Engineering Models Research Articles

Formation of various cell-aggregated structures in the core of hydrogel filament using a microfluidic device and its application as an in vitro neuromuscular junction model

Microfluidic systems have been widely used in various in vitro tissue engineering models. In this paper, we present a new microfluidic system for manufacturing cell filaments laden with cell aggregates of various shapes (beads, rosaries, and filaments) in the core region. The structures were obtained using the Rayleigh-Plateau instability of the two-phase flow of the injected bioinks (continuous phase of collagen/poly[ethylene glycol] diacrylate [PEGDA] and a dispersed phase of methacrylated gelatin (GelMA)). To demonstrate the potential of the system at the neuromuscular junction in vitro model, we injected a C2C12-laden collagen/PEGDA bioink into the sheath region and GelMA mixed with motor neuron cells (NSC-34) into the core region of the fabricated cell aggregates. The rosary-shaped NSC-34 aggregate in the core exhibited higher cell viability and more developed neurogenic gene expression than the cell aggregates of beads and filaments in the core region, owing to much greater mechanotransduction. Furthermore, when comparing the cell-laden struts (C2C12 in the sheath region and NSC34 in the rosary core region) with normally bioprinted struts with the same cell density, the expressions of myogenesis-, neuromuscular junction (NMJ)-, and neurogenesis-related genes in struts laden with rosary-shaped cell aggregates were significantly upregulated. The results of these experiments demonstrate the potential for the fabrication of new cell-laden core-sheath structures, which could be used for designing various in vitro models.

Research on Talent Cultivating Pattern of Industrial Engineering Considering Smart Manufacturing

In-depth exploration of the theory and technological applications of smart manufacturing (SM) is lacking in the current talent training model for industrial engineering (IE) majors, and there is a lack of practical education for SM environments. This makes it difficult for students of traditional IE majors to adapt to the modern trend of industrial intelligence and meet the needs of market demand and enterprise development. Therefore, how to cultivate IE talents for SM has become an urgent problem for IE majors to solve. To this end, this paper proposes a new “SM+IE” talent training model, aiming to cultivate more high-quality composite application talents. This model is based on the Lean Manufacturing course and analyzes the effect of the training mode of SM. Secondly, we used the topic of “Sorting Efficiency Improvement” to verify the effectiveness of the new talent training model. The materials were divided into three types: large, medium, and small, and the materials were sorted using traditional IE practices and smart manufacturing-oriented practices. Finally, interviews were conducted with the participants, and both teachers and students indicated that the learning effect of this teaching reform practice was significantly better than that of the traditional IE teaching mode. The results show that the new talent training model improved not only the application and practical skills of the IE students, but also their teamwork and leadership skills.

Feasibility of Work-Based Learning Model for Undergraduate Engineering and Technology Programmes in Tanzania

This study proposes a new approach to teaching-learning in engineering and technology programmes at the undergraduate level in Tanzania, and evaluates its feasibility. The rationale was to improve flexibility in learning by providing learners with alternative programmes to choose from. A conceptual model was introduced showing how the work-based approach can be implemented in training diploma holders to acquire bachelor’s degrees. A survey type of study with a mix of open- and closed-ended questions issued to a sample of 150 finalist students was conducted. The sampled population was all finalyear diploma students pursuing engineering and technology programmes at Mbeya University of Science and Technology in Tanzania. A stratified random sampling approach was followed to obtain the sample. More than 93% of the respondents supported the establishment of work-based programmes. This study, therefore, recommends, amongst other things, that Tanzanian learning institutions should set a pilot programme to test the effectiveness and practicability of this model.

A journey from mechanistic to data-driven models in process engineering: dimensionality reduction, surrogate and hybrid approaches, and digital twins

A journey from mechanistic to data-driven models in process engineering: dimensionality reduction, surrogate and hybrid approaches, and digital twins

Description of soliton and lump solutions to [formula omitted]-truncated stochastic Biswas–Arshed model in optical communication

This article negotiates the investigation of optical stochastic solitons and other exact stochastic solutions with the fractional stochastic Biswas–Arshed equation (FSBAE) describing the multiplicative white noise of optical signal propagation in birefringent fibers using the modified F-expansion method and Hirota Bilinear method. In order to manage this model, we used Itô calculus. After utilizing the aforementioned techniques and computational software, different stochastic solitary wave solutions are retrieved, including dark, bright, periodic, singular, hyperbolic, rational, combo, and trigonometric function solutions. Additionally, we also investigate several wave solutions, such as the cross-kink rational wave solution, the homoclinic breather wave solution, and M-shaped rational solution. To examine the different kinds of solitons and their dynamical behaviors, the solutions have been simulated by graphs. The discovered solutions are essential for illuminating the wave dynamics in diverse models. The obtained stochastic solitary wave solutions may be crucial in nonlinear science and engineering fields. It is impressive to see that the chosen methodologies are simple, appropriate, and effective scientific tools for determining stochastic solitary wave solutions for nonlinear engineering models (NLEMs). This is the first investigation into the lump solutions of the FSBA equation with multiplicative white noise, and the findings show how optical solitons propagate in nonlinear optics.

Rockburst Prediction and Evaluation Model for Hard Rock Engineering Based on Extreme Gradient Boosting Ensemble Learning and SHAP Value

Rockburst Prediction and Evaluation Model for Hard Rock Engineering Based on Extreme Gradient Boosting Ensemble Learning and SHAP Value

A numerical solution of fractional reaction–convection–diffusion for modeling PEM fuel cells based on a meshless approach

The purpose of this contribution is to present or implement generalized finite difference method (GFDM) for the first time in order to solve the reaction convection Diffusion equation (FRCDE) model. The FRCDE equations are nonlinear time fractional differential equations that can be used to describe mathematical models in physics and engineering, such as fuel cells and transport in inhomogeneous media. This model is a generalization of the classical RCDE, with time terms considered by Caputo derivative sense for 0<α(x,t)<1. The meshless GFDM, in conjunction with the ϑ-weighted finite difference method, is developed to approximate processes in the spatial direction. GFDM is based on the Taylor series expansion and the moving least squares (MLS) method to evaluate the derivatives of unknown variables. The proposed method, as a truly meshless approach, is very promising in the numerical approximation of engineering problems within convex, non-convex, irregular, and regular domains (complex domains). The reliability and accuracy of the proposed method are shown by considering a variety of computational domains. The sensitivity of the selection of local collocation points and ϑ is also reported.

Case Study: Comparing Different Software Engineering Models in Enhancing the Productivity of a Transportation Company

This case study aims to investigate how various software engineering life cycle models can impact the productivity of a transportation company. It also examines how the transition from manual to automated processes can optimize the company's output in terms of cost, labour, and time. By exploring different software engineering models, this study seeks to identify the most effective approach for enhancing the transportation company's productivity. The study recognizes that while some software engineering models can lead to increased profitability, others may have limitations or flaws that need to be addressed. Ultimately, the goal of the study is to provide insights into the advantages and disadvantages of different software engineering models and their impact on the productivity of a transportation company. Key Words: Case study, Software Engineering life cycle model, Productivity, Optimizes, profit-maximizing tactics, Waterfall model, Incremental Model, Spiral Model, customer- end and driver-end application

Modelling in engineering: A citation context analysis

Purely quantitative citation measures are widely used to evaluate research grants, to compare the output of researcher or to benchmark universities. The intuition that not all citations are the same, however, can be illustrated by two examples. First, studies have shown that erroneous or controversial papers have higher citation counts. Second, does a high-level citation in an introduction have the same impact as a reference to a paper that serves as a conceptual starting point? Companions to purely quantitative measures are the so-called citation context analyses which aim to obtain a better understanding of the link between citing and cited work. In this article, we propose a classification scheme for citation context analysis in the field of modelling in engineering. The categories were defined based on an extensive literature review and input from experts in the field of modelling. We propose a detailed scheme with six categories ( Perfunctory, Background Information, Comparing/Confirming, Critique/Refutation, Inspiring, Using/Expanding) and a simplified scheme with three categories ( High-level, Critical Analysis, Extending) that can be used within automatic classification approaches. The results of manually classifying 129 randomly selected citations show that 87% of citations fall into the high-level category. This study confirms that critical citations are not common in written academic discourse, even though criticism is essential for scientific progress and knowledge construction.

A Next-Generation 3D Tissue-Engineered Model of the Human Brain Microvasculature to Study the Blood-Brain Barrier.

More than a billion people are affected by neurological disorders, and few have effective therapeutic options. A key challenge that has prevented promising preclinically proven strategies is the translation gap to the clinic. Humanized tissue engineering models that recreate the brain environment may aid in bridging this translational gap. Here, we showcase the methodology that allows for the practical fabrication of a comprehensive microphysicological system (MPS) of the blood-brain barrier (BBB). Compared to other existing 2D and 3D models of the BBB, this model features relevant cytoarchitecture and multicellular arrangement, with branching and network topologies of the vascular bed. This process utilizes 3D bioprinting with digital light processing to generate a vasculature lumen network surrounded by embedded human astrocytes. The lumens are then cellularized with primary human brain microvascular endothelial cells and pericytes. To initiate mechanotransduction pathways and complete maturation, vascular structures are continuously perfused for 7 days. Constructs are validated for complete endothelialization with viability dyes prior to functional assessments that include barrier integrity (permeability) and immune-endothelial interactions. This MPS has applications for the study of novel therapeutics, toxins, and elucidating mechanisms of pathophysiology.

A variety of M-truncated optical solitons to a nonlinear extended classical dynamical model

This article secures optical pulses modeled by higher order generalized extended classical nonlinear Schrödinger equation (GECNLSE). The studied equation is discussed by the assistance of truncated M-fractional derivative and composed of self-steepening, and stimulated Raman scattering effects in nonlinear optical fibers. Because of their versatility in explaining a wide range of complicated physical events and their richer dynamical structures of localized wave solutions, the NLSE equations have received increased attention. The solutions are extracted with the assistance of modified Sardar sub-equation method (MSSEM), one of the newest integration methods. A variety of optical solitons are extracted like, bright, dark, combo, and singular soliton solutions. Furthermore, periodic, exponential, and hyperbolic type solutions are obtained. Assuming the right values for the parameters, various graph shapes are sketched to provide information about the visual format of the earned results. This paper’s findings support the efficacy of the approach taken in enhancing nonlinear dynamical behavior. We believe this research will be of interest to a wide variety of engineers that work with engineering models. Findings show the effectiveness simplicity, and generalizability of the chosen computational approach, even when applied to complicated systems.

High-precision computational modeling of soil-rock mixtures considering realistic shape of rock blocks

Soil-rock mixtures (SRMs) are heterogeneous geological bodies with complex spatial structures and peculiar mechanical properties. This paper proposes a high-precision computational modeling method to realistically simulate the shape of rock blocks in the SRMs as well as the mesostructure of SRMs. The precise control theory of the rock blocks is first described. Then, acceleration measures such as bounding volume hierarchies and position culling are introduced to increase the computational efficiency while retaining the model accuracy. Practical examples and comparisons with the existing methods are provided to demonstrate the advantageous features of this method. In the end, the modeling method is successfully integrated into the DEM platform to create engineering models involved in SRMs, which lays the foundation for further DEM analysis to understand the effects of the mesostructure on the mechanical properties of SRMs.

Artificial Intelligence and Agent based Modeling for Power System Engineering

The fields of power electronics and fuel cells have emerged as key players in the development of sustainable power sources. The prevailing demand for fuel cells is projected to increase as they become the principal source of energy for portable electronics. A high-efficiency converter is a crucial component of the whole system and an absolute must for this specific use case. This is because the converter has a huge impact on the portability of the system as a whole in terms of size, efficiency, cost, and reliability. Choosing appropriate converter architecture is a key and important aspect of increasing the network of fuel cells for embedded systems since the converters alone accomplishes such as significant role in determining the overall efficiency of the system in this study, we take a look at the many topologies configurations of AC inverters and DC converters that are employed in the installation of fuel cells for autonomous and portable. The techniques of switching used in fuel cell energy conditioning are also analyzed in this research. The current issue with DC converters and AC inverters is also discussed at the end of this paper.

Preface

2023 13th International Conference on Applied Physics and Mathematics (ICAPM 2023) was held in Singapore during March 10-12, 2023. In the past years, ICAPM was held in many large capital cities, such as Tokyo, Phuket, Singapore, Busan, Lisbon, Hong Kong, and Bangkok, etc. This conference provides a remarkable opportunity for the academic and industrial communities to address new challenges and share solutions, and discuss future research directions.The conference invited three internationally recognized experts in the field of applied physics and mathematics. They are Prof. Bakhodirzhon Siddikov, Ferris State University, USA, Prof. Naoyuki Ishimura, Chuo University, Japan, and Prof. Cheng-kuo Lee, National University of Singapore, Singapore. Scholars and researchers from China, Canada, India, Norway, Malaysia, Thailand, Indonesia, Philippines, Russia, and so on took this opportunity to share their research results and discuss the future development of related fields.All papers in the conference proceeding have passed vigorous preliminary review and peer review by the technical committee. Professional comments are given according to the aspects of originality, innovation, applicability, technical merit, organizing and writing, relevance to conference, and so on. Authors benefit from the valuable comments and improve their submissions to meet the satisfaction of the reviewers. The proceeding contains a collection of research papers, and is divided into 3 chapters: Chapter 1 is entitled Basic Mathematics and Mathematical Computation; Chapter 2 is entitled Application of Mathematical Calculations and Models in Engineering; Chapter 3 is entitled Physical Theory and Engineering Physics.List of Organizing Committees, Statement of Peer Review are available in this Pdf.

Deep learning guided enzyme engineering of Thermobifida fusca cutinase for increased PET depolymerization

A responsible and sustainable circular economy of polymers requires efficient recycling processes with a low CO2 footprint. Enzymatic depolymerization of polyethylene terephthalate (PET) is a first step to make PET polymers a part of a circular economy of polymers. In this study, a structure-based deep learning model was utilized to identify residues in TfCut2 that are responsible for improved hydrolytic activity and enhanced stability. Machine learning guided design identified novel beneficial positions (L32E, S35E, H77Y, R110L, S113E, T237Q, R245Q, and E253H), which were evaluated and stepwise recombined yielding finally the beneficial variant L32E/S113E/T237Q. The latter TfCut2 variant exhibited improved PET depolymerization when compared with TfCut2 WT (amorphous PET film, 2.9-fold improvement // crystalline PET powder (crystallinity > 40%), 5.3-fold improvement). In terms of thermal resistance the variant L32E/S113E/T237Q showed a 5.7 °C increased half-inactivation temperature (T5060). The PET-hydrolysis process was monitored via a quartz crystal microbalance with dissipation monitoring (QCM-D) in real-time to determine depolymerization kinetics of PET coated onto the gold sensor. Finally, conformational dynamics analysis revealed that the substitutions induced a conformational change in the variant L32E/S113E/T237Q, in which the dominant conformation enabled a closer contact between the catalytic site and PET resulting in increased PET-hydrolysis. Overall, this study demonstrates the potential of deep learning models in protein engineering for identifying and designing efficient PET depolymerization enzymes.

Disturbance-Observer-Based Finite-Time Antidisturbance Control for Markov Switched Descriptor Systems With Multi-Disturbances and Intermittent Measurements

This paper is concerned with the finite time <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_\infty$</tex-math> </inline-formula> composite anti-disturbance control problem for Markov switched descriptor systems with multiple disturbances and packet loss via a disturbance observer. Significantly, the switching topology of descriptor systems is controlled by nonhomogeneous Markov switching processes, whose time-varying transition probability is limited by a convex hull. Subsequently, a Bernoulli random variable is exploited to characterize the intermittent measurement mode behavior of controller-actuator packet loss. Furthermore, the stochastic <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_\infty$</tex-math> </inline-formula> finite time boundiness of the composite system and simultaneously suppression and rejection of external disturbances are established by resorting to disturbance observer-based robust control (DOBC) strategy and a new stochastic Lyapunov function technique. More importantly, a relaxed variable method is provided to eliminate the coupling between Lyapunov variables and the system matrix in the process of stability analysis, instead of eliminating the coupling by means of commonly-used traditional inequalities, which effectively increases the flexibility of the obtained stable results and greatly reduces the computational complexity of controller/observer in the existing works. Finally, the effectiveness and practicability of the developed results are verified by two practical engineering models.

Software Development and Tool Support for Curriculum Design: A Systematic Mapping Study

Curriculum design is the systematic process of establishing how a learning process is designed, developed, supported, and delivered. This process is supported by software tools which can help improve curriculum alignment and facilitate the design of courses or programs. This article aims to analyze software proposals for curriculum design support that consider using models, methods, and techniques in software development. To do this, a systematic mapping of studies was conducted, including six research questions. This study includes 45 articles published from 2011 to 2022. The results indicate that 60% use some model, method, or technique in software development. Most software uses some models, such as ontologies, UML diagrams, or IMS-1D models. Although most articles use some model, method, or technique, there is a lack of use of software engineering models such as UML diagrams, which are standard in the software industry and research.

Application of CHATGPT in civil engineering

Artificial Intelligence, machine learning, and the Internet of Things (IoT) are changing the way tasks are accomplished. CHATGPT is a well-known conversational artificial intelligence (AI) system based on the generative pre-trained transformer (GPT) architecture, launched by OpenAI. CHATGPT is trained through reinforcement learning based on human feedback. There are advantages to the use of CHATGPT in Civil engineering, including but not limited to design and planning: structural analysis and simulation, code compliance and regulations construction management, knowledge repository and information retrieval, education, and research. The limitation of CHATGPT is the bias based on the datasets used in CHATGPT training, the requirement of sufficient input information, as well as the risk of bias and transparency issues, and negative consequences if generating inaccurate content. The use of CHATGPT and other language models in civil engineering requires careful consideration to ensure not bypassing expert consultation in particular cases. Deep Learning based language models would have a positive impact on civil engineering rather than replacing human expertise and improving the infrastructure development in the world and solving challenges facing mankind

Some Mechanical Equilibrium Problems. A Geometrical Point of View

In this paper we give a geometrical solution for a mechanical equilibrium problem, namely for a bar that is hung by 2 threads from a fixed point. Despite the fact that most of the engineering modelling problems are solved using Mathematical Analysis, we will reduce the solution of our problem to determining the coordinates of a certain point in the Cartesian coordinate system. More, we will find the value of the forces appearing in the threads. Some generalizations are provided. The mechanical notions are minimal and they will be mentioned at first and some very simple geometric results, such as bisectrix theorem, law of cosines, the congruence of the angles will be used all along the paper. The forces that are not taken into account in the problem are considered negligible.

Smart home service terminal design for elderly families integrating the KANO model and perceptual engineering

In recent years, smart homes have gradually come into our lives and have brought many positive impacts to our lives. However, in specifically targeted application design planning, the designer community is not always able to consider and analyze every factor. This paper proposes an integrated nonlinear design that incorporates the KANO model as well as a mathematical model of sensible engineering coupled with design science. The application of different design solutions in different types of households is evaluated after dividing the different types of living of elderly households into specific situations. The results show that for elderly households of type 1 versus 4, scenario 2 generally has more accurate application feasibility compared to scenario 1. The maximum increase in application accuracy for Scenario 2 compared to Scenario 1 was 6.28%. However, the frequency of use decreased by 3.09%. And for elderly households of type 2 and 3, which tend to live alone, the feasibility of application of scenario 2 is similar or even worse than that of scenario 1. The improved Scenario 3 both have higher application feasibility than Scenarios 1 and 2 and has a more user-friendly visual aid to understand the design, which helps the elderly group to better use the smart home service terminal system.