Specific Engineering Research Articles

Comprehensive Investigations on Split Injection System Using Diesel/Biodiesel Blends Powered Common Rail Direct Injection Engine: Multi‐Objective Optimization

ABSTRACTA combined effect of injection pressure (IP) and split injection mechanism (SIM) on performance, combustion, and emission characteristics of a CRDI engine operated with diesel‐lemongrass biodiesel (LGB20) blend was analyzed and optimized the IP from the experimental results using RSM and ANOVA. The CRDI engine was tested under SIM conditions at various injection pressures (IPs) of 200, 300, 400, 500, and 600 bar, with limitations observed concerning specific engine characteristics. The SIM is accomplished by splitting the injection into two phases during the compression stroke. It was noted that the engine characteristics were improved concerning IPs in SIM by minimizing the intensity of heterogeneity of the mixture. The CRDI engine with 600 bar pressure registered higher in‐cylinder pressure, heat release rate, and brake thermal efficiency (BTE) with lower specific fuel consumption (SFC) when compared to the engine operated with other IPs. It also registered lower exhaust pollutants except oxides of nitrogen (NOx) and carbon dioxides (CO2) due to better combustion at 600 bar pressure. The CRDI engine was operated efficiently at 64.61% load with 600 bar IP and recorded engine parameters as 29.94% of BTE, 0.373 kg/kWh of SFC, 0.64% of CO, 4.55% of CO2, 244 ppm of NOx, 37.2 ppm of HC, and 64.58 HSU of smoke emissions. This study concluded that 600 bar IP is the optimum for better engine characteristics of CRDI engines operated with LGB20 fuel.

Achieving synergistic viscosity and mechanical performance in Poly(aryl ether ketone) copolymers through bisphenol A-phenolphthalein side group ratio modulation

Poly (aryl ether ketone) (PAEK) plays a critical role in the production and application of special engineering plastics. However, the traditional PAEK has some limitations in processing, such as high melt viscosity and high energy consumption. This study successfully synthesized a series of PAEK copolymers with bisphenol A and phenolphthalein side groups through nucleophilic polycondensation, aiming to reduce the high energy consumption associated with material processing. By adjusting the ratio of bisphenol A to phenolphthalein side groups, this research explores their influence on the properties of the copolymers. Comprehensive characterization using various testing methods revealed that increasing the bisphenol A content led to a decrease in heat deflection temperature and glass transition temperature. Although mechanical performance showed a slight decline, it remained comparable to other advanced engineering materials. Notably, tuning the ratio of bisphenol A to phenolphthalein significantly improved the melt rheological properties of the copolymers, reducing melt viscosity, enhancing polymer chain flexibility, decreasing crosslinking tendencies, broadening the processing window, and lowering energy consumption. This study provides a novel strategy for tailoring the performance of PAEK copolymers, offering substantial potential for further research and application. These copolymers are good candidates for next-generation high-performance engineering plastics.

Comparative Evaluation of the Effect of Exhaust Gas Recirculation Usage on the Performance Characteristics and Emissions of a Natural Gas/Diesel Compression-Ignition Engine Operating at Part-Load Conditions

The use of natural gas as an alternative fuel in dual-fuel compression-ignition engines can lead to a substantial reduction in the majority of pollutant emissions compared to fossil fuels, while the thermal efficiency of the engine can be maintained at adequate levels. Its usage has increased widely in recent years, and significant efforts have been made to investigate the inherent physical and chemical processes that take place during this engine’s combustion, as well as the parameters that affect the operation of the engine and use natural gas as energy source. The scope of this study is to investigate the effect of EGR temperature (cold and hot) and rate (10% and 20%) on the performance characteristics and emissions of a dual-fuel compression-ignition engine operating at a specific engine operating point under dual-fuel (diesel–natural gas) conditions. For this reason, a phenomenological two-zone combustion model was developed. The results of the model were validated against the experimental data obtained from a single-cylinder direct-injection, turbocharged compression-ignition dual-fuel research engine operated under part-load conditions (IMEP = 0.52 Mpa and engine speed = 1500 rpm) and at various replacement percentages of diesel using methane (which was treated as a natural gas surrogate). The model results were in good agreement with the experimental results, revealing the ability of the model to be used in the aforementioned EGR analysis. The results of the study revealed that engine operation with 10% cold EGR does not significantly affect the engine performance characteristics, and combined with the addition of 80% gaseous fuel energy, can lead to a substantial reduction in NO and soot emissions, with a moderate increase in CO emissions. On the other hand, a significant finding of the present work is that engine operation with hot EGR under the investigated operating conditions, even though it had a beneficial effect on NO-specific emissions, led to a reduction in engine efficiency and may raise issues regarding the mechanical strength of the engine.

Possibilities of Using Specific Jominy Distance in ANN Models for Predicting Low-Alloy Steels’ Microstructure

Understanding the volume fractions of microstructure constituents such as ferrite, pearlite, bainite, and martensite in low-alloy steels is critical for tailoring mechanical properties to specific engineering applications. To address the complexity of these relationships, this study explores the use of artificial neural networks (ANNs) as a robust tool for predicting these microstructure constituents based on alloy composition, specific Jominy distance, and heat treatment parameters. Unlike previous ANN-based predictions that rely on the hardness after quenching as an input parameter, this study excludes hardness. The developed model relies on readily available input parameters, enabling accurate estimation of microstructure composition prior to heat treatment, which significantly improves its practicality for process planning, optimization, and reducing trial-and-error on industrial applications. Three different input configurations were tested to evaluate the predictive capabilities of ANNs, with results showing that the use of specific Jominy distance as an input variable enhances model performance. Furthermore, the findings suggest that specific Jominy distance could serve as a practical alternative to detailed chemical composition data in industrial applications. The predictions for ferrite, pearlite, and martensite were more accurate than those for bainite, which can be attributed to the complex nature of bainite formation.

Research on the coupling control mechanism of yielding-bolt-grouting in deep water-enriched roadway and its engineering application

Groundwater seepage can easily cause large deformation and fracture instability of the surrounding rock in deep roadways, and the coupling support of “yield-bolt-grouting” can effectively control the occurrence of such accidents. This paper takes the specific engineering geological conditions of deep water-enriched roadway as the research background, revealing the coupling control mechanism of yield-bolt-grouting. The mechanical characteristics of the yielding tube were determined using lab analysis, and an investigation was conducted for the support control mechanism of high-strength yielding bolts. The control mechanism of grouting reinforcement is summarized, and a comprehensive coupling control technology system of “yield-bolt-grouting” is proposed based on the rheological large deformation characteristics of the surrounding rock of deep water-enriched roadway, with high-strength yielding grouting anchor rods and high-strength yielding grouting anchor cables as the core. The on-site monitoring results indicate that this technology effectively controls the deformation of the surrounding rock. The research results provide new ideas and technical approaches for controlling the surrounding rock of deep water-enriched roadways.

Development of an expert system based on fuzzy logic as support for heat pipes design

Heat pipe design and selection require specialist knowledge due to numerous possible combinations and restrictions that should be taken into account. The general objective of this work is to design a Specialist System that assists future engineers in material and working fluid selection for a suitable heat pipe applica-tion, based on the technical operating requirements. The methodology consisted of a qualitative perspective through interviews with two specialist engineers in the heat pipes area. The resulting information from the interviews was organized into a library, working as a source for the specialist system. In addition, several books from the literature completed the information in the library. Based on the operating conditions and the provided library, the program recommends suitable materials and working fluids and the necessity of porous media for the application, similar to a consult with a heat pipe specialist. The new expert system can be a tool for researchers and engineers in heat pipe design as passive control systems, providing more suitable solutions for each application.

Non-linear thermoelastic analysis of circular sandwich porous plates reinforced with functionally graded graphene platelets

The investigation of graphene-reinforced porous composites has garnered significant interest due to their exceptional mechanical, thermal, and electrical properties, positioning them as promising materials for advanced structural applications. To fully harness the potential of these materials, numerical modeling becomes essential for understanding their behavior and optimizing their performance for specific engineering applications. In the present study, the non-linear bending response of functionally graded (FG) circular sandwich porous plates reinforced with graphene platelets is systematically analyzed under varying boundary conditions. The plates are subjected to a uniform transverse load and a thermal gradient, with distributions of graphene platelets and porosity graded along the thickness. The effective material properties, including Poisson’s ratio, are computed using the Gaussian random field scheme in conjunction with the Halpin-Tsai micromechanical model. The governing equations of motion are derived from Von Kármán’s non-linear relations, utilizing both first-order shear deformation theory (FSDT) and modified higher-order shear deformation theory (MHSDT). These equations are subsequently solved using dynamic relaxation (DR) coupled with finite difference methods. To validate the results, comparisons with existing literature and finite element method (FEM) are conducted, ensuring the accuracy and reliability of the obtained solutions. A comprehensive parametric study is performed to investigate the influence of various factors, including boundary conditions, graphene distribution patterns, porosity variations, and the thickness-to-radius ratio, on the non-linear bending behavior of the composite plates.

Challenges of Engineering Skillsets Essential for Driving Circularity of Smart Cities

This study aims to define specific transferable engineering capabilities needed for the implementation (design and practices) of circular economy (CE) within a smart city setting. We conducted a critical literature review of over 100 studies on the core values of CE and smart cities to investigate the knowledge gap in this topic and understand what specific skillset is employed by industry experts that can be harnessed on a wider scale, which can allow for the optimization of CE. There is a lack of research on the skillsets needed to implement a circular economy in any setting, and there are very few studies on circularity practices in a smart city setting. Primary data collection allows us to bridge this knowledge gap, yielding new findings that do not already exist concerning the skillset employed by experts in the field, which can positively impact the smart city settings in which a circular economy is implemented. We conducted a qualitative analysis based on expert interviews of 21 participants who have experience in the circular economy. This information will benefit the industry by informing businesses and councils about the key skillsets and capabilities to look out for when employing people to implement any aspect of circular practices in a smart city setting, with an emphasis on enhancing efficiency, achieving deliverables, and thinking systemically to address complex challenges they may face during the implementation. We also investigated the implementation of CE in smart cities to provide a well-rounded view of the different achievements and challenges faced during the process. This mainly focuses on the work of governance in smart circular cities, a factor that has many important implications and externalities in different sectors. This study describes the methodology adopted to formulate a detailed questionnaire for expert interviews with respect to the skill gap and capabilities necessary for working in the industry, the results of which aid discussions regarding the different challenges faced in CE implementation. Our findings reveal that background knowledge in engineering and sustainability is the most ‘highly critical’ hard skill according to the experts, while communication and stakeholder engagement are the essential soft skills required to ensure the success of a circular economy within smart city settings.

Artificial Neural Networks as a Tool for High-Accuracy Prediction of In-Cylinder Pressure and Equivalent Flame Radius in Hydrogen-Fueled Internal Combustion Engines

The automotive industry is under increasing pressure to develop cleaner and more efficient technologies in response to stringent emission regulations. Hydrogen-powered internal combustion engines represent a promising alternative, offering the potential to reduce carbon-based emissions while improving efficiency. However, the accurate estimation of in-cylinder pressure is crucial for optimizing the performance and emissions of these engines. While traditional simulation tools such as GT-POWER are widely utilized for these purposes, recent advancements in artificial intelligence provide new opportunities for achieving faster and more accurate predictions. This study presents a comparative evaluation of the predictive capabilities of GT-POWER and an artificial neural network model in estimating in-cylinder pressure, with a particular focus on improvements in computational efficiency. Additionally, the artificial neural network is employed to predict the equivalent flame radius, thereby obviating the need for repeated tests using dedicated high-speed cameras in optical access research engines, due to the resource-intensive nature of data acquisition and post-processing. Experiments were conducted on a single-cylinder research engine operating at low-speed and low-load conditions, across three distinct relative air–fuel ratio values with a range of ignition timing settings applied for each air excess coefficient. The findings demonstrate that the artificial neural network model surpasses GT-POWER in predicting in-cylinder pressure with higher accuracy, achieving an RMSE consistently below 0.44% across various conditions. In comparison, GT-POWER exhibits an RMSE ranging from 0.92% to 1.57%. Additionally, the neural network effectively estimates the equivalent flame radius, maintaining an RMSE of less than 3%, ranging from 2.21% to 2.90%. This underscores the potential of artificial neural network-based approaches to not only significantly reduce computational time but also enhance predictive precision. Furthermore, this methodology could subsequently be applied to conventional road engines exhibiting characteristics and performance similar to those of a specific optical engine used as the basis for the machine learning analysis, offering a practical advantage in real-time diagnostics.

Protein Engineering of Substrate Specificity toward Nitrilases: Strategies and Challenges.

Nitrilase is extensively applied across diverse sectors owing to its unique catalytic properties. Nevertheless, in industrial production, nitrilases often face issues such as low catalytic efficiency, limited substrate range, suboptimal selectivity, and side reaction products, which have garnered heightened attention. With the widespread recognition that the structure of enzymes has a direct impact on their catalytic properties, an increasing number of researchers are beginning to optimize the functional characteristics of nitrilases by modifying their structures, in order to meet specific industrial or biotechnology application needs. Particularly in the artificial intelligence era, the innovative application of computer-aided design in enzyme engineering offers remarkable opportunities to tailor nitrilases for the widespread production of high-value products. In this discussion, we will briefly examine the structural mechanism of nitrilase. An overview of the protein engineering strategies of substrate preference, regioselectivity and stereoselectivity are explored combined with some representative examples recently in terms of the substrate specificity of enzyme. The future research trends in this field are also prospected.

Digital twin and the asset administration shell

AbstractEngineering digital twins is a software and systems engineering challenge for which no systematic approach exists. The Asset Administration Shell is becoming a popular foundation for digital twins in Industry 4.0 and it comes in different types that support the engineering of different kinds and parts of digital twins. We investigate how it supports realizing common requirements for digital twins. To this end, we investigate how each of the three Asset Administration Shell types can contribute to the systematic engineering of specific components of digital twins. Therefore, we analyzed popular definitions and conceptual models of digital twins and extracted requirements that at least two of them share. We compare the resulting requirements with Asset Administration Shells of different types and conclude with open challenges in the implementation of digital twins with this technology. This supports practitioners and researchers in identifying the most suitable type of Asset Administration Shell for their specific digital twin engineering needs and identifies gaps worthy of future research toward a systematic engineering of digital twins.

Bond Parameters and Economic Instability

During periods of economic crises, investment activity decreases. The growth of yields on the securities market, typical for such periods, is unprofitable for issuers. Fluctuations in interest rates and general instability in the economy favor mainly short-term investments of investors. Issuers construct bond parameters that help attract investors and reduce risks. The purpose of this work is to consider the behavior of some controlled parameters of the bond during periods of instability, to obtain mathematical evidence of the dependence of the duration and price of the bond on the frequency of coupon payments and to justify the possibility of considering the frequency of coupon payments as a parameter that reduces the risks of the investor and the issuer. Methods of differential calculus are used to obtain evidence. The novelty of the work consists in the fact that the proofs obtained in the work are not available in the literature. The results are obtained for bonds that do not have credit risk. It has been established that with an increase in the number of coupon payments per year at fixed values of the main parameters, the duration of the bond decreases, and the price increases. The proven statements about the behavior of the duration and the price of the bond are consistent with market observations. A decrease in the duration of the bond with an increase in the number of coupon payments per year means a decrease in the “real term” and a decrease in the interest rate risk of the bond, which may be of interest to the investor. The price increase indicates an increase in demand for bonds with an increase in the number of coupon payments per year and the possibility of increasing the issuer’s income. The relevance of the work lies in the fact that the conditions for economic instability in Russia and in the world remain and the results of the work may be of interest to participants in the bond market. Conclusions: the paper shows that an increase in the number of coupon payments per year contributes to an increase in the attractiveness of bond issuance for both investors and issuers. Conclusions: the paper shows that an increase in the number of coupon payments per year contributes to the growth of the attractiveness of a bond issue for both investors and issuers. Practical significance of the work: the results of the work can be useful for investors and issuers, financial engineering specialists in the design of bond parameters, as well as in theoretical studies of the investment properties of bonds.

Retraction notice to “Research on the construction of a collaborative ability evaluation system for the joint graduation design of new engineering specialty groups based on digital technology” [Heliyon 9 (2023) e16855

Retraction notice to “Research on the construction of a collaborative ability evaluation system for the joint graduation design of new engineering specialty groups based on digital technology” [Heliyon 9 (2023) e16855

Effect of precipitates on martensite formation and shape memory effect of FeMnSi-based shape memory alloys fabricated by laser powder bed fusion

Effect of precipitates on martensite formation and shape memory effect of FeMnSi-based shape memory alloys fabricated by laser powder bed fusion

Effect of Curing Methods on the Mechanical Properties of Cement Mortar Contaminated with Heavy Crude Oil

Crude oil contamination poses significant environmental issues, particularly in regions where oil spills affect soil and groundwater. Utilising damaged materials in construction offers a cost-effective rehabilitation strategy that repurposes waste and reduces pollution. This study examines the effects of curing methods and heavy crude oil contamination on the mechanical properties of cement mortar. Mortar samples with different amounts of heavy crude oil (0%, 2%, and 10%) were cured using air, water, and sealed plastic. Water curing attained the highest compressive strength across different pollution levels by maintaining moisture for complete hydration. In contrast, air curing resulted in the lowest strength, especially for uncontaminated and 2% oil samples, due to rapid drying that limited hydration and increased porosity. Curing techniques did not affect the strength of samples with 10% heavy crude oil, perhaps due to oil saturation impeding hydration. Increased oil contamination, particularly with heavy crude, significantly enhanced porosity and reduced compressive strength. The high viscosity and complex molecular structure of heavy crude oil form a dense coating around cement particles, hindering hydration and undermining the integrity of the cement matrix. The findings suggest that selecting an appropriate curing procedure for low-level crude oil may facilitate repurposing materials contaminated with heavy crude oil as sustainable, cost-effective alternatives for specific civil engineering applications, offering a viable option for oil-contaminated sand.

نحو معجم عربي موحد لمصطلحات الجيوماتكس: تحديات الترجمة العلمية والتعريب وأثر المرجعية الثقافية

The goal of this research is to identify the challenges and obstacles that hinder the development of a unified technical dictionary of Geomatics terms. The focus is on ensuring that synonyms are compatible in translation and Arabization, as they play a crucial role in comprehending the fundamental concepts of this field in classical Arabic. Geomatics is a scientific term for an engineering specialty that emerged from the development and integration of well-known scientific branches, but ambiguity surrounds this term, its function, and its importance to the public and even to those interested in spatial information about the Earth's surface. In order to strengthen classical Arabic as a language that works well for comprehension and communication in professional and educational environments, the research focused on the significance of having a unified technical dictionary of Geomatics terms. The Unified Dictionary Data Bank of the Arab Educational, Cultural, and Scientific Organization is one approved reference that was used to assess how familiar a sample of students from King Abdulaziz University's Department of Geomatics was with Arabic synonyms for the most well-known scientific and technical terms in this field. It was found that a variety of factors make it challenging to develop accurate, specialized synonyms. These include cultural references, dictionaries that don't keep up with technological advancements, the fact that Arabic synonyms often have different meanings and terminological variations, the lack of specialized Arabic sources, and the tendency to write and speak in a hybrid way.

Research on School Enterprise Collaborative Education Mode of Software Technology Specialty under the Background of Enhancing the Adaptability of Vocational Education

The rapid development of China's digital economy puts forward higher requirements for the cultivation of software technology talents. In view of the problems existing in the talent cultivation process of software technology major in higher vocational colleges, such as the teaching content can't fully adapt to the requirements of industrial technology, the teaching process can't adapt to students' diversified learning demands, and the evaluation mode can't adapt to students' sustainable growth needs in the future, we cooperated with industry leading enterprises to build the curriculum chain and classroom link of real projects of enterprises, "1+n" double classroom skill acquisition group and "three-dimensional simultaneous" skill acquisition evaluation mode, carried out the reform of school enterprise collaborative education mode, and practiced and explored in the software technology major of Wenzhou Polytechnic, and achieved good results.

Macroscopic Mechanical Properties of Periodic Nanocomposites Containing Arbitrarily-Shaped Inclusions

This study presents an in-depth analysis of the macroscopic mechanical properties of periodic nanocomposites containing arbitrarily-shaped inclusions, with a particular focus on the effective stiffness and its dependence on microstructural parameters. We employ a complex variable method to address the problem, considering the interface elasticity effect, which may significantly influence the stress distribution and overall stiffness of the nanocomposites. The research reveals that the effective stiffness of the nanocomposites is not only dependent on the volume fraction and shape of the inclusions but also on the interface properties, particularly the interface elasticity parameter. Our findings indicate that an increase in the interfacial elasticity parameter KS results in a stiffer composite, highlighting the importance of interfacial effects in determining the mechanical behavior of nanocomposites. The study also explores the impact of inclusion size and orientation on the effective stiffness, demonstrating size-dependent phenomena and the influence of orientation angle on the stiffness elements. These insights contribute to a better understanding of the mechanical properties of nanocomposites and provide a foundation for the design of materials with tailored properties for specific engineering applications.

Effects of Polyol Types on Underwater Curing Properties of Polyurethane.

This study aims to develop castable polyurethane suitable for applications on wet substrates or underwater construction. Polyurethanes were synthesized using various polyols with similar hydroxyl values, including poly(tetrahydrofuran) polyol, polyester polyol, castor oil-modified polyol, soybean oil-modified polyol, and cashew nut shell oil-modified polyol. The corresponding polyurethane curing products were evaluated for their underwater curing characteristics by volume expansion ratios and adhesion strength on dry and wet substrates, combined with analyses of reaction exothermic behavior, wetting properties on dry and wet substrates, interfacial tension, and microstructure characterization from the perspectives of reaction activity and water solubility. The results indicate that polyols with higher hydrophobicity and reactivity to isocyanates lead to reduced side reactions during underwater curing, making them more suitable for underwater applications. Soybean oil-based and cashew nut shell oil-based polyurethanes exhibited fast curing (gel times of 1.15 and 1.35 min, respectively), minimal volume change (within 2.5% after 7 days underwater), and strong wet adhesion (1.95 MPa and 2.38 MPa with minimal loss, respectively). The two polyols showed different mechanical properties, providing tailored options for specific underwater engineering applications.

Analysis of the results of research and testing of geomodifiers of friction

The practice of maintenance of any equipment can be significantly supplemented by nontraditional tribotechnics for the indiscriminate restoration of worn friction interfaces and the prevention of new equipment with GMT technology. The predecessor of this direction were solid lubricants, solid lubricants and hard lubricants. They entered the special engineering of the space age and nuclear energy. But for ordinary equipment, it is more appropriate to use non-traditional tribotechnics with running-in, preventive and especially with repair and restoration tribocompositions in-troduced into units during technical service. This analysis is devoted to the analysis of the features of this direction with one of the types of tribostats — namely, with friction geomodifiers made of highly dispersed powders of serpentine minerals — hydrosilicates Mg, Al, Ni, Fe.