Life Cycle Design Research Articles

Ambient and Heat-Cured Geopolymer Composites: Mix Design Optimization and Life Cycle Assessment

The feasibility of producing sustainable cement-free composites and its environmental impact were investigated in this research. Experimental parametric evaluation was carried out in this regard to explore the optimum mix design of the composites. The effect of synthesis parameters and curing conditions on the behavior of the produced geopolymer composites was investigated. The studied parameters included the molarity of the sodium hydroxide solution (12 M, 14 M, and 16 M), the sodium silicate to sodium hydroxide ratio (1, 1.5, 2, and 2.5), the fluid to binder ratio (0.6, 0.65, and 0.7), and the age. The curing conditions included ambient curing and heat treatment at 40 °C, 80 °C, and 120 °C for 24 h, 48 h, and 72 h. In addition, life cycle assessment was performed to compare the environmental impact of geopolymer and cementitious composites. The results reflected the possibility of producing geopolymer composites with significant positive environmental impacts over traditional cementitious composites. The synthesis parameters played a major role in the behavior of the produced geopolymers. Heat curing was necessary for the geopolymer mortar to achieve high early strength. However, strength development with age was more obvious for ambient-cured specimens than heat-cured specimens. The optimum fluid to binder ratio used in this research was 0.6. For this ratio, the compressive strength increased as the molarity of the sodium hydroxide solution increased for all sodium silicate to sodium hydroxide ratios. Finally, SEM images showed that the higher the molarity and as the amount of reacted FA particles increased, the better the microstructure of the geopolymer mortar was and the fewer pores the matrix had.

Investigation into the Performance of NiTi Shape Memory Alloy Wire Reinforced Sn-Bi Self-Healing Metal Matrix Composite.

Self-healing materials have the potential to create a paradigm shift in the life cycle design of engineered structures, by changing the relation between material damage and structural failure, affecting structures’ lifetime, safety, and reliability. However, the knowledge of self-healing capabilities in metallic materials is still in its infancy compared to other material systems because of challenges in the synthesis of organized and complex structures. This paper presents a study of a metal matrix composite system that was synthesized with an off-eutectic Tin (Sn)-Bismuth (Bi) alloy matrix, reinforced with Nickel–Titanium (NiTi) shape memory alloy (SMA) wires. The ability to close cracks, recover bulk geometry, and regenerate strength upon the application of heat was investigated. NiTi wires were etched and coated in flux before being incorporated into the matrix to prevent disbonding with the matrix. Samples were subjected to large deformations in a three-point bending setup. Subsequent thermo-mechanical testing of the composites confirmed the materials’ ability to restore their geometry and recover strength, without using any consumable components. Self-healing was accomplished through a combination of activation of the shape memory effect in the NiTi to recover the samples’ original macroscopic geometry, closing cracks, and melting of the eutectic material in the matrix alloy, which resealed the cracks. Subsequent testing indicated a 92% strength recovery.

An analysis model accounting for time-dependent shear lag effects in assembled composite bridge decks

The concrete deck of steel-concrete composite bridges made via prefabricated construction consists of precast slabs and construction joints between the slabs. When the age difference between the longitudinal joint concrete and precast slab concrete (new-old concrete) across a beam section is considered, the time-dependent characteristic of the assembled deck is different from that of the whole prefabricated deck. Based on the virtual work principle, differential equations were established to analyse the influence of the time-dependent characteristics of new-old concrete across a beam section on the shear lag effect of the composite beams. The analysis of examples showed that the proposed model was more accurate than the traditional model, which ignores the concrete age difference across a beam section, especially when analysing the long-term stress of joint concrete. The long-term stress of the joint concrete obtained by the proposed model decreased faster than that obtained by the traditional model with time, which increased the non-uniformity of the distribution of stress along the concrete flange. Overall, the proposed model could reasonably forecast the long-term performance of composite beams with assembled decks, which is beneficial to the life-cycle design and service behaviour analysis of composite bridges.

The Relevance of Recyclability for the Life Cycle Assessment of Packaging Based on Design for Life Cycle

The awareness for more environmentally sustainable packaging solutions is steadily growing. With both consumers and manufacturers looking to minimize their impacts on the environment, the need for easy-to-implement and standardized measures strengthening a circular economy rises. In the research, the goal was to determine whether the carbon footprint and circularity of non-food plastic packaging can be improved by simple design changes. The results should then lead to design recommendations, providing a Design for Life Cycle approach. The methodology of the study was to conceptually design a single-use plastic packaging with attributes having positive and negative effects on recyclability. Herein, only design characteristics from products obtainable on the market were regarded. Moreover, a comparison over existing recyclability assessment methods is given. The recyclability was then determined with the selected approach by Cyclos HTP, and a reference calculation was conducted. Life Cycle Assessments were implemented for 14 packaging designs using the GaBi software and the Environmental Footprint method. The results showed that dark color, material compounds, insoluble adhesives, and large labels result in lower recyclability of the single-use packaging. The impacts on climate change range from 0.13 kg CO2-equivalent emissions (100% recyclability) to 0.21 kg CO2-equivalent emissions (0% recyclability) per packaging, showing that lower recyclability leads to a larger carbon footprint in all assessed scenarios. Concluding, the research demonstrated that by applying Design for Life Cycle measures, impacts on climate change can be reduced. Lastly, design recommendations for decision makers are outlined.

Influence of localised corrosion on the cyclic response of reinforced concrete columns

The evaluation of the corrosion effects on both the local and global behaviour of reinforced concrete elements is nowadays a topical problem, since many structures have reached their design life cycle. Reinforced concrete structures damaged by reinforcement corrosion can exhibit not only reduction of the bearing capacity but also an alteration of the collapse mechanism with a reduction of the structural ductility. In order to study the problem, some of the authors carried out experimental tests and numerical models. The presented paper provides in-depth information, since a new experimental survey is presented and discussed. In particular, full-scale experimental tests on four columns subjected to localised corrosion of the longitudinal reinforcement are performed under vertical force and horizontal cyclic loads. The results of the cyclic experimental tests show how the reinforcement corrosion (in terms of amount and morphology) can lead to a reduction of both the structural strength and ductility, and/or can change the failure modes.

An investigation for integration of deep learning and digital twins towards Construction 4.0

PurposeThe purpose of this paper is to investigate the potential integration of deep learning (DL) and digital twins (DT), referred to as (DDT), to facilitate Construction 4.0 through an exploratory analysis.Design/methodology/approachA mixed approach involving qualitative and quantitative analysis was applied to collect data from global industry experts via interviews, focus groups and a questionnaire survey, with an emphasis on the practicality and interoperability of DDT with decision-support capabilities for process optimization.FindingsBased on the analysis of results, a conceptual model of the framework has been developed. The research findings validate that DL integrated DT model facilitating Construction 4.0 will incorporate cognitive abilities to detect complex and unpredictable actions and reasoning about dynamic process optimization strategies to support decision-making.Practical implicationsThe DL integrated DT model will establish an interoperable functionality and develop typologies of models described for autonomous real-time interpretation and decision-making support of complex building systems development based on cognitive capabilities of DT.Originality/valueThe research explores how the technologies work collaboratively to integrate data from different environments in real-time through the interplay of the optimization and simulation during planning and construction. The framework model is a step for the next level of DT involving process automation and control towards Construction 4.0 to be implemented for different phases of the project lifecycle (design–planning–construction).

Opportunities and Adoption Challenges of AI in the Construction Industry: A PRISMA Review

Artificial intelligence (AI) is a powerful technology with a range of capabilities, which are beginning to become apparent in all industries nowadays. The increased popularity of AI in the construction industry, however, is rather limited in comparison to other industry sectors. Moreover, despite AI being a hot topic in built environment research, there are limited review studies that investigate the reasons for the low-level AI adoption in the construction industry. This study aims to reduce this gap by identifying the adoption challenges of AI, along with the opportunities offered, for the construction industry. To achieve the aim, the study adopts a systematic literature review approach using the PRISMA protocol. In addition, the systematic review of the literature focuses on the planning, design, and construction stages of the construction project lifecycle. The results of the review reveal that (a) AI is particularly beneficial in the planning stage as the success of construction projects depends on accurate events, risks, and cost forecasting; (b) the major opportunity in adopting AI is to reduce the time spent on repetitive tasks by using big data analytics and improving the work processes; and (c) the biggest challenge to incorporate AI on a construction site is the fragmented nature of the industry, which has resulted in issues of data acquisition and retention. The findings of the study inform a range of parties that operate in the construction industry concerning the opportunities and challenges of AI adaptability and help increase the market acceptance of AI practices.

Potential Loss in Prestressing Tendon Forces under Long-Term Service Conditions: Cross-Laminated Timber Shear Wall Applications

The seismic performance of post-tensioned cross-laminated timber (CLT) shear walls depends on the existing prestressing tendon force. The prestressing force will change over time because of the time-dependent elastic, creep, and environmental deformation of timber. In this study, post-tensioned CLT shear walls under three different prestressing force levels were monitored over 540 days to study the prestressing force loss under varied environments. The long-term experimental results of temperature and relative humidity, moisture content, prestressing force, and timber strain were carefully recorded and analyzed. Subsequently, a comprehensive numerical model was established which includes four modules: moisture diffusion analysis, time-dependent elastic deformation analysis, time-dependent creep and environmental deformation analysis, and prestressing force updating. The long-term experimental results were used to validate the established model. Good agreement between the simulated and the experimental results was achieved. Lastly, the validated numerical model was implemented to predict the potential loss of prestressing force in post-tensioned CLT shear walls during a service life of 50 years. The loss percentage under three different stress levels in uncontrolled environment scenario were 26.8%, 25.2%, and 21.1%. This information can be used to support the life cycle design of post-tensioned CLT structures ensuring the long-term structural safety.

A framework to implement human reliability analysis during early design stages of advanced reactors

Nuclear power plants require human actions throughout their lifecycle from design, construction, operation, and decommissioning. However, for advanced reactors (e.g., Generation IV), the reliance on human intervention in safety-related actions is expected to be reduced or completely replaced by automated actions. The Probabilistic Risk Assessment (PRA) Standard for Advanced Non-LWR Nuclear Power Plants requires that the impacts of all operator actions are captured and incorporated in the risk of the modeled plant. Moreover, the Modernization of Technical Requirements for Licensing Advanced Reactors requires human reliability analysis (HRA) to be included throughout all design and PRA development stages. However, due to the lack of details during the early design stages, HRA is often postponed until the design is mature enough. Conducting HRA in later design stages, though it may be adequate in capturing pre-, at-, and post-initiators comes short of informing the design itself in the iterative design lifecycle. Hence, this paper presents a framework to include HRA during the design's early stages, pre-conceptual or conceptual. The proposed framework provides a process for the removal of operator actions that do not contribute to the risk and the identification of all key operator actions that are critical to the safety of the design. The results of this framework are then used to inform the design of those safety-related operator actions to update the design further. Then, using information from the updated design, this framework can be reapplied to investigate the impact of the design update on human reliability. The PRA model of the X-energy's pre-conceptual Xe-100 high-temperature gas-cooled pebble-bed reactor (HTGR-PB) design is used to demonstrate the approach. In the pre-conceptual Xe-100 PRA model, also called Phase 0 PRA model, human actions were considered an integral part of analyzing the plant response to different initiating events. Hence, in this paper, all possible human actions in the Xe-100 PRA model are identified, analyzed, and removed to emulate a design relying only on the available automated control systems. The preliminary results of this assessment show how safe the Xe-100 design is even without crediting any human actions. The results also list necessary sequences in which operator actions are critical to the risk profile of the design.

Ontology-Based Approach Supporting Multi-Objective Holistic Decision Making for Energy Pile System

The traditional way of designing energy pile system is mostly single domain/objective oriented, which lacks of means to coherently consider different while relevant factors across domains. The cost for life cycle design, construction and maintenance, return of investment, CO2 emission related sustainable requirements, and so on also need to be considered, in a systematic manner, along with the main functional design objective for loading capacity and robustness. This paper presents a novel multi-objective holistic approach for energy pile system design using ontology based multi-domain knowledge orchestration, which can holistically provide the designers with across domain factors regarding financial, safety, and environmental impact, for smart and holistic consideration during the early design stage. A prototypical ontology-based decision tool has been developed, aiming at the holistic optimization for energy pile system by combining ontology and Semantic Web Rule Language rules. A case study was performed to illustrate the details on how to apply knowledge query to provide a series of design alternatives autonomously by taking different design parameters into account. The method has demonstrated its practicability and scientific feasibility, it also shows the potential to be adopted and extended for other domains when dealing with multi-objective holistic design making.

Energy Key Performance Indicators for Mobile Machinery

Mobile machinery manufacturers must face and deal with reducing fuel consumption, rising prices, and environmental pollution. The development of methods to evaluate the efficiency and effectiveness of the energy performance of hydraulically actuated systems has become a priority for researchers and OEMs, Original Equipment Manufacturers. In this paper, a new methodology that is based on Key Performance Indicators, KPI, is proposed with different goals: (i) to evaluate the energy performance and the monitoring of its evolution in the different stages of its life cycle (design, commissioning, optimization, retrofit, etc.); (ii) compare the energy levels between machines of different sizes and different brands in a benchmarking process; and (iii) establish a database that is state of the art, which facilitates setting achievable goals or limits for improvement. These KPI values can be deduced simply from the energy balances that were made from the experimental study of various machines over a relatively long period. This methodology has been applied to typical hydraulic systems for lifting and lowering loads that are used in a wide variety of mobile machines of different mechanical designs and sizes. Still, it can be included in the generic name of “loaders”. A KPI’s values for the three machines are presented in a dashboard as a decision-making tool.

System Identification of Two-Dimensional Transonic Buffet

When modeled within the unsteady Reynolds-averaged Navier–Stokes framework, the shock wave dynamics on a two-dimensional airfoil at transonic buffet conditions is characterized by time-periodic oscillations. Given the time series of the lift coefficient at different angles of attack for the OAT15A supercritical profile, the Sparse Identification of Nonlinear Dynamics (SINDy) technique is used to extract a parameterized, interpretable, and minimal-order description of this dynamics. For all the operating conditions considered, SINDy infers that the dynamics in the lift-coefficient time series can be modeled by a simple parameterized Stuart–Landau oscillator, reducing the computation time from hundreds of core hours to seconds. The identified models are then supplemented with equally parameterized low-dimensional dynamic mode decomposition based state observers enabling real-time estimation of the whole flowfield from the predicted lift. The value of this simple model is in the possibility of enriching sparse data sets in the buffet regime for new geometries. Only a few unsteady simulations need to be performed to adjust the coefficients of the identified model and then supplement the data set with new cases. Simplicity, accuracy, and interpretability make the identified model an attractive tool toward the construction of real-time systems to be used during the design, certification, and operational phases of the aircraft life cycle.

Effect of Rehydration on the Performance of Mechanically Loaded UHPC

Unhydrated cementitious materials in ultrahigh-performance concrete (UHPC) with a low water-to-binder ratio stop hydrating owing to water shortage but can continue to hydrate after re-exposure to water; this phenomenon is referred to as rehydration. This article discusses the effects of rehydration on the performance of mechanically loaded UHPC when subjected to continuous water exposure. For this purpose, UHPCs with a steel fiber content of 0 and 2% were prepared with a constant water–binder ratio of 0.20. A uniaxial compression load was applied to generate microcracks in the UHPC, where cube specimens were preloaded up to 50, 70, 90, and 100% of the ultimate compressive load. After preloading, UHPC specimens were stored in water for 90 days. Preloading is found to have a more significant effect on the splitting tensile strength than on the compressive strength. At different preload levels, the splitting tensile strength first increases and then decreases with increasing water curing time. The cumulative capillary water absorption decreases with increasing water curing time, and the percentage decrease increases with an increasing preload level. The chemically bound water content increases with increasing water curing time, and the increase becomes more significant at a higher preload level. The filling effect of the rehydration reduces the connectivity of the internal pores, which is the main reason for the increase in strength and decrease in permeability observed under water curing. These results provide a foundation for the application and life-cycle design of UHPC structures over long service periods in water environments.

Cognition in Software Engineering: A Taxonomy and Survey of a Half-Century of Research

Cognition plays a fundamental role in most software engineering activities. This article provides a taxonomy of cognitive concepts and a survey of the literature since the beginning of the Software Engineering discipline. The taxonomy comprises the top-level concepts of perception, attention, memory, cognitive load, reasoning, cognitive biases, knowledge, social cognition, cognitive control, and errors, and procedures to assess them both qualitatively and quantitatively. The taxonomy provides a useful tool to filter existing studies, classify new studies, and support researchers in getting familiar with a (sub) area. In the literature survey, we systematically collected and analysed 311 scientific papers spanning five decades and classified them using the cognitive concepts from the taxonomy. Our analysis shows that the most developed areas of research correspond to the four life-cycle stages, software requirements, design, construction, and maintenance. Most research is quantitative and focuses on knowledge, cognitive load, memory, and reasoning. Overall, the state of the art appears fragmented when viewed from the perspective of cognition. There is a lack of use of cognitive concepts that would represent a coherent picture of the cognitive processes active in specific tasks. Accordingly, we discuss the research gap in each cognitive concept and provide recommendations for future research.

A study on pressurizer cutting scenario for radiation dose reduction for workers using VISIPLAN

The operations in the design lifecycle of a nuclear power plant targeted to be decommissioned lead to neutron activation. Operations in the decommissioning process include cutting, decontamination, disposal, and processing. Among these, cutting is done close to the target material, and thus workers are exposed to radiation. As there are only a few studies on pressurizers, there arises the need for further research to assess the radiation exposure dose. This study obtained the specifications of the AP1000 pressurizer of Westinghouse and the distribution of radionuclide inventory of a pressurizer in a pressurised water reactor for evaluation based on literature studies. A cutting scenario was created to develop an optimal method so that the cut pieces fill a radioactive solid waste drum with dimensions 0.571 m × 0.834 m. The estimated exposure dose, estimated using the tool VISIPLAN SW, in terms of the decontamination factor (DF) ranged from DF-0 to DF-100, indicating that DF-90 and DF-100 meet the ICRP recommendation on exposure dose 0.0057 mSv/h. At the end of the study, although flame cutting was considered the most efficient method in terms of cutting speed, laser cutting was the most reasonable one in terms of the financial aspects and secondary waste.

Web-Based Structured Education for Type 2 Diabetes: Interdisciplinary User-Centered Design Approach.

BackgroundDigital health research encompasses methods from human-computer interaction and health research.ObjectiveThis paper aims to describe how these methods were combined to develop HeLP-Diabetes: Starting Out, a web-based structured education program for people newly diagnosed with type 2 diabetes.MethodsThe development process consisted of three phases: initial design for effectiveness, optimization for usability, and in the wild testing in the National Health Service with people newly diagnosed with type 2 diabetes, and further revisions. We adopted an iterative user-centered approach and followed steps from the human-computer interaction design life cycle and the Medical Research Council guidelines on developing and evaluating complex interventions.ResultsThe initial design process resulted in an 8-session program containing information and behavior change techniques targeting weight loss, being more active, and taking medication. The usability testing was highlighted at an early stage, where changes needed to be made to the language and layout of the program. The in the wild testing provided data on uptake of and barriers to use. The study suggested low uptake and completion of the program, but those who used it seemed to benefit from it. The qualitative findings suggested that barriers to use included an expectation that the program would take too long. This informed refinements to the program.ConclusionsThe use of interdisciplinary methods resulted in an iterative development process and refinements to the program that were based on user needs and data on uptake. The final intervention was more suitable for a definitive evaluation than the initial version. The description of our approach informs other digital health researchers on how to make interventions more sensitive to user needs.

Education for optimized Life Cycle Management: The Project e-CIRP and its insights into embedding circular economy aspects to product design via teaching

The integration of circular economy-based life cycle management (LCM) into product design and optimisation is essential for the transformation towards a circular economy (CE). However, companies often lack the expertise to adapt life-cycle design (LCD) thinking in their business operations and are in need of respective capacity building. To close this apparent gap is the aim of the project e-CirP (Embedding Circular Economy into Product Design and Optimization) where LUT University, Fraunhofer, Technical University of Denmark, University of Padova, Delft University of Technology, University of Helsinki and Metso Outotec have worked together to develop a program that allows Master students across Europe to learn how to integrate CE and Life Cycle Thinking principles into product design by analysing real industrial cases. In the project, modern pedagogical approaches have been applied. A modular training package covering general circular economy aspects, as well as detailed value chain perspectives, has been created. Next to the content-related aspects, a great focus was also on the support of so-called soft-skills development, e.g. through international student cooperation on case studies. The paper presents the perspective of participating students as well as the cooperating companies that supplied the industry cases to allow an overview of opportunities and challenges.

Operationalizing Human Values in Software Engineering: A Survey

Human values (e.g., pleasure, privacy, and social justice) are what a person or a society considers important. The inability to address them in software-intensive systems can result in numerous undesired consequences (e.g., financial losses) for individuals and communities. Various solutions (e.g., methodologies, techniques) are developed to help "operationalize values in software". The ultimate goal is to ensure building software (better) reflects and respects human values. In this survey, "operationalizing values" is referred to as the process of identifying human values and translating them to accessible and concrete concepts so that they can be implemented, validated, verified, and measured in software. This paper provides a deep understanding of the research landscape on operationalizing values in software engineering, covering 51 primary studies. It also presents an analysis and taxonomy of 51 solutions for operationalizing values in software engineering. Our survey reveals that most solutions attempt to help operationalize values in the early phases (requirements and design) of the software development life cycle. However, the later phases (implementation and testing) and other aspects of software development (e.g., "team organization") still need adequate consideration. We outline implications for research and practice and identify open issues and future research directions to advance this area.

Selection of Requirement Elicitation Techniques: A Neural Network based Approach

Requirement Elicitation is key activity of requirement engineering and has a strong impact on design and other phases of software development life cycle. Poor requirement engineering practices lead to project failure. A sound requirement elicitation process is the foundation for the overall quality of software product. Due to criticality and high impact of this phase on overall success and failure of projects, it is very necessary to perform the requirements elicitation activities in a perfect and specific manner. The most difficult and demanding jobs during Requirement Elicitation phase is to select appropriate and specific technique from a wide array of techniques and tools. In this paper, a new approach is proposed using an artificial neural network for selection of requirement elicitation technique from a wide variety of tools and techniques that are available. The training of Neural Network is done by back propagation algorithm. The trained and resultant network can be used as a base for selection of requirement elicitation techniques.

Research and development of public service platform for integrated circuit test

Integrated circuit (IC) test is a key technical part of IC chain, which works through the entire life cycle of IC design, manufacturing, packaging, and application. Based on the increasing requirements of IC test, this paper analyzes the breakthrough point to promote the development of IC test and puts forward an accurate and feasible programme of public test platform construction so as to achieve long-term sustainable development of IC industry.