bluuebunny/crossref_metadata_2025_split huggingface dataset:
Investigation of Thermal Characteristics of Turbulent Non-Premixed Flames in a Conical Bluff Body Using Ridge and Support Vector Regressor Algorithms
Authors: Quadros Jaimon Dennis , Mogul Ibtisam , Ata Alper , Bedii Ozdemir I. , Mohin Ma 
Published: January 2025

Abstract
The current work aims to develop computational models for the thermal characteristics of turbulent CH4 flames for varying burner dimensions. This study develops a platform for data-driven analysis of temperature prediction of turbulent non-premixed flames, in which the influence of flow and geometric parameters, including burner head diameter (D), half cone angles (α), and co-flow air velocity (Ucf), have been considered. The algorithms used were ridge regressor (RR), linear regressor (LR), and three variations of support vector regression (SVR): SVR with a linear kernel (SVR-LR), SVR with a radial basis function (SVR-RBF), and SVR with a polynomial kernel (SVR-Poly). The performance of each computational model was evaluated and contrasted based on several metrics: mean absolute error, regression coefficient (R2), mean absolute percentage error, and mean Poisson deviance. From the modeling of the output data, it was observed that the SVR-RBF predictions were more accurate compared to those from the other algorithms, as it achieved the highest training value of 0.955. The testing predictions of RR, SVR-LR, SVR-RBF, and SVR-Poly algorithms were also robust, with R2 values ranging between 0.91 and 0.94. It is, therefore, established that these computational models are effectively suited for predicting sensitive turbulent CH4 flame characteristics based on varying input factors.
Comparison of Analytical Models for Heat Flux Measurement Using Slug Calorimeter: Integration of Finite Element Analysis and Optimization Technique
Authors: Saputra M Dito , Gantina Hendra , Abrizal Haryadi , Priyadana Ikhwannuary Raditya , Sanjaya Arief Budi , Jihad Bagus Hayatul , Sutrisno  
Published: January 2025

Abstract
This study focuses on comparing the accuracy of existing analytical models for heat flux measurement using a copper slug calorimeter in high-temperature environments. Two analytical models, the No Loss Model, with simpler calculations by ignoring heat loss, and the Slug Loss Model, which incorporates heat loss for greater accuracy, are evaluated. A novel measurement approach, combining finite element analysis (FEA), optimization techniques, and experimental data, was developed to provide a robust framework for this comparison. The new method was tested by comparing its results with those obtained from the two existing models. The heat flux values were 237.181Wcm−2 for the No Loss Model, 255.26Wcm−2 for the Slug Loss Model, and 253.36Wcm−2 from the proposed approach (Numerical Estimation method). The results demonstrated that the proposed approach aligns more closely with the Slug Loss Model, suggesting its suitability for accurate heat flux measurement in high-temperature environments and its utility as a tool for comparing analytical methods. These findings provide valuable insights for choosing appropriate models in various heat flux measurement applications.
Wave Energy Converter for Off-Grid Applications
Authors: Anunobi Francisca , Spitler Quinton , McGarrah Patricia , Duan Shawn 
Published: January 2025

Abstract
This project explores the design and manufacture of a wave energy converter (WEC) for off-grid applications. The objective of the project was to build from existing designs to reduce production costs, enhance efficiency, and produce a device that could be integrated into off-shore or near-shore power systems. The authors proposed a point-absorber style WEC prototype to meet these objectives, where a flotation device was used to convert the oscillating force of the waves to electricity. The device uses a stationary rack and a floating buoy that contains a pinion gear, a gear box, and a generator. The vertical translation movement of the buoy along the rack rotates the pinion shaft. The pinion shaft is attached to a gear box that uses a set of clutches to convert the bidirectional input to a unidirectional output, driving a three phase AC generator that powers a LED. After finalizing the design for the WEC and its power-takeoff system, a series of analyses, simulations, and testing protocols were carried out to validate the proposed design elements. Physical prototype testing of the WEC yielded a frequency of 6.5 Hz and 12.37 VDC.
AI-Powered Robot-Assisted Automated Assembly Inspection System for Industry 4.0
Authors: Chauhan Vedang Dilipkumar , Maziarz Grant , Cardoso Dos Santos Simone 
Published: January 2025

Abstract
The integration of robotics in the industry offers the potential for optimizing resources, productivity, and manufacturing efficiency. With the increasing prevalence and affordability of industrial robots, there is a possibility of reducing the prices of goods produced with their assistance, making them more accessible and affordable to a broader consumer base, thereby enhancing living standards and quality of life. This research project focuses on the design and implementation of an advanced AI-powered robot assisted automated assembly inspection system that combines Fanuc robot LR Mate 200 iD/4s, computer vision, and AI. The robot facilitates material handling and precise positioning of a vision camera for capturing images, while an AI-trained model aids in the classification of assemblies as either good or defective. Additionally, a machine vision system is employed to locate defects. The project aims to minimize defects and enhance product quality, thereby reducing costs associated with rework, scrap, and warranty claims. The system’s proof of concept involves testing it with a small car assembly consisting of multiple components. A database of images, encompassing both good and defective cars from various camera views, is generated. Deep learning algorithms are utilized to train the AI system, and computer vision algorithms are developed to identify defects. The decisions made by the AI system are communicated to the robot for sorting products into good and defective categories. The robot demonstrates impressive repeatability and absolute accuracy. The AI system achieves a classification accuracy of 98% on a test dataset, while the machine vision system accomplishes 96% accuracy in defect localization. Combining the accuracies of AI classification and the vision system, the overall accuracy of the system reaches 94%. The developed system represents a scaled-down version of an Industry 4.0 system and can be expanded to larger-scale industrial automation. The research work presents two significant contributions: (1) the demonstration of a small-scale Industry 4.0 system that integrates a robot, vision system, and AI for assembly defect detection, and (2) the encouragement of student engagement in AI applications through project-based learning.
The Legacy of Henry R. Towne - The Business Digital Twin Built Upon a Business Model Ontology
Authors: Stefanov Trifon , Stefanov Stefan 
Published: January 2025

Abstract
This paper introduces a pervasive digital technology called Business Digital Twin (BDT), developed over the last 25 years, as a software that digitally recreates all enterprise processes and allows for their efficient management in real-time and even simulation of future enterprise variant states. The paper also outlines the ontological foundation of BDT called Business Model Ontology (BMO) which represents the culmination of three engineering waves in the development of managerial knowledge initiated by Henry R. Towne.
In 2024, we commemorate 100 years since Henry R. Towne’s death, one of the most prominent figures in the fields of engineering and shop management and the 8th President of ASME. To honor his memory and understand the necessity for a Business Digital Twin, we would like to remind and bring attention to one of Henry R. Towne’s most notable and vital presentations — “The Engineer as an Economist.” In his work, Henry R. Towne states that it is challenging for machine-related manufacturing enterprises to be developed since their success depends on the “ability of the managers while receiving little benefit or aid from all that may have been done previously by others in precisely the same field of work.”
Henry R. Towne defined the difficulties and challenges related to the creation and management of manufacturing enterprises, due to the lack of systemic scientific knowledge about it. We define this systemic knowledge as Business Model Ontology. Towne states that “A vast amount of accumulated experience in the art of workshop management already exists, but there is no record of it available to the world in general...” Nearly 140 years since the publication of this statement by the American Society of Mechanical Engineering (ASME), a universally accepted and comprehensive Business Model Ontology has yet to be widely disseminated.
The methodology used to develop the Business Digital Twin as well as the Business Model Ontology is based on the laboratory approach to scientific research. All new developments were practically tested in industrial enterprises, as specifically created real-world R&D test ground environments.
Given the thorough and detailed nature of both the Business Model Ontology and the Business Digital Twin, we propose that a vast cognitive database could be constructed through the Business Digital Twin framework to encompass various types of manufacturing enterprises. The development of such a crucial open-source database would significantly aid in the establishment of new enterprises and the restructuring and optimization of old ones. This, among other potential impacts discussed in the paper, would facilitate the successful implementation of Industry 4.0 and 5.0 strategies, which aligns with the vision set out by Henry R. Towne in “The Engineer as an Economist.”
Solar Power Tower: An Alternative Method to Power Egypt
Authors: Imam Ramy K. 
Published: January 2025

Abstract
This research aims to identify and evaluate potential locations for establishing solar power tower systems in Egypt, with the objective of determining the optimal site for a concentrated solar power (CSP) plant. The study focuses on identifying the most suitable location for a solar power tower system in the country. Four potential sites are identified and meticulously assessed through a preliminary design analysis conducted at each location, facilitating an informed and optimal site selection process. To ensure a comprehensive evaluation, the study involves an extensive review of meteorological data and irradiance potential for each location. This includes analyzing factors such as solar radiation levels, temperature, and weather patterns, which are critical for assessing the feasibility and efficiency of CSP technologies. The rigorous analysis of these factors ensures that each site’s suitability is thoroughly examined, taking into account the local environmental conditions that could impact the performance of the solar power tower system. By evaluating these sites, this research aims to maximize the efficiency and effectiveness of the solar power tower system. This strategic approach contributes significantly to the broader goal of leveraging Egypt’s abundant solar resources for sustainable energy generation, thereby addressing the country’s energy crisis and reducing reliance on fossil fuels. The findings of this research are expected to provide valuable insights into the optimal deployment of CSP technology in Egypt, promoting a shift towards cleaner and more sustainable energy solutions.
Characterization and Performance Evaluation of New Nanocomposite Materials Derived From Recycled Polypropylene and Nano Fillers
Authors: Alsafy Mahmoud , Alzebdeh Khalid , Al-Hinai Nasr 
Published: January 2025

Abstract
Recently, a growing interest in investigating alternatives to synthetic fibers has been increased due to environmental concerns such as increased carbon footprints and waste management. Thus, various industries’ principal focus has been on developing Nano-sized filler from biomass material to manufacture products for an abundance application. Furthermore, to develop green composites in the industrial sector, extraction and Nano-sized fibers have proven desirable. From a commercial and environmental standpoint, chemical fragmentation and shrinking of waste lignocellulosic fibers to small particles is a potential alternative.
The aim of this research is to assess the mechanical and physical properties of two newly formulated nanocomposite materials. These composites are produced by blending recycled polypropylene (rPP), serving as the primary matrix, with either Nano date palm particles (NDPP) or Nano calcium dioxide particles (NCaP) at varying contents to act as reinforcing fillers. The process involves pulverizing date palm microfibers derived from agricultural waste into nano-sized lignocellulose fillers using a ball milling machine operating at an efficient speed of 12 cycles per hour. Subsequently, the two types of Nano fillers are mixed with rPP using a double screw extruder machine to fabricate the nanocomposites — Nano Date Palm Composite (NDPC) and Nano Calcium Dioxide Composite (NCaC). Compression molding is employed to produce sheets, and test specimens are prepared in compliance with ASTM standards for evaluation using a Universal Testing Machine (UTM). Results indicate that the highest tensile strength among the reinforced polymers was attained with 3% wt. NDPC and 2% wt. NCaC, exhibiting enhancements of 48% and 61%, respectively, compared to neat rPP. Moreover, flexural strength increased by 30% with 3% NDPC and by 38% with 2% NCaC over the neat matrix. While both nanoparticles resulted in a slight decrease in Young’s modulus — 15.6% with 3% NDPC and 2% NCaC — their inclusion enhanced elongation at break and flexural modulus, thereby augmenting the ductility of the neat polymer.
Morphological analysis via Scanning Electron Microscopy (SEM) is important to illustrate the crosslinking between the matrix and the nanoparticles. It revealed that 2% NCaC exhibited superior filler dispersion and greater physical interlocking with the polymeric matrix compared to 3% NDPC. In addition, physical properties illustrate the importance of the material density and melting flow rate to the manufacturer as indication of productivity of the composites. Therefore, NDPC displayed a lower density than NCaC, yet exhibited higher viscosity as indicated by Melt Flow Index (MFI) analysis. This is due to the density of the NDPP is higher than the NCaP. Consequently, NDPC, serving as a Nano bio-composite, offers economically viable and sustainable production prospects, showing promise for diverse industrial applications.
Analysis of the Factors and Coupling Mechanism of Nozzle Jam in Continuous Carbon Fibre 3D Printing
Authors: Bai Jieren , Deng Ziguang , Liu Xiaolong , Yu Ying , Wang Yu 
Published: January 2025

Abstract
Dual-nozzle pre-impregnated filament (PPF) printing has emerged as a leading method in continuous carbon fibre reinforced thermoplastic composites (CCFRTP) 3D printing due to its reduced porosity and enhanced interphase interface. However, frequent nozzle jamming issues in this process can significantly decrease printing efficiency and even damage printing equipment. Although measures have been developed to promptly detect clogging to prevent the blockage from further expanding, and numerous experiments have shown that various complex factors contribute to nozzle clogging, the underlying mechanisms triggering the nozzle jam remain unclear. In this paper, firstly, the characteristics of continuous carbon fibre and the differences of process between PPF printing and traditional resin printing are identified; secondly, three primary causes of nozzle clogging and seven specific clogging scenarios are summarized, with the factors responsible for each scenario and their interplay mechanisms analyzed; ultimately, from a process perspective, these factors are categorized into three classes: printing equipment, filament printability, and process parameters/strategies. By identifying potential mechanisms for nozzle jam, recommendations are made for equipment positioning accuracy and toolhead quality, PPF printability requirements are outlined, and theoretical frameworks are provided for determining optimal process parameters for different filaments, thereby reducing the likelihood of nozzle jam in this process.
A Depth Analysis of Hydrogen Utilization in the Automotive Sector From a Long-Term Perspective
Authors: Carrera-Rivera Gabriel , Espinoza-Andaluz Mayken , Ordóñez-Saca Brayan , Santana-Villamar Jordy 
Published: January 2025

Abstract
This analysis provides an overview of hydrogen and its use in the automotive industry. With the depletion of fossil fuel supplies and the rapid increase in energy costs, it is crucial to develop environmentally friendly propulsion systems to address the growing social and environmental demands. The use of PEM fuel cells as a hydrogen conversion element is experiencing a significant surge. It could pave the way for realizing its enormous potential as a clean energy source. In this context, a review of the various uses of these technologies within the automotive sector is conducted, particularly emphasizing the use of renewable raw materials or sustainable energy sources. As is common with most technological innovations, the initial stages of development and implementation are often linked to government policies and initiatives. In nations with an established automotive industry, long-term funds have been set up to invest in the research and development of fuel cell technologies.
Cold Spray-Produced Functional Surfaces for Triboelectric Nanogenerators
Authors: Kim Young Won , Akin Semih , Jun Martin Byung-Guk , Sutherland John W. 
Published: January 2025

Abstract
Triboelectric nanogenerators (TENGs) are cutting-edge energy harvesting devices to convert abundant mechanical energy sources into electrical power. High-throughput manufacturing of triboelectric surfaces with improved performance and reliability is the key for the large-scale deployment of TENG technology. In the present study, the cold spray (CS) particle deposition technique is employed to fabricate functional surface structures to realize TENGs and smart sensors. Both soft (e.g., tin) and hard (e.g., copper) micron-scale particles are deposited on the target substrates to create the functional surfaces. Additionally, CS is coupled with an electroless deposition process to produce electrically conductive micro-porous (Ra = 2.17 μm) copper surfaces. These surfaces serve as a positive friction layer and a back-electrode for the TENGs. The fabricated surfaces are subsequently utilized to develop innovative TENGs, demonstrating the potential of these surface structures in triboelectric energy harvesting and smart sensing applications. The results reveal that the CS-based functional surfaces lead to significantly improved energy harvesting performance (≈3.5-fold higher performance) compared to friction layer and back-electrodes made of conventional materials, such as copper and aluminum foil.
Surface Profile Analysis of Stainless-Steel Guidewire Post-Cutting: Stainless Steel vs. Tungsten Carbide-Coated Blades
Authors: Ali Mohammod , Srivastava Rupal , Kelly Damian 
Published: January 2025

Abstract
This study investigates the surface profile alterations of stainless-steel guidewires after cutting using two distinct cutting instruments: stainless steel and tungsten carbide-coated scissors. Guidewires are vital components in various medical procedures, including cardiovascular interventions and minimally invasive surgeries. It is essential to find an in-house snapping method for medical professionals to manipulate the dimension of the stainless-steel guidewire based on the requirement. The surface quality of these guidewires post-cutting significantly influences their performance and biocompatibility within the human body. The traditional method of cutting stainless steel guidewires employs stainless steel scissors, whereas modern approaches incorporate tungsten carbide blades for enhanced precision and durability. This comparative analysis evaluates surface characteristics, such as roughness, microstructural changes, and potential defects, induced by each cutting method. The investigation employs scanning electron microscopy (SEM) to quantify the surface alterations at micro scales. Repeated cutting was also carried out to study the effect on the blades caused by the continuous use of stainless-steel scissors and tungsten-carbide-coated scissors. Additionally, in future studies, the mechanical properties, including tensile strength and flexibility, of the cut segments will be evaluated to correlate surface features with structural integrity. The findings from this study are expected to provide valuable insights into the effects of cutting methods on the surface profile of stainless-steel guidewires, enabling medical device manufacturers and practitioners to optimize cutting techniques for improved performance and biocompatibility. Ultimately, this research aims to contribute to the advancement of medical device manufacturing processes, ensuring the delivery of quick, safe, and effective healthcare interventions.
Failure Mode and Effect Analysis in the Risk Assessment of the Main Engine System of an Anchor Handling Tug Supply Vessel
Authors: Ibazebo Ehidiame , Savsani Vimal , Siddhpura Arti , Siddhpura Milind 
Published: January 2025

Abstract
In the shipping industry, machinery and engine failure has been cited as the foremost cause of shipping incidents. Thus, ship owners and operators are now focused on achieving a safe and reliable ship system throughout a vessel’s lifespan through effective maintenance. This is very important for offshore supply vessels like anchor handling tug and supply vessels, as they serve a combination of function in the maritime sector. An efficient maintenance system is crucial for increasing operational efficiency, reducing costs, and ensuring safety and reliability of vessels. The challenge amongst ship operators is to identify the most critical components of the various systems present in the vessel. In this paper, a failure mode and effect analysis are used to assess the possible risks of components failure in the main engine system of an anchor handling and tug supply vessel operating off West Africa waters. Multiple experienced subject matter experts through questionnaires identified the main engine as the most important system of the anchor handling tug supply vessel, and data from the vessel owners were analyzed and used to identify the most critical components of the main engine system. The result allowed for a wider variety of opinion in selecting the most important system of the anchor handling tug supply vessel. Also, the risk assessment of the main engine was crucial in identifying the most critical components of the main engine.