Traditional Engineering Research Articles

Redefining structural soundness in concrete constructions: A groundbreaking technique for water–cement ratio assessment in sustainable building integrated with explainable artificial intelligence

Predicting concrete’s compressive strength (CS) is a crucial and challenging task in civil engineering as it directly impacts the longevity and structural integrity of infrastructure initiatives. Precise estimation of the water–cement ratio (W/C) is essential for guaranteeing the structural integrity of structures since it is a critical parameter that greatly affects concrete’s CS. This study carries out an extensive investigation of the prediction of the W/C of concrete, utilizing the enormous potential of machine learning, including the backpropagation neural network (BPNN), bilayer neural network, boosted tree algorithm, bagged tree algorithm (BGTA), and support vector regression (SVR), using 108 datasets. We integrate artificial intelligence models with traditional engineering techniques to develop a reliable, precise, and efficient forecasting system. The study input includes curing days (D), fiber (F), cement (C), fine and coarse aggregate (FA and CA), density (Den), CS, water (W), and W/C as the output variables. The result shows that, in comparison to the other models, BGTA-M3 achieved the best performance evaluation criterion. In the calibration and verification phases, NSE, PCC, R, and WI = 1 and MAPE = 0.00, respectively. BPNN-M3 had an MAPE of 0.0004 in the verification phase. The study uses SHapley Additive exPlanations (SHAP), an explainable artificial intelligence (AI) technique, to improve decision-making in complex systems, with cement “C” significantly contributing to higher predictions in SVR-M2. Future studies should expand the dataset to include information from diverse geographic areas, environmental conditions, and concrete mixes to enhance the applicability and dependability of the models.

Managing Complexity in Socio-Technical Systems by Mimicking Emergent Simplicities in Nature: A Brief Communication.

In the context of socio-technical systems, traditional engineering approaches are inadequate, calling for a fundamental change in perspective. A different approach encourages viewing socio-technical systems as complex living entities rather than through a simplistic lens, which enhances our understanding of their dynamics. However, these systems are designed to facilitate human activities, and the goal is not only to comprehend how they operate but also to guide their function. Currently, we lack the appropriate terminology. Hence, we introduce two principal concepts, simplexity and complixity, drawing inspiration from how nature conceals intricate mechanisms beneath straightforward, user-friendly interfaces.

Curing characteristics and performance of a bio-based polyurethane engineered sealant with high bonding strength: Effect of R value and chain extender content

Polyurethane (PU) engineering sealants can be used to fill construction joints and pavement cracks with excellent practical results. However, traditional engineering sealants have the disadvantages of poor strength and raw materials that are not environmentally friendly. In this paper, a novel composition system of bio-based polyurethane engineering sealant was developed. The effects of the isocyanate/macroglycol molar ratio (nNCO/nOH, R value) for component A and the contents of amine chain extender (AME) on the curing characteristics and properties of the PU sealant were investigated using a series of experiments. Firstly, the curing process of the sealant was studied by Fourier transform infrared spectroscopy (FTIR) test, surface drying time test and gel time experiments. Secondly, the basic physical properties of the sealant were studied by tensile and hardness tests. And the water resistance of the sealant was judged. Then, the characteristics of molecular movement of polyurethane sealant were analyzed by dynamic mechanical analysis (DMA). The tensile cross-sections of the specimens were observed by scanning electron microscopy (SEM). Finally, the thermal stability of sealants was studied by thermogravimetric (TG) analysis. The results indicated that the material developed in this research can be used as a high-performance engineering sealant in actual projects. The increase in the R value and the decrease in AME content resulted in a longer curing process of the sealant. The rise of R value and AME content was able to raise the tensile strength, bonding strength and hardness of the sealant. The water resistance of the sealant was better. Also, the glass transition temperature (Tg) and storage modulus could also be increased and the thermal stability of the previous stage could be reduced by increasing the R value and AME content. Considering both the performance and construction requirements, the optimum R value and AME contents are recommended to be 2.1 and 1.4%, respectively.

A scientometric analysis of multicriteria decision-making research

ABSTRACT Multi-criteria decision-making (MCDM) is an important decision-making technique for incorporation into Decision Support Systems (DSS). This paper uses bibliographic techniques to characterise the MCDM research field. This research identifies the historical origin of MCDM in both Operations Research/Management Science (OR/MS) and Computer Science. This research identifies the increasing importance of environmental and medical applications in addition to traditional engineering and business applications. It also examines the core literature and the extent to which newer papers are cited.

Three years of morphological dune development after planting marram grass on a beach

AbstractCoastal regions globally face escalating challenges from climate change, including rising sea levels and intensified storm events. To address these threats, coastal resilience emerges as a critical paradigm advocating the integration of nature‐based solutions with traditional engineering approaches. Coastal dunes, acting as protective barriers, offer a promising avenue. This three‐year study assesses the efficacy of an artificial dune system to address local sand‐related nuisances on the adjacent seawall featuring planted marram grass in Oosteroever, Belgium. The focus is on understanding sediment accumulation, dune morphology and vegetation development. The results demonstrate a significant increase in dune height, reaching up to 2 m in the zones planted with marram grass, surpassing the height of the adjacent seawall. Comprehensive profiles and drone surveys revealed consistent dune growth of 27 m3/m, which contrasted with the substantial erosion in the adjacent unvegetated beach areas of up to 30 m3/m. One storm event caused dune toe erosion of 1.5 m3/m, but the dune demonstrated rapid recovery through natural aeolian processes. Marram grass development was not impacted by the initial planting configuration and density and was more pronounced at the perimeter edges of the dune. This study highlights the success of the ‘dune‐in‐front‐of‐a‐dike’ approach, offering insights for sustainable coastal resilience strategies.

Computational Fluid Dynamics (CFD) Analysis of Bioprinting.

Regenerative medicine has evolved with the rise of tissue engineering due to advancements in healthcare and technology. In recent years, bioprinting has been an upcoming approach to traditional tissue engineering practices, through the fabrication of functional tissue by its layer-by-layer deposition process. This overcomes challenges such as irregular cell distribution and limited cell density, and it can potentially address organ shortages, increasing transplant options. Bioprinting fully functional organs is a long stretch but the advancement is rapidly growing due to its precision and compatibility with complex geometries. Computational Fluid Dynamics (CFD), a carestone of computer-aided engineering, has been instrumental in assisting bioprinting research and development by cutting costs and saving time. CFD optimizes bioprinting by testing parameters such as shear stress, diffusivity, and cell viability, reducing repetitive experiments and aiding in material selection and bioprinter nozzle design. This review discusses the current application of CFD in bioprinting and its potential to enhance the technology that can contribute to the evolution of regenerative medicine.

Comprehensive energy solution planning (CESP) framework: an evidence-based approach for sustainable energy access projects in developing countries

Access to affordable, reliable, and modern energy remains a critical goal under the Agenda 2030 for Sustainable Development, especially in remote areas of developing countries. Based on traditional engineering approaches, many energy solution planning tools have been developed to identify the optimal solution in these areas to assess the competition across different technological options. Nevertheless, these approaches, based on an economic optimum, do not necessarily grant long-term sustainability of the solution in specific local contexts, since they are not able to capture the social implications within the Energy-Development nexus. Moreover, also in light of the 2030 Agenda, scientific and grey literature on energy access highlights how energy solutions planning methodologies developed in the last decades need to be complemented by a more comprehensive view, able to integrate evidence from various disciplines, especially engineering and social sciences. Based on the above considerations, this paper introduces a novel framework under the name of CESP, where three social sciences-based phases complement three engineering phases, each one characterized by specific tools, to offer an informed decision framework for the local planner. CESP encompasses a set of techno-economic and socio-technical actions to prevent potential failure as evidenced by a counterfactual analysis used to identify the reasons behind past project failures. The CESP framework presents a sequential and iterative structure that underlines the cyclic perspective of a holistic decision process where social sciences feed the engineering analysis and vice versa. Finally, CESP emerges as a practical and applicable framework for supporting energy access planning in critical areas.

The impact of specialized software on concept generation

AbstractSoftware implementations of traditional engineering design methods can potentially enrich the original methods. A study was conducted to better understand how concept generation can be facilitated using software. Participants of the study were asked to generate concepts using either specialized software, or by using traditional means, for applying function-means modeling and morphological matrices. A concept concretization metric was used to evaluate the results, which indicated that there are both positive and negative aspects of performing concept generation using specialized software.

Synergistic mechanism of substrate hydrolysis and methanogenesis under “gradient anaerobic digestion” process

The destruction of the synergistic effect of the hydrolysis-methanogenesis process (HMP) of substrate may lead to the serious carbon loss of substrate and low biogas yield in traditional straw biogas engineering. In this study, the influence of substrate composition on anaerobic digestion (AD) was investigated under pilot conditions, and the relationship between HMP was further investigated under full-scale plants. The results showed that straw with a high content of soluble substances had the highest methane yield (264.25 L/kg VS) and degradation rate (59.32 %). At HRT = 20 d, the full-scale plant achieved the highest biogas yield (576.92 L/kg VS, 3.47 L/L/d) and degradation rate (67.50 %). Microbial analysis showed that substrate composition affected microbial community and methanogenic metabolic pathway. The analysis results of PICRUSt2 confirm that gradient AD guarantees the synergistic relationship of HMP. This study provides the theoretical basis and engineering guidance for improving the AD process in traditional straw biogas engineering.

Enhancing flexibility in BaTiO3:Sm3+ freestanding nanofiber membranes through Poisson's ratio design

In recent years, flexible functional materials have attracted increasing interest, but there is a lack of designing mechanisms of flexibility design with superstructures. In traditional engineering mechanics, the maximum bending strain (MBS) was considered universal for describing the bendable properties of a given material, leading to the universal designing method of lowering the dimension such as thin membranes designed flexible functional materials. In this work, the MBS was found only applicable for materials with uniformly distributed Poisson's ratio, while the MBS increases with the thickness of the given material in case there is a variation Poisson's ratio in different areas. This means the MBS can be enhanced by certain Poisson's ratio design in the future to achieve better flexibility of thick materials. Here, the macroscopic freestanding inorganic functional BaTiO3:Sm3+ (BTO:S) nanofiber membranes, which have a nonconstant Poisson's ratio response on stress/strain for creating nonuniformly distributed Poisson's ratio, were proven applicable for designing larger MBS and lower Young's modulus for flexible functional materials.

Practical Exploration of Simulation Technology Based on Artificial Intelligence in Engineering Design

This paper discusses the application and practice of the simulation technology based on artificial intelligence (AI) in the field of engineering design. By integrating AI into the traditional engineering design process, we can achieve more efficient and accurate design solutions. Taking a specific engineering design project as an example, this article shows how AI simulation technology contributes to design optimization, risk assessment and cost control. The results show that AI simulation technology can not only improve the design quality, but also shorten the design cycle, bringing revolutionary changes to the field of engineering design.

Self-controlled in silico gene knockdown strategies to enhance the sustainable production of heterologous terpenoid by Saccharomyces cerevisiae

Microbial bioengineering is a growing field for producing plant natural products (PNPs) in recent decades, using heterologous metabolic pathways in host cells. Once heterologous metabolic pathways have been introduced into host cells, traditional metabolic engineering techniques are employed to enhance the productivity and yield of PNP biosynthetic routes, as well as to manage competing pathways. The advent of computational biology has marked the beginning of a novel epoch in strain design through in silico methods. These methods utilize genome-scale metabolic models (GEMs) and flux optimization algorithms to facilitate rational design across the entire cellular metabolic network. However, the implementation of in silico strategies can often result in an uneven distribution of metabolic fluxes due to the rigid knocking out of endogenous genes, which can impede cell growth and ultimately impact the accumulation of target products. In this study, we creatively utilized synthetic biology to refine in silico strain design for efficient PNPs production. OptKnock simulation was performed on the GEM of Saccharomyces cerevisiae OA07, an engineered strain for oleanolic acid (OA) bioproduction that has been reported previously. The simulation predicted that the single deletion of fol1, fol2, fol3, abz1, and abz2, or a combined knockout of hfd1, ald2 and ald3 could improve its OA production. Consequently, strains EK1∼EK7 were constructed and cultivated. EK3 (OA07△fol3), EK5 (OA07△abz1), and EK6 (OA07△abz2) had significantly higher OA titers in a batch cultivation compared to the original strain OA07. However, these increases were less pronounced in the fed-batch mode, indicating that gene deletion did not support sustainable OA production. To address this, we designed a negative feedback circuit regulated by malonyl-CoA, a growth-associated intermediate whose synthesis served as a bypass to OA synthesis, at fol3, abz1, abz2, and at acetyl-CoA carboxylase-encoding gene acc1, to dynamically and autonomously regulate the expression of these genes in OA07. The constructed strains R_3A, R_5A and R_6A had significantly higher OA titers than the initial strain and the responding gene-knockout mutants in either batch or fed-batch culture modes. Among them, strain R_3A stand out with the highest OA titer reported to date. Its OA titer doubled that of the initial strain in the flask-level fed-batch cultivation, and achieved at 1.23 ± 0.04 g L−1 in 96 h in the fermenter-level fed-batch mode. This indicated that the integration of optimization algorithm and synthetic biology approaches was efficiently rational for PNP-producing strain design.

Advancing overall water splitting via phase-engineered amorphous/crystalline interface: A novel strategy to accelerate proton-coupled electron transfer

Traditional phase engineering enhances conductivity or activity by fully converting electrocatalytic materials into either a crystalline or an amorphous state, but this approach often faces limitations. Thus, a practical solution entails balancing the dynamic attributes of both phases to maximize an electrocatalyst’s functionality is urgently needed. Herein, in this work, Co/Co2C crystals have been assembled on the amorphous N, S co-doped porous carbon (NSPC) through hydrothermal and calcination processes. The stable biphase structure and amorphous/crystalline (A/C) interface enhance conductivity and intrinsic activity. Moreover, the adsorption ability of water molecules and intermediates is improved significantly attributed to the rich oxygen-containing groups, unsaturated bonds, and defect sites of NSPC, which accelerates proton-coupled electron transfer (PCET) and overall water splitting. Consequently, A/C-Co/Co2C/NSPC (Co/Co2C/NSPC with amorphous/crystalline interface) exhibits outstanding behavior for oxygen evolution reaction (OER) and hydrogen evolution reaction (HER), requiring the overpotential of 240.0 mV and 70.0 mV to achieve 10 mA cm−2. Moreover, an electrolyzer assembled by A/C-Co/Co2C/NSPC-3 (anode) and A/C-Co/Co2C/NSPC-2 (cathode) demonstrates a low drive voltage of 1.54 V during overall water splitting process. Overall, this work has pioneered the coexistence of crystalline/amorphous phases in electrocatalysts and provided new insights into phase engineering.

In Situ Bioprinting: Process, Bioinks, and Applications.

Traditional tissue engineering methods face challenges, such as fabrication, implantation of irregularly shaped scaffolds, and limited accessibility for immediate healthcare providers. In situ bioprinting, an alternate strategy, involves direct deposition of biomaterials, cells, and bioactive factors at the site, facilitating on-site fabrication of intricate tissue, which can offer a patient-specific personalized approach and align with the principles of precision medicine. It can be applied using a handled device and robotic arms to various tissues, including skin, bone, cartilage, muscle, and composite tissues. Bioinks, the critical components of bioprinting that support cell viability and tissue development, play a crucial role in the success of in situ bioprinting. This review discusses in situ bioprinting techniques, the materials used for bioinks, and their critical properties for successful applications. Finally, we discuss the challenges and future trends in accelerating in situ printing to translate this technology in a clinical settings for personalized regenerative medicine.

Sustainable procurement of medical devices in an international context - Part 3

Background and Objectives This article is the third in a series of three manuscripts published in this journal. It aims to describe how sustainable procurement of medical devices (MDs) can be implemented in operational projects in the context of developing countries. It also further details how the biomedical/clinical engineer lead (BCEL) in charge of technical support during the MD procurement process can apply sustainability principles and concepts of value-based procurement. Material and Methods Based on the authors’ experience of more than 20 years in procurement projects and implementation of MDs, the role of the BCEL will be developed from a theoretical point of view with the description of the second and third pillars of a sustainable purchase following the needs assessment: the assessment of existing conditions along with local capacities and the evaluation of the use conditions during the lifetime of the medical equipment. The application of these principles in operational projects will be further discussed by analyzing literature and lessons learned from projects implemented in developing countries. Results/Proposal The BCEL has a key role in the sustainable procurement of MDs to design the technical specifications of the goods, related services, and post-sales conditions to maximize the benefit of the investment. As the specialist can analyze the local existing conditions and capacities while ensuring efficient use of the MDs during their lifespan, they can contribute to a sustainable implementation of MDs in developing countries. The BCEL shall also be able to analyze the local and international markets to find all possible technological solutions that meet the needs, local conditions, and capacities and ensure quality use during the lifespan of the purchased MD. The BCEL shall have competencies in identifying all the risks related to the use of the MD from the safety risks linked to its installation, use, and maintenance to the sustainability risks linked to obtaining the conditions that guarantee the use of the device and maintaining them as long as possible. Examples of these conditions include the presence of qualified and trained users, availability of maintenance and consumable budgets, availability and maintenance of infrastructure conditions (access, electrical power, water, drainage, medical gasses, etc.), and last but not least, presence of patients requiring a diagnosis or treatment using the purchased MD who were identified during the evaluation of the first pillar: a sound needs assessment. Conclusion As an evolution of the BCEL’s traditional biomedical and clinical engineering work, he/she shall assume the responsibility to guarantee the sustainability of the MD purchase. This quality assurance and control role is achieved by a sound theoretical background knowledge based on the three sustainable procurement pillars: the needs, existing and lifetime use conditions assessments, the analysis of the local and international markets, and a broad understanding of sustainability risks.

Virtual Full Scale Static Test of a Civil Tilt Rotor Composite Wing in Non-Linear Regime

This study addresses the crucial role of post-buckling behavior analysis in the structural design of composite aeronautical structures. Traditional engineering practices tend to result in oversized composite components, increasing structural weight. EASA AMC 20-29’s Building Block Approach suggests phased testing, but its time and cost challenges necessitate a shift to high-fidelity post-buckling analyses, exemplified by MSC NASTRAN SOL 400. This approach, showcased in the analysis of the Next Generation Civil Tilt Rotor Technology Demonstrator’s wing (NGTCTR-TD), effectively de-risks static tests, contributing to a more efficient certification process. The study demonstrates how advanced simulations provide detailed insights into local buckling phenomena, allowing precise stress distribution analysis. These analyses eliminate the risk of structural failure, paving the way for safer, more efficient, and cost-effective airframe structures. Future developments aim to validate numerical analyses with experimental data, further emphasizing the reliability and benefits of high-fidelity simulations.

Improving the hot corrosion resistance of additively manufactured Inconel 718 via recrystallization-based grain boundary engineering induced by its residual stress

Metals containing abundant coherent twin boundaries (TBs) can improve corrosion resistance. Tailoring TBs in additive manufacturing (AM)-fabricated metallic materials with lower stacking fault energy, however, has proven impracticable because the traditional grain boundary engineering (GBE) involved in thermomechanical processing is not appropriate for AM-fabricated alloys with complicated geometric shapes. Here, the AM-fabricated Inconel 718 superalloy was successfully utilized to form abundant TBs induced by the intrinsic residual internal stresses, produced by AM processing via direct heat treatment. The microstructural characteristics and corresponding hot corrosion behaviors of different specimens – initial AM-fabricated, directly aged, and GBE-treated specimens – exposed to a mixed salt of 75 wt% Na2SO4 + 25 wt% NaCl at 650 °C were compared and analyzed systematically. The corrosion mechanisms affecting each of the specimens are discussed in detail. The obtained results reveal that the GBE-treated specimen has the most intact surface after the corrosion test, suffering minimum mass loss and having the shallowest corrosion layer depth, exhibiting optimal hot corrosion resistance. This optimal performance is mainly attributed to the penetration of S and O elements that were efficiently impeded by the TBs. This result holds implications for improving hot corrosion resistance in AM-fabricated metallic materials via directly GBE induced by residual stress.

Integrating artificial intelligence into engineering processes for improved efficiency and safety in oil and gas operations

This paper delves into the significance, challenges, and potential of AI applications within the oil and gas sector. In the dynamic landscape of oil and gas operations, efficiency and safety stand as paramount concerns. Traditional engineering processes, while robust, often face limitations in adapting to the evolving complexities of the industry. However, the advent of AI technologies offers a paradigm shift, presenting unprecedented opportunities for optimization and risk mitigation. This paper explores the multifaceted role of AI in engineering processes throughout the oil and gas value chain. It examines how AI, encompassing machine learning, deep learning, and predictive analytics, empowers decision-makers with real-time insights, optimizing exploration, production, transportation, and refining processes. Efficiency gains are witnessed through predictive maintenance strategies, enabling proactive asset management and minimizing downtime. Additionally, AI-driven process optimization techniques enhance resource allocation, streamlining operations and maximizing output while reducing costs. Moreover, AI's integration fosters a culture of safety by augmenting risk assessment and hazard identification capabilities. Through advanced algorithms, AI systems analyze vast datasets to detect anomalies and predict potential safety hazards, enabling proactive intervention and accident prevention. However, the journey towards AI integration is not without challenges. Technical complexities, regulatory frameworks, and cyber security concerns pose significant hurdles that require careful navigation. Moreover, ethical considerations surrounding data privacy and algorithmic bias necessitate robust governance frameworks to ensure responsible AI deployment. Looking ahead, the paper delineates future trends and opportunities in AI adoption within the oil and gas sector. It underscores the potential for continued innovation and disruption, reshaping workforce dynamics and skill requirements. Embracing AI not only drives operational excellence but also propels the industry towards a sustainable and resilient future

Protection of Gully Slope in Loess Plateau

Rigid protection of traditional engineering slope protection measures can play a certain role in slope protection at the initial stage of the project, but with the passage of time, the slope will be affected by weathering, the stability of the slope will be reduced, in addition, a large area of engineering rock surface exposed will not be coordinated with the surrounding natural vegetation environment, which does not meet the requirements of sustainable development. Therefore, the ecological engineering restoration technology combining engineering measures and biological measures has become the trend and mainstream of slope management and restoration.

Research on design requirements for passive residual heat removal system of lead cooled fast reactor via model-based system engineering

Traditional text-based system engineering, which has been used in the design and application of passive residual heat removal system (PRHRS) for lead-cooled fast reactors, is prone to several problems such as low development efficiency, long iteration cycles, and model ambiguity. This study aims to effectively address the above-mentioned problems by adopting a model-based system engineering (MBSE) method, which has been preliminarily applied to meet the design requirements of a PRHRS. The design process has been implemented based on the preliminary design of the system architecture and consists of three stages: top-level requirement analysis, functional requirements analysis, and design requirements synthesis. The results of the top-level requirements analysis and the corresponding use case diagram can determine the requirements, top-level use cases, and scenario flow of the system. During the functional requirements analysis, the sequence, activity, and state machine diagrams are used to develop the system function model and provide early confirmation. By comparing these sequence diagrams, the requirements for omissions and inconsistencies can be effectively checked. In the design requirements synthesis stage, the Analytic Hierarchy Process is used to conduct preliminary trade-off calculations on the system architecture, after which a white box model is established during the system architecture design. Through these two steps, the analysis and design of the system architecture are ultimately achieved. The resulting system architecture ensures the consistency of the design requirements. Ultimately, a functional hazard analysis was conducted for a specific incident to validate case requirements and further refine the system architecture. Future research can further reduce the design risk, improve the design efficiency, and provide a practical reference for the design and optimization of PRHRS in digital lead-cooled fast reactors.