving and static obstacles to be avoided by the ferry, and the subsequent process of collision risk warning calculation. Software failures are identified and evaluated in collision scenarios where the ferry operates under foggy conditions. The paper shows that the proposed systematic approach provides an improved process for identifying and analyzing critical software failures. This facilitates enhanced risk mitigation in the design and testing phases contributing to autonomous systems' safety and security.

Introducing a multipliable BOM-based automatic definition of information retrieval in plant engineering

AbstractThe complexity of process plants and the growing demand for digitalization require efficient and accurate information retrieval throughout the lifecycle phases of a process plant. This paper discusses the concept of instantiation and introduces a method for identifying and multiplying required information in plant engineering using scalable so-called Instantiation Blocks linked to the Bill of Material. Core functionality, an ontology graph and a user interface based on Python and React are developed to demonstrate the implementation of the framework and validate its effectiveness in practice.

Design measures to address carbon emissions in products’ lifecycle: an empirical analysis

AbstractCompanies need to implement low-carbon operations, including product-related innovation initiatives. The literature on low-carbon product design has grown, but existing studies are primarily theoretical. This empirical study identifies design measures adopted by companies committed to GHG emission reduction. A qualitative analysis of the climate change reports from a sample of companies reporting to the CDP was conducted. Design measures were identified and classified. The findings shed light on design measures contributing to emission reduction in different product lifecycle phases.

Pollen thermotolerance of a widespread plant, Lotus corniculatus, in response to climate warming: possible local adaptation of populations from different elevations.

One of the most vulnerable phases in the plant life cycle is sexual reproduction, which depends on effective pollen transfer, but also on the thermotolerance of pollen grains. Pollen thermotolerance is temperature-dependent and may be reduced by increasing temperature associated with global warming. A growing body of research has focused on the effect of increased temperature on pollen thermotolerance in crops to understand the possible impact of temperature extremes on yield. Yet, little is known about the effects of temperature on pollen thermotolerance of wild plant species. To fill this gap, we selected Lotus corniculatus s.l. (Fabaceae), a species common to many European habitats and conducted laboratory experiments to test its pollen thermotolerance in response to artificial increase in temperature. To test for possible local adaptation of pollen thermal tolerance, we compared data from six lowland (389-451 m a.s.l.) and six highland (841-1,030 m a.s.l.) populations. We observed pollen germination in vitro at 15 °C, 25 °C, 30 °C, and 40 °C. While lowland plants maintained a stable germination percentage across a broad temperature range (15-30 °C) and exhibited reduced germination only at extremely high temperatures (40 °C), highland plants experienced reduced germination even at 30 °C-temperatures commonly exceeded in lowlands during warm summers. This suggests that lowland populations of L. corniculatus may be locally adapted to higher temperature for pollen germination. On the other hand, pollen tube length decreased with increasing temperature in a similar way in lowland and highland plants. The overall average pollen germination percentage significantly differed between lowland and highland populations, with highland populations displaying higher germination percentage. On the other hand, the average pollen tube length was slightly smaller in highland populations. In conclusion, we found that pollen thermotolerance of L. corniculatus is reduced at high temperature and that the germination of pollen from plant populations growing at higher elevations is more sensitive to increased temperature, which suggests possible local adaptation of pollen thermotolerance.

Salinity Stress in Maize: Consequences, Tolerance Mechanisms, and Management Strategies

Maize, along with rice and wheat, is a popular staple food crop worldwide, and the most widely produced cereal crop. It is a versatile crop that may be utilized as a source of raw materials for human and animal fodders. Low agricultural yield and rapid population expansion significantly threaten future food security. Maize production is hampered by biotic and abiotic causes, with abiotic factors being the most critical limitation to agricultural output worldwide. Soil salinity is a key abiotic factor that reduces agricultural production by imposing negative impacts at several life cycle phases, including germination, seedling, vegetative, and reproductive development. Maize plants experience many physiological changes due to osmotic stress, toxicity of particular ions, and nutritional imbalance induced by salt stress. The degree and duration of stress, crop growth phases, genetic characteristics, and soil conditions influence yield reduction. Maize plants can tolerate salt stress involving a complex mechanism by changing their physiological, biochemical, and metabolic activities like stomatal functioning, photosynthesis, respiration, transpiration, hormone regulation, enzymes, metabolite generation, etc. After studying the salt tolerance mechanisms of maize plants under stress, integrated management techniques should be developed for maize agriculture in saline settings. Therefore, the study of plant responses to salt stress, stress tolerance mechanisms, and management strategies is one of the most imperative research fields in plant biology, and the study will focus on the effects of salt stress in different growth stages, plant tolerance mechanisms, and agronomic management practices for successful maize production all over the world.

Creating cloud platforms for supporting FAIR data management in biomedical research projects.

Biomedical research projects are becoming increasingly complex and require technological solutions that support all phases of the data lifecycle and application of the FAIR principles. At the Berlin Institute of Health (BIH), we have developed and established a flexible and cost-effective approach to building customized cloud platforms for supporting research projects. The approach is based on a microservice architecture and on the management of a portfolio of supported services. On this basis, we created and maintained cloud platforms for several international research projects. In this article, we present our approach and argue that building customized cloud platforms can offer multiple advantages over using multi-project platforms. Our approach is transferable to other research environments and can be easily adapted by other projects and other service providers.

Enhancing sustainability considerations in construction industry projects

AbstractIn today’s society, the construction sector significantly influences all three aspects of sustainability: economic, environmental, and social. Industry and academia have recognized sustainability in construction projects as a key concern. The New Zealand government also focuses on providing a sustainable construction sector centred on high performance, high productivity, enhanced innovation, and improving community well-being through a better-built environment. Project management and sustainability are two distinct areas of research. Previous empirical research on the effectiveness of construction project implementation lacked sustainability success components. This research aims to provide criteria for project sustainability success for future performance on construction projects. Based on the existing literature, many economic, environmental, and social sustainability indicators were compiled for consideration at various pipeline project life cycle phases. The information gathered from the Scopus database was analyzed using ATLAS.ti 9 software to create project sustainability success criteria. Pipeline construction projects and sustainability must focus on environmental challenges while managing economic and social advantages. The research investigated sustainable construction adoption, revealing weak awareness among organizations due to limited understanding among key actors like clients, regulatory bodies, and construction organizations. Lack of effective application of sustainability guidelines, inadequate legislation, and building codes were significant hurdles in implementing sustainable practices in the construction sector. The study highlights essential issues to promote sustainable practices in the industry. The study findings suggest that organizations and individual factors are strong predictors for achieving sustainable construction and are vital antecedents leading to greater sustainability adoption. Finally, the study points to construction project managers’ knowledge of how to set up criteria connected to sustainability and how it could affect the outcome of their projects.