Hasil untuk "Engineering machinery, tools, and implements"

Mustafa S Mustafa, Basma A.M. Al-Jawadi

The current study highlights the importance of accurate temperature prediction in Iraq, a country facing economic challenges due to its hot, arid climate and increasing climate change effects. Conventional forecasting methods, such as statistical and shallow machine learning models, struggle to address the complex time-dependent characteristics of meteorological data. The present study proposes to improve the temperature forecasting of the three large cities in Iraq, i.e., Dohuk, Erbil, and Mosul, using the deep learning models that can learn both short- and seasonal weather trends. A meteorological dataset of 24 years (2000-2024) was created with five major characteristics, namely, temperature, wind speed, relative humidity, total precipitation, and surface pressure. The models to be used in the deep learning model were three, namely (Long Short-term memory (LSTM), Gated Recurrent Unit (GRU), and Artificial Neural Network (ANN). The metrics of performance were Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Squared Error (MSE), and R². The LSTM model performed the best in all the cities with RMSE values of 2.544, 2.366, and 2.323 and R² scores of 0.941, 0.948, and 0.952 in Dohuk, Erbil, and Mosul, respectively. The study confirms that LSTM is the most effective in modeling complex temporal dependencies in climatic time series, making it a significant contribution to understanding deep learning's application in weather forecasting in the Middle East. It suggests integrating AI-driven technology into the national meteorological system for climate-resistant decision-making in agricultural, water resource management, and urban development sectors.

Mohammed Amine Khater, Chaaban Aroussi, Elamine Abdelouahed et al.

This paper presents a numerical evaluation of pipeline damage caused by an external circumferential semi-elliptical crack. The study utilizes the Abaqus software and the Extended Finite Element Method (XFEM) to model and analyze the crack behavior. Various parameters such as crack size, internal pressure, and loading conditions are investigated to assess their influence on pipeline integrity.   The results reveal that as internal pressure increases from 300 to 600 bar, the pipe’s bearing capacity significantly decreases due to heightened stress concentrations around crack tips, leading to increased hoop stress and Stress Intensity Factors (SIFs), which accelerate crack propagation. Higher pressures also promote crack nucleation and growth, further reducing the effective cross-sectional area and weakening the pipe's load-carrying ability. Additionally, the analysis highlights the critical influence of defect size (a/t ratio) on stress distribution and residual strength: as the a/t ratio increases, the pipe becomes more vulnerable to failure at lower stress levels. The critical crack size is identified at the intersection of the resistance curve and the ultimate stress line, beyond which failure occurs before reaching the material’s full strength. Non-physical regions, where resistance exceeds ultimate stress, are disregarded to ensure realistic defect assessments. Under an internal pressure of 30 MPa, pipes with a/t ratios of 0.50 and 0.62 remain within the safety zone, while those with a/t ratios of 0.75 and 0.80 enter the failure zone, indicating a substantial loss of structural integrity and an increased risk of fracture.

Victor Rizov

A pipe subjected to an evenly distributed internal pressure is investigated in this theoretical paper. The pipe has a thin wall that is built-up by a functionally graded engineering material. The circumferential stresses and strains in the pipe wall are investigated. In essence, the current investigation is non-linear since the wall behaves as a non-linear elastic body with non-linearly distributed properties through the wall thickness. The different stages of the work of the wall are investigated and the corresponding parameters of stressed and strained state are derived. The dependence of the pressure on the material and geometrical parameters are studied.

Saranya Govindakumar, Vijayalakshmi Sankaran, Paramasivam Alagumariappan et al.

The COVID-19 epidemic has raised awareness of exactly how crucial it is to continuously observe issues and diagnose respiratory problems early. Although the respiratory system is the primary objective of the disease’s acute phase, subsequent complications of SARS-CoV-2 infection might trigger enduring respiratory problems and symptoms, according to new research. These signs and symptoms, which collectively inflict considerable strain on healthcare systems and people’s quality of life, comprise, but are not restricted to, congestion, shortage of breath, tightness in the chest, and a decrease in lung function. Wearable technology offers a promising remedy to this persistent issue by offering continuous respiratory parameter monitoring, facilitating the early control and intervention of post-COVID-19 issues with respiration. In an effort to enhance patient outcomes and reduce expenses related to healthcare, this paper examines the possibility of using wearable technology to provide remote surveillance and the early diagnosis of respiratory problems in individuals suffering from COVID-19. In this work, a fog computing-based cost-effective smart health monitoring device is proposed for infectious disease applications. Further, the proposed device consists of three different biosensor modules, namely a MAX90614 infrared temperature sensor, a MAX30100 pulse oximeter, and a microphone sensor. All these sensor modules are connected to a fog computing device, namely a Raspberry PI microcontroller. Also, three different sensor modules were integrated with the Raspberry PI microcontroller and individuals’ physiological parameters, such as oxygen saturation (SPO2), heartbeat rate, and cough sounds, were recorded by the computing device. Additionally, a convolutional neural network (CNN)-based deep learning algorithm was coded inside the Raspberry PI and was trained with normal and COVID-19 cough sounds from the KAGGLE database. This work appears to be of high clinical significance since the developed fog computing-based smart health monitoring device is capable of identifying the presence of infectious disease through individual physiological parameters.

Jehosheba Margaret Matthew, Masoodhu Banu Noordheen Mohammad Mustafa, Madhumithaa Selvarajan

Emotion recognition is a valuable technique to monitor the emotional well-being of human beings. It is found that around 60% of people suffer from different psychological conditions like depression, anxiety, and other mental issues. Mental health studies explore how different emotional expressions are linked to specific psychological conditions. Recognizing these patterns and identifying their emotions is complex in human beings since it varies from each individual. Emotion represents the state of mind in response to a particular situation. These emotions, that are collected using EEG electrodes, need detailed emotional analysis to contribute to clinical analysis and personalized health monitoring. Most of the research works are based on valence and arousal (VA) resulting in two, three, and four emotional classes based on their combinations. The main objective of this paper is to include dominance along with valence and arousal (VAD) resulting in the classification of 16 classes of emotional states and thereby improving the number of emotions to be identified. This paper also considers a 2-class emotion, 4-class emotion, and 16-class emotion classification problem, applies different models, and discusses the evaluation methodology in order to select the best one. Among the six machine learning models, KNN proved to be the best model with the classification accuracy of 95.8% for 2-class, 91.78% for 4-class and 89.26% for 16-class. Performance metrics like Precision, ROC, Recall, F1-Score, and Accuracy are evaluated. Additionally, statistical analysis has been performed using Friedman Chi-square test to validate the results.

Ziyang Ji, Jabir Mumtaz, Ke Ke

This paper investigates the problem of processing jobs on unrelated parallel batch machines, taking into account job arrival times, machine deterioration effects, and variable preventive maintenance (VPM). To address this complex scheduling problem, this paper proposes a Self-Adaptive Artificial Bee Colony (SABC) algorithm, incorporating an adaptive variable neighborhood search mechanism into the algorithm. To verify the effectiveness of the proposed algorithm, we designed comparative experiments, comparing the SABC algorithm with the NSGA-III algorithm on problem instances of different scales. The results indicate that the SABC algorithm outperforms the NSGA-III algorithm in terms of solution quality and diversity, and this advantage becomes more pronounced as the problem scale increases.

Li-Xian Chen, Shih-Wen Su, Chia-Hung Liao et al.

Computational thinking (CT) has become one of the critical goals of teaching CS programming courses. Computational skills consist of skills taken in a computational form in learning programming and dealing with daily life. More research adopted games to teach CT skills. This paper investigated two games, Little Alchemy 2 and Dr. Sudoku, to promote CS students’ CT skills and applied international Bebras tests to measure their CT skills. The results showed that CT skills in problem decomposition and pattern recognition could be improved via digital games. Thus, this study contributes to computing education using available digital games to promote CS college students’ CT abilities.

Bronius Žalys, Kęstutis Venslauskas, Kęstutis Navickas et al.

The degradation of lignocellulose in biogas processes has been focused on the inoculant microorganisms involved, with a view to gaining a deeper understanding in order to improve lignocellulose degradation. The maximum volumetric biogas yield (12.17 L/L) was achieved with the inoculum used in experiment “B”, containing 400 g of digestate from the bioreactor along with 400 g of rumen fluid. The highest concentration of methane in biogas was obtained from the same inoculum composition (63.2 ± 1.5%). The second largest volumetric yield of 8.41 ± 0.45 L/L biogas was achieved in experiment “C,” where digestates were used as the main inoculum. Accordingly, in this case, the volumetric yield of biogas was 8.41 ± 0.45 L/L. The composition of rumen fluid and digestate increased biogas production from the same amount of alfalfa leaves by 30.9%.

Adenike A. Moradeyo, Adegboyega Oyedijo, Hana Trollman

This research aims to develop a better understanding of how the adoption of Industry 4 [...]

Waleed Nasir Khan, Syed Ghayyoor Hussain Kazmi, Anwar Khitab

The present study concerns the application of nano-/micro-sized fibers (bio-char of Santa Maria feverfew) in cementitious mortars. The bio-char was added @ 0, 0.05 and 0.1% by mass of cement. The addition of bio-char did not affect the setting and consistency of the mortars. The fresh density was reduced by 11%, while the followability decreased by 50%. It is concluded that the bio-char results in a light-weight cementitious material, without affecting the setting time or consistency. Bio-char produces carbon-rich materials, the use of which as building materials adds to carbon sequestration in accordance with the Sustainable Development Goals of the UNO.

Ashwaq Fadhel Muhkaber Alomare, Tahrir Taki Ali AL-Musawi

The impact of urban infill has been an important topic within urban research. Despite the vast knowledge, however, there is a gap in reporting the effect of adding contemporary malls to Baghdad urban context; therefore, we studied two main contemporary malls built after 2003, Al-Mansour Mall in Al-Mansour district and Baghdad Mall in Harthiya district, selected for this study because of their large-scale and their contribution to the development growth of the city. The findings of this research showed they both have a strong impact on different aspects such as urban, social, economic, and the environment. The paper also highlights critical views concerning the spread of malls in Baghdad and discusses the importance of traditional suqs and the reasons of transition to the contemporary malls with suggestions for improvement. This paper contributes to the urban literature by developing a theoretical framework of urban infill indicators. Findings may have implications for future infill developments both for architecture and urban design strategies for city growth.

Masaki NODA, Yuki NOGUCHI, Takayuki YAMADA

This paper provides a vector-valued level set-based topology optimization method for multiple materials. The proposed method is characterized by a perfectly symmetric representation of multi-material by a vector valued level set function, which lowers the dependence of initial configuration in the optimization calculation. The problem that the multi-material optimal configuration depends on how the parameters are given, due to the asymmetric material representation, is fundamentally solved. Also, this paper implements the method to adjust the geometrical complexity of optimal configurations with the regularization parameter. First, a topology optimization problem is formulated based on the representation by the perfectly symmetric vector-valued level set function, and the method to regularize the optimization problem is generalized for multi-material topology optimization. Next, we construct an optimization algorithm in which the level set function is updated by the reaction-diffusion equation. Finally, two- and three-dimensional numerical examples are shown to confirm the validity and utility of the proposed topology optimization method.

Kazuma SHIMIZU, Hiroto SHOJI, Taichiro KATO et al.

Weibull stress criterion based on the “Local Approach” is applied for rational brittle fracture assessment of steel components taking account of the plastic constraint effect on fracture resistance. Once the cumulative distribution of critical Weibull stress is identified for the material itself, that is Weibull shape parameter m as a material constant independent of size/shape of components, loading mode and temperature, fracture toughness can be corrected to the fracture resistance of structural components on the basis of the Weibull stress criterion. On the other hand, a miniature fracture toughness specimen is useful for evaluating the toughness of local area of the component and limited material such as irradiated test sample. Then, this study focuses on developing a method for identification of shape parameter m of critical Weibull stress distribution using miniature specimens. Two types of miniature 3PB (3-point bend) specimen with thickness B=1.65mm that has different crack depth are used to identify the m-value. The m-value determined from the two types of miniature specimen is found to be almost the same as that obtained from normal size specimens with thickness B=15mm, whereas both testing are conducted at different temperature. It is demonstrated that the fracture toughness of the steel at the other temperature can be precisely corrected to the fracture resistance of the cracked component with lower crack-tip plastic constraint by means of the m-value identified from test results for two types of miniature specimen.

Yoshihiro KAI, Atsushi KANETA, Keisuke IKEDA et al.

Safety is an important requirement in rehabilitation assist suits. We have developed a velocity-based mechanical safety device (VBMSD) for an assist suit to aid in the flexion and extension of a patient’s knee joint. The VBMSD is attached to the assist suit. The VBMSD stops the suit’s motor when the angular velocity of the knee joint matches or exceeds a preset threshold level. This level is called the “detection velocity level (DVL)” and it is adjustable based on the specification of each patient’s gait training. Since the VBMSD is composed only of passive mechanical elements such as a rotary damper, it works even when the suit’s computer has stopped working. In view that portability is equally important as safety in wearable assist devices, the size and the weight of the VBMSD must be reduced for practical use. This paper presents the design and development of a new compact and light VBMSD. First, we describe the problems in the previous VBMSD. Second, we present the requirements and design specifications in the new VBMSD. The requirements and design specifications in the new VBMSD’s size are determined by considering International Organization for Standardization (ISO) 13482 and Advanced Industrial Science and Technology (AIST) human body dimensions data. Third, we propose the structure and the mechanism of the new VBMSD. Fourth, we explain the design process of the new VBMSD. In the design process, the frequency response and the transient response of the new VBMSD are also considered. Fifth, experimental results to check whether the new VBMSD achieves the necessary function are presented. Lastly, the possibility of installing the new VBMSD to an ankle joint assist suit and a wrist joint assist suit is discussed using AIST human body dimensions data, etc.

A. Kulikov

Haiyang Pan, Jinde Zheng

As an effective tool for nonlinear and non-stationary signal separation method, empirical mode decomposition (EMD) has attracted a lot of attention of many scholars and has been successfully applied to many engineering areas. Since the kernel of EMD is to define a baseline and then implement the sift process, it is important to select an appropriate baseline to improve the performance of EMD for an accurate decomposition. However, it is difficult to choose the most suitable method for dealing with a given arbitrary signal. Besides, the baseline constructed through the existing methods generally does not equal the expected one. To address these problems, we propose a new generalized framework for adaptive mode decomposition (GF-AMD) based on EMD, in which the optimal baseline is firstly chosen from different ones and a weighted factor is introduced to adjust the baseline for getting the optimal one. Then the optimal baseline is implemented to the sift process of EMD. Two simulation signals are used to verify the effectiveness and superiority to EMD. Finally, the proposed GF-AMD method is applied to the vibration signal analysis of faulty rotary machinery by comparing with EMD method and the analysis results indicate its effect and superiority.

M. Gopalakrishnan, Mukund Subramaniyan, A. Salonen et al.

S. Thipprakmas, Yingyot Aue-u-lan, A. Jarfors et al.

During the last decades, across all fields of engineering sciences, the evolution of complex systems in design and manufacturing processes has progressed along with the development of computational methods that can treat more and more complex design and simulation problems. Many design and manufacturing processes are now tackled using computational methods that aim at improvement in manufacturing performance. The development of increasingly sophisticated computational methods and the improvement in computer performance represent an emerging issue from both an industry and an academic viewpoint. Nowadays, a lot of research activities in the field of design andmanufacturing processes have been accomplished and there are a wide range of applications where the computational methods are used. Theobjective of this special issue is to present awide spectrum of computational methods used as a valuable tool for solving more and more complex design and manufacturing processes as well as providing readers with a representative outlook of the latest achievements in this field. The focus of this special issue is placed on the understanding of the enabling computational simulation to replace a big data of experiments and computational optimization to handle and implement multidisciplinary design in complex manufacturing processes. This special issue offers an articulated overview of the examined topics. It contains fourteen original research articles. Eight research articles in this special issue cover a wide range of computational simulation techniques to design and construct mechanical elements applied in several manufacturing processes such as a high-energy mill for handling magnesium powder and to design PID controllers. Four research articles discuss various computational optimization techniques to determine optimal working process parameters applied in several manufacturing processes such as a pickand-place optimization of the die attaching process in semiconductor industry and an optimization of a robotic arm under fuzziness. Two research articles in this special issue also address computational evolving techniques for casting processmodeling and a newmathematical method applied to the singularity problem of 3-RSR multimode mobile parallel mechanism. The guest editors hope the information provided in this special issue is useful and offers stimulation to the new developments and applications of computational methods in design and manufacturing processes.

Muhammad Minarul Islam, Md. Tusher Mollah, Sheela Khatun et al.

Numerical investigation for unsteady, viscous, incompressible Bingham fluid flow through parallel plates is studied. The upper plate drifts with a constant uniform velocity and the lower plate is stationary. Both plates are studied at different fixed temperatures. To obtain the dimensionless equations, the governing equations for this study have been transformed by usual transformations. The obtained dimensionless equations are solved numerically using the explicit finite difference method (FDM). The studio developer Fortran (SDF) 6.6a and MATLAB R2015a are both used for numerical simulations. The stability criteria have been established and the system is converged for Prandtl number <inline-formula> <math display="inline"> <semantics> <mrow> <msub> <mi>P</mi> <mi>r</mi> </msub> <mo>&#8805;</mo> <mn>0.08</mn> </mrow> </semantics> </math> </inline-formula> with <inline-formula> <math display="inline"> <semantics> <mrow> <mo>&#916;</mo> <mi>Y</mi> <mo>=</mo> <mn>0.05</mn> </mrow> </semantics> </math> </inline-formula> and <inline-formula> <math display="inline"> <semantics> <mrow> <mrow> <mo>&#916;</mo> <mi mathvariant="sans-serif">&#964;</mi> </mrow> <mo>=</mo> <mn>0.0001</mn> </mrow> </semantics> </math> </inline-formula> as constants. As a key outcome, the steady-state solutions have been occurred for the dimensionless time <inline-formula> <math display="inline"> <semantics> <mrow> <mrow> <mi mathvariant="sans-serif">&#964;</mi> <mtext>&nbsp;</mtext> </mrow> <mo>=</mo> <mtext>&nbsp;</mtext> <mn>4.00</mn> </mrow> </semantics> </math> </inline-formula> The influence of parameters on the flow phenomena and on shear stress, including Nusselt number, are explained graphically. Finally, qualitative and quantitative comparison are shown.