Engineering Principles Research Articles

An alternative approach to biokinetic modelling for phenol pollutant degradation and microbial growth using Genetic Programming

ABSTRACT Biokinetic models can optimise pollutant degradation and enhance microbial growth processes, aiding to protect ecosystem protection. Traditional biokinetic approaches (such as Monod, Haldane, etc.) can be challenging, as they require detailed knowledge of the organism's metabolism and the ability to solve numerous kinetic differential equations based on the principles of micro, molecular biology and biochemistry (first engineering principles) which can lead to discrepancies between predicted and actual degradation rates. More recently, data-driven machine-learning techniques have emerged as a promising alternative for modelling microbial systems. A few machine learning models (such as ANN, SVM, RF, DT, XG BOOST, etc.) have been used recently for modelling phenol degradation, but they lack the robustness of generating mathematical models. This gap is addressed in this study using Genetic Programming (GP) as the modelling approach for modelling the phenol degradation. This study utilises the microalgae Acutodesmus Obliquus, finding that phenol degradation of 98% required 216 hours. Both the traditional kinetic approach and the Genetic Programming (GP) approach were used to determine the specific growth rate (µ max) and saturation constant (Ks ). It is noted that without any a priori information on the form of the mathematical mode, GP can evolve a model which closely fits the Monod kinetics, thus demonstrating that data-driven models can bring out the first engineering principles on which biokinetic models are dependent or framed in a most swift and effective way. Performance was assessed using root mean square error (RMSE) and correlation coefficient (R), with the GP model showing superior predictive accuracy.

The convergence of big data and SRE in modern agriculture: Transforming farming through technology

This article examines the transformative integration of Big Data analytics and Site Reliability Engineering (SRE) principles in modern agriculture. The article explores how precision agriculture leverages advanced technologies including IoT sensors, drone surveillance, and satellite imagery, to revolutionize traditional farming practices. It analyzes the implementation of sophisticated data collection infrastructures, Big Data systems, and SRE practices in agricultural settings. The article investigates the operational benefits and sustainability implications of these technological integrations, highlighting improvements in resource optimization, yield enhancement, and environmental conservation. Furthermore, it discusses future perspectives in agricultural technology, including edge computing applications, AI-driven autonomous systems, blockchain integration, and climate change adaptation strategies.

Research on Improving the Horizontal Bearing Performance of Wind Power Pile Foundation with Added Wing Structure

The growing recognition of renewable energy’s importance, particularly its role in sustainability, has propelled wind energy to a prominent position. Receiving substantial global policy support due to its unique advantages, wind energy has seen a significant increase in installed turbine capacity. Consequently, expectations for the foundational bearing performance of these turbines have heightened, reflecting the enhanced focus on sustainable energy solutions. In response to these demands, this research introduces an innovative single pile foundation design that aims to elevate bearing capabilities to new heights. This research delves into the horizontal bearing properties of this novel foundation and the stress-strain dynamics of geotechnical materials under loading conditions. To achieve this, we utilize the Gudehus-Bauer subplastic model, specifically tailored for coastal sands within the ABAQUS finite element analysis software. Calibration and verification of the Gudehus-Bauer model’s parameters were meticulously conducted based on laboratory tests focusing on the coastal sands of the Yangtze River basin in China, enabling the development of a precise finite element model for the new single pile foundation in sandy coastal soils. Our findings reveal that this reinforced single pile foundation not only mirrors the horizontal bearing capacity and failure mechanisms of traditional designs but also surpasses them in performance. Numerically, this innovative structure boasts a remarkable 19.34% increase in horizontal ultimate bearing capacity and a minimum of 21.91% reduction in maximum displacement compared to standard single piles. These results underscore the superior horizontal bearing performance of our novel foundation design, which not only enhances structural integrity but also aligns with the principles of sustainable engineering by optimizing material usage, reducing environmental impact, and contributing to the broader goal of promoting renewable energy as a sustainable energy source.

Mechanical characterization of intracellular drug transport based on optimization of chemical engineering principles

At present, the measurement of cellular mechanical properties is divided into contact and non-contact, combined with the actual situation of the research in this paper, according to which the optical tweezers measurement technology in the non-contact type is adopted. Taking the measured value of cellular mechanical properties as the entry point of this research, the optimization method commonly used in chemical engineering principles was adopted, and the optimization model based on the separation of viscoelasticity parameters was set up by constantly changing the viscoelasticity parameters of intracellular transport of drugs and setting up certain criteria to optimize and obtain the viscoelasticity parameters that best represent the mechanical properties of intracellular transport of drug cells. The model was used to experimentally analyze the mechanical properties of intracellular drug transport. The deformation of drug cells when reaching the predetermined elastic force was small when transported with the optimized transport speed curve of parameter , and the transport speed was the largest, while the deformation obtained with the transport speed curve of parameter was between the two, indicating that the optimized speed curve of viscoelasticity parameter can effectively reduce the mechanical damage of the drug cells in the process of transport.

Make It and Break It: Bioplastics from Plant Starch with Incorporation of Engineering Principles

Make It and Break It: Bioplastics from Plant Starch with Incorporation of Engineering Principles

Water Treatment Technologies: Development of a Test Bench for Optimizing Flocculation-Thickening Processes in Laboratory Applications

This study introduces an automated test bench designed to optimize flocculation-thickening processes in the wastewater treatment industry. Addressing current challenges in operational efficiency and cost reduction, the test bench employs Model-Based Systems Engineering (MBSE) principles, leveraging SysML modeling within the CESAM framework. By integrating advanced technologies, including PLC programming and a closed-loop control system, this bench provides precise and efficient testing under varying operational conditions. Economic implications are explored, demonstrating the cost-effectiveness of optimized flocculation processes, which reduce chemical use and operational expenditures while enhancing water clarity and sludge management. The system’s 3D modeling enables detailed simulations, aiding in both research and pedagogical applications. This platform highlights the potential of MBSE in creating scalable, robust solutions that contribute to sustainable water management.

Evaluation and Analysis of Passive Energy Saving Renovation Measures for Rural Residential Buildings in Cold Regions: A Case Study in Tongchuan, China

Energy-saving renovation of rural residences is an effective means of promoting sustainable rural development. This study focuses on a single-story rural residential building located in Tongchuan City, Shaanxi Province, China (a cold region), as a case study. Retrofits were conducted on the exterior windows, roof, and exterior walls, with the addition of a sunroom. Using life cycle assessments (LCAs) and orthogonal experimental methods combined with value engineering principles, we calculated various indicators including the energy efficiency improvement rate, implied carbon emissions, proportion of implied carbon emissions, carbon footprint, carbon reduction rate, carbon payback period, and investment payback period. The impact of traditional retrofitting measures on these indicators was analyzed. The results indicate that carbon emissions from the production of building materials are a key concern among the embodied carbon emissions from the retrofits, while transportation, construction, and demolition contribute minimally. Changes in the depth of the sunroom had the most significant impact on comprehensive indicators, followed by changes to the roof. After retrofitting, the carbon reduction rate was underestimated by 9.35% to 12.02% due to embodied carbon emissions. The carbon payback period for all schemes is estimated to be between 3.27 and 4.21 years. Based on current market conditions, developing corresponding carbon economics can enhance the economic viability of the project. This approach extends the investment payback period by more than 7% while also helping to narrow the income gap between urban and rural residents to some extent. Overall, the environmental impact assessment of the alternative schemes promotes sustainable rural development and provides scientific and effective guidance for the construction of project decision-making evaluation systems and architectural designers.

Cluster Engineering in Water Catalytic Reactions: Synthesis, Structure-Activity Relationship and Mechanism.

Four fundamental reactions are essential to harnessing energy from water sustainably: oxidation reduction reaction (ORR), oxygen reduction reaction (OER), hydrogen oxidation reaction (HOR), and hydrogen evolution reaction (HER). This review summarizes the research advancements in the electrocatalytic reaction of metal nanoclusters for water splitting. It covers various types of nanoclusters, particularly those at the size level, that enhance these catalytic reactions. The synthesis of cluster-based catalysts and the elucidation of the structure-activity relationships and reaction mechanisms are discussed. Emphasis is placed on utilizing atomically precise cluster materials and the interplay between the carrier and cluster in water catalysis, especially for applying catalytic engineering principles (such as synergy, coordination, heterointerface, and lattice strain engineering) to understand structure-activity relationships and catalytic mechanisms for cluster-based catalysts. Finally, the field of cluster water catalysis is summarized and prospected. We believe that developing cluster-based catalysts with high activity, excellent stability, and high selectivity will significantly promote the development of renewable energy conversion reactions.

Transforming Quantum Programmes in KDM to Quantum Design Models in UML

Quantum computing has come to stay in our lives. Companies are investing billions of dollars in it because of the potential benefits that it can achieve, providing promising applications in almost every business sector. Although quantum computing is evolving at an exponential rate, the development of tools, techniques, or frameworks for the evolution of current information systems towards quantum software systems is still proving to be a challenge. This research contributes to the evolution of current information systems towards hybrid information systems (combining the classical and quantum computing paradigm). We propose a software modernization process, by following model-driven engineering principles, adapted to the quantum paradigm, based on modified versions of standards for reverse engineering of classical, quantum software assets, and for the design of the target system. In particular, this paper focuses on the restructuring transformation from KDM to UML models, where KDM models have been generated from Q# code. This proposal has been validated through a case study involving 17 programmes. The results obtained show optimistic values regarding the complexity of the UML models generated, their expressiveness and scalability. The main implication of this research is that UML models can indeed help the software evolution of/toward hybrid information systems.

The Role of Social Engineering in the Rehabilitation of Drug Addicts: A Legislative Analysis of Indonesia's Drug Policy Framework

This study examines the role of social engineering in the rehabilitation of drug addicts within Indonesia’s drug policy framework through a normative juridical analysis. The research evaluates legislative provisions, such as those outlined in Law No. 35 of 2009 on Narcotics, focusing on their alignment with social engineering principles and their effectiveness in achieving rehabilitation and reintegration. Findings reveal that while Indonesia's policies incorporate rehabilitative elements, challenges such as limited resources, inconsistent judicial practices, and societal stigma hinder optimal implementation. Comparative insights from countries like Portugal and Switzerland demonstrate the potential of adopting harm reduction and public awareness strategies to enhance outcomes. This study underscores the need for a more integrated, inclusive policy approach to strengthen Indonesia’s rehabilitation framework, reduce stigmatization, and promote sustainable recovery.

Drug Delivery Applications of Hydrophobic Deep Eutectic Solvent-in-Water Nanoemulsions: A Comparative Analysis of Ultrasound Emulsification and Membrane-Assisted Nanoemulsification.

The emergence of green chemistry and engineering principles to enforce sustainability aspects has ensured the prevalence of green solvents and green processes. Our study addresses this quest by exploring drug delivery applications of hydrophobic deep eutectic solvents (DESs) which are alternative green solvents. Initially, this work showcases the hydrophobic drug solubilization capabilities of a natural hydrophobic DES, menthol, and decanoic acid. To consider biomedical applications wherein polar media are encountered, this work further demonstrates the potential drug delivery application of these systems by encapsulating the anti-inflammatory local anesthetic lidocaine in hydrophobic DES-in-water nanoemulsions. NMR studies confirm the high solubility of the hydrophobic drug in hydrophobic DES comprising menthol and decanoic acid (1:2 molar ratio). Ultrasound emulsification and energy-efficient membrane emulsification techniques were employed to disperse 4% (v/v) DES into a 2% (w/w) Tween 20 surfactant aqueous solution. An isoporous microengineered membrane (nominal pore size ∼ 9 μm) was used to produce lidocaine-loaded DES-based nanoemulsions. Such membrane-assisted nanoemulsification was possible because the hydrophobic DES exhibits relatively low interfacial tension with the continuous phase and acts as a cosurfactant. Moreover, increased concentrations of lidocaine within the DES resulted in a further decrease in the interfacial tension and a lower melting point. Among the kinetic models analyzed to evaluate the release of lidocaine encapsulated in hydrophobic DES-in-water nanoemulsions, the Korsmeyer-Peppas kinetic model provided the best fit. The release constant "n" of <0.5 indicates that the drug release mechanism is predominantly governed by diffusion. Additionally, cytotoxicity against various human cell lines demonstrated the nanoemulsion's potential for anti-inflammatory drug delivery applications. Consequently, the nanoemulsion of DES presents a promising solution for the effective loading and delivery of poorly soluble drugs. This innovative approach enhances drug solubility and bioavailability, providing a versatile platform for controlled drug release. By leveraging the advantages of nanoemulsion technology, our study underscores the potential of DES-based formulations to promote drug delivery systems across a variety of therapeutic applications.

Optimization of Interstellar Travel through Design Approaches with Gimballing Ion Thrusters

Interstellar travel, constrained by current propulsion technologies, suffers from limitations in efficiency and maneuverability essential for vast interstellar distances. This paper presents a rigorous investigation into optimizing interstellar travel through advanced design methodologies, with a primary focus on the deployment of gimbaled ion thrusters to enhance maneuverability and trajectory correction. The research meticulously examines two-axis thrust vectoring, propulsion system efficiencies, fuel transfer mechanisms, and energy management strategies, aiming to significantly improve propulsion and control system performance. A detailed comparative analysis of gimbaled thrust versus traditional thrust systems evaluates the impact on fuel efficiency and overall spacecraft performance. By integrating aerospace engineering and materials science principles, this study advances the discourse on interstellar travel. The findings and recommendations from this research aim to drive the development of cutting- edge spacecraft propulsion systems, facilitating more efficient and adaptable exploration beyond the solar system.

Mechanical Engineering Applications in Military Vehicles

The integration of mechanical engineering principles into military vehicle design and operation is critical for enhancing performance, reliability, and safety. This literature review synthesizes various studies that explore the applications of mechanical engineering in military vehicles, focusing on areas such as crash prevention technologies, hybrid systems, suspension design, reliability, and advanced materials. In addition, brief explanations about military vehicle roles in defense systems are also highlighted.

New Technologies of Grain Boundary Engineering of Materials for Improving the Corrosion Resistance of High Alloy Stainless Steel Pipes

Abstract. Problem. Pipes made of highly alloyed corrosion-resistant steels are widely used in corrosive-aggressive environments in priority industries. In connection with the increasing severity of their operating conditions, increased requirements for resistance to intercrystalline, pitting corrosion, corrosion cracking, and sulfide corrosion cracking under stress become the most important in accordance with the requirements of foreign and international standards. Previous studies have shown that currently operating technologies for the production of pipes do not meet the modern, comprehensive requirements for quality characteristics. To solve this problem, it is necessary to apply new progressive scientific and technological methods. Goal. The purpose of the work is to increase the corrosion resistance and operational reliability of pipes made of highly alloyed austenitic and ferritic-austenitic steels by improving their structure during deformation and temperature treatments according to the principle of grain boundary engineering of materials. Methodology. To achieve the goal, the latest scientific achievements and technologies for improving the structure and increasing the corrosion resistance of rolled products made of high-alloy steel were analyzed. When conducting experimental studies, modern methods were used and methods of metal structure research and complex corrosion tests for resistance to local types of corrosion to which corrosionresistant steels are subjected in operating conditions were developed. The results. The latest technologies for the production of pipes from austenitic chromenickel and ferritic-austenitic chrome-nickelmolybdenum steels, based on the principle of grain boundary construction of polycrystalline materials, have been developed. They ensure obtaining a structure of pipes with an increased content of special low-energy grain boundaries in the theory of coinciding site lattices (CSL) and high resistance against local types of corrosion in accordance with new industry requirements. Originality. For the first time, special low-energy grain boundaries in the ferritic component and interphase boundaries with reduced surface energy in highly alloyed ferriticaustenitic steels were found. The leading role of special boundaries in increasing resistance to local types of corrosion that originate at grain boundaries is shown. Practical value. The results of the work were implemented in the production at Centravis Production Ukraine PJSC, which contributed to the improvement of the quality and competitiveness of products

Impact of Resilience Engineering on Physical Symptoms of Construction Workers

Physical symptoms plague construction workers and pose threats to safety performance and productivity. Following the resilience engineering (RE) principles, recent construction safety management practices enhance construction workers’ safety capability and safety management system resilience. This paper established an exploratory structural model explaining how construction workers’ safety capability alleviates their physical and psychological symptoms through safety management system resilience. To validate and estimate the structural model, 741 valid responses from construction workers based in Shanghai, China were obtained. Given no established scales for the constructs in the model, a cross-validation procedure, consisting of exploratory and confirmatory factor analysis and path analysis, was performed. The results showed that although neither safety capability nor safety management system resilience has direct negative impacts on physical symptoms, they can reduce physical symptoms via alleviating psychological symptoms. Furthermore, safety capability can reduce psychological and physical symptoms via safety management system resilience. This paper therefore suggests that cultivating construction workers’ safety capability would be the first step in implementing resilience engineering principles in construction. The continuous implementation of cost-effective and tailored resilience training programs are suggested to enhance construction workers’ safety capability. Safety management systems are suggested to improve with the fostering of a just culture and emerging technologies.

Chemical ethics practices in HEBUST of China

Abstract Hebei University of Science and Technology (HEBUST) actively carries out chemical ethics education practices and incorporates chemical ethics modules into the curriculum, aiming to improve students’ morality, responsibility, knowledge and skills. In the teaching of basic courses, relevant content of chemical ethics is introduced to guide students to think about the ethics of chemical. At the same time, the university has built a diversified practical platform and organized students to participate in laboratory research projects. HEBUST invites enterprise engineers to give lectures and carry out “practical month” activities. The design homework of senior students also incorporates ethical considerations to cultivate students’ ability to practice ethical principles in actual engineering. In addition, the school also invited retired experts from the Organisation for the Prohibition of Chemical Weapons (OPCW) to give lectures. The relevant majors have passed the Washington Accord certification and the certification of the China Engineering Education Professional Certification Association. External supervision has promoted the continuous deepening of the reform of chemical ethics education. Therefore, HEBUST has provided an effective example for cultivating chemically and engineering-talented people with social responsibility and also provided a reference for other colleges and universities to carry out chemical ethics education.

Significant Advances in Application Resiliency: The Data Engineering Perspective on Network Performance Metrics

Purpose: The purpose of the article is to explore how network metrics like latency, packet loss, and throughput, combined with application logs, can help organizations improve the reliability and performance of their applications. It focuses on how these insights support Site Reliability Engineering (SRE) teams in proactively addressing issues to achieve better application resiliency, enhancing user experience and market trust. Methodology: The article uses a combination of case studies and analysis to demonstrate how monitoring specific network metrics and application logs helps identify and resolve performance issues. It examines real-world scenarios where proactive adjustments based on these metrics improved application reliability and aligned with organizational objectives. Findings: The findings show that by analyzing network metrics and application logs, organizations can pinpoint causes of transaction failures, such as high latency, packet loss, or misconfigured firewalls. Proactive resolutions based on these insights result in smoother application performance, reduced downtime, and increased user satisfaction. Unique Contribution to theory, practice and policy: This article makes valuable contributions to theory, practice, and policy. For theory, it expands the understanding of how network metrics and application logs can work together to improve application resiliency, offering a framework for integrating Site Reliability Engineering (SRE) principles with network observability. For practice, it provides clear, actionable steps for SRE teams to identify and resolve performance issues, helping organizations enhance reliability and user satisfaction. For policy, it highlights the importance of proactive network monitoring and metric-driven decision-making, encouraging organizations to adopt policies that prioritize resiliency, ensure consistent performance, and meet service-level agreements (SLAs).

Development of the brain network control theory and its implications.

Brain network control theory (NCT) is a groundbreaking field in neuroscience that employs system engineering and cybernetics principles to elucidate and manipulate brain dynamics. This review examined the development and applications of NCT over the past decade. We highlighted how NCT has been effectively utilized to model brain dynamics, offering new insights into cognitive control, brain development, the pathophysiology of neurological and psychiatric disorders, and neuromodulation. Additionally, we summarized the practical implementation of NCT using the nctpy package. We also presented the doubts and challenges associated with NCT and efforts made to provide better empirical validations and biological underpinnings. Finally, we outlined future directions for NCT, covering its development and applications.

Synthetic biology and artificial intelligence in crop improvement.

Synthetic biology (SynBio) plays a pivotal role in improving crop traits and increasing bioproduction by using engineering principles that purposefully modify plants through "design, build, test and learn" cycles, ultimately resulting in improved bioproduction based on input genetic circuit (DNA, RNA, and Proteins). Crop synthetic biology is new tool following circular principles to redesign and create innovative biological components, devices, and systems to enhance yields, nutrient absorption, resilience, and nutritional quality. In the digital age, artificial intelligence (AI) has demonstrated great significance in the design and learning. The application of AI has become an irreversible trend, with its potential in the field of crop breeding being particularly remarkable. However, a systematic review of AI-driven synthetic biology pathways for plant engineering is lacking. In this review, we explore the fundamental engineering principles employed in crop synthetic biology and their applications in crop improvement. The approaches to genetic circuit design include gene editing, synthetic nucleic acid and protein technologies, multi-omics analysis, genomic selection, directed protein engineering and AI. We then outline strategies for developing crops with higher photosynthetic efficiency, reshaped plant architecture, modified crop metabolic pathways, improved environmental adaptability and nutrient absorption, establishing trait networks, and constructing crop factories. Additionally, we propose the development of Self-Monitoring, Adapted, and Responsive Technology (SMART) crops through AI-empowered synthetic biotechnology. Moreover, we address the challenges associated with synthetic biology development and present potential solutions for crop improvement.

Homogeneous Charge Compression Ignition Engines for Enhanced Energy Efficiency and Reduced Emissions in Transportation and Power Generation

Rising emissions and pollution from traditional automotive engines, along with the increasing demand for more fuel-efficient and environmentally friendly technologies, have led to the development of "Homogeneous Charge Compression Ignition" (HCCI) engines. Unlike conventional internal combustion engines, HCCI engines do not rely on spark plugs to initiate combustion. Instead, the air-fuel mixture auto-ignites through compression, resulting in a highly efficient thermal process. This technology significantly reduces HC (hydrocarbon) and CO (carbon monoxide) emissions, making it a promising solution for modern environmental and energy challenges. Despite these advantages, the widespread commercialization of HCCI engines has been hindered by several technical challenges. The lack of spark plugs complicates combustion control, particularly in maintaining consistent ignition timing. Additionally, cold starts remain a significant obstacle. This paper will explore the historical development and operating principles of HCCI engines, outline their advantages and limitations, and examine potential solutions to these challenges. Finally, the paper will discuss the application of HCCI technology in power generation, highlighting its future prospects and contributions to sustainable energy.