Engineering Design Process Research Articles

Point-enhanced convolutional neural network: A novel deep learning method for transonic wall-bounded flows

Low order models can be used to accelerate engineering design processes. Ideally, these surrogates should meet the conflicting requirements of large design space coverage, high accuracy and fast evaluation. Within the context of aerospace applications at transonic conditions, this can be challenging due to the associated non-linearity of the flow regime. Different methods have been investigated in the past to predict the flow-field around shapes such as airfoils or cylinders. However, they usually have reduced spatial resolution, limiting the prediction capabilities within the boundary layer which is of interest for transonic wall-bounded flows. This work proposes a novel Point-Enhanced Convolutional Neural Network (PCNN) method that combines the advantages of the well-established PointNet and convolutional neural network approaches. The PCNN model has relatively low memory requirements in the training process, preserves the spatial correlation in the domain and has the same resolution as a traditional computational method. The architecture is used for the flow-field prediction of civil aero-engine nacelles in which it is demonstrated that the flow features of peak isentropic Mach number (Mis), pre-shock isentropic Mach number and shock location (X/Lnac) are captured within ΔMis = 0.02, ΔMis=0.04, ΔX/Lnac=0.007, respectively. The PCNN model successfully predicts the integral parameters of the boundary layer, in which the incompressible displacement thickness, momentum thickness and shape factor are typically within 5% of the CFD. Overall, the PCNN method is demonstrated for transonic wall-bounded flows for a range of flow physics that include shock waves and shock-induced separation.

Interdisciplinary STEM education foundational concepts: Implementation for knowledge creation

Interdisciplinary thinking is essential to understanding and solving real-life problems and requires multiple disciplinary viewpoints. Research into STEM education highlights that it promotes an interdisciplinary learning process integrating science, mathematics, engineering, and mathematics knowledge and skills. However, STEM definitions are varied, and implementation recommendations are scant, resulting in diversity in the development and implementation of the learning process. This study critically analyses the literature to determine the fundamental concepts of STEM education and STEM discipline integration. Our analysis discovers six key components of STEM education, encompassing the integration of discipline, utilization of multiple representations, engagement with realistic and relevant problems, application of the engineering design process, encouragement of active collaboration, and emphasis on student-centered learning approaches. Then, we transform these key components to a practical learning process. The STEM-DTaM (STEM with Design Thinking and Makerspace) learning model consists of seven steps. We then unfold how this proposed learning could facilitate interdisciplinary thinking construction.

Preface

2024 4th International Conference on Fluid and Chemical Engineering (ICFCE 2024) has been successfully held on July 26-27, 2024, in Wuhan China as a virtual event. Organized by Hubei Zhongke Institute of Geology and Environment Technology, ICFCE 2024 intends to invite worldwide famous scientists, experts, scholars, and researchers for academic presentations. ICFCE 2024 proceeding is a collection of outstanding submissions in the field of biofluid mechanics, chemically reacting fluids and combustion, computational fluid dynamics (CFD), experimental fluid mechanics, flow through porous media, fluid–solid interactions (FSI), geophysical fluid dynamics, granular/suspension flows, heat and mass transfer, hydrodynamics, physical, theoretical and computational chemistry, chemical engineering fundamentals, chemical reaction engineering, chemical engineering equipment design and process design, thermodynamics, catalysis & reaction engineering, particulate systems, crystallization, etc. Around 65 articles were selected from 146 submissions after peer-review, and authors and guests participated in ICFCE 2024 with keynote speeches, oral presentations and posters, promoting the communication among researchers and experts from institutes and universities, including University of Sharjah, The University of Manchester, Harbin Engineering University, China University of Petroleum (East China), Shanghai Maritime University, Jiangxi University of Science and Technology, Nagoya University, Marine Design & Research Institute of China, Tianjin Transportation Technical College, Okayama University, etc. Cordial gratitude is delivered to Technical Program Committee of ICFCE 2024 for the professional work on guarantying the high standard of conference as well as the proceedings. We believe the proceedings will enhance the exchange of ideas and state-of-art knowledge on Fluid and Chemical Engineering. Finally, we thank all the staff members at IOP Publishing for their valuable editorial support. Professor Omid Mahian Xian Jiaotong University, China Associate Professor Sébastien Déon University of Bourgogne-Franche-Comté, France List of Technical Committee is available in the pdf

A coupled machine-learning-individual-based model for migration dynamics simulation: A case study of migratory fish in fish passage facilities

The extensive development of hydropower projects has notably changed the ecohydrological conditions of fish habitats, affecting fish behavior, including habitat usage and migration, to varying extents. Understanding fish migration dynamics is essential for quantitatively assessing the impact of ecological restoration measures on migratory fish. However, no model has yet demonstrated sufficient accuracy to be considered valuable in ecological restoration engineering. To address this issue, in this article, a coupled machine-learning-individual-based model (ML-IBM) consisting of random forest (RF) and Eulerian–Lagrangian–agent method (ELAM) is constructed for predicting fish migration, aiming to find effective fish passage solutions before implementation. In this study, the passage data of ya-fish (Schizothorax prenanti) in vertical slot fishways (VSFs) is compiled to train ML-IBM to simulate fish migration in fish passage facilities. In movement prediction, the accuracy of swimming behavior classification reaches 83.4 %, and the R² for swimming speed regression exceeds 0.77. Compared with other state-of-the-art migration dynamic models, the proposed ML-IBM achieves the lowest root mean square error (RMSE) of 7.35 and a mean absolute error (MAE) of 6.26 in migration simulation results. Further, RF is used to quantitatively calculate the importance of input features. The contributions of each feature are analyzed and discussed from a hydrodynamic perspective, with the importance ranked as follows: flow velocity (FV) > turbulent kinetic energy (TKE) > total hydraulic strain (THS). This approach enhances the interpretability of the model and provides further insights into the mechanism of fish migration. The results presented in this study have significant implications for informing decision-making in the management of living resources and guiding engineering design processes.

The Significance of Integrating Engineering Design-Based Instruction in STEM Education

Engineering design-based learning activities can successfully spark students’ interest in real-world issues by motivating them to apply their disciplinary knowledge in mathematics, science and more to analyze and solve problems identified (Uzel & Bilici, 2022). Generally speaking, problem identification and problem solving are the two primary steps in the engineering design process. Researchers assert that engineering design-based instruction (EDBI) is a novel paradigm of teaching, particularly valuable in inquiry-based instructional practices (Cooper et al., 2015). Research finds that the enactment of EDBI for addressing open, practical issues is substantially beneficial for increasing the problem-solving and design abilities of primary and secondary students (Crotty et al., 2017; Capobianco et al., 2018), and that EDBI implementation in STEM education can significantly improve students’ attitudes towards the STEM curriculum, promote their academic success, and support their 21st-century skills development (Moore et al., 2015).

ФОРМАЛИЗАЦИЯ ПРИПУСКА, УДАЛЯЕМОГО ПРИ ОБРАБОТКЕ РЕЗАНИЕМ, ДЛЯ РЕШЕНИЯ ЗАДАЧИ АВТОМАТИЗАЦИИ РАЗРАБОТКИ ТЕХНОЛОГИЧЕСКОГО ПРОЦЕССА

The paper considers the problem of lacking systems for automating the production preparation while developing the technological process of manufacturing parts by cutting. The solution to this problem will increase enterprises’ competitiveness and reduce errors arising from the human factor. The objectives of the article are to develop an approach to automating the technological process design by defining the technological process as a function of removing the allowance. The work analyses the allowance and determines the principle of its decomposition into elementary components for classification, identifies the allowance parameters for its formalization and determines the relationship of the allowance parameters with processing methods. The authors carry out the analysis of the existing processing methods and their relationship with the removable allowance, its geometric shape and parameters, propose an approach for the allowance formalization, the implementation of which will automate the technological preparation of production in terms of developing technological processes for mechanical processing. The work suggests an approach for formalizing the allowance, based on its classification and application as its basic element of “allowance removed by the cutting tool in one working stroke”, describes additional properties and characteristics of the allowance for its mathematical description and preservation of the relationship with the processing methods. Formalization of the allowance, its classification and assignment of the function for its removal will allow automating the technological process development, improving the quality of manufactured products by reducing the influence of the human factor and using optimal methods for processing parts.

Design of a Yokeless double disc axial flux motor for light electric vehicles

One of the main challenges in designing electric vehicles is determining traction system performance, as engine power directly impacts battery size and the engine itself. Therefore, high power density, efficiency, and torque are all essential for vehicle autonomy and performance. This study proposes developing a dual-disc axial synchronous motor for Society of Automotive Engineers (SAE) Formula-type light vehicles. It addresses key motor design parameters such as current, terminal voltage, winding configuration, and reactances. The objective was to meet demands for specific vehicle dynamics, e.g., a wide RPM range, high torque, and dynamic performance. These parameters were validated using finite element simulations, which were then compared to a three-phase induction motor in a simulation software used by the Cheetah vehicle racing E-competition team. The motor designed here aims to provide superior dynamism, especially given the absence of reduction systems, which in turn reduces the losses associated with transmission ratios. This study not only details the dual-disc AFPM engine design process, but also validates it using finite element simulations, and presents justifications for improved dynamic performance and efficiency relative to an engine used in a Formula SAE competition. The side-by-side comparison clearly showed significant gains in speed, and significant reductions in lap time for the motor developed here.

Методика проектирования технологических процессов шлифования рельсов рельсошлифовальными поездами

Методика проектирования технологических процессов шлифования рельсов рельсошлифовальными поездами

Investigating the correlation between visual representation flow, physical prototyping, and designers’ creativity

This study aims to explore how prototypes, sketches and CAD models supported designers during the designers during the early ideation, idea development in the engineering design process flow. Using a mixed-methods study, the designer’s roles and contributions were evaluated with respect to the achieved design quality. 81 Professional industrial designers were observed and interviewed after participating in five workshop sessions. After exploring different permutations of sketching, prototyping and CAD modelling, results indicate that starting with ‘Prototyping’ in the early ideation stage contributed significantly to more ideas of higher quality, broadening the ideation space. Using CAD modelling too early in the engineering design process constrains ideation and prematurely limits solution spaces.

Computational Thinking Integration into Pre-Service Science Teacher Education: A Systematic Review

ABSTRACT Computational Thinking (CT) has emerged as a fundamental aspect of modern science education, especially within pre-service teacher education. This study examines the current landscape of CT integration in pre-service science teacher education, drawing insights from an analysis of 18 empirical studies conducted since the implementation of the Next Generation Science Standards in 2013. The findings reveal the predominantly exploratory nature of research in this area and underscore the prevalence of positive outcomes associated with CT integration. Moreover, the study identifies prominent pedagogical strategies such as problem-based learning and the engineering design process, highlighting their integral roles in CT integration. Additionally, the findings uncover the interconnectedness of modeling and simulation, computational problem-solving, and systems thinking practices within CT-integrated science interventions. This suggests the necessity for a more holistic approach, including the integration of unplugged activities, the generalization component of CT, and diverse science disciplines, encompassing life science and Earth/space science. Ultimately, these findings emphasize the imperative for further investigation to comprehensively explore CT integration within pre-service science teacher education, aligning closely with contemporary educational standards and practices.

Methanogenesis kinetics of organic matter of the leachate in an up-flow anaerobic sludge blanket reactor

Understanding the treatment of leachate mediated by the development of anaerobic sludge makes it possible to create an effective design process of biodegradation technology. This study used an up-flow anaerobic sludge blanket (UASB) reactor equipped with a gas–liquid-solid separator to capture CH4 for treating landfill leachate to improve understanding of methanogenesis kinetics of organic matter. The performance of UASB was able to remove 154.75 g/L of chemical oxygen demand (COD) content of the leachate originally anticipated to emit 2.99 L of CH4 production into the atmosphere. The trend in the variation of internal mass transfer (IMT) factor was close to the global mass transfer factor; however, it was far higher than that of external mass transfer (EMT) factor. After 30 days of the experiment, methanogenesis kinetics of organic matter of the leachate were supported mainly by the breakdown of complex molecules. The rate-limiting step of CH4 desorption was controlled by IMT at the beginning and then by EMT after 30 days of the experiment. The strongly decreased EMT factor was counterbalanced by an increased value of the IMT factor at before 5 days of the experiment. It would be of interest to predict the methanogenesis kinetics of CH4 desorption using the Generalized Fulazzaky equations, which cannot be evaluated using other models. Analysis of the methanogenesis kinetics of organic matter of the leachate provides a new insight into the performance of UASB reactor, which may contribute to advanced treatment of landfill leachate in the future.

Development of STEAM activity “Eco-Friendly Straw” based science learning kit to examine students’ basic science process skills

To response the calls of reducing single-use plastic consumption, scientists are increasingly interested in exploring alternatives to plastic for making drinking straws. Many commercial eco-friendly drinking straws are made using several raw materials namely paper, wheat, or rice. These involve complex machinery process and advanced technology that are too complicate for students to learn applying skills and knowledge in implementation. One of alternatives is the straw from nature innovation of Sakon Nakhon Rajabhat University (SNRU). It uses flours as raw materials and relies on basic science knowledge of polymer. The innovation has been simplified as an affordable science learning kit for students learning science through making edible drinking straws without using machine and chemical contained. This study developed a STEAM activity “Eco-Friendly Straw” based the science learning kit to examine students’ basic science process skills (BSPS). The STEAM activity consisted of four sections corresponding to six-procedure engineering design process (EDP). The samples were 120 students from secondary school and high school levels with 60 people per level. The students’ group worksheets and produced drinking straws were analyzed and revealed that BSPS performance of the high school students was higher. The art discipline of the STEAM activity was found fostering learning engagement of the students whose BSPS scores were low. The change of pre-test to post-test on polymer of both student levels was found a significant difference. The satisfaction of the secondary school students was higher. Guidance for teachers interested applying this STEAM activity to their classrooms is provided.

Research on Piano Program Programming and Creative Optimization Methods Based on Big Data Technology

This study focuses on the programming and creative optimization methods of piano tracks based on big data technology. Through in-depth analysis of the potential application of big data technology in the field of music creation, we propose an innovative framework for piano repertoire programming and creative optimization. This framework fully utilizes the data processing and analysis capabilities of big data technology to mine massive piano repertoire data, extract music elements, style features, and creative patterns. In terms of piano repertoire programming, we use big data technology to quantitatively analyze music elements and construct a data-driven programming model. This model can automatically generate piano repertoire frameworks that match specific styles, emotions, and rhythms based on user creative needs, providing inspiration and direction for creators. In terms of creative optimization, we utilize machine learning algorithms based on big data technology to intelligently evaluate and improve piano tracks. By comparing and analyzing the advantages and disadvantages of different tracks in terms of melody, harmony, structure, etc., we have discovered and extracted the common characteristics of excellent works, providing guidance for creators to optimize their work. This article will focus on the programming and control capabilities of music programming in the design and composition process of big data technology, as well as optimization methods for music creation. Provide precise services for music teaching and research, promote the prosperity and development of music, and accelerate the integration and innovative development of information technology and music education and teaching. In terms of piano repertoire programming, we utilized big data technology to quantitatively analyze music elements and constructed a data-driven programming model. This model can provide creators with rich inspiration and clear direction based on their creative intentions and specific styles. In addition, our study also considered the recognition rates of training models for different instrument types. Through training and optimizing models, we have ensured that piano program programming and creative optimization processes can achieve high recognition rates and accuracy on different instrument types, thereby further expanding the application scope of big data technology in the field of music creation.

Elementary teachers' self-efficacy and its role in STEM implementation

To equip students with 21st-century skills, teachers must have both deep STEM content knowledge and the confidence to implement and teach appropriate STEM content. Many elementary teachers have inadequate STEM background knowledge, low confidence, and STEM self-efficacy for implementing STEM in the classroom; as a result, teachers' classroom practices are affected. The study examined how elementary teachers perceive their ability to implement STEM in the classroom. The STEM Efficacy Survey was sent to a randomized pool of 100 elementary educators, and 18 of them agreed to participate in the study. This instrument was designed to elicit responses related to the teachers' previous background in STEM, their beliefs about their ability to implement STEM, and their actual STEM implementation in the elementary classroom. The results revealed that participants were confident in their understanding of the engineering design process and problem-based learning. However, teachers were unwilling to apply the engineering design process in the classroom. From this research, the researchers concluded that higher levels of training in STEM education may influence how teachers perceive their ability to implement STEM in the classroom. Further research should focus on exploring how STEM training affects teachers' self-efficacy in STEM implementation.

ENRICHMENT OF SYSTEMS THINKING FOR PROBLEM SOLVING IN ENGINEERING SYSTEMS USING THE HERMENEUTIC LOOP: CASE STUDIES FOR DESIGNERS IN THE FIELD OF REMOTE COMMUNICATION

The systems thinking approach to problem solving is a dynamic and productive approach. However, emphasizing only the objective aspects of a phenomena and neglecting their subjective aspects can decrease its problem solving power. In order to enhance the problem solving power of systems thinking, it is proposed in this article to enrich systems thinking by using the hermeneutic loop. This applied research adopts practical aspects of systems thinking and hermeneutics in understanding and solving problems more effectively. The proposed approach is comprised of an additive loop, named the hermeneutic loop, concerning simultaneously “the whole system and its parts” and “subjectively and objectively”. Requirements of systems thinking are highlighted involving the holism and life cycle of the system. A summary of the considerations for systems thinking regarding holism and lifetime are as follows: (1) feedback in lifetime, (2) feed forward, (3) combining human and tools, (4) resources, (5) stock and flow and (6) carrying capacity (saturation). The utilization of this enriched systems thinking is investigated in three real engineering design processes, including case studies for designers in the field of remote communication. As the result, the proposed enriched systems thinking provides an improved understanding of the whole, which improves the solving power of the designers of components, and adds subjective product design to the objective design.

When engineering design meets STEAM education in hybrid learning environment: teachers’ innovation key through design heuristics

ABSTRACT Implementing STEAM education in classrooms can be enhanced by incorporating other methods to bring students flexibility during learning, such as the engineering design process (EDP) and hybrid learning. We developed design heuristics to support teachers in enhancing the quality of STEAM lessons, emphasizing EDP within hybrid learning to assist teachers in developing lesson plans. The design heuristics were implemented in three groups of online professional development programs within educational design research, with a hundred and eighty-three teachers submitting their lesson plans. We scored the lesson plans and conducted the Kruskal Wallis H test procedure. The result showed that teachers who participated in this study were likely to incorporate the key principles of design heuristics in their lesson planning practices. However, we found that there is a necessity for further exploration, especially in the variation of assessment strategies and the exploration of problems or context for STEAM learning. Therefore, the result emphasized the significance of future exploration that defines and formulates problems for STEAM activities and its implications on teachers’ lesson planning. This study harmonizes technological advancement and pedagogical practices within hybrid learning by integrating emerging technologies into lesson planning and evolving a design approach into the STEAM curriculum.

Finite Element Analysis and Optimization of the Rotational Stiffness of Semi-Rigid Base Connection under Simultaneous Moment and Tension

The base connection is flexible, not fully pinned/fixed, implying a nonlinear moment–rotation relationship. This deviates from a linear response, where rotation is not directly proportional to the applied moment. Numerical investigations using the commercial software ABAQUS were conducted to analyze the steel base plate connections. The finite element (FE) models were verified against previous experimental results. Moreover, numerical findings of a comprehensive parametric investigation were conducted. The studied connections were examined with different configurations, including variations in the diameter, spacing, and number of the anchor bolts; the thickness of the base plate; and the applied axial force. The current study aims to use numerical results combined with the whale optimization algorithm (WOA) and classical genetic algorithm (GA) to derive a formulation for the moment–rotation (M-θr) relationship. The distinctive aspect of this formulation is that it aims to simulate the nonlinear rotational behavior exhibited by flexible base connections under combined moment and tension loads, while also considering various parameters such as bolt number/diameter and plate thickness. The findings indicate that the WOA is capable of obtaining an optimal equation for accurately simulating the M-Ɵr relationship. This underscores the ability of the WOA to effectively address the complexity of the problem and provide a reliable equation for predicting the rotational behavior of such connections. Consequently, the WOA method can be utilized to calculate the rotational stiffness at H/150, offering valuable support for engineering design processes.

Optimization of Interior Engineering Design Process and Application Based on Enhancing Aesthetic Experience of Interactive Design

Optimization of Interior Engineering Design Process and Application Based on Enhancing Aesthetic Experience of Interactive Design

Condensation and Precipitation of Water Vapor: The Emergence of a Precursor Model through the Engineering Design Process

Condensation and Precipitation of Water Vapor: The Emergence of a Precursor Model through the Engineering Design Process

An engineering design-based mathematics activity example based on STEM approach in middle school: Cold storage design

Engineering design practices in STEM education focus on reflecting the discipline-specific work of engineers in a manner that is suitable for the student level and course learning objectives. Using an engineering design context also facilitates student identification of global problems and feasible solutions to address such problems. In this article, within the framework of STEM approach, an engineering design activity that can be applied in middle school mathematics course is presented. Additionally, examples of students’ experiences of the engineering design-based mathematics activity are given. The "Cold Storage Design Activity" was executed in a classroom setting, and the implementation process underwent examination and evaluation. 12 eighth-grade students from a middle school in Turkey took part in the implementation. The middle school were able to successfully perform an engineering design process and effectively overcome challenges through teamwork. The results of the activity show that middle school students are excited and eager to participate in a design activity.